pmid stringlengths 8 8 | pmcid stringlengths 8 11 ⌀ | source stringclasses 2
values | rank int64 1 9.78k | sections unknown | tokens int64 3 46.7k |
|---|---|---|---|---|---|
28690975 | null | s2 | 8,922 | {
"abstract": "Intrinsically stretchable semiconductors will facilitate the realization of seamlessly integrated stretchable electronics. However, to date demonstrations of intrinsically stretchable semiconductors have been limited. In this study, a new approach to achieve intrinsically stretchable semiconductors is introduced by blending a rigid high-performance donor-acceptor polymer semiconductor poly[4(4,4dihexadecyl4Hcyclopenta [1,2b:5,4b' ] dithiopen2yl) alt [1,2,5] thiadiazolo [3,4c] pyridine] (PCDTPT) with a ductile polymer semiconductor poly(3hexylthiophene) (P3HT). Under large tensile strains of up to 75%, the polymers are shown to orient in the direction of strain, and when the strain is reduced, the polymers reversibly deform. During cyclic strain, the local packing order of the polymers is shown to be remarkably stable. The saturated field effect charge mobility is shown to be consistently above 0.04 cm"
} | 228 |
39937904 | PMC11817942 | pmc | 8,925 | {
"abstract": "Intense microbial competition in soil has driven the evolution of resistance mechanisms, yet the implications of such evolution on plant health remain unclear. Our study explored the conversion from antagonism to coexistence between Bacillus velezensis ( Bv ) and Trichoderma guizhouense ( Tg ) and its effects on Fusarium wilt disease (FWD) control. We found a bacilysin transmembrane transporter ( Tg MFS4) in Tg , critical during cross-kingdom dialogue with B v. Deleting Tgmfs4 (Δ Tgmfs4 ) mitigated Bv - Tg antagonism, reduced bacilysin import into Tg , and elevated its level in the coculture environment. This increase acted as a feedback regulator, limiting overproduction and enhancing Bv biomass. Δ Tgmfs4 coinoculation with Bv demonstrated enhanced FWD control relative to wild-type Tg ( Tg -WT). In addition, the Tg -WT+ Bv consortium up-regulated antimycotic secretion pathways, whereas the Δ Tgmfs4 + Bv consortium enriched the CAZyme (carbohydrate-active enzyme) family gene expression in the rhizosphere, potentiating plant immune responses. This study elucidates the intricacies of bacterial-fungal interactions and their ramifications for plant health.",
"introduction": "INTRODUCTION The utilization of beneficial bacterial and fungal species in the plant rhizosphere has gradually gained popularity, emerging as a crucial alternative to agrochemicals in controlling soil-borne diseases ( 1 , 2 ). In soil ecosystems, bacteria and fungi frequently share microhabitats where they aggregate into dynamic, coevolved communities that play a crucial role in orchestrating the complexities of plant growth and health ( 3 – 5 ). Recent studies indicate that the composition and function of these bacterial and fungal communities are influenced not only by the host and environmental cues but also by their interactions within the host niche ( 6 ). These interactions are key drivers of ecosystem functions and are crucial for plant health outcomes ( 7 ). However, the underlying molecular mechanisms, especially bacterial-fungal interactions (BFIs) and their importance for plant health remain poorly understood. BFIs are intricate and dynamic, giving rise to myriad interactions ranging from antagonism to cooperation that can affect the functional ecology of bacteria and fungi regarding growth, reproduction, stress resistance, and pathogenicity ( 8 , 9 ). Both bacteria and fungi react differentially depending on the interacting partners and often evolve strategies to use secreted metabolites and overcome the defense mechanisms of competitors ( 10 , 11 ). Moreover, the competition for nutrients and niches between bacteria and fungi has led to the development of a vast array of chemical weapons (i.e., antibiotics and volatile compounds) over the millions of years of interactions ( 7 ). On the other hand, the occurrence of antibiotic-resistant genes and the evolution of resistance through mutation or horizontal gene transfer are commonly reported in microbes ( 12 , 13 ). Besides, the intra- and intermicrobial interactions can induce the resistance of individual species or communities to antagonistic compounds even in the absence of antibiotic-resistance genes ( 14 , 15 ). Both the production of antibiotics and the development of counter-resistance strategies lead to fitness costs in microbes, which reduce their growth and ecosystem functions ( 16 ). This makes plant growth–promoting biocontrol bacterial and fungal strains spend much energy for their survival in highly competitive soil environments rather than developing mutualistic interactions with each other and plants, ultimately causing the failure of their biocontrol capabilities ( 17 ). The energy-consuming antagonistic microbial interactions are so robust that they can shift mutualistic interactions to antagonistic interactions in the human gut microbiome ( 18 ). This mechanism could also be important in soils for the success of plant growth–promoting microbes, especially for bacteria-fungi consortia ( 19 ). As antibiotic resistance evolution due to selection pressure, adaptation, or horizontal gene transfer is commonly found in natural ecosystems ( 20 ), it would be interesting to evaluate whether the reduction or elimination of antagonistic interactions can reverse the process from antagonism to mutualism. Several studies have elucidated transitions from antagonism to mutualism in plant-herbivore interactions ( 21 – 23 ). Similarly, the development of cooperative behavior has been reported for seed-borne bacterium, Burkholderia glumae and airborne fungi Fusarium graminearum ( 8 ). Plant antagonist bacterium Pseudomonas protegens evolved into mutualists in the rhizosphere by improved nutrient competitiveness and enhanced tolerance to plant-secreted antimicrobials ( 24 ). However, limited evidence is available regarding the occurrence of interaction changes among soil microbes and their consequences on plant growth and health. Bacillus spp. and Trichoderma spp. are the most widely distributed beneficial microbes in the plant rhizosphere, capable of effectively improving plant growth and preventing disease incidence ( 25 – 27 ). Here, we selected these representative strains to investigate the impact of BFIs on plant health. Preliminary results suggested that the synthetic consortium of Bacillus sp. and Trichoderma sp. did not improve Fusarium wilt disease (FWD) control efficiency compared to the application of individual strains. We hypothesized that this lack of difference might be attributed to antagonistic interactions between Bacillus and Trichoderma , and a change in their interaction could potentially affect the ability of consortium to control FWD. To address this hypothesis, we used forward mutagenesis and molecular biology techniques and manipulated Trichoderma ’s resistance to critical antibiotics produced by Bacillus through gene editing. The subsequent improvement in resistance strategy in Trichoderma reduced antibiotic production by Bacillus . It shifted their interactions from antagonism to coexistence, which saved fitness costs and increased the biomass of the individual strains but also led to dynamic changes in the functional dynamics of the rhizosphere microbial community. This shift resulted in forming a more effective barrier against pathogen invasion and achieved higher control efficiency of FWD with the combined application of Bacillus and Trichoderma .",
"discussion": "DISCUSSION Plant roots host a diverse microbiota, including symbiotic consortia of bacteria and fungi, known to protect plants by warding off microbial pathogens, modulating host immune responses, and improving nutrient uptake ( 35 , 36 ). Despite their significance, the complex dynamics of BFIs and its influence on plant health still need to be fully understood. Previous research has demonstrated that ABC transporters are capable of transporting not only endogenous metabolites but also a variety of xenobiotic substances, including antifungal compounds. This versatility makes certain ABC transporters key contributors to antifungal drug resistance ( 37 ). Typically, efflux pump proteins encoded by the MFS family proteins are closely associated with antibiotic resistance due to their ability to extrude a wide range of antibiotics from the cell ( 38 ). In this study, we delineated the impact of the inward-facing transport of antibiotics by MFS family proteins on the change in BFIs. Tg MFS4 showed a notable enhancement in transport efficiency in solutions with low bacilysin concentrations, indicating a high affinity for bacilysin. It is important to note that, in the natural environment, such as the plant rhizosphere, the concentration of most antimicrobial peptides produced by Bacillus may be deficient ( 39 ). Therefore, the observed high-affinity transport is consistent with natural conditions. An analogous mode of action has been identified in bacterial-bacterial interactions. For example, the ompC gene disruption in Escherichia coli , when cocultivated with Pseudomonas aeruginosa , reduces the inhibitory effect of P. aeruginosa on E. coli . This was attributed to the potential entry of pyocyanin into E. coli cells through the OmpC porin protein ( 40 ). Other evidence also suggests that the expression levels of membrane transporter proteins are associated with the ecological adaptability of soil microbes. The MDR pump enhanced the ecological adaptability of Shewanella oneidensis in aquifer sediments by extruding other compounds present in the ecosystems, such as humic acids ( 41 ). The constitutive overexpression of MDR pumps has also been shown to shift the behavior of P. aeruginosa from virulent to nonvirulent in response to certain bioactive compounds ( 42 ). Thus, a similar mechanism of action for Tg MFS4 may be common in nature, and a deficiency in its function could also represent an ecological adaptation strategy in the ongoing natural evolution process. The co-occurrence of bacteria and fungi, especially in the host’s niche, indicates that cross-kingdom interactions are key selective forces driving the diversity, variability, and stability of microbial communities ( 43 ). Furthermore, interspecies communication between bacteria and fungi may promote differentiation, diversity, and stability within microbial consortia ( 44 ). Our study further corroborated this notion, showing that the Tg MFS4-mediated change in BFIs not only affected the colonization density of the two beneficial microbial strains in the rhizosphere but also potentially influenced plant health by altering the functional capabilities of the microbial community. In the field of microbial biocontrol for fungal plant diseases, various mechanisms have been identified, such as the production of antifungal metabolites, secretion of hydrolytic enzymes like chitinases and glucanases, and induction of systemic resistance in plants ( 45 – 48 ). Our findings revealed that the BFI change changed the paradigm for maintaining plant health. The incorporation of the Δ Tgmfs4 + Bv consortium notably enhanced the expression of CAZyme family genes compared to Tg -WT+ Bv consortium, which might play a direct or indirect role in resisting the invasion of FOL by the following three aspects: (i) the potential stimulation of plant immune responses ( 49 , 50 ), (ii) the facilitation of beneficial strains to acquire carbon substrates for proliferation ( 51 – 53 ), and (iii) the degradation of pathogen cell walls to erect a barricade that impedes their invasive progress ( 52 , 53 ). This supports previous reports that bacteria and fungi have a range of interactions, from antagonism to coexistence, affecting the growth, reproduction, stress resistance, and pathogenicity of the associated partners in various ways ( 7 ). Concurrently, these interactions occur within the microbiota of plants or animals, affecting host health in many ways ( 54 ). BFIs are extensively applied within agricultural systems, encompassing the exploration of constructing synthetic communities to safeguard plant health ( 55 ). Most biocontrol research now available focuses on a limited number of single microbial strains ( 56 , 57 ). However, microbes naturally exist in complex communities, influenced by their host, the surrounding environment, and other community members. In theory, applying beneficial microbes in combination for disease control should enhance the efficacy of biocontrol. However, in practice, combining multiple microbes is sometimes less effective than using a single microbe ( 56 ). This is primarily because the selection of beneficial strains focuses on their disease-control effects, often overlooking the interactions and compatibility among microbes ( 58 ). This study provides more effective insights for future efforts in constructing synthetic microbial communities. This approach can be improved by leveraging existing beneficial microbes and strategically modifying their interactions, thus avoiding the complexities of laborious strain selection and the limitations of functional microbial cultivation. Microbes reside within ecosystems not in solitude but in perpetual proximity to other life forms, engaging in the exchange and communion of chemical signals, including secondary metabolites ( 59 ). These secondary metabolites are often considered weapons for their competition with other microbes, aiding in acquiring a survival advantage ( 60 ). Research has indicated that fungi have evolved various strategies to enhance their drug resistance, including alterations in drug targets, augmentation of drug efflux, and the induction of cellular stress response pathways ( 61 ). A suite of adaptive mechanisms emerges during the direct dialogue between fungi and bacteria. Researchers have discovered that fungi can modulate interactions with different bacteria by differentially generating ROS (reactive oxygen species), thereby selectively symbiotic with certain bacteria ( 62 ). In addition to the involvement of fungal genes encoding the HOG (high-osmolarity glycerol) MAPK (mitogen-activated protein kinase) signaling pathway and lipid metabolism in regulating BFIs ( 63 ), a hallmark of symbiotic interactions is the transcriptional up-regulation of genes in the cAMP (cyclic adenosine 3′,5′-monophosphate) signaling pathway and the rearrangement of the cytoskeleton ( 62 ). Moreover, fungi can alter the ratio of 1,3-β-glucans to chitin in their cell walls in response to cell wall–antagonistic drugs, such as chitin synthase or glucan synthase inhibitors ( 64 ). In addition to these defensive strategies, fungi can also modulate their interactions with host microbiota, including bacteria, by secreting specific effector proteins to facilitate their colonization ( 65 ). Even so, the ecological impact of the processes by which fungi acquire adaptive advantages is seldom reported. This study uncovered the capacity of fungi to mitigate the uptake of bacterial toxins by modulating the expression of transmembrane proteins, and this perturbation in the symbiotic dynamic subsequently exerted an influence on the well-being of plants. This study provides a framework for future systematic research on BFIs, particularly the ecological impact of fungal adaptive changes during the coevolutionary process between bacteria and fungi."
} | 3,591 |
36032714 | PMC9402938 | pmc | 8,927 | {
"abstract": "Alkaliphilic cyanobacteria have gained significant interest due to their robustness, high productivity, and ability to convert CO 2 into bioenergy and other high value products. Effective nutrient management, such as re-use of spent medium, will be essential to realize sustainable applications with minimal environmental impacts. In this study, we determined the solubility and uptake of nutrients by an alkaliphilic cyanobacterial consortium grown at high pH and alkalinity. Except for Mg, Ca, Co, and Fe, all nutrients are in fully soluble form. The cyanobacterial consortium grew well without any inhibition and an overall productivity of 0.15 g L −1 d −1 (AFDW) was achieved. Quantification of nutrient uptake during growth resulted in the empirical formula CH 1.81 N 0.17 O 0.20 P 0.013 S 0.009 for the consortium biomass. We showed that spent medium can be reused for at least five growth/harvest cycles. After an adaptation period, the cyanobacterial consortium fully acclimatized to the spent medium, resulting in complete restoration of biomass productivity.",
"conclusion": "Conclusion Growth of cyanobacteria can benefit from high pH and alkalinity by improving carbon delivery. The low solubility of iron and cobalt was shown to potentially limit growth in alkaline media. A comprehensive empirical formula was determined for an alkaliphilic cyanobacterial consortium. Reuse of spent cultivation medium was successfully demonstrated. Future research should focus on determining the practical limits for medium reuse, either by establishing a maximum number of cycles or a bleeding rate. In-depth biochemical analysis of the spent medium could help identify potential inhibitors and their tolerable concentrations. This research provides a way of improving the economics and reducing the environmental footprint of cyanobacterial cultivation, with applications in production of phycocyanin, nutraceuticals, food, and animal feed.",
"introduction": "Introduction Photosynthetic microorganisms such as cyanobacteria and eukaryotic microalgae have been proposed as a source of biomass for the production of bioenergy and bioproducts ( Chisti, 2007 ; Mata et al., 2010 ; Khan et al., 2018 ). These microorganisms can grow on non-arable land and can potentially reach higher areal productivities than traditional food crops ( Chisti, 2007 ; Brennan, 2010 ; Johnson and Wen, 2010 ; Christenson and Sims, 2012 ; Singh et al., 2017 ). While eukaryotic microalgae are investigated for their high lipid content, possibly contributing to renewable energy, cyanobacteria are mainly cultivated at large scale to produce high value products such as pigments, proteins, and vitamins ( Chisti, 2007 ; Hoh et al., 2016 ; Singh et al., 2017 ). Current large-scale systems for algal cultivation have a high-water footprint and nutrient demand ( Scott et al., 2010 ; Zhang et al., 2014 ; Farooq et al., 2015 ; Lu et al., 2020 ). In fact, some studies have reported that to produce 1 L of microalgal biodiesel, over 3000 L of water is required ( Farooq et al., 2015 ). Nutrient demand is typically associated with nitrogen and phosphorus, as they are energy intensive to obtain or their worldwide reserves are depleting ( Rösch et al., 2012 ). Although carbon dioxide is less associated with the topic of nutrient demand, it is also crucial for algal biomass production and its supply to the culture needs to be considered. Depending on the growth conditions carbon can be supplied as CO 2 that is bubbled into the media or in the form of bicarbonate (HCO 3 \n − ) ( Chi et al., 2011 ; Rafa et al., 2021 ; Zhu et al., 2021 ). For systems that bubble in CO 2 there are high capital and operating costs associated with CO 2 transportation and bubbling, as well as high energy requirements ( Chi et al., 2011 ; Rafa et al., 2021 ; Zhu et al., 2021 ). In systems that use bicarbonate there are costs associated with the high concentration of bicarbonate in the growth medium. Some studies have shown that the use of bicarbonate may also avoid costs by preventing culture crashes ( Rafa et al., 2021 ; Zhu et al., 2021 ). As the global demand for high value cyanobacterial products increases ( Singh et al., 2017 ; Bhalamurugan et al., 2018 ), the water and nutrient requirements will only increase, potentially leading to an unsustainable process ( Hannon et al., 2010 ; Farooq et al., 2015 ; Lu et al., 2020 ). To implement an effective cultivation strategy and mitigate the high water and nutrient demand, multiple strategies have been proposed: 1 ) usage of nutrient-rich wastewater streams as a main source of nutrients and 2 ) re-use of spent media with supplementation of the depleted nutrients ( Acién Fernández et al., 2012 ; Acién Fernández et al., 2018 ; Barbera et al., 2018 ). Although mitigation with nutrient-rich wastewater streams is a promising strategy, it could potentially introduce foreign substances (e.g., heavy metal ions, pathogenic microbes, etc .) into the cultivation system. Therefore, it might not be a viable option for biomass that is cultivated for food and pharmaceuticals ( Barbera et al., 2018 ). Cultivation of alkaliphilic, “high pH loving,” cyanobacteria has gained interest over the recent years because of their robustness and ability to capture carbon dioxide directly from the atmosphere ( Bell et al., 2016 ; Canon-Rubio, 2016 ; Sharp et al., 2017 ; Zhu et al., 2018 ; Ataeian et al., 2019 ; Chowdhury et al., 2019 ; Kim et al., 2019 ; Berthold et al., 2020 ). Previously, we enriched a consortium consisting of the alkaliphilic filamentous cyanobacterium Candidatus “Phormidium alkaliphilum” (80–90%) and associated heterotrophs ( Ataeian et al., 2021 ; Ataeian et al., 2022 ). It was enriched from soda lakes located on the Cariboo Plateau (British Columbia, Canada) and was cultivated at a pH of up to 11.2 and with 0.5 mol/L of combined carbonates. This pH was high enough to demonstrate regeneration of spent media with carbon dioxide captured directly from the air ( Ataeian et al., 2019 ). Long-term, crash-free productivity was shown in the laboratory (15.2 ± 1.0 g L-1 d-1, Ataeian et al. (2019) ), as well as in an outdoor, high latitude pilot plant (5.8 g/m 2 /d, Haines et al. (2022) ). The consortium contains 11–17% phycocyanin ( Ataeian et al., 2021 ), which is a valuable, nutritious, and healthy blue pigment. Consortium composition at harvesting contains 60.9% protein, 13.4% lipids and 12% carbohydrates ( Sharp et al., 2017 ; Demirkaya et al., 2022 ). Both productivity and biomass composition were typical of cyanobacteria, including Arthrospira ( Spirulina ). Although replenishing of inorganic carbon using air was a major step forward, reuse of other nutrients (P, N, Mg, S, Na, K, Ca, and Fe) is as important to make the cultivation system sustainable. Using wastewater as a source of nutrients would not work for such a high-alkalinity cultivation system, because if an alkaline medium is combined with wastewater for cultivation, the alkalinity would be lost by dilution with non-alkaline wastewater. Re-use of spent media would mitigate both water and nutrient demand ( Farooq et al., 2015 ; Lu et al., 2020 ). One study found that reusing spent media can reduce nutrient and water usage by 55 and 84%, respectively ( Yang et al., 2011 ). The biggest advantage to reusing spent media is the cost savings on water, water pumping and nutrients ( Yang et al., 2011 ; Farooq et al., 2015 ; Lu et al., 2020 ). Therefore, it is important to understand the effect of spent medium on biomass growth. Re-use of spent medium has been shown to increase, decrease or have no effect on biomass growth, depending on many factors such as culture conditions and harvesting methods ( Lu et al., 2020 ). One area where the reuse of spent medium has not been well studied for biomass growth is in the cultivation of alkaliphilic cyanobacteria. Here, we extend our previous work on the cultivation of an alkaliphilic cyanobacterial consortium and describe the nutrient solubility/availability and nutrient uptake rates at high pH (>10) and alkalinity (0.5 M). We also design and demonstrate cultivation conditions that allow re-use of the spent growth medium. The objectives of this study are to 1 ) determine the solubility of the provided nutrients at high pH, 2 ) investigate which nutrients are present at the end of a cultivation cycle and 3 ) determine if the alkaliphilic cyanobacterial consortium can be grown with recycled, spent media.",
"discussion": "Results and discussion Nutrient solubility Although it is hard to know to what extent an element is “bio-available,” at least we can be fairly confident that elements dissolved as ions in the medium are available for uptake by microorganisms ( Suzuki et al., 1995 ; Lee et al., 2009 ). Because of the high pH (>10.4) and high ionic strength (0.73 M) of the growth medium, some elements (especially Mg, Ca, and Fe) were likely to precipitate ( Vandamme et al., 2012 ). We performed a comprehensive analysis on the freshly prepared medium to determine the solubility of each element. First, we used Visual Minteq 3.1 software (KTH, Sweden) to predict both the likelihood of precipitation and the nature of expected precipitates in the high alkalinity medium as a function of pH. For Mg 2+ , Ca 2+ , and especially Fe 3+ and Co 2+ , the salts added to the medium were expected to precipitate nearly completely at the actual medium pH of 10.46 ( Figures 1A,B ). For, Mn 2+ , 64% of the added manganese was expected to precipitate. Lastly, nickel was only predicted to precipitate above pH 11. Further, under equilibrium conditions, the software predicted that above pH 7, both Mg and Ca would form carbonate salts such as dolomite (MgCO 3 *CaCO 3 ) and magnesite (MgCO 3 ) ( Figure 1C ). For iron, it would mainly precipitate as hematite (Fe 2 O 3 , Figure 1C ), with production of a minor fraction of cobalt ferrite (CoFe 2 O 4 , Figure 1C ). Manganese would mainly precipitate as rhodochrosite (MnCO 3 ) from pH 10.46 to 11 and as MnHPO 4 from pH 5 to 9. Lastly, nickel at pH 11 would precipitate as Ni(OH 2 ). FIGURE 1 Percentage of magnesium, calcium, nickel, and manganese precipitated (A) , concentration dissolved and precipitated for iron and cobalt (B) , and predicted precipitates (C) of calcium, magnesium, cobalt, nickel, and iron over a pH range of 5–11 with an ionic strength of 0.73 M. Data was obtained using Visual Minteq 3.1 equilibrium model. To verify the equilibrium model’s predictions, we collected precipitates from freshly prepared medium and analyzed them using a scanning electron microscope with energy-dispersive X-ray spectroscopy (SEM-EDS). The SEM images shown in Figures 2A,B indicate that the surface of the filter was covered with amorphous precipitates. EDS analysis confirmed experimentally that the amorphous precipitates mainly consisted of calcium carbonate and iron oxide ( Figures 2A,B ). For Mn, Co, and Mg it was difficult to identify the nature of the precipitates by using the EDS analysis, because the signals for Ca and Fe overpowered the spectrum. It was also possible that the precipitates formed from Mn, Co and Mg passed through the 0.2 µm filter and for that reason weren’t observed in the EDS analysis. FIGURE 2 SEM image and EDS spectrum of the recovered precipitates (A) CaCO 3 and (B) Fe (OH) 3 . The fresh culture medium at pH = 10.46 was further analyzed using inductively coupled plasma mass spectrometry (ICP-MS) to determine the concentrations of dissolved sodium, potassium, phosphorus, sulfur, magnesium calcium, and iron. In parallel, the pH of the culture medium was decreased to less than 3, to dissolve any precipitated minerals, and analyzed it on ICP-MS. Together, these two measurements provided the dissolved and total amounts for each element, respectively. The ICP-MS analyses were compared with the Minteq predictions, and the amounts actually added to the growth medium ( Table 1 ). ICP-MS showed that the added sodium, potassium, phosphate, and sulfate remained fully dissolved ( Table 1 ). ICP-MS also showed that this was not the case for magnesium, calcium, and iron, indicating significant precipitation (ANOVA single factor, p = 0.02, Table 1 ). The experimentally determined concentration of dissolved Mg, Ca and Fe was still higher than the Minteq predictions. This indicated that the high pH culture medium was supersaturated in Mg, Ca, and Fe. Supersaturation of carbonate salts is a well-known phenomenon occurring in many natural waters ( Minde et al., 2020 ). Despite supersaturation, the soluble fraction of Mg, Ca and Fe was significantly reduced due to precipitation in the high pH medium. TABLE 1 Concentration (mM) of nutrients at high pH (10.4), reduced pH (<3), and solubility (%). Elements Expected concentration (mM) Concentration in solution (mM) Solubility (%) Analyzed at pH 10.4 \n a \n \n Analyzed at pH < 3 \n b \n \n C-HCO 3 \n − \n \n c \n \n 77.85 33.3 ± 0.8 N/A N/A N-NO 3 \n − \n \n d \n \n 3.06 2.97 ± 0.07 100 N-NH 4 \n + \n \n e \n \n 0.92 0.75 ± 0.04 82 Na 500 483.6 ± 5.5 476.5 ± 26.8 100 Mg 1 0.3 ± 0.04 1.0 ± 0.09 30 K 8.5 7.96 ± 0.42 8.0 ± 0.74 100 P 1.44 1.44 ± 0.05 1.4 ± 0.1 100 S 1 1.0 ± 0.07 0.88 ± 0.08 100 Ca 0.25 0.08 ± 0.02 0.25 ± 0.01 32 Fe 0.04 0.007 ± 0.001 0.02 ± 0.001 17 a To determine the total amounts of elements by ICP-MS, the pH of growth medium was reduced using 5% HNO 3 . b High pH growth medium was directly analyzed on ICP-MS to obtain the concentration of dissolved elements. c (bi)carbonate was calculated using TA which was determined by titration with 0.2 H 2 SO 4 , and pH values. d Nitrate was measured using an ion chromatograph. e Ammonium concentrations were determined using colorimetry. For inorganic carbon, it is well known that at pH 9–10, the dissolved CO 2 concentration is low and HCO 3 \n − is the dominant species. As the pH further increases (pH > 10), CO 3 \n 2− becomes dominant. Since cyanobacteria have the ability to utilize both CO 2 and HCO 3 \n − , but not CO 3 \n 2− ( Raven, 1994 ), it was important to determine the bicarbonate concentration in the high pH medium. The actual HCO 3 \n − concentration was calculated using the measured total alkalinity (TA, 0.5 ± 0.003 M) and pH (10.46 ± 0.02) values. The actual HCO 3 \n − concentration (33.3 ± 0.8 mM) was lower than the amount of bicarbonate added to the growth medium (77.9 mM, Table 1 ). This was caused by equilibration (outgassing) of dissolved CO 2 with ambient air, increasing pH and leading to the production of CO 3 \n 2− ( Wolf-Gladrow et al., 2007 ). Nitrogen, another important nutrient, was also analysed for solubility. We added 3.98 mM total N to the medium, in the form of NaNO 3 (3.06 mM) and NH 4 Cl (0.92 mM). Nitrate measurements indicated that close to 100% of the added NO 3 \n − remained dissolved in the medium (2.97 ± 0.07 mM, Table 1 ). On the other hand, measured NH 4 \n + concentrations indicated that the medium contained 20% less ammonium than was added (0.75 ± 0.04 mM compared to 0.92 mM, Table 1 ). The decrease in the N-NH 4 \n + could be explained by outgassing of volatile NH 3 from the medium at high pH ( Körner et al., 2001 ). Overall, more than 90% (3.72 mM) of the nitrogen added remained in the media to support cyanobacterial growth. Biomass growth and nutrient uptake Growth profile of cyanobacterial consortium Next, we performed cultivation experiments to evaluate the biomass growth and nutrient uptake at high pH. The microbial consortium was grown in Erlenmeyer flasks (15 flasks) with a light:dark cycle of 16:8 h, with 4 days between harvests. Every day, three flasks were removed from the experiment and used for analysis. The consortium used in this study mainly consisted of (>90% relative DNA sequence abundance) the filamentous cyanobacterium Candidatus “Phormidium alkaliphum” ( Sharp et al., 2017 ; Ataeian et al., 2019 ; Ataeian et al., 2021 ; Ataeian et al., 2022 ). This cyanobacterial consortium was inoculated at an initial concentration of 0.43 ± 0.10 g/L AFDW (Day 0, Figure 3A ). Initially the alkalinity was 0.5 ± 0.003 M, and the pH was 10.46 ± 0.02 (Day 0, Figure 3B ). A 4-day incubation period was chosen because the biomass growth plateaued after 4 days of incubation in previous experiments, presumably due to nitrogen sources being fully depleted ( Ataeian et al., 2019 ). The cultures exhibited an initial lag phase followed by growth ( Figure 3A ). A lag phase is common for many bacteria and algae, including the green algae Desmodesmus sp. F2 ( Huang et al., 2012 ). Overall, cultures grew well without any apparent growth inhibition to a final biomass concentration of 1.04 ± 0.12 g/L AFDW. In parallel, the pH increased to 10.69 ± 0.1 (Day 4, Figures 3A,B ). The corresponding volumetric biomass productivity (0.15 gL −1 d −1 AFDW, estimated using Eq. 3) was higher than previously reported (0.048 gL −1 d −1 AFDW) ( Vadlamani et al., 2017 ). The improvement in biomass productivity was likely due to a higher initial inoculum concentration and higher light intensities used in this report. FIGURE 3 \n (A) Increase in the biomass concentration and (B) change in pH (left y -axis) and total alkalinity (right y -axis) over the incubation period. Error bars represent the standard deviation of the triplicate samples for each time point. Nutrient analysis of supernatant and biomass The estimated bicarbonate depletion observed at the end of the growth period was 16.4 ± 1.4 mM ( Figure 4B ). Simultaneously, an increase in carbonate concentration was also observed (8.1 ± 0.18 mM, Figure 4B ). Since for every 1 mol of carbon fixed, 2 mol of bicarbonate are converted and 1 mol of carbonate is produced ( Ataeian et al., 2019 ), the remainder of the bicarbonate decrease (8.4 ± 1.4 mM) was attributed to uptake by the cyanobacterial consortium. However, the net increase in organic carbon in the biomass (estimated from CHN analysis and gains in the ash free dry biomass concentration) was 22.9 ± 0.72 mM ( Figure 4B ). Thus, the net increase in organic carbon content was more than twice as much as could be sourced from the bicarbonate added to the medium. Additional bicarbonate was most likely added to the medium by spontaneous air-capture of CO 2 during cultivation ( Vadlamani et al., 2017 ; Ataeian et al., 2019 ; Vadlamani et al., 2019 ). FIGURE 4 \n (A) Soluble nitrogen (NH 4 \n + and NO 3 \n − ) depleted in the media and change in biomass. (B) Bicarbonate (squares, left y -axis) and carbonate (circles, left y -axis) concentration in the media and change in carbon in the biomass (mM) (triangles, right y -axis). (C – E) Concentration of elements (P, S and K) in the spent media and change in the biomass. Values shown in the graphs are averages based on three replicates and error bars represent the standard deviation of the triplicate samples for each time point. Uptake and depletion of nitrogen, phosphorus, sulfur, and potassium were analyzed along with carbon ( See \n Figure 4 ). Figure 4A shows that the initial NO 3 \n − concentration was 2.97 ± 0.07 and the initial NH 4 \n + concentration was 0.75 ± 0.04 mM. By the end of the growth period the nitrogen was almost fully depleted with only 0.16 ± 0.03 mM of nitrate remaining in the media (Day 4, Figure 4A ). Concomitantly, the amount of organic nitrogen in the biomass increased, equivalent to an uptake of 4.15 ± 0.03 mM (Day 4, Figure 4A ). Although there was no significant increase in biomass during the lag phase ( Figure 4A ), 50% of the nitrogen supplied was consumed during this period ( Figure 4A ). The decoupling of nutrient uptake and biomass growth, known as luxurious uptake, is a well-documented phenomenon occurring in cyanobacteria and microalgae. See for example, Huang et al. (2012) . The initial phosphorus concentration in the growth medium was 1.32 ± 0.04 mM (Day 0, Figure 4C ). By the end of day 4, the final concentration of phosphorus in the media was 1.18 ± 0.03 mM ( Figure 4D ), which means nearly 0.14 ± 0.01 mM (Day 4, Figure 4C ) of the phosphorus was depleted in the growth medium. This indicated that nearly 90% of the added phosphorus was left unused in the growth medium. Simultaneously, the concentration of phosphorus in the biomass increased by 0.25 ± 0.10 mM at the end of day 4 ( Figure 4D ). On day 0 the sulfur concentration in the growth medium was 1.1 ± 0.04 mM ( Figure 4D ) and by day 4 the final concentration was 0.95 ± 0.02 mM ( Figure 4D ), which means 86% of the initial sulfur added to the medium remained unused. This result was supported by the estimated uptake of sulfur in the biomass after 4 days, which was 0.16 ± 0.07 mM. Finally, the initial potassium concentration in the media was 8.79 ± 0.25 mM (Day 0, Figure 4E ) and by day 3 the concentration was 8.05 ± 1.70 mM (Day 3, Figure 4E ). The potassium concentration on day 4 was not reported because it had a high margin of error. The concentration of potassium in the biomass increased by 0.36 ± 0.13 mM over 4 days (Day 4, Figure 4E ). ICP-MS measurements showed that the soluble fractions of Mg, Ca, and Fe in the fresh medium were 0.30, 0.32 and 0.17, respectively in the fresh medium ( Table 1 ). A previous study showed that the concentration of these elements is also low in the alkaline Soda Lakes (Cariboo, BC) from which this microbial community was collected ( Zorz et al., 2019 ). We hypothesize that the alkaliphilic microbial consortium is adapted to cope with low concentrations of Mg, Ca, Co, and Fe, for example by expressing high affinity ABC transporters, producing siderophores and siderophore receptors ( Chakraborty et al., 2019 ; Årstøl and Hohmann-Marriott, 2019 ). Results from Ataeian et al. (2021) revealed that the dominant species in the cyanobacteria consortium ( Candidatus “Phormidium alkaliphilum”) used in this study, contains the genes required for iron scavenging using ABC transporters, siderophores and siderophore receptors. The type of siderophores that would be produced are classified as hydroxamates ( Ataeian et al., 2021 ). In addition, this cyanobacterium appeared to have minimized gene content dependent on Cobalt. The concentration of Fe, Ca, and Mg in the growth medium was depleted over the incubation period ( Supplementary Figure S2 ). However, as Mg, Ca, and Fe precipitate at high pH, it remains unknown if these elements were assimilated by cells or if the precipitates were trapped in the extracellular polymeric layer surrounding the cells. Consequently, the depletion rate of these three elements (Fe, Ca, and Mg) in the culture medium cannot be directly equated to assimilation. Elemental composition and empirical formula of alkaline biomass Using the experimental data obtained in this study, we estimated the elemental composition of the cyanobacterial consortium ( Table 2 ). For comparison, we also analyzed the elemental composition of microbial mats collected from four different Soda Lakes located in the Cariboo Plateau, British Columbia, Canada: namely, Last Chance Lake (LCL-M), Probe Lake (PL-M), Deer Lake (DL-M), and Goodenough Lake (GEL-M). These mats were used as inoculum for the original enrichment of the cyanobacterial consortium ( Sharp et al., 2017 ). Compared to the consortium, most mat samples were enriched in minerals, such as sodium, copper, manganese, and nickel. These were likely present as precipitates, concentrated by evaporation. Nitrogen and phosphorus were less abundant, likely because of a lower contribution of microbial cells to the mat biomass. Overall, the elemental composition obtained for both the cyanobacterial consortium and the microbial mats collected from the Soda Lakes were still comparable to previously reported pure cultures ( Campanella et al., 1998 ; Volkman and Brown, 2006 ; Silva et al., 2015 ; Tibbetts et al., 2015 ). TABLE 2 Comparison between elements in cultivated cyanobacteria consortium, microbial mats from soda lakes (Cariboo Plateau, British Columbia) and literature values. Elements Cyanobacterial consortium cultivated in lab environment Microbial mats collected from soda lakes Literature values \n a \n \n Day 3 Day 4 DL-M PL-M GEL-M LC-M 2014 2017 2014 2017 2014 2017 2014 2017 C (g/kg) 543.9 ± 2.6 503.0 ± 9.0 303.0 395.3 81.0 262.0 1288.12 528.0 412.0 364.9 175–650 H (g/kg) 72.6 ± 13.5 79.7 ± 31.2 43.8 55.7 11.2 34.2 192.6 73.4 54.1 51.0 ND N (g/kg) 114.0 ± 17.45 85.2 ± 5.3 15.6 35.6 10.1 30.3 91.0 61.1 25.5 31.1 50–105 Ca (g/kg) 1.1 ± 0.4 1.5 ± 1.2 26.9 33.6 79.9 20.5 10.9 91.7 1.9 4.2 3–21 K (g/kg) 21.4 ± 3.6 14.9 ± 3.1 6.2 8.8 8.4 17.2 7.9 20.1 7.8 5.8 6–21 Mg (g/kg) 5.1 ± 0.1 4.2 ± 0.6 74.5 89.8 75.8 40.9 31.5 322.3 5.0 10.3 1–37 Na (g/kg) 63.7 ± 20.1 91.5 ± 10.1 251.4 110.4 178.1 135.3 129.6 281.8 71.6 51.9 7–321 P (g/kg) 13.3 ± 5.7 9.7 ± 3.1 1.4 4.5 6.3 17.6 3.0 11.0 1.0 2.3 0.9–30 S (g/kg) 8.1 ± 0.9 6.5 ± 1.2 5.7 9.3 36.1 10.7 81.4 18.8 21.6 9.2 4–14 Cu (mg/kg) 72.2 ± 0.4 14.7 ± 4.8 90.7 22.6 343.9 39.3 7.1 38.5 19.4 25.4 1–650 Mn (mg/kg) 88.2 ± 20.2 125.3 ± 55.3 313.9 385.1 1873.9 389.2 98.1 765.6 46.5 121.6 17–592 Zn (mg/kg) 49.5 ± 14.0 41.6 ± 9.2 51.7 50.1 212.6 51.6 16.3 75.5 14.8 30.3 2–64 Ni (mg/kg) 7.0 ± 5.7 7.1 ± 3.2 26.3 38.9 180.2 49.4 8.3 60.5 7.9 18.1 1–3 Co (mg/kg) 2.9 ± 0.9 5.9 ± 4.2 8.4 10.0 69.0 14.5 2.3 16.7 1.8 4.4 ND Fe (mg/kg) 2.3 ± 0.5 2.9 ± 1.8 ND ND ND ND ND ND ND ND 83–7,000 Deer Lake Microbial Mat (DL-M), Probe Lake Microbial Mat (PL-M), Goodenough Lake Microbial Mat (GEL-M) and Last Chance Lake Microbial Mat (LC-M). ND is no data. a From Silva et al. (2015) , Tibbetts et al. (2015) , Campanella et al. (1998) , Volkman and Brown (2006) . We used the elemental composition reported in Table 2 to calculate the empirical formula for the cyanobacterial consortium and microbial mats. The formula for the cyanobacterial consortium was CH 1.81 N 0.17 O 0.20 P 0.013 S 0.09; results for all empirical formulas are shown in Supplementary Table S1 . Although this formula pertains to a microbial consortium, the stoichiometry of C to HNOPS was similar to cyanobacteria grown in pure culture ( Figure 5 and Supplementary Table S2 ). With regards to CHNO, all forms of cellular biomass are very close, but many (eukaryotic) micro-algae have up to four times lower nitrogen content. This difference can be explained by the higher protein content of cyanobacteria. FIGURE 5 Biomass elemental composition of the cyanobacterial consortium relative to carbon. For comparison, literature values for Algae (Eukaryotes) and Cyanobacteria are shown. See \n Supplementary Table S2 for tabulated values and literature references. Error bars represent the interquartile range and solid lines represent the median. Asterisk represents the elements in the literature where only a single data point was collected for M. aeruginosa. \n Interestingly, the consortium’s Ca and Mg was low compared to the values previously reported for other cyanobacteria such as M. aeruginosa . This may be due to the consortium originating from soda lakes with a pH >10 where the solubility of Ca and Mg is low. Therefore, it may be naturally adapted to use less Ca and Mg. The iron content in the consortium was up to five times higher than for most (eukaryotic) micro-algae, but it remains unknown if this Fe was cellular or was present in the extracellular polymeric matrix. Regrowth of the cyanobacterial consortium in spent medium One way to reduce the costs and improve the sustainability of algal cultivation is reusing the spent cultivation medium ( Yang et al., 2011 ; Farooq et al., 2015 ; Lu et al., 2020 ). Depending on the culture and growth conditions, this may or may not be possible ( Loftus and Johnson, 2017 ; Lu et al., 2020 ). In some cases, the reuse of spent cultivation medium has caused cultures to crash or suffer, while spent medium has also promoted growth ( Lu et al., 2020 ). \n Figure 4 shows that the inorganic carbon and nitrogen provided in the growth medium were significantly depleted. Therefore, to enable reuse of spent medium, inorganic carbon and nitrogen need to be supplemented. As more than 80% of the P, S and K remained unused ( Figure 4 ), these nutrients would only need to be supplemented less than once every five growth cycles. To investigate the consequences of reusing spent cultivation medium for growth, the cyanobacterial consortium was inoculated into freshly prepared media in a 12 L carboy (working volume = 10 L) at a pH of 10.5 and alkalinity of 500 mM. After 6 days the biomass was harvested by centrifugation. In the (unsterilized) spent medium, the nitrogen concentration was restored to 4 mM of combined nitrate and ammonium and the bicarbonate concentration was restored by sparging with CO 2 . The spent medium was not sterilized to mimic an actual commercial scale process more closely, where the high energy needs of sterilization would compromise both sustainability and economics. Part of the harvested biomass was added back to start the next growth cycle. In total, four growth cycles were carried out like this in triplicate (three carboy’s) using spent medium over a period of 24 days. Biomass growth \n Figure 6 shows the biomass growth in experiments with freshly prepared medium (cycle 1) and spent medium (cycles 2–5). The average biomass productivity (67.1 ± 0.4 mg-AFDW L −1 d −1 ) in 12 L carboys during cycle 1 was lower than in 0.5 L Erlenmeyer flasks (150 ± 20 mg-AFDW L −1 d −1 ), even though the same growth medium was used ( Section 3.2 ). This decrease in productivity was likely caused by reduced light penetration due to the larger cultivation volume ( Supplementary Figure S3 ). The width of the 12 L carboy was 10 inches, compared to four inches for the Erlenmeyers. With spent medium in cycle 2, both the biomass concentration (0.45 g-AFDW L −1 , see \n Figure 6B ) and the estimated productivity (48.2 ± 5.7 mg-AFDW L −1 d −1 ) decreased by 25% compared to with freshly prepared medium in cycle 1. In cultivation cycles 3 and 4, the biomass concentration and productivity recovered ( Figure 6B ). Nevertheless, it was still 20% lower than with fresh medium. In the final growth cycle, the biomass concentration (0.59 g-AFDW L −1 ) and productivity (60.8 ± 8.0 mg-AFDW L −1 d −1 ) were comparable to fresh medium ( p > 0.05, ANOVA single factor) ( Figure 6B ). This showed that the consortium acclimatized to the spent media. All cycles (1–5) displayed a consistent relationship between growth and pH ( Figure 6A ). FIGURE 6 \n (A , B) Biomass growth and pH overtime in the fresh (cycle 1) and spent medium (cycle 2–5). (C , D) Nitrogen and carbon accumulated in the biomass overtime in the fresh (cycle 1) and spent medium (cycle 2–5). Error bars represent the standard deviation of the triplicate samples for each time point. The dashed vertical lines represent the transition between one growth cycle and the next. Biomass and supernatant composition Carbon uptake, measured as AFDW, was consistent with the carbon depletion in the media. Further, the carbon to nitrogen ratio across all cycles was 1:0.2, consistent with the carbon to nitrogen ratio reported above ( Figures 6C,D ). The carbohydrate, protein, and ash content of the harvested biomass at the end of each cycle is reported in Table 3 . The most significant change was observed in the ash content, which decreased from 21% at the end of the first cycle to 12% at the end of the last cycle. This may be explained by decreasing amounts of precipitated minerals in the media after each cycle, as part of these minerals get removed when biomass is harvested. Carbohydrates and protein content only displayed minor variations, with carbohydrates varying in the range 9–12%, and proteins fluctuating around 56–68%. This was consistent with the stable carbon to nitrogen ratio that was reported above for all cycles. These results suggest that reusing spent media did not have a significant influence on the biochemical composition of the cyanobacterial consortium. TABLE 3 Biochemical composition (carbohydrates, protein, and ash) of the cyanobacterial consortium over five cycles of reusing spent medium. Cycle Carbohydrate (%) Protein (%) Ash (%) 1 10.15 ± 0.41 56.97 ± 6.19 21.19 ± 0.79 2 9.60 ± 1.06 63.35 ± 5.16 16.63 ± 0.44 3 10.58 ± 0.45 64.52 ± 1.16 15.05 ± 0.81 4 11.07 ± 0.69 64.11 ± 4.76 15.06 ± 2.23 5 11.48 ± 0.68 67.57 ± 4.58 12.05 ± 1.17 Throughout the experiments, the concentration of sodium in the media remained stable at around 500 mM, while potassium decreased from 4.72 mM ± 0.15 to 3.80 ± 0.14 mM at the end of cycle 5 ( Supplementary Figure S4 ). Both phosphorus and sulfate concentrations decreased drastically in cycle 1 compared to the cycles where spent medium was used (cycles 2–5). Overall, the decrease of both elements after each cycle declined. For example, in cycle 2 phosphorus decreased by 17%, but decreased by only 8% in cycle 3 ( Supplementary Figure S4 ). The phenomenon that could explain this is called luxurious uptake ( Solovchenko et al., 2019 ). This is when microorganisms such as cyanobacteria, which grow typically in low phosphorus and sulfur environments, assimilate more than they need of any nutrient and store it. It is possible that at first, a large amount of both elements was uptaken and stored, but over time since so much was already assimilated the consortium needed less of these elements. Previous studies using low-sodium (<20 mM) media ( Mokashi et al., 2016 ; Barbera et al., 2018 ) have reported a loss of productivity due to evaporation, resulting in an increase in salinity ( Discart et al., 2014 ; Church et al., 2017 ; Lu et al., 2019 ; Lu et al., 2020 ). This was not an issue for the cyanobacterial consortium used here, obtained from alkaline soda lakes, and grown in high alkalinity medium (0.5 mol L −1 NaHCO 3 ), as shown by a complete recovery of productivity after five growth cycles. It is conceivable that the initial reduction in productivity was caused by the accumulation of organic compounds, as previously observed ( Rodolfi et al., 2003 ; Discart et al., 2014 ; Depraetere et al., 2015 ; Lu et al., 2019 ; Lu et al., 2020 ). Indeed, the spent medium had a yellow/greenish colour, likely associated with remains of cell lysis during harvesting by centrifugation, also observed previously ( Rodolfi et al., 2003 ; Singh and Patidar, 2018 ). Some of thse coloured compounds might have directly inhibited regrowth but could also simply have reduced light penetration, resulting in lower growth. In either case, if the accumulation of organic compounds was the cause of the initial loss of activity, it is likely that the heterotrophic bacteria, that were also part of the cyanobacterial consortium, started to consume these organic compounds and so facilitated the acclimatization of the culture. Many of these heterotrophs can grow on cyanobacterial metabolites and components such as cell walls, proteins, lipids and fatty acids ( Ataeian et al., 2022 )."
} | 8,752 |
37242092 | PMC10223044 | pmc | 8,929 | {
"abstract": "Sound wave is an extensively existing mechanical wave, especially in marine and industrial plants where low-frequency acoustic waves are ubiquitous. The effective collection and utilization of sound waves provide a fresh new approach to supply power for the distributed nodes of the rapidly developing Internet of Things technology. In this paper, a novel acoustic triboelectric nanogenerator (QWR-TENG) was proposed for efficient low-frequency acoustic energy harvesting. QWR-TENG consisted of a quarter-wavelength resonant tube, a uniformly perforated aluminum film, an FEP membrane, and a conductive carbon nanotube coating. Simulation and experimental studies showed that QWR-TENG has two resonance peaks in the low-frequency range, which effectively extends the response bandwidth of acoustic–electrical conversion. The structural optimized QWR-TENG has excellent electrical output performance, and the maximum output voltage, short-circuit current and transferred charge are 255 V, 67 μA, and 153 nC, respectively, under the acoustic frequency of 90 Hz and sound pressure level of 100 dB. On this basis, a conical energy concentrator was introduced to the entrance of the acoustic tube, and a composite quarter-wavelength resonator-based triboelectric nanogenerator (CQWR-TENG) was designed to further enhance the electrical output. Results showed that the maximum output power and the power density per unit pressure of CQWR-TENG reached 13.47 mW and 2.27 WPa −1 m −2 , respectively. Application demonstrations indicated that QWR/CQWR-TENG has good capacitor charging performance and is expected to realize power supply for distributed sensor nodes and other small electrical devices.",
"conclusion": "4. Conclusions In this paper, a novel acoustic triboelectric nanogenerator QWR-TENG was firstly presented for the efficient collection of low-frequency sound wave energy. QWR-TENG was coupled by a quarter wavelength resonant tube and a contact-separation TENG to achieve acoustic–electrical conversion within a broad bandwidth. Simulation and experimental results showed that QWR-TENG was characterized by two resonance modes in the low-frequency range of 30~250 Hz, which can effectively extend the response bandwidth of the sound energy collector. The effects of structural parameters, including the length and cross-sectional diameter of the quarter-wavelength tube, the thickness of the FEP film, and the power generation area, were experimentally studied to enhance the electrical output performance of QWR-TENG. Results showed that the peak open-circuit voltage, short-circuit current, and transferred charge of the optimized QWR-TENG reached 255 V, 67 µA, and 153 nC, respectively. On this basis, a conical concentrator was introduced to the open end of the QWR to form a composite quarter-wavelength resonator-based triboelectric nanogenerator CQWR-TENG to further improve the electrical output of the acoustic collector. Experimental results showed that compared with QWR-TENG, the peak open-circuit voltage, short-circuit current, and transferred charge of CQWR-TENG increased by 43%, 33%, and 38%, respectively. More specifically, the maximum output power and the power density per unit pressure reached 13.47 mW and 2.27 WPa −1 m −2 . Demonstration experiments on capacitor charging and sensor power supply showed that the proposed QWR/CQWR-TENG has good output performance and the application potential in the field of acoustic energy collection. The response characteristics of being low-frequency and having a wide bandwidth make the QWR/CQWR-TENG promising for sound energy collection in marine and industrial plants, and to power distributed sensor nodes.",
"introduction": "1. Introduction With the rapid development of artificial intelligence (AI) and Internet of Things (IoT) technologies, the demand for distributed energy resources has increased dramatically [ 1 , 2 , 3 , 4 , 5 ]. As a clean, widespread, and sustainable energy source, sound waves are almost ubiquitous in the environment. In general, sound waves with frequencies ranging from 0 to 500 Hz are defined as low-frequency acoustic waves [ 6 , 7 , 8 ]. Such kinds of sound waves are characterized by low energy density and long wavelengths, and are able to penetrate obstacles and propagate over long distance. Notably, the acoustic waves in marine and industrial plants are mainly characterized by low-frequency and high sound pressure levels [ 9 , 10 ]. The application of acoustic energy collection technology is expected to provide a novel way to achieve acoustic–electrical conversion and supply power for the widely distributed sensors in the above-mentioned scenarios [ 11 , 12 , 13 ]. The basic principle of sound energy collection technology is to amplify sound waves using acoustic amplification devices such as Helmholtz resonator, tube resonator and acoustic metamaterials, and then convert the mechanical vibration energy into electrical output based on electromagnetic induction, piezoelectric effect, triboelectric effect or hybrid mechanism. In specific, acoustic energy harvesting devices based on electromagnetic induction use sound waves to drive conductors to cut magnetic lines in the magnetic field and generate induced current. Khan et al. [ 14 ] combined the Helmholtz resonator cavity with an electromagnetic generator for sound energy collection. The device generated a root-mean-square load voltage of 319.8 mV and a maximum power output of 1966.77 μW. On this basis, Izhar et al. [ 15 ] used a conical Helmholtz resonator to improve the electrical output of the sound energy collector. Results showed that the harvester had two resonance frequencies of 330.3 and 1332 Hz. At the first resonance frequency, the device generated a peak power of 177.2 mW under the incident sound pressure of 100 dB, which effectively improved the electrical output. However, due to the large scale of electromagnetic generator structures and the low conversion efficiency between sound waves and electromagnetic waves, external magnetic fields are usually required, resulting in low sound energy collection efficiency. Piezoelectric materials have good vibration sensitivity and can undergo mechanical deformation under the action of sound waves to generate electric fields. Yuan et al. [ 16 ] designed a sound energy collector consisting of an adjustable Helmholtz resonator, a fixed piezoelectric disk and a correction mass body. The device generated an output power of 3.49 μW and an energy conversion efficiency of 38.4% under an incident sound pressure of 100 dB. In addition to the traditional resonators, Qi et al. [ 17 ] proposed a new concept of using planar acoustic metamaterial to absorb and utilize high-frequency sound waves. Generally, the piezoelectric materials are susceptible to external interference and the output efficiency is relatively low. The triboelectric nanogenerator (TENG), driven by Maxwell displacement currents, can effectively convert distributed and disordered mechanical energy into electrical energy, and has shown great potential in energy collection [ 18 , 19 , 20 , 21 , 22 ] and self-powered systems [ 23 , 24 , 25 , 26 , 27 , 28 , 29 ]. In particular, the high vibration sensitivity of TENG makes it a possible high-efficient acoustic collection technology [ 20 , 30 , 31 ]. In recent years, researchers have conducted some studies on acoustic energy harvesting using TENG technology. In 2016, Yang et al. [ 32 ] designed a sound energy harvester by combining an adjustable Helmholtz resonant cavity with a contact-separation triboelectric nanogenerator. The design of a flexible film-based acoustic triboelectric nanogenerator was achieved for the first time, and good acoustic–electrical conversion efficiency was obtained at a resonant frequency of 240 Hz. Recently, Zhao et al. [ 33 ] proposed a dual-tube Helmholtz resonator-based triboelectric nanogenerator (HR-TENG). Compared to the previous acoustic TENGs based on traditional Helmholtz resonant cavities, the HR-TENG has a better output performance, with the maximum output voltage increased by 83%. The open-circuit voltage and short-circuit current reached 132 V and 32 µA at the optimal acoustic frequency. On this basis, Yuan et al. [ 34 ] presented an acoustic triboelectric nanogenerator using a conical Helmholtz resonator, which further improved the output performance of the sound energy harvester. Furthermore, Fan et al. [ 35 ] designed a paper-based triboelectric nanogenerator of 125 μm thickness to collect sound wave energy. The device generated a power density of 121 mW/m 2 at the frequency of 320 Hz and a sound pressure level of 117 dB. Xu et al. [ 36 ] developed a self-powered laminated electrospun nanofiber triboelectric nanogenerator for sound energy harvesting. The open-circuit voltage was 170 V when two TENGs were stacked and operated at a frequency of 200 Hz. The above research shows that triboelectric nanogenerator technology has provided an effective way for efficient sound energy collection. However, the current researches mainly focus on acoustic waves with relatively high frequency, and can only achieve acoustic–electrical conversion in a narrow bandwidth, which greatly constrains the application of sound energy harvesters. Quarter-wavelength resonator (QWR) is a typical acoustic amplifier with superior characteristics of simple structure, excellent sound pressure amplification effect, and wide resonance bandwidth, which has great potential for low-cost large-scale production [ 37 , 38 , 39 ]. Therefore, this paper presented a quarter-wavelength resonator-based triboelectric nanogenerator QWR-TENG for low-frequency acoustic energy harvesting. Based on the bimodal resonance characteristic of the acoustic–electrical coupling system in the low-frequency range, QWR-TENG has an excellent electrical output performance and effectively broadens the response bandwidth of acoustic TENG. Furthermore, a composite quarter-wavelength resonator-based triboelectric nanogenerator CQWR-TENG was proposed by introducing a conical energy concentrator to further improve the sound-electrical conversion efficiency and the electrical output. The as-designed sound energy harvester QWR/CQWR-TENG is expected to provide a low-power and cost-effective power solution for IoT technology.",
"discussion": "2. Results and Discussion 2.1. Structure Design and Working Principle of QWR-TENG Figure 1 a depicts the application scenario of QWR/CQWR-TENG in various low-frequency sound sources such as ships and industrial plants. The QWR/CQWR-TENG can provide electrical energy for distributed wireless sensor nodes through acoustic energy harvesting. QWR-TENG consists of a quarter-wavelength resonant tube and a contact-separation TENG fixed on the closed side of the tube. As shown in Figure 1 b, the TENG is composed of a uniformly perforated aluminum film, a flexible FEP film, and a carbon nanotube conductive ink layer. To improve the electrical output of QWR-TENG, the FEP film was sanded with 10,000 grit sandpaper. Figure 1 b also shows the SEM images of the surface morphology of the FEP film before and after polishing. It can be seen that the surface roughness and the micro/nanostructures of the FEP film are significantly increased after sanding. The sound waves produced by the sound source propagate in the form of vibration. In QWR-TENG, the quarter-wavelength resonant tube is used to amplify the acoustic waves, and then TENG technology is applied to convert the sound waves from vibration energy into electricity. The specific working principle is shown in Figure 1 c. The FEP membrane is initially separated from the aluminum electrode, and the electrons in the aluminum film are free electrons. Under the excitation of sound waves, periodic pressure changes occur between the aluminum electrode and the FEP film, which cause the FEP membrane to vibrate and generate contact-separation with the aluminum film. When the FEP film comes into contact with the aluminum electrode, the FEP film becomes negatively charged due to its high electronegativity, and an equal amount of positive charge is generated on the aluminum electrode ( Figure 1 (ci)). Under the action of the changing sound pressure, the FEP membrane is separated from the aluminum electrode, and the positive and negative charges no longer overlap in the same plane, resulting in a dipole moment and potential difference between the surfaces. Therefore, free electrons are driven to flow between the top carbon nanotube electrode and the bottom aluminum electrode through an external circuit to balance the local electric field ( Figure 1 (cii)). The flow of electrons ceases when the separation between the two contact surfaces reaches its maximum ( Figure 1 (ciii)). Thereafter, the FEP film starts to move in the opposite direction and approach the bottom aluminum electrode. At this stage, the potential difference between the two electrodes weakens, and free electrons flow back to the top carbon nanotube electrode, thus generating a reverse current ( Figure 1 (civ)). Finally, the FEP film and the aluminum electrode come into contact again to complete a full power generation cycle ( Figure 1 (ci)). Figure 1 d displays the potential changes on different electrodes obtained by COMSOL Multiphysics simulation. Apparently, the simulation results were consistent with the above analysis. Therefore, continuous alternative current (AC) pulses were generated in the external circuit of QWR-TENG and the conversion of mechanical energy into electrical energy was realized. 2.2. Bimodal Resonance Characteristic of QWR-TENG Figure 2 a shows the schematic diagram of the experimental system for acoustic energy harvesting. The signal generator generates a sinusoidal electrical signal and drives the loudspeaker to produce sound waves. The frequency and sound pressure of the sound waves are controlled by the frequency and voltage of the electrical signal. During the experiment, the acoustic energy harvester is placed in an acrylic cover with soundproofing cotton on all sides to form a good sound insulation and shock absorption environment and ensure the accuracy of the experimental values. Under the excitation of sound waves, the triboelectric nanogenerator generates electrical signals through contact and separation between the dielectric material and the metal electrode. The electrical output is detected by an electrostatic high-impedance meter and collected by a data acquisition card. The quarter-wavelength resonator is an important component of the acoustic energy harvester QWR-TENG, and its acoustic performance directly affects the electrical output of the device. QWR is a common acoustic amplification device, and its basic structure is a straight pipe with one end open and the other end closed. In order to systematically study the acoustic field of the quarter-wavelength resonator and its influence on the electrical output of QWR-TENG, the sound pressure difference of the quarter-wavelength tube and the output voltage of the triboelectric nanogenerator were measured at the inlet acoustic frequency of 30 to 250 Hz. As shown in Figure 2 b, two peaks of sound pressure difference appeared in the resonator of QWR-TENG within the frequency band, which corresponded to the two natural resonance frequencies of 80 and 210 Hz, respectively. It is worth noting that the sound pressure difference caused by the first-order resonance in the quarter-wavelength resonant tube is significantly higher than that formed by the second-order resonance, that is, the sound pressure amplification factor attenuates at higher resonant mode. Specifically, the sound pressure difference reached 15.6 dB at the resonant frequency of f = 80 Hz, while the value was only 11.5 dB at the resonance frequency of f = 210 Hz. Consistent with the variation trend of the sound pressure difference, there were two output peaks in the open-circuit voltage of QWR-TENG as the frequency increased, which were 194 and 158 V, respectively. Since a larger acoustic pressure difference can enhance the contact-separation between the dielectric material and the aluminum electrode of TENG, a higher electrical output was generated at the first resonance frequency. According to the acoustic theory of pipelines, each resonance frequency corresponds to a specific vibration mode, and the resonant of the system is named the first-order characteristic mode and the second-order characteristic mode in order of increasing resonant frequency [ 40 , 41 ]. Due to the bimodal resonance characteristics of QWR, the QWR-TENG can be used to collect sound wave energy with a broad bandwidth in the low-frequency region. Furthermore, the acoustic field distribution in the quarter-wavelength resonant tube and the vibration characteristic of the FEP film in the acoustic field were studied by using the acoustic-solid coupling numerical simulation method based on COMSOL 6.0 software. Figure 2 c,d show the variation of sound pressure level (SPL) in the quarter-wavelength resonator and the vibration mode of the FEP membrane at the first-order resonance and the second-order resonance, respectively, in which the FEP film is subjected to a tensile stress of 10 N∙m −1 . It can be seen that the quarter-wavelength resonator has a significant sound pressure amplification effect regardless of the resonant mode. Especially in the first-order resonance mode, the sound pressure level difference between the two ends of the resonant tube can reach 10 dB. In this resonant mode, the vibration displacement of the FEP membrane varies between 1 to 6 μm, and the displacement peak appears in the middle of the membrane and gradually decreases along the circumference. This indicates that both the highest positive pressure level and the lowest negative pressure level appear in the middle of the resonant cavity, which is beneficial for the contact-separation between the FEP membrane and the metal film and the electrical output of the acoustic TENG. When the inlet acoustic frequency exceeds the first resonant frequency, the acoustic field in the quarter-wavelength resonant tube gradually transforms to the second resonant mode. As demonstrated in Figure 2 d, the sound pressure amplification effect decreases at the second-order resonance frequency, and the maximum sound pressure difference between the two ends of the resonator is about 5 dB. More importantly, the sound pressure in the resonator no longer exhibits a circular distribution, but presents multiple symmetrical distributions of sound pressure peaks. Correspondingly, the FEP membrane reveals multiple displacement peaks under the second resonant mode. For the proposed acoustic–electrical coupling system, the stress-strain behavior of the FEP film directly affects its contact-separation with the aluminum electrode, which in turn determines the electrical output of the device. According to the working principle of TENG [ 8 ], its output voltage follows: (1) V o c = σ x ( t ) ε 0 \nwhere V o c is the open-circuit voltage, σ is the charge density, x ( t ) is the film displacement and ε 0 is the dielectric constant. It can be seen that when the material is determined, the dielectric constant is fixed, and the electrical output performance of TENG is related to the film displacement and the charge density of the surface. In the second-order resonance mode, although the peak displacement of the FEP film is enlarged, the specific vibration mode leads to a decrease in the effective contact area between the FEP membrane and the aluminum film, which in turn results in a reduction in the surface charge density. Therefore, the output voltage of QWR-TENG under the second-order resonance mode is reduced compared with that under the first-order resonance mode. 2.3. Output Performance of QWR-TENG In order to optimize the electrical output performance of QWR-TENG, sensitivity studies were conducted on the structural parameters of the acoustic–electrical coupling system, including the power generation unit area of TENG, the thickness of the FEP film, the length, and diameter of the quarter-wavelength resonant tube. The side length and thickness of the square FEP film are defined as d 1 and d 2 , respectively, as shown in Figure 3 a. Figure 3 b displays the influence of the TENG power generation area on the electrical output performance of QWR-TENG. As the side length d 1 of the FEP film increases from 35 to 65 mm, the first-order resonance frequency decreases from 120 to 70 Hz, but the change in second-order resonance frequency is small. This indicates that the response bandwidth of QWR-TENG increases as the effective power generation unit area is enlarged. In addition, the output voltage of QWR-TENG is positively correlated with the power generation unit area. As the power generation area increases, the deformation of the FEP film and its effective contact area with the aluminum electrode is increased. Accordingly, the peak voltage under the first-order and second-order resonance modes increases from 76 to 165 V and from 59 to 125 V, respectively. Similar variations in the output short-circuit current and transferred charge can also be found in Figure S1 of the Supplementary Materials . Therefore, for the acoustic triboelectric nanogenerator with a fixed quarter-wavelength resonant tube, the adoption of a larger TENG dielectric layer can not only increase the electrical output of the sound energy collector, but also extend the response bandwidth and operating range of the device. The effect of the FEP film thickness d 2 on the electrical output of QWR-TENG is shown in Figure 3 c. Three types of FEP film with thicknesses of 30, 50, and 100 μm were tested and the effective area was set at 55 × 55 mm. The input acoustic wave frequency varied from 30 to 220 Hz with a step of 10 Hz during the experiment. On the one hand, as the thickness of the dielectric layer increased from 30 to 100 μm, the first-order resonance frequency decreased from 100 to 50 Hz, while the second-order resonance frequency remained basically unchanged. Therefore, increasing the thickness of the FEP film can expand the working bandwidth of QWR-TENG to a certain extent. Figure S2 in the supplementary reveals the short-circuit current and transferred charge. On the other hand, the electrical output of QWR-TENG did not change monotonically with the increase of film thickness, but showed a trend of first increasing and then decreasing. Specifically, under the first-order resonance mode, the output voltage of QWR-TENG reached 82 V when the FEP film thickness was set to 50 μm, which is 73% and 93% higher than that of the QWR-TENGs with a dielectric layer thickness of 30 and 100 μm, respectively. Furthermore, the peak output voltage was increased by 54% and 82%, respectively, at the second-order resonance frequency. The reason for this phenomenon is that when the thickness of the dielectric layer is increased (30 to 50 μm), its load impedance on the resonator enlarges gradually and is more suitable for the output impedance of the resonator, so the output voltage of QWR-TENG is increased. However, as the thickness of the FEP film is further enlarged (50 to 100 μm), the stiffness of the FEP film enhances significantly, which leads to a decrease in both the elastic deformation and effective contact area. As a result, the electrical output of QWR-TENG is decreased. Thus, in order to achieve the best output performance of QWR-TENG, it is necessary to select a dielectric layer material with a large area and an appropriate thickness for membrane-acoustic cavity coupling. Transmission loss ( T L ) is the key indicator for acoustic performance evaluation [ 42 ]. Generally, it can be expressed as: (2) T L = 20 l g | P i / P t | \nwhere P i and P t represent the incident sound pressure and the transmitted sound pressure at the exit of the resonator, respectively. Therefore, a higher acoustic TL indicates a better resonance effect inside the resonant cavity. Acoustic studies show that the transmission loss TL of the quarter-wavelength resonator is related to quality factors, which mainly include the length, cross-sectional area, and impedance of the resonator. Therefore, the effects of the tube length and diameter of the quarter-wavelength resonator on the output performance of the QWR-TENG were studied. The length and diameter of the quarter-wavelength tube are defined as L and D , respectively, as shown in Figure 3 d. Figure 3 e shows the influence of quarter-wavelength tube length on the resonance frequency and output voltage of the QWR-TENG, in which the length is set as 40, 60, and 80 cm. It can be seen that the QWR-TENG has two output peaks regardless of the length, which corresponds to the two resonance frequencies of QWR. As the length of QWR decreased from 80 to 40 cm, the first-order resonance frequency increased from 70 to 100 Hz, but the output performance was enhanced. As shown in Figure S3 of the supplementary , similar variations can also be observed in short-circuit current and transferred charge. This indicates that the length of QWR-TENG can be adjusted to adapt to various acoustic frequencies. Since the present QWR-TENG is designed to harvest sound energy with low frequency, the QWR with a length of 60 cm was adopted for subsequent research by comprehensively considering the response frequency and electrical output performance. The cross-sectional area of the quarter-wavelength tube is determined by its diameter, so the electrical output of three QWR-TENGs with different tube diameters was tested in the frequency range of 30 to 220 Hz. Figure 3 f shows the output open-circuit voltage of the QWR-TENG, in which the diameter of the quarter-wavelength tube is 95, 80, and 65 mm, respectively. With the increase of pipe diameter and cross-sectional area, the first-order resonance frequency of QWR-TENG increases, but the second-order resonance frequency remains unchanged. More importantly, the electric output of QWR-TENG is effectively enhanced as the cross-sectional area increases. This is because a larger cross-sectional diameter indicates a higher impedance and a greater transmission loss of the resonator, thereby resulting in an increased electrical output of QWR-TENG. When the diameter of the quarter-wavelength resonant tube reached 95 mm, the peak open-circuit voltage of QWR-TENG reached 83 V, as shown in Figure 3 f. Figure S4 in the supplementary reveals the short-circuit current and transferred charge, in which similar variation profiles can be observed. In addition, the impact of the inlet sound pressure level on the electric output of QWR-TENG is described in Figure 3 g–i. The increase in inlet sound pressure amplifies the sound pressure difference at the outlet of the resonant tube, resulting in an enlarged deformation and radial displacement of the FEP membrane. Therefore, the electrical output of QWR-TENG increases with the incident sound pressure. More specifically, as the inlet sound pressure level raised from 50 to 100 dB, the open-circuit voltage, short-circuit current, and transferred charge of QWR-TENG increased from 4 to 255 V, from 1.2 to 67 μA, and from 2 to 153 nC, respectively. Figure S5 in the Supplementary Materials further demonstrates the electrical output of QWR-TENG under the incident sound pressure of 100 dB. 2.4. Structure Design and Optimization of CQWR-TENG The conical cavity structure can effectively guide the propagation of sound waves, and improve the sensitivity and effectiveness of sound radiation [ 43 ]. To further improve the output performance of the proposed acoustic–electrical coupling system, a conical energy concentrator was introduced to the open end of the quarter-wavelength tube to form a composite quarter-wavelength tube resonator-based triboelectric nanogenerator CQWR-TENG. The physical structure of CQWR-TENG and the simplified two-dimensional model of the conical cavity are shown in Figure 4 a. Along the direction of sound wave propagation, the variation of the conical cavity diameter satisfies [ 44 ]: (3) r ( x ) = r ( l ) − x l [ r ( l ) − r ( 0 ) ] \nwhere r ( 0 ) and r ( l ) are the inlet and outlet diameter of the conical cavity, respectively, l is the total length of the conical tube, and x is the length from the inlet end to the certain position inside the conical tube. According to the acoustic amplification theory of the conical cavity, the acoustic amplitude at the outlet of the conical cavity satisfies: (4) A ( x ) = 1 r ( x ) = l [ l r ( l ) − x ( r ( l ) − r ( 0 ) ) ] For a tapered conical cavity, r ( x ) decreases with the increase of x , so the amplitude of the sound wave A ( x ) is magnified along the outlet direction of the conical tube. The sound pressure of acoustic waves is proportional to sound frequency and the square of the amplitude. Therefore, the increase in amplitude directly causes the amplification of sound pressure and sound intensity in the resonance cavity, thereby improving the electrical output of the acoustic energy collector. Figure 4 b,c validate the enhancement effect of the conical concentrator on the output of the acoustic triboelectric nanogenerator. Under the same acoustic condition, the peak open-circuit voltage of QWR-TENG and CQWR-TENG are 242 and 348 V, respectively. Figure S6 in the supplementary displays the detailed output of QWR-TENG and CQWR-TENG under the acoustic frequency of 100 Hz and sound pressure level of 95.8 dB. Compared to QWR-TENG, the application of the conical concentrator increases the open-circuit voltage, short-circuit current, and transferred charge of the TENG by 43%, 33%, and 38%, respectively. In addition, the structural parameters of the conical concentrator have a significant impact on the electrical output of TENG. The effect of the length of the conical cavity on the output performance of CQWR-TENG is displayed in Figure 4 d, in which the lengths x are 5, 6, and 7 cm, respectively. Obviously, with the increase in the length of the conical concentrator, the output of CQWR-TENG is effectively enhanced, with the peak open-circuit voltage increasing from 285.2 to 339.1 V. The fact is that a larger length of the conical tube can make the reflection and interference phenomena more significant and enhance the accumulation of acoustic energy in the tube. This causes the enlargement of sound pressure and the increase of electrical output of CQWR-TENG. Figure 4 e exhibits the effect of the opening diameter r ( 0 ) of the conical concentrator on the output voltage. The open-circuit voltage of CQWR-TENG increased from 275.3 to 358 V as the opening diameter raised from 18 to 24.2 cm. This is because a larger opening diameter can diminish the reflection of sound waves at the entrance. In addition, the energy dissipation of sound waves along propagation can be reduced with a larger entrance diameter, thus maintaining a high amplification effect of sound pressure. In summary, increasing the opening diameter and the length of the conical energy concentrator is beneficial to the enhancement of sound pressure in CQWR-TENG. Therefore, the adoption of a conical energy concentrator is recommended within the available environmental space to increase the electrical output of acoustic TENG and improve the efficiency of acoustic–electrical energy conversion. 2.5. Demonstration of QWR/CQWR-TENG Demonstration experiments were carried out to verify the sound energy harvesting and power generation performance of QWR-TENG and CQWR-TENG, as shown in Figure 5 . Figure 5 a shows the circuit diagram and the results of QWR-TENG charging different capacitors. It takes about 9, 42, and 131 s for QWR-TENG to charge the capacitors of 47, 330, and 1000 μF to 3 V. This indicates that QWR-TENG has a good charging ability for capacitors and can supply electricity for low-power electronics. In addition, as exhibited in Figure 5 b, after charging the 1000 μF capacitor to about 2.7 V, the humidity and temperature sensor was successfully lit by QWR-TENG. The Video S1 in the Supplementary Material shows that the sensor can operate continuously with the power supply of QWR-TENG. Figure 5 c demonstrates the experiment of QWR-TENG lighting up 196 LEDs simultaneously under a sound pressure level of 90.1 dB and a frequency of 100 Hz, and the corresponding video can be found in Video S2 in the Supplementary Material . A demonstration experiment was also conducted in an onshore machinery compartment to test the sound energy harvesting ability of QWR-TENG. The experimental diagram can be found in Figure S6 in the supporting document , in which the sound waves were generated by the operation of a diesel engine. It can be seen that the QWR-TENG can output a voltage signal of 5~8 V at a certain distance from the sound source. The significant difference from the resonance frequency of QWR-TENG results in the limited electrical output of the device. In the future, the design of QWR-TENG structural parameters can be based on the actual industrial application scenarios to make its resonance frequency consistent with the frequency of the equipment, which is conducive for the application of QWR-TENG in sound energy harvesting. The introduction of the conical accumulator can further enhance the sound energy collection and electrical output performance of the acoustic triboelectric nanogenerator. Figure 5 d depicts the variation of CQWR-TENG output with external resistance under the acoustic condition of 90 Hz and 100 dB. As the external load resistance increased from 1 to 10 MΩ, the output current of CQWR-TENG gradually decreased from 91.5 to 20.7 μA. However, the output power of CQWR-TENG increased first and then decreased. Specifically, the maximum output power and the power density per unit pressure of CQWR-TENG reached 13.47 mW and 2.27 WPa −1 m −2 , respectively. The comparison with the earlier electromagnetic, piezoelectric, and triboelectric nanogenerator-based sound energy harvesters is presented in Table S1 of the supporting document [ 8 , 14 , 17 , 32 , 33 , 38 , 39 , 45 , 46 , 47 , 48 ], and the results indicate that the as-presented QWR-TENG has a superior performance in low-frequency acoustic–electrical conversion. Furthermore, the durability test result of CQWR-TENG is shown in Figure 5 e. After seven days of operation, the electrical output decreased by about 1%, which confirmed the robustness of CQWR-TENG. Therefore, the as-designed QWR/CQWR-TENG has great application potential in the field of acoustic power generation, and is expected to be applied to specific acoustic scenarios for environmental low-frequency sound energy harvesting."
} | 8,691 |
36593317 | PMC9807645 | pmc | 8,931 | {
"abstract": "In insect-pollinated plants, the foraging behavior of pollinators affects their pattern of movement. If distinct bee species vary in their foraging behaviors, different models may best describe their movement. In this study, we quantified and compared the fine scale movement of three bee species foraging on patches of Medicago sativa. Bee movement was described using distances and directions traveled between consecutive racemes. Bumble bees and honey bees traveled shorter distances after visiting many flowers on a raceme, while the distance traveled by leafcutting bees was independent of flower number. Transition matrices and vectors were calculated for bumble bees and honey bees to reflect their directionality of movement within foraging bouts; leafcutting bees were as likely to move in any direction. Bee species varied in their foraging behaviors, and for each bee species, we tested four movement models that differed in how distances and directions were selected, and identified the model that best explained the movement data. The fine-scale, within-patch movement of bees could not always be explained by a random movement model, and a general model of movement could not be applied to all bee species.",
"conclusion": "Conclusions For some bee species, bee movement cannot be explained by a simple random movement model, but resource information collected by the individual, and persistence of movement directionality must be considered. Bee species differ in foraging behaviors that affect movement, and different models best describe movement for distinct bee species. A general movement model should not be applied to all bee species.",
"introduction": "Introduction The vast majority of flowering plants are pollinated by insects. Pollinating insects move between flowers, picking up pollen from one flower and depositing it on the next flower visited. Different aspects of pollinator behavior, such as the distances and directions traveled between racemes and between plants 1 – 3 , and the number of flowers visited within a foraging bout or residence 4 , will influence how far a pollinator moves, together with the pollen it carries. A foraging bout represents one pollinator visit in a patch, and a patch is a group of plants growing in the same area and spatially separated from other groups of plants. Pollinators exhibiting directionality of movement, where directions of successive flight segments are correlated within foraging bouts, tend to move farther net distances relative to pollinators that move randomly among flowers 1 , 5 . A net distance describes the distance between where a pollinator starts and ends foraging in a patch; it is the direct line between the first and last flowers or inflorescences visited in a foraging bout. The net distances traveled by pollinators will influence the distances traveled by the pollen they carry and the resulting seeds. It is therefore important to understand pollinator movement because it influences how pollinators affect pollen dispersal and gene flow. Modeling animal movement has been an important goal for animal ecologists, and studies have recognized the importance of linking behavior to models of animal movement 6 , 7 . For many animal species, models of movement are built from estimated distances and directions traveled based on telemetry data, and different statistical methods exist to analyze individual animal tracking data, depending on the type of movement data available 8 , 9 . These modeling approaches tend to examine the movement of larger animals over the landscape 9 . For bees, harmonic radars have been successfully used to accumulate location data every three seconds, and with a position precision within ± 3 m, at least on flat terrains without obstacles 10 – 12 . These data have provided useful information on various aspects of bee behavior, including their foraging range 11 , the ontogeny of bumble bee flight trajectories 12 , 13 , and dispersal patterns of bumble bee queens after hibernation 14 . The location data obtained with harmonic radars provide information on larger-scale movements of bees. To fully understand bee movement, however, one must consider not only the behavioral rules used by bees at a larger scale, but also the rules used at the smaller, local scale 7 . This fine-scale movement describes bees moving from flower to flower, inflorescence to inflorescence, and plant to plant, movement patterns that occur at a scale typically less than three meters 2 , 15 . Fine-scale movement best delineates bees moving within a patch or an agricultural field, considered continuous landscapes. Previous studies at this smaller scale have examined how reward quantity and quality 15 – 17 , and floral and plant traits, including floral display size and flower color 18 , 19 affect plant, inflorescence, and flower choices, together with the role of learning in these selection processes 20 . Various studies have examined the development of traplines (multi-destination routes) by bees, both empirically and via models that examined factors affecting the process 21 – 24 . Methods of resource partitioning by traplining bees has also been recently modeled 25 . While traplining aimed at describing bees moving among flowers, the low number of artificial flowers or feeding stations used to empirically examine the process (< 10), and the associated modeling, may best describe movement among patches 23 , 26 , and thus movement at a larger scale 23 . Here, we examine the fine scale movement of three bee species that pollinate Medicago sativa flowers and, for each bee species, identify the model that best describes their movement. The three bee species are the honey bee, Apis mellifera L., the common eastern bumble bee, Bombus impatiens Cresson , and the alfalfa leafcutting bee, Megachile rotundata F. We examine fine-scale movement of bees on plants that can each bear 100–1000 flowers 19 , and do not control for any plant traits such as floral display size. To describe within patch movement, we measured distances and directions traveled between consecutive racemes, and number of flowers visited per raceme, and for each bee species, we tested four models of bee movement. Each model differed in the method used to select distances and directions traveled between consecutive racemes (inflorescences) (Table 1 ). The best model for each bee species was identified using a randomization approach. Results indicated differences among bee species in their foraging behaviors, and distinct models best explaining bee movement for the different species. Table 1 The four models of bee movement. Model Distance Direction Model I: Random distance-random direction Distance obtained from the distribution of distances traveled between consecutive racemes for a bee species Direction obtained from the distribution of directions traveled between consecutive racemes for a bee species Model II: Random distance-modeled direction Distance obtained from the distribution of distances traveled between consecutive racemes for a bee species Direction determined using the matrix of transition probabilities or the transition vector for a bee species Model III: Modeled distance-random direction Distance obtained from the best statistical model for distance for a bee species Direction obtained from the distribution of directions traveled between consecutive racemes for a bee species Model IV: Modeled distance-modeled direction Distance obtained from the best statistical model for distance for a bee species Direction determined using the matrix of transition probabilities or the transition vector for a bee species",
"discussion": "Discussion The approach used in this study differs from previously published models such as BEEHAVE 27 , and BEESCOUT 28 . The aim of BEEHAVE is to assert the impact of distinct factors, including pesticides, diseases, changes in landscape structure, and foraging on honey bee colony health and growth, while BEESCOUT aims more at determining the probabilities of bees detecting food sources over the landscape based on the configuration of the landscape and on the bee search behavior. In this study, we examined the fine scale movement of bees foraging in a patch, and identified the best model of bee movement for each of three bee species. In this respect, the models introduced here share some similarities with Rands 7 , but in the current study, data on observed bee foraging behavior of distinct bee species are used to select best models of bee movement. The general approach follows Levey et al. 29 , 30 who use perching time, move length, and move direction to describe small-scale bird movement. In the current study, distances and directions travelled between consecutive racemes by bees are used to parameterize the models of bee movement, without the need for data error correction 31 . Results indicate differences in foraging behaviors among bee species, and differences in models of bee movement. For bumble bees, we obtained a large enough sample size to successfully discriminate among the four distinct movement models. The “Modeled Distance-Modeled Direction” model best explained bumble bee movement. Bumble bees show directionality of movement within foraging bouts 1 and the number of flowers visited on a raceme affects the distance traveled to the next raceme (results therein). These foraging behaviors improved predictions of the movement of bumble bees over a continuous landscape, and this supports the importance of linking animal behavior to model of animal movement 6 , 31 . For leafcutting bees, none of the four models could be rejected. In retrospect, however, all four models for leafcutting bees make similar predictions and reflect a pattern of random movement. For example, for leafcutting bees, only the intercept was significant in a model of the distance traveled to the next raceme (“Modeled Distance”). This means that distances traveled can be described by a normal distribution with an estimated mean and variance, which is quite similar to randomly selecting distances from a distribution (“Random Distance”). In addition, the matrix of transition probabilities (“Modeled Direction”) had an equal probability of moving in any of the directions, because leafcutting bees did not exhibit directionality in their pattern of movement within foraging bouts 1 . This is not very different from randomly selecting each direction from the distribution of directions (“Random Direction”). In other words, all four models made fairly similar predictions with respect to bee movement, which all reflected “Random Distance” and “Random Direction”. The four models could therefore not be distinguished and the data suggest a model of “Random Distance-Random Direction” as the most likely model to describe leafcutting bee movement. We could not discriminate among the different models for honey bees, likely due to the lower sample sizes providing less statistical power. This conclusion is supported by the fact that we could not discriminate among the different models when we reduced the sample size of bumble bees to the sample size observed for honey bees. Moreover, we still could not discriminate among models when combining data from both years for honey bees. Combining years for honey bees provided a similar number of foraging bouts, but still fewer clips (520 relative to 751 or 658) compared to one year for bumble bees. Like bumble bees, honey bees exhibit directionality of movement within foraging bouts 1 and they travel shorter distances to the next raceme after visiting more flowers on a raceme (results herein). Based on the results obtained for bumble bees, we propose the “Modeled Distance-Modeled Direction” model as the most likely model to describe honey bee movement. This assumes the model would best explain the data were sample sizes to be larger. When we examined solely the “Modeled Distance” portion of the model, a bumble bee or a honey bee traveled a shorter distance to the next raceme when more flowers were visited on a raceme and the distance increased when fewer flowers were visited. This information suggests bumble bees and honey bees can assess resource availability and this information influences their movement. Many factors can affect floral resource availability, including recent visits to flowers by bees 32 , which may be detectable via scent marks 33 , 34 . Bees may visit more flowers on racemes that provide good resources, and travel shorter distances after visiting more flowers on a raceme, potentially expecting to find other profitable neighboring racemes in the vicinity, either on the same or on a different plant. Bumble bees can identify flowers that offer pollen 17 and both bumble bees and honey bees prefer inflorescences with more flowers 35 , 36 . Moreover, both bumble bees and honey bees prefer inflorescences with more pollen-producing flowers when foraging for pollen, and inflorescences with more nectar-producing flowers when they forage for nectar 17 , 37 , 38 . Using artificial flowers presenting nectar as a reward, Waddington 39 reports bumble bees traveling short distances after visiting rewarding flowers, but the distance did not vary with the number of rewarding flowers visited. However, the distance traveled by the bee increased with the number of non-rewarding flowers visited. Lihoreau et al. 22 found bumble bees increase the distance traveled to visit high-reward sites but only for small departure (18%) from the shortest possible distance. Interestingly, for leafcutting bees, previously visited resources did not guide their movement to the next resource. Results of this study highlight differences in how bee species use information about previously visited resources to guide their pattern of movement. Future research should determine whether social bees, relative to solitary bees, are more likely to use information about previously visited resources in determining their next move, and why such differences may exist between groups of bees. The models developed herein illustrate movement over continuous landscapes. Studying seabirds looking for prey, Miramontes et al. 40 showed how the landing pattern did not resemble the search pattern, and concluded that the pattern of movement depended little on the forager behavior, but more on the spatial distribution of resources. In the current study, we compare three bee species under similar conditions (resource distribution) and find differences in the models that best explained their landing patterns. Because these models reflect different bee behaviors, such as resource information collected by the individual, and persistence of movement directionality, we conclude that bee foraging behavior affects their movement patterns. Bees have complex foraging behaviors, and flower selection does not depend solely on the spatial distribution of resources. Bees use visual and olfactory cues to select which plants to visit 19 , and learn to associate floral traits with rewards, a process called associative learning 41 – 43 . Resources get depleted following bee visits and the reward landscape is constantly changing. We are not claiming that resource distribution does not affect the pattern of bee movement, of course it will because bees visit plants to gather resources and do not land on the ground while foraging. However, our results indicate that resource distribution is not sufficient to explain bee movement, differences in bee foraging behavior among bee species must be considered. The interaction of bee foraging behavior with resource distribution will determine bee movement patterns. The approach developed herein could be extended to discontinuous landscapes. Bees follow decision rules not only to select plants and inflorescences within patches but also to decide which patch to move to next 18 , 26 . The bee movement model over discontinuous landscapes could include two modes of movement, with bees switching between behavioral modes as they forage over the landscape 6 , 8 . The first mode represents bee movement within patches, and the second mode addresses bees selecting the next patch to move to. Furthermore, a third mode could be added to represent bees switching between plant species, either within or between patches. When incorporating these modes, it is important to consider that the rules followed by bees within a mode may vary among bee species. For example, bee species may follow different rules when selecting the next patch to move to. In addition, for the mode switching between plant species, a previous study examining bumble bees and honey bees foraging over the landscape detected pollen from a single plant family in 90% of the foraging trips made by honey bee individuals, but only in over 60% of the foraging trips made by bumble bees 44 . A foraging trip, the time elapsed between a bee leaving and returning to the hive, measured using Radio Frequency Identification (RFID), lasted approximately 50 min on average for both bee species 45 . While pollen was not identified at the plant species level in the study, results suggest potential differences in plant species fidelity between the two bee species. A clear message from the current study is the importance of considering differences in foraging behavior among bee species when developing models of bee movement, and that a general movement model cannot be applied to all bee species."
} | 4,353 |
28604679 | PMC5603288 | pmc | 8,932 | {
"abstract": "Microbial ecologists are increasingly turning to small, synthesized ecosystems 1 – 5 as a reductionist tool to probe the complexity of native microbiomes 6 , 7 . Concurrently, synthetic biologists have gone from single-cell gene circuits 8 – 11 to controlling whole populations using intercellular signaling 12 – 16 . The intersection of these fields is giving rise to new approaches in waste recycling, 17 industrial fermentation 18 , bioremediation 19 , and human health 16 , 20 . These applications share a common challenge 7 well known in classical ecology 21 , 22 ; stability of an ecosystem cannot arise without mechanisms that prohibit the faster growing species from eliminating the slower. Here, we combine orthogonal quorum sensing systems and a population control circuit with diverse self-limiting growth dynamics in order to engineer two ‘ortholysis’ circuits capable of maintaining a stable co-culture of metabolically competitive strains in microfluidic devices. While no successful co-cultures are observed in a two-strain ecology without synthetic population control, the ‘ortholysis’ design dramatically increases the co-culture rate from 0% to approximately 80%. Agent-based and deterministic modeling reveal that our system can be adjusted to yield different dynamics, including phase-shifted, anti-phase or synchronized oscillations as well as stable steady-state population densities. The ‘ortholysis’ approach establishes a paradigm for constructing synthetic ecologies by developing stable communities of competitive microbes without the need for engineered codependency."
} | 399 |
38468854 | PMC10925793 | pmc | 8,933 | {
"abstract": "Stover mulching, as a sustainable agricultural conservation practice, has been shown to effectively increase soil organic matter and enhance crop yields. The impact of stover mulching on soil microorganisms has been extensively studied. However, less attention has been given to endophytic and rhizospheric microorganisms that have closer relationships with crops. How do the quality and frequency of stover mulching affect the composition and structure of these endosphere and rhizosphere microbial communities? And what is their influence on critical indicators of soil health such as bacterial plant pathogen and Rhizobiales? These questions remain unresolved. Therefore, we investigated the responses of the microbial functional guilds in the endosphere and rhizosphere to maize stover mulching qualities (0%, 33%, 67%, and total stover mulching every year) and frequencies (once every 3 years and twice every 3 years) under 10-year no-till management. Results showed significant correlations between Bacillales and Rhizobiales orders and soil SOC, NO 3 − N, and NH 4 + N; Hypocreales and Eurotiales orders were significantly correlated with soil NO 3 − N, with the Aspergillus genus also showing a significant correlation with soil SOC. The frequency and quality of stover mulching had a significant effect on root and rhizospheric microbial communities, with the lowest relative abundance of bacterial plant pathogens and highest relative abundance of nitrogen-fixing bacteria such as Rhizobiales and Hypocreales observed under F1/3 and F2/3 conditions. The most complex structures in endosphere and rhizospheric microbial communities were found under Q33 and Q67 conditions, respectively. This research indicates that from a soil health perspective, low-frequency high-coverage stover mulching is beneficial for the composition of endosphere and rhizosphere microbial communities, while moderate coverage levels are conducive to more complex structures within these communities. This study holds significant ecological implications for agricultural production and crop protection.",
"conclusion": "5 Conclusion The study found that the quality and frequency of stover mulching significantly influence the composition and structure of endophytic and rhizospheric microbial communities. Nitrogen-fixing bacteria and rhizosphere-promoting microorganisms showed significant correlations with SOC, NO 3 − N, and NH 4 + N. Cellulose-degrading fungi were notably related to SOC content. Different amounts and frequencies of stover mulching had varying impacts on the microbiota within both the endosphere and rhizosphere. The conditions F1/3 and F2/3 proved most beneficial for the composition of endophytic and rhizospheric microbial communities, while Q33 and Q67 were optimal for the structural complexity of endophytic and rhizospheric microbial communities, respectively. Stover mulching has a dual impact on soil carbon sequestration, and the balance between carbon fixation and release is likely to be a focal point of future research. This study highlights that certain stover mulching conditions that are favorable to overall soil microbiota may not necessarily be advantageous for the composition of endophytic and rhizospheric microbial communities, and conditions that promote a beneficial composition in these root-associated microbiota might not always favorably influence their structural organization. The underlying reasons for this phenomenon require further exploration. This research holds significant ecological implications for agricultural production and conservation practices.",
"introduction": "1 Introduction Maize ( Zea mays L.) is one of the world’s three principal cereal crops. As an agricultural powerhouse, China contributes to 23% of the global maize production ( Wang Y. Q. et al., 2019 ). However, this substantial yield also generates a considerable amount of crop residue, particularly cornstalks, which require proper disposal. In the past, many farmers opted for field burning due to the high costs associated with managing these residues. This practice led to the emission of particulate matter, nitrogen oxides, sulfur dioxide, and other pollutants into the atmosphere, causing air pollution, nutrient loss, and posing health risks to humans ( Wang Z. Z. et al., 2019 ; Cao et al., 2022 ). In line with sustainable agricultural development in China, it is imperative to utilize crop residue resources effectively. Stover mulching, as a key method for such utilization, has been shown to increase soil organic matter content and enhance crop yields, thus contributing positively to agricultural sustainability ( Liu et al., 2010 ). In soil, there exists a diverse community of microorganisms that play crucial roles in energy flow, nutrient cycling, and information exchange ( Chaparro et al., 2012 ; Frąc et al., 2018 ), serving as biological indicators of soil health ( Doran and Zeiss, 2000 ). A wealth of research has demonstrated significant differences in the microbial community composition between soils subjected to stover mulching compared to those under conventional tillage practices ( Zhang et al., 2019 ; Yang et al., 2022 ). Overall, stover mulching tends to shift soil microbial communities toward a composition that is more conducive to crop growth; however, it can also introduce potential drawbacks, such as an increase in pests and diseases ( Gao et al., 2022 ). Studies have shown that both the quantity and frequency of stover mulching directly impact the soil microbial community, with specific frequencies and quantities capable of effectively steering the microbial populations toward a composition that benefits crops ( Wang et al., 2020a ; Yang et al., 2022 ). Therefore, altering the quantity and frequency of stover mulching may be a critical strategy for optimizing this practice while minimizing potential risks. The rhizosphere, the narrow region surrounding plant roots within a few millimeters, is a critical zone where microorganisms engage in intensive material exchange and information transfer with plants, often hosting the most active soil microbial communities ( Hassan et al., 2019 ; Song et al., 2023 ). The endosphere refers to the internal plant tissues where diverse microorganisms coexist symbiotically within the plant ( Adeleke et al., 2023 ), and endophytic microorganisms are more similar in the ecological niche to “producers” ( Song et al., 2023 ). Compared to soil microorganisms, both endophytes and rhizosphere microbes have more direct interactions with plants, being more intimately related to plant health and functioning ( Attia et al., 2021 ). In evaluating the impact of stover mulching on soil health, investigating changes in the endophytic and rhizosphere microbial communities are of paramount importance. However, there is currently a dearth of research specifically addressing how stover mulching affects endophytes and rhizosphere microbes within the root system. It remains uncertain whether the effects of stover mulching on endophytes and rhizosphere microbiota are merely the extension of its influence on the soil microbial community or if they involve more intricate and unique relationships. Existing studies have indeed assessed the effects of variations in stover mulching frequency and amount on nitrifying bacterial and fungal plant pathogens within both the endosphere and rhizosphere ( Song et al., 2022 ), with some research delving down to the species level ( Wang et al., 2020a , b ). However, there remain substantial gaps in the research on how the quality and frequency of stover mulching influence endosphere and rhizosphere microbial communities, particularly with respect to critical groups such as rhizobia and bacterial plant pathogens. Stover mulching is a process involving the release and mineralization of organic nutrients, with numerous factors influencing its decomposition, including soil properties, types of microorganisms, and hydrothermal conditions. Microorganisms are core elements in the cycling and transformation of soil carbon and nitrogen, and primarily rely on these organisms to decompose stover and release nutrients into the soil ( Hu et al., 2012 ). Typically, the decomposition of initial components such as proteins and cellulose in straw is predominantly carried out by bacteria ( Marschner et al., 2011 ), while fungi play a major role in the breakdown of more recalcitrant components like lignin during later stages. However, existing studies have shown that bacteria play a significant role throughout the entire process of straw decomposition ( Lee et al., 2011 ; Fan et al., 2014a ). Throughout the process of stover decomposition, microorganisms constantly interact with soil and plants. Their biological activities have a direct or indirect impact on soil physical properties as well as plant health and productivity ( Xiong et al., 2021 ; Zhu et al., 2021 ). Research has shown that the composition and functions of endophytic and rhizospheric microbiota significantly vary across different growth stages of plants, exerting distinct ecological roles ( Xiong et al., 2020 , 2021 ). Beyond the interactions between environmental factors and microbial communities, there are also complex interrelationships among different microorganisms within these communities. Prior study have demonstrated that stover mulching can increase the complexity of microbial interaction networks ( Wang et al., 2020b ). Thus, it is hypothesized that the quality and frequency of stover mulching could affect the connectivity between endophytic and rhizospheric microbial populations, with varying degrees of influence. However, current research largely focuses on the impacts of mulch quantity and frequency on overall soil microbial communities ( Wang et al., 2021 ), with relatively little attention given to their specific effects on endophytic and rhizospheric microbiota. Currently, there is a substantial body of research examining the effects of stover mulching quantity and frequency on soil microbial communities across various crops such as rice, wheat, soybeans, among others ( Wang et al., 2021 , 2023 ; Wei et al., 2021 ), including corn which is under investigation in our study. However, literature addressing the specific impacts of straw return on endophytic and rhizosphere microbial populations is scarce. As a result, the precise influence of different stover mulch frequencies and amounts on the composition and structure of both the endosphere and rhizosphere microbial communities remains largely unknown. Previous studies on soil microbial communities showed that a high-frequency while small-quantity mulch is more beneficial for soil microbial communities ( Kou et al., 2020 ; Yang et al., 2022 ). Thus, our research hypothesis is that this phenomenon will continue to endophytic and rhizosphere microbial communities, where a high-frequency while small-quantity mulch is also beneficial to endophytic and rhizosphere microbial communities. This study aims to investigate the effects of different stover mulching frequencies and qualities on the composition and structure of endophytic and rhizospheric microbial communities at the order and lifestyle levels. The objective is to identify optimal frequencies and quantities of straw return from a perspective of maintaining and promoting the health of microbial communities, which holds significant ecological implications for the protection and enhancement of agricultural production.",
"discussion": "4 Discussion 4.1 Frequency and quantity of stover mulching affected the composition and structure of microbial community Compared to the control group, the bacterial community structures within the rhizosphere and endosphere in different experimental groups were relatively similar, while the fungal community structures exhibited greater variations. Research by Wakelin et al. (2007) suggests that the impact of stover mulching on fungal community structures in the soil is more pronounced than its impact on bacterial community structures. This phenomenon was still applicable both within the endosphere and rhizosphere. Additionally, within the fungal community, the influence of stover mulching on the endosphere was stronger than its impact on the rhizosphere, whereas no such trend was observed in bacterial communities. This may be explained by the morphology of fungi in the soil. Fungi can form a mycelial network with plant roots, facilitating the connection between roots and soil. Hence, they are more susceptible to soil environment changes compared to bacterial communities in the endosphere and rhizosphere ( Song et al., 2023 ). The microbial communities within the endosphere and rhizosphere can be categorized into two systems based on their ecological niches. The endophytic microbial community in the endosphere often engages in symbiosis with plants, while the rhizospheric microbial community serves as a bridge between plant roots and the soil ( Song et al., 2023 ). The fungal community in the endosphere relies more on the mycelial network; therefore, changes in the mycelial network result in more noticeable variations in the fungal community of the endosphere. Some studies suggest that a high-frequency while small-quantity mulch is more beneficial for soil microbial communities ( Kou et al., 2020 ; Yang et al., 2022 ). However, in our current study, the enrichment of Rhizobiales in the conditions of high-frequency mulch did not exist both in the endosphere and in the rhizosphere. Although the high-frequency while small-quantity mulch benefits the soil microbial community, it may not necessarily favor the microbial communities within the endosphere and rhizosphere. Studies have shown that certain members of the Rhizobiales order exhibit nitrogen-fixing capabilities and can form stable symbiotic relationships with plants, stimulating plant growth and enhancing productivity ( Yang et al., 2022 ). The observation that F1/3 and F2/3 increase the relative abundance of Rhizobiales in both the endosphere and rhizosphere suggests that F1/3 and F2/3 may be beneficial to the composition of endophytic and rhizosphere microbial communities. And we found that stover mulching effectively inhibited the relative abundance of bacterial plant pathogen, while F1/3 had the most obvious inhibition among experimental groups. Similarly, literature indicates that F1/3 and F2/3 exhibit the lowest abundance of nitrifying bacteria and anaerobic nitrifying bacteria, the highest abundance of nitrogen-fixing bacteria, and F2/3 significantly reduces the relative abundance of fungi plant pathogens in the rhizosphere ( Song et al., 2022 ). Multiple lines of evidences suggest that frequency but not the quantity of stover mulching plays a dominant role in influencing the microbial communities within the endosphere and rhizosphere. Moreover, the low-frequency while high-intensity mulch leads to a healthier microbial composition in the endosphere and rhizosphere. Some research has revealed that the quantity of stover mulching is a crucial factor influencing the correlation of soil microbial communities. In comparison to other levels of stover mulching, a moderate level of stover mulching leads to a more complex network of soil microbial community, while a small quantity of stover mulching (less than 50% mulching) reduces the complexity of the network ( Wang et al., 2021 ). In our current study, we found that Q33 reduced the complexity of the rhizospheric bacterial genus-level community network, similar to the trends observed in soil microbial networks ( Wang et al., 2021 ). However, the bacterial community network at the genus level within the endosphere was found to be most complex under the stover mulching quantity of Q33, while Q67 significantly reduced the interconnectivity among communities, even resulting in lower association levels than those observed in the Q0 group. This could be attributed to the differences between endophytic and rhizospheric microorganisms, where plants exhibit a stronger selectivity for endophytic microorganisms ( Hardoim et al., 2008 ; Berendsen et al., 2012 ). Unlike rhizospheric microorganisms, endophytic microorganisms experience fewer biotic and abiotic stresses within plant tissues, and their abundance is less influenced by soil nutrient levels ( Wang et al., 2016 ; Chen et al., 2020 ). Furthermore, this explains why, in comparison to rhizospheric microorganisms, the impact of stover mulching frequency on the correlation of endophytic microorganisms at the genus level is not as significant. Our study indicates that microbial community correlations vary significantly under different quantities and frequencies of stover mulching, and there is substantial dissimilarity between endophytic and rhizospheric microorganisms. In this study, the stover mulching quantities that resulted in the most complex bacterial community networks at the genus level for endophytic and rhizospheric microorganisms were Q33 and Q67, respectively. More complex community networks may signify stronger interactions among microorganisms, allowing more microorganisms to share ecological niches ( Berry and Widder, 2014 ), thereby promoting the improvement of plant endophytic or rhizospheric environments. 4.2 Relationship between microbial communities and soil carbon and nitrogen Many microorganisms have a significant impact on plant growth and soil physicochemical properties. Under natural conditions, Rhizobiales generally do not form nodules with non-leguminous plants but can colonize the endosphere or rhizosphere such as rice and corn, acting as Plant Growth-Promoting Rhizobacteria (PGPR) to enhance plant growth ( Baset Mia and Shamsuddin, 2010 ). Therefore, the relative abundance of Rhizobiales in the rhizosphere was highly significant correlated with soil NO 3− N and NH 4+ N levels. Previous research has shown that many groups within Bacillales can fix atmospheric nitrogen, explaining the significant positive correlation observed in this study between the relative abundance of endophytic and rhizospheric Bacillales and soil NO 3− N levels ( Ding et al., 2005 ; Yousuf et al., 2017 ). Bacillales have been reported to be used as Plant Growth-Promoting Rhizobacteria (PGPR) in the cultivation of various crops and horticultural plants, contributing to the solubilization of mineral elements. Many species within Bacillales, such as Bacillus subtilis and Bacillus amyloliquofaciens, can produce various antibiotics. They also support plant growth by producing plant hormones, releasing ammonia from nitrogen-containing organic compounds, and increasing the plant’s demand for nutrients, thereby promoting nitrogen uptake by plants ( Goswami et al., 2014 ). This explains the significant positive correlation observed in this study between the relative abundance of endophytic Bacillales and soil NH 4+ N levels. Corn stover organic matter undergoes two processes in the soil, mineralization and humification. Mineralization involves the breakdown of organic matter into simple inorganic compounds through microbial action, which is a crucial pathway for Soil Organic Carbon (SOC) loss ( Thuriès et al., 2001 ). Humification is a process that retains nutrients in the soil, and humus is the most stable component of soil organic matter ( Adam et al., 1985 ; Pei et al., 2015 ). The decomposition of cellulose in corn stover is a vital step in its degradation. Some strains of filamentous fungi from Penicillium exhibit strong secretion capabilities of cellulolytic enzymes, and they have advantages in terms of enzyme performance and strain growth rate ( Gusakov, 2011 ). Research has shown that the relative abundance of endophytic Penicillium is significantly negatively correlated with SOC levels during the flowering stage, which may be related to the secretions produced by endophytic Penicillium. When interacting with plants, these fungi secrete antibiotics and other biocontrol agents that positively influence plant growth, thereby promoting nutrient release in the soil ( Bashan and De-Bashan, 2010 ). Stover mulching can both enhance SOC recovery and improve soil fertility through increasing carbon input ( Fan et al., 2014b ); however, it may also indirectly decrease SOC content due to the promotion of plant growth by specific fungi like Penicillium. The effect of stover mulching on soil carbon sequestration is dual-sided, and how to regulate the balance between carbon storage and release remains an area for further research."
} | 5,130 |
34529974 | PMC8498467 | pmc | 8,934 | {
"abstract": "Bacterial signaling histidine kinases (HKs) have long been postulated to function exclusively through linear signal transduction chains. However, several HKs have recently been shown to form complex multikinase networks (MKNs). The most prominent MKN, involving the enzymes RetS and GacS, controls the switch between the motile and biofilm lifestyles in the pathogenic bacterium Pseudomonas aeruginosa . While GacS promotes biofilm formation, RetS counteracts GacS using three distinct mechanisms. Two are dephosphorylating mechanisms. The third, a direct binding between the RetS and GacS HK regions, blocks GacS autophosphorylation. Focusing on the third mechanism, we determined the crystal structure of a cocomplex between the HK region of RetS and the dimerization and histidine phosphotransfer (DHp) domain of GacS. This is the first reported structure of a complex between two distinct bacterial signaling HKs. In the complex, the canonical HK homodimerization interface is replaced by a strikingly similar heterodimeric interface between RetS and GacS. We further demonstrate that GacS autophosphorylates in trans , thus explaining why the formation of a RetS-GacS complex inhibits GacS autophosphorylation. Using mutational analysis in conjunction with bacterial two-hybrid and biofilm assays, we not only corroborate the biological role of the observed RetS-GacS interactions, but also identify a residue critical for the equilibrium between the RetS-GacS complex and the respective RetS and GacS homodimers. Collectively, our findings suggest that RetS and GacS form a domain-swapped hetero-oligomer during the planktonic growth phase of P. aeruginosa before unknown signals cause its dissociation and a relief of GacS inhibition to promote biofilm formation.",
"discussion": "Discussion Initially, the Gac/Rsm pathway was discovered as a central signal transduction pathway in Pseudomonads that regulates the production of secondary metabolites ( e.g. , antimicrobials, hydrogen cyanide, siderophores) and also the switch between a motile, invasive lifestyle and a sessile biofilm-associated lifestyle ( 16 , 30 , 31 , 32 , 33 ). However, beyond the biological significance of this particular signaling pathway, the GacS-GacA system has become the model for studying crosswise interactions between multiple signaling kinases. HKs have been demonstrated to maintain a high degree of fidelity for their cognate RRs and vice versa, but we are beginning to recognize that MKNs are often necessary to control complex outputs ( 9 , 34 ). Such MKNs were once postulated to be prohibited, but it now appears many bacterial species use them to integrate diverse extracellular signals to regulate adaptive responses ( 34 ). MKNs control transitions associated with virulence, response to switching from aerobic to anaerobic conditions, the integration of diverse quorum sensing signals, as well as sporulation and fruiting body formation ( 34 ). However, none is more complex than the MKN associated with the regulation of the GacS-GacA system. At least seven HKs coordinate their signaling to fine-tune P. aeruginosa gene expression. LadS and RetS do so through direct interactions with GacS ( 11 , 12 , 18 , 20 ), while PA1611 appears to sequester RetS to promote GacS signaling ( 35 , 36 ). However, RetS, PA1611, ErcS, and SagS all appear to also interact with HptB to modulate RsmY levels ( 37 , 38 , 39 , 40 ). SagS interacts with BfiS to integrate the BfiS/BfiR system, which promotes biofilm formation into the MKN ( 39 ). The mechanism whereby these signaling pathways integrate are varied and, in some cases, multifaceted as the interactions can be both activating and suppressing. Often, the molecular mechanisms underlying the MKNs can be readily understood as they involve well-characterized protein–protein interactions mirroring canonical signaling pathways. The basis for the direct pairwise interactions of the HK regions observed for RetS-GacS but also RetS-PA1611 and SagS-BfiS in P. aeruginosa , as well as the DivL-CckA interactions in Caulobacter crescentus are less well understood ( 41 ). The present evidence of domain-swapping between DHp domains in the RetS-GacS complex suggests that once again MKN signaling evolved from known contact interfaces of regular linear HK systems. Although, earlier work suggests that the interface formed between PA1611 and RetS involves the DHp domain of PA1611 and the beta-sheet of the CA domain of RetS, suggesting an interface that does not have an equivalent in known HK contacts ( 36 ). The present structure may broadly represent the basis for how heteromeric HK-HK interactions inhibit autophosphorylation in MKNs. The RetS HK -GacS DHp complex structure answers the question of how binding between the RetS and GacS DHp domains prevents GacS autophosphorylation because the formation of a heterodimeric DHp-DHp interface should inhibit GacS trans -autophosphorylation ( 11 , 12 ). However, perhaps this inhibition is not complete, thus explaining why RetS uses not one but three distinct mechanisms to inhibit GacS signaling ( Fig. S1 ). Potential trans -autophosphorylation of GacS in a heteromeric RetS-GacS complex is at this point only speculative; however, the siphoning of phosphates from the catalytic histidine in GacS-HK by the second receiver domain of RetS would otherwise appear to be redundant. Yet, Francis et al . ( 11 ) demonstrated that this phosphatase activity is critical for inhibiting GacS signaling in vivo . The RetS HK region also dephosphorylates the receiver domain of GacS in a manner similar to transmitter phosphatase activity ( 2 , 11 , 42 ). It is not known if RetS-GacS binding through the DHp-DHp increases the efficiency or is in fact a prerequisite for the efficient working of the two other inhibitory mechanisms. In recent years, some progress has been made toward elucidating the roles of periplasmic sensory domains of RetS and GacS in regulating their interplay. Remarkably, the sensory domain of RetS appears to promote the inhibition of GacS when exposed to host cell-derived mucins, while P. aeruginosa lysis releases a molecular signal, also recognized by the RetS sensory domain that causes GacS activation ( 43 , 44 ). The sensory domain of GacS, on the other hand, is required for GacS activation, but the longstanding hunt for the elusive ligand is ongoing ( 32 ). Overall, the present study has uncovered the novel heterodimeric DHp-DHp interface in the RetS-GacS complex, which readily explains how direct binding of RetS-HK to GacS-HK interferes with GacS trans -autophosphorylation. The observed RetS HK -GacS DHp structure is also consistent with the proposed model for regulation of RetS-GacS binding via RetS helix-cracking, which predicted that a structurally dynamic section of RetS would form the N-terminal end of the DHp α1 helix and interact with GacS ( 21 ). Another structurally dynamic feature of the RetS-HK dimer, the so-called ATP lid loop was shown to play an important role in stabilizing the RetS homodimer but not the RetS-GacS complex ( 21 ). Consistent with this prediction, the ATP lid loop region and a short α helix N-terminal to the ATP lid loop region of the RetS CA domain are unstructured in the RetS HK -GacS DHp complex. The mutational analysis of the DHp-DHp interface offered additional insight into which residues might be critical in providing specificity for the unusual heteromeric RetS-GacS interactions in favor of the RetS-RetS and GacS-GacS interfaces. We demonstrated upon variation of select residues (GacS I302, GacS L309) an inhibition to binding in the heterodimeric interface of the cytoplasmic regions, but not an equivalent inhibition to binding in the homodimeric interface of the cytoplasmic regions. We also demonstrated a phenotype comparable to the hyperbiofilm retS mutant for the GacS I302V strain in an in vivo assay, demonstrating the importance of I302 in RetS binding ( 13 ). There is a disparity between the observation that RetS disrupts the GacS DHp-DHp dimerization interface and our previous finding that RetS overall does not disrupt the GacS homodimer ( 20 ). This apparent contradiction may be explained by the fact that the GacS protein construct used in the original FRET measurements included not only the histidine kinase region but also the HAMP domain of GacS ( 21 ). HAMP domains are ubiquitous signaling domains of signaling HKs and methyl accepting chemotaxis proteins and facilitate homodimerization and signal transduction by forming structurally dynamic intermolecular four-helix bundles ( 45 ). The GacS HAMP domain appears to maintain GacS-GacS association even in the presence of RetS ( Fig. 8 ). This observation is also consistent with the finding that the HAMP domain is required for GacS homodimerization in Pseudomonas fluorescens ( 29 ). Similarly, the periplasmic domain of RetS has also been demonstrated to dimerize in vitro ( 46 , 47 ). If and how this interaction is affected by GacS binding is unknown. Figure 8 Models for RetS-GacS tetramers. Binding between the two proteins could be asymmetric (Model 1), where only one DHp-DHp interface forms. This model allows for the possible formation of a polymer consisting of repeat units of asymmetric tetramers linked through DHp-DHp interactions. Alternatively, RetS and GacS could form a symmetric tetramer with two DHp-DHp interfaces (Model 2). Collectively, the present work and previous results support a model in which RetS and GacS form a domain-swapped complex ( Fig. 8 ). The exact stoichiometry and size of this complex remain to be determined. While the presence of additional GacS-GacS and RetS-RetS interfaces might make it tempting to propose the formation of a symmetric heterotetramer ( Fig. 8 , Model 2), steric factors may create an asymmetric complex, cause dissociation of the RetS dimer, or may even facilitate the formation of a larger polymeric structure consisting of alternating RetS and GacS dimers."
} | 2,503 |
25348004 | PMC4210941 | pmc | 8,936 | {
"abstract": "Vibration energy harvesters scavenge energy from mechanical vibrations to energise low power electronic devices. In this work, we report on vibration energy harvesting scheme based on the charging phenomenon occurring naturally between two bodies with different work functions. Such work function energy harvester (WFEH) is similar to electrostatic energy harvester with the fundamental distinction that neither external power supplies nor electrets are needed. A theoretical model and description of different operation modes of WFEHs are presented. The WFEH concept is tested with macroscopic experiments, which agree well with the model. The feasibility of miniaturizing WFEHs is shown by simulating a realistic MEMS device. The WFEH can be operated as a charge pump that pushes charge and energy into an energy storage element. We show that such an operation mode is highly desirable for applications and that it can be realised with either a charge shuttle or with switches. The WFEH is shown to give equal or better output power in comparison to traditional electrostatic harvesters. Our findings indicate that WFEH has great potential in energy harvesting applications.",
"discussion": "Discussion Work-function energy harvesters are similar to the electrostatic energy harvesters as they both employ the same principle of energy conversion with variable capacitance. Therefore, the device geometries and various broadband vibration energy harvesting techniques utilized in electrostatic energy harvesters 6 33 34 can also be used in WFEHs. The key advantage of the work function energy harvester over the electrostatic energy harvester is the fact that the work function energy harvester does not need external power source or electret materials in the operation. In this sense the WFEH becomes closer to piezoelectric harvesters that also rely on fundamental properties of solid materials. Another unique feature of WFEH is that it can be operated in the charge shuttle mode, which is impossible to realise with electrostatic harvesters. The charge shuttle mode can provide extremely large maximum capacitance and, therefore, high output power. The physical contact between the surfaces, however, often results in stiction problems and reduced lifetime, but recently reported SiC-based nanoelectromechanical switches 35 have been shown to operate reliably over 10 7 switching cycles. WFEHs can generate more power than the electrostatic harvesters in many operating conditions (see Section 5 of Supplementary information ). A simple comparison can be performed by assuming that the initial charging voltage V in of the electrostatic harvester is equal to the built-in voltage V bi of the WFEH. A more detailed comparison would need the details of the specific applications of the devices. In principle, high values of V in can be used in the electrostatic harvester, since the charging voltage is limited only by the pull-in voltage and the breakdown voltage of the variable capacitor of the device. In reality, the charging voltage is limited by the available power supply, which is a battery with the nominal voltage 1–4 V in many applications. This voltage range can also be realized with the built-in voltages of many known material pairs. In general, energy harvesters can be operated in two modes: continuously and in pulsed mode. In the pulsed mode the WFEH needs to supply energy to, for example, sensing and communicating circuit which measures and transmits signals for further processing at time intervals. The use of a work-function charge pump of either Fig. 5a or c in both of these operating modes can be designed using the results shown in Fig. 5d and e . The charging power can be maximized by selecting large storage capacitors, so that C sto /C min ≥ 100. Work-function charge-pump devices need an initialization time where they gather electric energy in the storage capacitor while increasing its charging power as the voltage across the storage capacitor increases. The number of operating cycles N mpp needed to reach the maximum charging power is proportional to C sto /C min . In the pulsed mode the time interval between the pulses can be optimized so that the electric energy in the storage capacitor is not completely consumed, causing the charging power to collapse. On the other hand, unlike in the case of electrostatic harvesters using external battery all energy of the storage capacitor can be consumed during every cycle if needed. Finally, we note that a supercapacitor can provide an attractive solution to achieve high capacitance energy storage 36 that can be integrated with WFEH. In conclusion, we have experimentally tested the work-function energy harvester concept. The operation of the test device was in a good agreement with our theoretical model. Based on the theory two ideal modes of operation were devised. The charge-constrained mode was shown to produce much higher output power than the voltage-constrained mode. The results show that for maximum output power the electrical time constant of the work-function energy harvester should be optimized in respect to the operating period of the device. Use of switches or a charge shuttle in mimicking the ideal cycle was shown to increase the output power of the WFEH remarkably. We have also presented two work-function charge pump designs for charging of storage capacitors for powering of, e.g., autonomous sensors. The feasibility of miniaturizing work function energy harvesters was shown by simulating a realistic MEMS device. Finally, the comparison of work function and electrostatic energy harvesters showed that work function energy harvesters can generate more power than the electrostatic harvesters in many operating conditions, but without the need of external power source or electret materials. This was also confirmed with the MEMS simulations. The results presented in this article point out that the work function energy harvesters have vast potential to be used in many applications. For maximum power output material pairs with maximal difference in their work functions need still to be sought and MEMS versions of the work function energy harvester need to be realized. The principle, however, does not require realization in microscale, but miniaturization is needed in many applications and achieving high capacitances is easier with microfabrication techniques. The optimal design of these MEMS devices can be achieved by utilizing the models presented in this article."
} | 1,624 |
28678287 | null | s2 | 8,938 | {
"abstract": "Collagen mimetic peptides that alone formed two-dimensional nanoscale discs driven by hydrophobic interactions were shown in electron microscopy studies to also co-assemble with natural fibrous proteins to produce discs-on-a-string (DoS) nanostructures. In most cases, peptide discs also facilitated bundling of the protein fibers. This provides insight into how synthetic and natural proteins may be combined to develop multicomponent, multi-dimensional architectures at the nanoscale."
} | 121 |
28775265 | PMC5543068 | pmc | 8,939 | {
"abstract": "Today the high demand for electronics leads to massive production of waste, thus green materials based electronic devices are becoming more important for environmental protection and sustainability. The biomaterial based hydrogels are widely used in tissue engineering, but their uses in photonics are limited. In this study, silk fibroin protein in hydrogel form is explored as a bio-friendly alternative to conventional polymers for lens applications in light-emitting diodes. The concentration of silk fibroin protein and crosslinking agent had direct effects on optical properties of silk hydrogel. The spatial radiation intensity distribution was controlled via dome- and crater-type silk-hydrogel lenses. The hydrogel lens showed a light extraction efficiency over 0.95 on a warm white LED. The stability of silk hydrogel lens is enhanced approximately three-folds by using a biocompatible/biodegradable poly(ester-urethane) coating and more than three orders of magnitude by using an edible paraffin wax coating. Therefore, biomaterial lenses show promise for green optoelectronic applications.",
"conclusion": "Conclusions In summary, the replacement of conventional plastics with eco-friendly materials is important for a sustainable and clean environment. The lenses occupy an important volume and mass in LEDs. As a solution, in this study we introduced the biomaterial of silk hydrogels as an optical material for lens application in LEDs. For this we extracted silk fibroin proteins from cocoons, transformed it into its hydrogels and fabricated crater- and dome-type lenses to control the spatial intensity profile. The scattering due to the proteins and crosslinks had direct effect on the optical properties. Silk hydrogel lenses showed light extraction efficiency over 0.95 on a warm white LED and the stability was significantly increased with a biocompatible and biodegradable poly(ester-urethane) coating. Moreover, using edible paraffin wax coating the stability of silk hydrogel lens was approximately increased by three orders of magnitude. Therefore, biomaterial lenses show promise for eco-friendly device applications.",
"introduction": "Introduction Electronic device consumption increases day by day and this trend leads to massive amounts of electronic waste (e-waste). For example, in 2011 more than 2 million tons of e-waste was produced by U. S. only 1 , and even though a significant portion of e-waste (24.9%) is recycled, the remaining waste generates a substantial hazard to the environment 2 . When the global e-waste produced by the entire world is considered, the consequences become catastrophic (e.g., great garbage patch in the Pacific Ocean). Therefore, a transition toward ‘green’ materials is necessary in electronics for environmental protection and sustainability. The invention of efficient blue light-emitting diodes (LEDs) has opened up a new way toward bright and energy-saving solid-state lighting (SSL) 3 , which has a very important potential to replace conventional light sources because of its energy saving, long lifetime and compactness 4 , 5 . For example, SSL can generate 50% reduction in electricity consumption and therefore decrease carbon emissions by 28 million tons per year, if the targeted LED performance levels are reached 6 . Light-emitting diodes (LEDs) are now being used for lighting applications in cars, homes, offices and displays. According to BCC Research, the LED market had a value of $38.2 billion in 2013 and this will approximately triple by 2019 7 . As the production of LED and LED based devices will increase in the future, the same it will happen with the production of electronic waste. A typical LED chip is made of a semiconductor die, wire bonding, a heat sink, metal contacts, packaging and a lens 8 . The lens occupy a significant portion of the whole LED device and are generally fabricated from high-performance silicone based polymers and epoxy resins, which are widely available, but not biodegradable 9 , 10 . Hence, a transition toward LED lenses based on eco-friendly materials has the potential to enhance the environmental protection and sustainability. Biocompatible material based hydrogels are widely used in tissue engineering as scaffolds 11 , 12 . Silk fibroin protein obtained from Bombyx-mori cocoons has been tested for various biomedical applications 4 , 13 – 15 , and a new type of hydrogel made of silk fibroin was recently demonstrated, which was used for microfluidic systems, multiphoton micromachining and tissue engineering 16 – 21 . Even though liquids have been used for various optoelectronics device applications, such as liquid crystals displays (LCDs), fluidic adaptive focusing and colour conversion layers 22 , 23 , silk hydrogel lenses have not been investigated for LED applications. In this study, we explored the feasibility of using silk hydrogels as a lens material for light-emitting diodes. We investigated the optical properties of the silk hydrogel lenses and showed that the fibroin protein concentration and cross-linking have a direct effect on the optical property of hydrogels. We demonstrated high control on the spatial light distribution via dome- and crater-type silk-hydrogel lenses for LED applications. Moreover, the hydrogel lenses extracted light with high efficiency on warm white LEDs. Finally, their stability was significantly enhanced by using a polymer top coating.",
"discussion": "Results and Discussion Formation and optical transparency of silk hydrogel The optical transparency of materials is important for light guiding and extraction in optoelectronic devices 24 . Silk fibroin from Bombyx mori silkworm is a fibrous protein whose primary structure is dominated mainly by a repeating sequence of six aminoacids, (Gly-Ala-Gly-Ala-Gly-Ser) 25 – 27 . The silk fibroin is composed of two quasi-crystalline structures, silk I and silk II, with some amorphous residues in silk II (tyrosine) 28 . Each crystal site is statistically occupied by two antiparallel β-sheet chains with different relative orientations, the inter-sheet stacking occurring at a ratio of 1:2 29 . The quasi-crystalline structure of silk fibroin facilitates its use for optical applications in addition to structural, medical and tissue engineering applications 16 – 18 . Silk hydrogel can be chemically obtained by mixing silk fibroin solution with horseradish peroxidase (HRP) in the presence of hydrogen peroxide. The role of H 2 O 2 is to activate the HRP by forming an oxyferryl center and a porphyrin-based cation radical at the active site of HRP, which makes the activated enzyme a powerful reducing agent 30 . HRP then undergoes two single electron oxidation reactions in the presence of a phenolic oxidizing agent (tyrosine in the silk fibroin) to return to its ground state. It produces two water molecules and two phenolic radicals of tyrosine which can react with each other to form covalent bonds. Based on this enzymatically catalysed reaction, we obtained a transparent network of cross-linked fibroin polymer chains containing a large amount of water (Fig. 1a ). Figure 1 Optical properties of silk hydrogel. ( a ) Photograph showing the level of transparency of a silk hydrogel piece placed on top of the Koc University logo printed on a paper; inset: schematic of silk hydrogel structure showing water molecules that are trapped inside covalently crosslinked silk fibroin proteins. Scale bar, 0.5 cm. ( b ) Photograph of silk hydrogels with concentrations of 3.0, 5.0, 8.0, 14.0 and 18.0 wt%, respectively. Scale bar, 1 cm. ( c ) Transmittance of silk hydrogels in dB/cm units in visible spectrum at concentrations of 3.0, 5.0, 8.0, 14.0 and 18.0 wt%, respectively. Inset: Averaged transmittance of silk hydrogels in the visible spectrum. ( d ) Comparison of transmittance between the silk solution and hydrogel at the same concentration (8.0 wt%). \n We investigated the transmittance of hydrogel with the fibroin concentrations of 3.0, 5.0, 8.0, 14.0, and 18.0 wt% (Fig. 1b ). In order to prepare silk hydrogels with lower and higher concentration, the initial fibroin solutions (8–10 wt%) were either diluted with pure water or concentrated by thermal evaporation. As the fibroin protein concentration increases, the silk hydrogels start to show a yellowish appearance due to high attenuation at shorter wavelengths (Fig. 1c ). The attenuation of transmission was strongly dependent on fibroin concentration and wavelength. For example, 18 wt% fibroin hydrogel showed a −2.9 dB per cm at 550 nm (Fig. 1c ), but as the protein content was decreased, the transmittance increased to −0.5 dB per cm at 550 nm for 3 wt% silk solution. Since the optical absorption of water is comparatively small (e.g., 0.0003 dB/cm at 550 nm) 31 , the loss of light in these hydrogels must be due to the silk proteins. In addition to the protein concentration, the crosslinking affected the optical properties. For this purpose we compared the change of the optical properties for the transition from silk solution to hydrogel phase (Fig. 1d ). We observed that the average transmittance of hydrogels decreased approximately 0.41 dB/cm in the visible spectrum (from 450 to 700 nm) relative to the silk solution phase. Even though this effect was significant, it is relatively small in comparison with the concentration effect of silk fibroin proteins, which was −0.17 (dB/cm)/wt% (inset of Fig. 1c ). Therefore, both the crosslinking process and protein concentration have direct effect on the optical properties of silk hydrogel. The refractive index of silk hydrogel is another important parameter and the refractive index value needs to be slightly higher than the water due to its major water and the minor biopolymer content. The refractive index of silk hydrogel was calculated using equation 1, where C is the concentration of silk in solution (g/mL), dn/dC is the specific refractive index, and n SH and n water are the refractive index of silk hydrogel and water, respectively 32 . Here we know the specific refractive index of silk solution (dn/dC = 0.18 ml/g at 488 nm) and we obtained the refractive index of silk hydrogel as 1.35 at 488 nm. Moreover, the temperature (5–70 °C) does not significantly affect the optical performance of silk hydrogel 32 . 1 \\documentclass[12pt]{minimal}\n\t\t\t\t\\usepackage{amsmath}\n\t\t\t\t\\usepackage{wasysym} \n\t\t\t\t\\usepackage{amsfonts} \n\t\t\t\t\\usepackage{amssymb} \n\t\t\t\t\\usepackage{amsbsy}\n\t\t\t\t\\usepackage{mathrsfs}\n\t\t\t\t\\usepackage{upgreek}\n\t\t\t\t\\setlength{\\oddsidemargin}{-69pt}\n\t\t\t\t\\begin{document}$$\\frac{dn}{dC}=\\frac{{n}_{SH}-{n}_{water}}{C}$$\\end{document} d n d C = n S H − n w a t e r C \n Intensity distribution of spatial radiation of silk hydrogel lenses To understand the spatial intensity distribution of LEDs with and without lens, we used ray tracing method. Light is generated via electroluminescence by the semiconductor die and refracted by the lens above the LED. We measured the radiation pattern of a LED die without a lens as the reference LED emission, and generated an identical LED die emission profile in the simulation. To understand the effect of lenses on light distribution profile, crater- and dome-type lenses 4 were simulated on top of the LED die (Fig. 2a ). Numerical simulation of ray tracing with and without lenses are shown in Fig. 2b . The crater-type lens (Fig. 2b , middle) exhibits maximum intensity of light at 16° and −16° which disperse light to wider angles (inset Fig. 2b , middle). In contrast, the dome-type lens (Fig. 2b , right) focuses light in the center (inset Fig. 2b , right). Figure 2 ( a ) Schematic representation of LED die (left), crater-type silk hydrogel lens on LED die (middle) and dome-type silk hydrogel lens on LED die (right). ( b ) Intensity distribution of spatial radiation of ray tracing simulation (without scattering effects). Inset: spatial radiation distribution. ( c ) Photographs of LED chip used for experimental testing (left), LED covered with crater-type hydrogel lens (middle) and dome-type hydrogel lens (right). Scale bar, 1 cm. ( d ) Experimental intensity distribution of spatial radiation of the LEDs. Inset: photographs of spatial radiation distribution. \n To control the light intensity distribution we fabricated crater- and dome-type silk hydrogel lenses. An advantage of using hydrogels is that they can be simply molded into any shape required for specific optical application 12 , 33 – 35 . To shape the silk hydrogels for lens application, the molds were designed (with Solidworks software) and 3D printed (with ULTRA 3SP) (Fig. S1 ). After the silk solutions were poured into their molds and covalently crosslinked, the solid structures were integrated on top of the dies (Fig. 2c ). We experimentally measured the intensity distribution of spatial radiation of crater-type silk hydrogel lens and dome-type silk hydrogel lens on a cool white LED (Fig. 2d ). The dome-type lens shows similar focusing of light around the center (inset Fig. 2d , right). The crater-type lens showed maximum intensity of light at 20° and −20° (inset Fig. 2d , middle), which is close to the value of numerical simulations. When we re-sampled simulation data with 10 degree polar angle intervals which was identical with the experimental sampling condition, the peak angle for crater- and dome-type lenses of simulation and experimental results were equal. However, it was observed that silk hydrogels broaden the peaks in crater- and dome-type lenses, probably due to scattering, (Fig. 2d ) in comparison with the simulation (in which the scattering effect was not included) (Fig. 2b ). To understand the scattering phenomena in silk protein hydrogels, we introduced scattering and anisotropy g-factor to the ray tracing simulation. When light is scattered, it deviates from its expected trajectory in a homogenous medium between two spatial points defined by the Fermat’s Principle of least time (Fig. 3a ), and the amount of retained light after a single scattering event is defined by the anisotropy factor. The scattering in silk hydrogels originate due to the local refractive index changes by the fibroin protein and water. The scattering coefficients for the simulated hydrogels were swept between 0–0.3, and the anisotropy factors were swept between 0.1–0.95 both for crater- and dome-type lenses to understand the spatial broadening of light distribution. The intensity distribution of spatial radiation were obtained for each value of scattering coefficient and anisotropy factor, and sampled with 10° intervals. Then, the root mean square error (RMSE) between experimental and simulated data were calculated. The RMSE of dome- and crater-type errors between simulated and experimental data for each sweeping condition is shown in Fig. 3b . The minimum average error was obtained for a scattering coefficient of 0.05 per mm and an anisotropy factor of 0.7, which lead to a similar angular intensity profile for dome- and crater-type radiation patterns, respectively (Fig. 3c and d for dome- and crater-type lenses, respectively). Figure 3 ( a ) Schematic representation of scattering in silk protein hydrogel. ( b ) Root mean square error between experimental and ray tracing results. Scattering coefficient was varied between 0 and 0.3 mm −1 and g-factor was varied between 0.1 and 0.95. ( c ) Experimental measurement and simulated ray tracing of intensity distribution of spatial radiation for dome-type lens and ( d ) for crater- type lens while minimum error was obtained at a scattering coefficient of 0.05 mm −1 and g-factor of 0.7. \n Light extraction and stability of silk hydrogel lenses We investigated the optical efficiency of silk hydrogel lenses. To analyze the light extraction efficiency (LEE) of lenses, we prepared silk hydrogel hemisphere lenses (Fig. 4a ) and measured LEE of the samples using an integrating sphere for white LEDs (Supplementary Fig. S2 ). Since the silk hydrogel transmittance was affected by the wavelength of the light, we tested the extraction efficiency for both cool and warm white LEDs, which have distinct blue and orange peaks in the visible spectrum (Fig. 4b and c ). While the 8 wt% silk hydrogel lens had a LEE of 0.81 for a cool white LED (Supplementary Table S1 ), LEE of the lens increased to 0.89 for a warm white LED (Table 1 ). This increase in the efficiency from a cool to a warm white LED is expected due to the rise in the transmittance of the silk hydrogel at longer wavelengths (Fig. 1 ). Another important parameter that can enhance the extraction efficiency is the decrease of the silk concentration in the hydrogel. Thus, we decreased the silk concentration to 3 wt% and extraction efficiency dramatically increased to 0.85 for a cool white LED and 0.96 for a warm white LED (Fig. 4d ). We compared the performance of the silk hydrogel with another widely used material of polydimethylsiloxane (PDMS) and the PDMS lens showed LEE of 0.90 for cool white LED and 0.91 for warm white LED. Therefore, silk hydrogel lenses with 3 wt% is preferable for the integration with a warm white source that can significantly enhance the performance of the power conversion efficiency of the LEDs. Figure 4 Light extraction efficiency and stability of biomaterial lenses. ( a ) Schematic of silk hydrogel with biopolymer layer coating. ( b ) Absolute irradiance of cool and warm white LED. ( c ) Photographs of 8 wt% silk hydrogel lens on a cool white LED (top) and on a warm white LED (bottom). Scale bar, 1 cm. ( d ) Light extraction efficiency (LEE) of silk hydrogel (SH) lenses with and without top coating, and PDMS lens on cool and warm white LEDs. ( e ) Weight decay of silk hydrogel lens. Black line: sole silk hydrogel lens, cyan line: 8 wt% silk hydrogel lens with poly(ester-urethane) coating, blue line: 8 wt% silk hydrogel lens with paraffin wax coating. Inset: zoomed weight decay of silk hydrogel lens with paraffin wax coating. \n Table 1 Optical parameters of biomaterial lenses on warm white LED. LEE: Light extraction efficiency, SH: silk hydrogel. Lens LER (lm/W opt ) Luminous flux (lm) Luminous efficiency (lm/W elec ) Electrical input Power (mW) Optical output Power (mW) LEE Chromaticity coordinates (x, y) No lens 362 2.78 78.68 35.33 7.70 — 0.46, 0.42 8 wt% SH lens 365 2.51 71.04 35.33 6.89 0.89 0.47, 0.43 PDMS lens 366 2.58 73.02 35.33 7.06 0.91 0.46, 0.42 Paraffin wax coated 8 wt% SH lens 365 2.28 64.50 35.33 6.25 0.81 0.47, 0.43 Poly(ester-urethane) coated 8 wt% SH lens 372 2.42 68.49 35.33 6.51 0.84 0.47, 0.44 3 wt% SH lens 370 2.74 77.55 35.33 7.41 0.96 0.46, 0.43 \n We also studied the stability of silk hydrogel lenses by measuring its weight change due to the evaporation at 23 °C. The half lifetime of only silk hydrogel (without any polymer coating) was approximately 24 hours (Fig. 4e ). To enhance the lifetime of silk hydrogel lenses, we synthesized biocompatible and biodegradable poly(ester-urethane) coating material by the stoichiometric reaction of 1,6-hexamethylene diisocyanate (HMDI) (Acros Organics, >99.5%) and polycaprolactone diol oligomer (PCL) (<M n > = 2000 g/mol) 36 , and coated the hydrogel lens with the poly(ester-urethane) film. The biopolymer film coating increased the lifetime approximately 3-fold to 70 hours. To further extend the lifetime, a film that shows a strong water vapour barrier needs to be incorporated on the hydrogel lens. For that paraffinic, wax-like materials show high performance since they can significantly block the moisture vapour transmission and they can even be obtained from natural sources (such as beeswax) 37 . We selected the use of paraffin wax, which is an edible biopolymer 37 and used its film to coat the hydrogel. Thus, the lifetime has increased to 2 years and 341 days. Even though the top coating decreased the light extraction, other biopolymers such as polylactic acid, polymethyl methacrylate and waxes can be also explored to determine the coating layer for optimum light extraction efficiency and stability."
} | 5,003 |
38550695 | PMC10967257 | pmc | 8,940 | {
"abstract": "Smooth interfaces embedded with low surface free energy allow effortless sliding of beaded droplets of selected liquids—with homogeneous wettability. Such slippery interfaces display low or moderate contact angles, unlike other extremely liquid repellent interfaces ( e.g. superhydrophobic). These slippery interfaces emerged as a promising alternative to extremely liquid repellent hierarchically rough interfaces that generally suffer from instability under severe conditions, scattering of visible light because of the hierarchically rough interface, entrapment of fine solid particulates in their micro-grooves and so on. However, a controlled and precise modulation of surface free energy and nanometric roughness is essential for designing a more compelling solid and dry antifouling interface. Here, we have unprecedentedly demonstrated the ability of covalent cross-linking chemistry for precise and simultaneous modulation of both essential surface free energy (∼49 mN m −1 to ∼22 mN m −1 ) and roughness (root mean square roughness from 30 nm to 3 nm) of a solid interface for achieving liquid, substrate, and process independent, robust slippery properties. The strategic selection of β-amino-ester linkage through a 1,4-conjugated addition reaction between amine and acrylate groups of a three component reaction mixture (dominated by a 61% (w/w) crosslinker) under ambient conditions provided a facile basis for associating various important and relevant properties—including self-cleaning ability, anti-smudge properties (against both water and oil-based inks), thermal stability (>300 °C), chemical stability, physical durability, optical transparency (∼95%) and so on. The embedded slippery properties of the coating remained unaffected at both low (0 °C) and high (100 °C) temperatures. Thus, the prepared coating would be appropriate to maintain the unperturbed performance of commercially available solar cell modules and other relevant objects under outdoor conditions.",
"conclusion": "Conclusions While an extremely water-repellent hierarchically rough coating and a liquid-infused slippery porous surface generally suffered from incomplete self-cleaning of ultra-fine particulates and poor shelf-life, respectively, we successfully developed a non-fluorinated liquid-independent solid slippery coating through precise and simultaneous modulation of nanometric roughness and surface free energy. This current covalent crosslinking-based approach aims to design a more comprehensive solid slippery coating that is embedded with various other relevant properties—including high optical transparency, chemical, thermal, and mechanical stability. Moreover, the prepared coating was successfully applied on various types of substrates (glass, plastic, paper, wood, and metal) following commonly and widely accepted different deposition processes (doctor blade method, dip-coating, spray coating, spin coating, etc ). In our current design, the 1,4-conjugate addition reaction between three selected reactants (polydimethylsiloxane (poly[dimethylsiloxane- co -(3-aminopropyl) methylsiloxane] (PDMS- co -APMS), 3-(2-aminoethylamino)propyltrimethoxysilane (AEAPTMS) and dipentaerythritol penta-acrylate (5-Acl)) yielded a gel, where the β-amino-ester bond provided the essential low surface energy to display effortless sliding of beaded droplets of water, polar/nonpolar organic solvents, crude, and refined oils. Moreover, the selection of an appropriate crosslinker improved the thermal stability of the coating from 190 °C to 310 °C. The prepared coating remained appropriate to survive prolonged exposures (15 days) to extremes of pH (1 and 12), seawater and surfactant-contaminated aqueous phases. It remained tolerant to commonly adopted physical abrasion tests including adhesive tape peeling, cotton wiping, tissue paper wiping tests and sand drop test. More importantly, such durable coating that displayed superior anti-smudge, anti-fouling and self-cleaning abilities was successfully applied to a commercially available solar cell module without compromising its photovoltaic performance. The liquid independent solid slippery coating remained efficient in self-cleaning beaded oil-droplets and solid particulates to display unaltered photovoltaic performance of the coated solar cell module even after repetitive exposures to oil and dust. Although the sliding angle of beaded liquids on the prepared coating is relatively higher than that of the earlier reported liquid like or semisolid slippery coating, the prepared liquid-independent solid slippery coating with all-inclusive features would be appropriate for various other potential applications—including underwater gas transport. 76,77 In addition to sliding various beaded liquids in air, this chemical approach of controlled modulation of topography and surface free energy is likely to provide a facile basis for precisely modulating both air-bubble wettability and adhesion. Thus, the current approach has the ability for controlled underwater gas delivery, gas sensing, efficient water splitting etc.",
"introduction": "Introduction The growing concerns about the worldwide change in the climate and global energy crisis trigger the search for potential renewable power sources. 1–7 In this context, the outdoor installation of photovoltaic solar panels that convert sunlight into electrical energy emerged as one of the leading and promising approaches. 8–11 However, unavoidable deposition of different forms of particulate matter, such as dust, dirt, soot, fly ash, pollen, and other organic waste, under outdoor conditions appeared as an Achilles heel towards its unperturbed performance. 12–18 In fact, the deposition of fine dust particles that block exposure to sunlight reduces the efficiency of the solar panel by up to 50%. 13 While the limited efficiency of solar panels remained a concern towards energy production cost, the deposited dust would also substantially impact the cost of operation and maintenance of solar panels. To address this concern, various cleaning approaches—including manual cleaning, equipment-based brush cleaning, electrostatic cleaning, vibrating cleaning, heliotex cleaning, forced-air cleaning, etc. , were introduced in the literature. 12,13,19–23 While manual cleaning is time-consuming and laborious, equipment-based cleaning approaches demand complex construction and external power sources. Similarly, several other routinely used commercial goods made up of glass, wood, metal, etc. , suffer from unwanted and unavoidable fouling of liquids (aqueous and oil/oily contaminants)—causing inconvenience to keep these substrates clean and dry. Hence, further development is required to achieve a convenient and energy-efficient cleaning process for the cost-effective maintenance of solar panels and other widely used commercial goods. In this context, inspired by the self-cleaning phenomenon of extremely water-repellent lotus leaves, many research groups have developed different artificial superhydrophobic coatings that displayed heterogeneous water wettability with a water contact angle of >150°, to demonstrate the removal of deposited dust particles by simply rolling beaded water droplets. 24–28 Even after significant progress on this research topic, it is still difficult to design an optically transparent and robust superhydrophobic coating that would be adequate for outdoor applications. The meta-stable trapped air present in the hierarchically featured interface (consisting of micro and nanodomains) that confers superhydrophobicity remains highly labile under abrasive and severe conditions—including scratching, extremes of temperature, high humidity, etc. 29–32 More importantly, porous/hierarchically featured superhydrophobic interfaces with empty groves and pores tend to accumulate fine solid particulates and fail to self-clean the interface completely. 33 On the other side, superhydrophobic interfaces are readily fouled by the exposure of low surface tension liquids. 34 As an alternative approach, superamphiphobic interfaces were developed through the association of rough and specialized topography with environmentally toxic fluorinated modifications to prevent wetting by low surface tension liquids. 35–41 However, such interfaces would be inappropriate to self-clean fine particles as these rough interfaces are likely to trap any deposited fine particulate matter in their groves. 35 The only option to minimize the trapping of fine particles on solid surfaces is to prepare super liquid-repellent interfaces with low (below 500 nm) pore size. 33,42 Hence, the design of a non-fluorinated ultra-smooth coating that displays homogeneous liquid wettability and effortlessly slides all types of liquids—including water, organic solvents, crude/refined/natural oils, and fluorinated liquid droplets, irrespective of the contact angle of the beaded liquid droplet, would be a promising alternative to achieve comprehensive self-cleaning and anti-fouling performance, unlike extremely liquid repellent interfaces ( e.g. superhydrophobic). In this context, the nepenthes pitcher plant-inspired slippery liquid-infused porous surface remained capable of sliding various liquid droplets, but it fails to provide a dry interface; rather unavoidable leaching of the infused liquid lubricant affects its shelf-life. 43–47 To address this challenge, recently solid–slippery interfaces were introduced following a few approaches, i.e. , (1) infusion of phase transitioning solid lubricants (polymer and paraffin) in a porous matrix, 48–53 (2) attachment of a flexible polymer, 54–60 (3) growth of polymer brushes, 61–63 (4) layer-by-layer surface growth of nanoparticles 53,64 and deposition of nanoparticles, 65,66 and (5) assembly of oligomers. 67–70 Such earlier reported approaches mainly concentrated on minimizing the nanometric roughness to achieve sliding of beaded droplets of water and organic solvents. Thus, the reports of solid slippery coatings with a comprehensive ability to slide beaded droplets of all types of liquids—including water, polar/non-polar organic solvents, crude oil, commercially available refined and natural oils and even fluorinated liquids are very limited in the relevant literature ( Table 1 ). Moreover, reported solid slippery coatings predominantly suffer from tedious or specific synthesis processes, additional thermal/UV-assisted curing steps, optical transparency, thermal stability, and limited scope for substrate selection, as illustrated in Table 1 . Earlier methods were less appropriate to simultaneously and precisely modulate both nanometric roughness and surface free energy. Hence, further design of solid slippery coating is essential to address all these relevant and important concerns. Instead of attaching or infusing polymers and growing polymer brushes, here, we report a completely different strategy to develop a highly compelling solid slippery coating, where a covalently cross-linked gelation process is introduced through a 1,4-conjugate addition reaction between selected non-fluorinated three components of a reaction mixture ( Scheme 1A–F ) under ambient conditions to modulate essential roughness and surface free energy for developing a highly optically transparent (above 95%) and substrate-independent ( e.g. , paper, wood, metal, plastic, glass etc. ), process-independent and liquid (polar/nonpolar solvents, and natural, refined and crude oils)-independent tolerant solid slippery coating. The coating was successfully prepared following various commonly adopted methods—including dip-coating, spin coating, paint-brush, doctor blade and spray deposition ( Scheme 1C ). The covalent cross-linking between selected reactants through β-amino ester bond formation contributed to achieving smooth coating with low surface free energy for conferring liquid-independent solid slippery properties with thermal, mechanical, and chemical stability ( Scheme 1D ). Taking advantage of high optical transparency and durability, a solar cell module is successfully coated with this prepared solid slippery coating without any perturbation to its photovoltaic performance ( Scheme 1F ). Moreover, the self-cleaning and anti-fouling ability of this coating protects its performance from deposited dust and oil/oily substances. Thus, this simple chemical approach provided a highly compelling and liquid-independent solid slippery coating that would be useful in various practically relevant applications. The comparison of the prepared solid slippery coating with previous reports with respect to substrate independence, fabrication process, liquid repellency, optical transparency, thermal stability, and chemical durability Selected substrates Fabrication conditions Ability to slide oils Optical transparency Thermal stability Chemical durability Ref. no. Glass Room temperature No 92% — — \n 49 \n Polymer film 130 °C in a vacuum oven No — — NIR irradiation and silicone oil for 6 months \n 50 \n Glass 80 °C temperature No — — pH (1–13) for 40 h \n 51 \n ITO Hydrothermal/80 °C No — — — \n 52 \n Glass, silicon, ceramics, metals, and plastics 100 °C temperature Silicone oil 77.3% 60 °C — \n 53 \n Glass 60 °C, 50 mbar No — — — \n 54 \n Glass and PET 75 °C No ∼90% 100 °C — \n 55 \n Silicon wafer and gold Room temperature No — — — \n 56 \n Silicone wafer, glass, FTO, conductive glass, and metals UV irradiation No — — 1 M NaOH (10 min) \n 57 \n NaCl solution (1 h) Gold wafer Room temperature No — 35 °C — \n 58 \n Glass, silicon, and aluminium 60 °C temperature Crude oil ∼92% 105 °C — \n 60 \n Glass, silicon wafer, titanium dioxide, silicon oxide, and zinc oxide Room temperature Castor oil and seed oil ∼90% 70 °C Sonication (45 kHz, 60 W) for 6 h in toluene \n 61 \n Glass, stainless steel, wood, and cotton fabric 120 °C temperature No 90% — — \n 62 \n Glass and silicon wafer Room temperature No 90% 100 °C UV irradiation (30 days) \n 63 \n 100 °C (30 days) Glass 120 °C temperature Veg oil ≥92% 200 °C pH 1 and pH 2 for 1 month \n 64 \n pH 11 and pH 12 for 12 h Glass and Al-plate Room temperature No 80.6% 240 °C UV irradiation for 1 month \n 65 \n Ambient conditions for 6 months Glass and polymer films 80 °C temperature No 97% — pH 1, pH 12, DTAB (1 mM), SDS (1 mM), seawater, river water, and UV (15 days) \n 66 \n Glass and PET UV curing No 98% — — \n 67 \n Glass, PTFE, Al, and Cu sheets Melt casting Grape seed oil and olive oil — 90 °C UV irradiation (30 days) \n 68 \n Glass, PET, and steel UV curing Pump oil, cooking oil, coal oil, and crude oil >80% 100 °C pH (2–13) for 12 h \n 69 \n Organic solvent exposure for 72 h Glass 150 °C temperature No 95% — — \n 70 \n Glass, paper, metal, plastic, and wood Room temperature, no additional treatment with UV light or elevated temperature Krytox, vegetable oil, motor oil, crude oil, diesel, petrol, and kerosene ∼95% 300 °C Exposure to pH 1, pH 12, DTAB (1 mM), SDS (1 mM), seawater, and river water for 15 days This work Exposure to UV (254 nm and 365 nm) for 1 month and ambient conditions for 6 months Scheme 1 Design of highly compelling liquid independent solid slippery coating. (A) Chemical structures of 1,6-hexanediol diacrylate (2-Acl), trimethylolpropane triacrylate (3-Acl), dipentaerythritol penta-acrylate (5-Acl), poly[dimethylsiloxane- co -(3-aminopropyl)methylsiloxane] (PDMS- co -APMS) and 3-(2-aminoethylamino)propyltrimethoxysilane (AEAPTMS). (B) 1,4-Conjugate addition reaction between amine groups of PDMS- co -APMS and AEAPTMS and acrylate groups of the selected cross-linker, i.e. , 5-Acl, yielded a covalently cross-linked transparent gel through the formation of β-amino ester bonds. (C) Schematic illustration of the preparation of a solid slippery interface utilizing various common approaches—including dip-coating, spin coating, paint-brush, doctor blade and spray deposition. (D and E) Schematic representation of an optically transparent, highly durable liquid independent solid slippery interface on various substrates including paper, wood, metal, plastic and glass. (F) Schematic demonstrating antifouling and self-cleaning of beaded droplets of oil/water and solid particles on a liquid independent solid slippery coated solar cell module.",
"discussion": "Results and discussion In the past, 1,4-conjugate addition reaction was extended to develop hierarchically rough coatings to associate heterogeneous liquid wettability. 71–74 In spite of developing rough/porous coating, here, a completely orthogonal strategy is adopted. Covalent crosslinking chemistry is strategically and unprecedentedly introduced to obtain a simple and rapid sol–gel conversion of a reaction mixture of selected primary amine-containing polydimethylsiloxane (poly[dimethylsiloxane- co -(3-aminopropyl)methylsiloxane] (PDMS- co -APMS)), self-polymerizable monomer (3-(2-aminoethylamino)propyltrimethoxysilane (AEAPTMS)) and selected crosslinkers (1,6-hexanediol diacrylate (2-Acl), trimethylolpropane triacrylate (3-Acl), and dipentaerythritol penta-acrylate (5-Acl)) through a 1,4-conjugate addition reaction under ambient conditions, as shown in Scheme 1 . In this three component-based design of liquid-independent solid slippery coating, AEAPTMS acts as a binder while PDMS- co -APMS and the cross-linker synergistically modulate the desired nanometric roughness and low surface energy to confer liquid independent slippery properties. The reaction mixture (RM) of PDMS- co -APMS, AEAPTMS and 5-Acl denoted as RM-III produced a transparent gel within 40 minutes, as shown in Fig. 1A, C and S1C † where the molar ratio of 5-Acl, PDMS- co -APMS and AEAPTMS was kept at 370 : 2 : 340. In this design, the major constituent (∼61% (w/w)) of the RM-III is the selected crosslinker, i.e. , 5-Acl, whereas the weight percentages of other reactants PDMS- co -APMS and AEAPTMS are maintained at ∼15% (w/w) and ∼24% (w/w), respectively. The progress of the 1,4-conjugate addition reaction under ambient conditions was monitored with attenuated total reflection-Fourier transform infrared (ATR-FTIR) analysis, where the characteristic IR signatures for the symmetric C–H deformation of the vinyl moiety at 1410 cm −1 gradually depleted with respect to the normalized IR signature at 1730 cm −1 for carbonyl stretching, as shown in Fig. 1D . This simple IR study unambiguously supported the mutual covalent reaction between selected reactants. Fig. 1 Optimization of reaction mixtures. (A and B) Digital photographs showing sol–gel conversion of RM-III (where 5-Acl was selected as the cross-linker) resulting in the formation of a transparent gel within 40 min (A), whereas the reaction mixture in the absence of any cross-linker remains unaltered even after keeping it for 1 day (B). (C) Bar graph indicating the time required for conversion of optically transparent different (with respect to selection of crosslinkers: 2-Acl, 3-Acl and 5-Acl) reaction mixtures (RM-I (crosslinker: 2-Acl), RM-II (crosslinker: 3Acl) and RM-III (crosslinker: 5-Acl)) into a gel, where RM-1 failed to form any gel even after 1 day, rather provided a turbid solution. Inset digital images represent the transparent and opaque gels and turbid reaction mixture. (D) Attenuated total reflection-Fourier transform infrared (ATR-FTIR) spectra of RM-III at different time intervals. The 1,4-conjugate addition reaction between amine and acrylate resulted in the formation of a β-amino ester bond—where the vinyl moiety is consumed, keeping the carbonyl moiety unaffected ( Fig. 1D and S2 † ). On the other side, a prominent appearance of characteristic IR signatures at 1087 cm −1 and 1047 cm −1 for antisymmetric stretching vibrations of Si–O–Si was noticed, as shown in Fig. 1D . This simple study validated the self-polymerization of the silane moiety of AEAPTMS. It is worth mentioning that the 1,4-conjugated addition between available amine and acrylate in the reaction mixture resulted in a gradual depletion of the IR signature at 1410 cm −1 , whereas IR signatures (at 1087 cm −1 and 1047 cm −1 ) for Si–O–Si linkage because of the self-condensation reaction of selected silane dominated later. Thus, the sol–gel conversion process involves cross-linking through β-amino ester bond formation and the self-polymerization of the silane moiety. In the absence of a cross-linker, the physical state of the transparent reaction mixture of selected reactants remained unaltered and failed to transform into a gel, as shown in Fig. 1B and S1D. † However, for other reaction mixtures, RM-II (reaction mixture-II) and RM-I (reaction mixture-I) having different crosslinkers, i.e. , 3-Acl and 2-Acl, provided an opaque gel and a turbid dispersion, respectively, as shown in Fig. 1C , S1A, B and S4. † The choice of cross-linker having the difference in the cross-linking point ( i.e. , the acrylate group) displayed an obvious influence on the sol–gel conversion process and optical transparency of the resultant gels. Dynamic light scattering (DLS) study revealed the existence of smaller aggregates in RM-III (∼122 ± 3.8 nm) compared to RM-II (∼377 ± 15.7 nm), prior to their complete sol–gel conversion. RM-II with bigger aggregates appeared more turbid because of more scattering of light. It is worth mentioning that the molar concentration of acrylate functional groups was kept identical for all three different reaction mixtures (RM-I, RM-II, and RM-III)—though different crosslinkers (2-Acl, 3-Acl and 5-Acl) were utilized. The analysis of FTIR spectra of these reaction mixtures after sol–gel conversion revealed the presence of a very similar content of residual acrylate groups (Fig. S3 and S4 † ), suggesting a similar extent of 1,4-conjugate addition reaction between the available acrylate and amine groups in the respective reaction mixtures. Thereafter, all these reaction mixtures (RM-I, RM-II, and RM-III) were prepared individually—and explored further to prepare liquid independent solid slippery coatings. Thereafter, a series of reaction mixtures (analogues of RM-III) were prepared by mixing primary amine containing reactants (PDMS- co -APMS and AEAPTMS) with a selected cross-linker, i.e. , 5-Acl in ethanol where the concentration of 5-Acl was altered gradually from 0.07 M to 1.3 M maintaining the concentrations of PDMS- co -APMS (0.048 g ml −1 ) and AEAPTMS (0.07 g ml −1 ) unperturbed. These reaction mixtures were individually applied on clean glass substrates following the doctor blade method and air-dried under ambient conditions to achieve respective solid and dry coating. Thereafter, both static contact angle (SCA; volume of droplets: 5 μl) and sliding angle (SA) of beaded droplets of water (40 μl) and crude oil (a highly complex organic liquid; 10 μl) on the prepared coatings were examined. The concentration of the selected cross-linker ( i.e. , 5-Acl) influenced the slippery properties of the resultant coatings. When the concentration of 5-Acl in the deposition solution was maintained in the range of 0.37 M to 0.97 M, the prepared coatings displayed slippery properties for beaded droplets of both water and crude oil with sliding angles of <20° as shown in Fig. 2A . Fig. 2 Crosslinker-assisted simultaneous and precise modulation of roughness and surface free energy. (A) Bar graph depicting the change in static contact angle (SCA) and sliding angle (SA) of beaded droplets of water and crude oil on the coated interface, where the concentration of the selected crosslinker (5-Acl) was gradually increased in reaction mixtures. (B and C) SCA and SA images of beaded droplets of water (B) and crude oil (C) on the optimized (concentration of 5Acl: 0.37 M) coated interface. (D and E) The atomic force microscope (AFM) 3D topography images of coatings obtained with a crosslinker (5-Acl) concentration of 0.07 M (D) and 0.37 M (E) in RM-III. (F–I) Tapping mode 2D topographic AFM images of coatings that were derived maintaining the concentrations of the crosslinker (5-Acl) at 0.07 M (F) and 0.37 M (G) and the corresponding height profiles measured along the red, blue and green lines for coatings with crosslinker (5-Acl) concentrations of 0.07 M (H) and 0.37 M (I). (J) The surface free energy (SFE) of coatings that are derived from different reaction mixtures having only a difference in the concentration of 5-Acl. (K–M) Static contact angle, digital (scale bar: 1 cm) and sliding angle of beaded water and crude oil droplets (5 μl) on 5-Acl/PDMS- co -AMPS coated (K), 5-Acl/AEAPTMS coated (L) and PDMS- co -AMPS/AEAPTMS coated (M) glass slides. The star mark indicates spilling of crude oil. (N) Bar graph illustrating the surface free energy (SFE) of coatings derived from three different reaction mixtures-5-Acl/PDMS- co -AMPS, 5-Acl/AEAPTMS, PDMS- co -AMPS/AEAPTMS and RM-III (5-Acl/PDMS- co -AMPS/AEAPTMS) where content of acrylate and amine groups was maintained identical. For example, the coating derived by maintaining the concentration of 5-Acl at 0.37 M enabled the effortless sliding of both beaded droplets of water and oil droplets with a SCA of 105.1° and 31.5° and SA of 17° and 15°, respectively, as shown in Fig. 2B and C . However, for other reaction mixtures having the 5-Acl concentration below and above the mentioned range, the resultant coatings displayed slippery properties only for beaded water droplets at higher sliding angles and absolutely failed to slide beaded droplets of crude oil, as shown in Fig. 2A . To understand this phenomenon, the topography of the three different coatings that were prepared by selecting three distinct concentrations of crosslinker (5-Acl)— i.e. 0.07 M, 0.37 M and 1.1 M in RM III, was examined with 3D atomic force microscopy images. A very apparent change in topography for these coatings was noted, as shown Fig. 2D, E and S5. † Moreover, the line profiles presented in Fig. 2F–I and S5 † unambiguously indicated the formation of smoother coating on increasing the concentration of the selected crosslinker. The root mean square (RMS) roughness depleted with increasing the concentration of 5-Acl, where RMS roughness values were measured to be ∼30 nm, 6 nm and 3 nm for coatings that were derived by maintaining the crosslinker concentration at 0.07 M, 0.37 M and 1.1 M, respectively. Upon further increasing the concentration of crosslinker 5-Acl beyond 1.1 M, the roughness of the coatings remains very similar (Fig. S5 and S6 † ). The extent of covalent crosslinking is likely to provide a more or less compact polymeric network in the prepared coatings. A denser polymer network is expected to contribute to lowering the surface roughness, and such depletion of surface roughness by the association of crosslinking chemistry has been realized in the past to modulate cell adhesion behavior. 75 But, interestingly, the coatings with the highest and lowest RMS roughness among these selected coatings displayed inability to slide beaded droplets of crude oil as shown in Fig. 2A ; rather spillage and spreading of beaded droplets of crude oil were noticed. Thus, the current study unambiguously suggests that surface topography alone is not instrumental in controlling the sliding behaviour of beaded droplets of liquid on a smooth solid interface. Thereafter, another important parameter, i.e. , surface free energy (SFE), of the prepared coating was measured, where the concentration of the selected crosslinker in RM-III was gradually increased. It was observed that the concentration of the cross-linker influenced the surface free energy of the coating. At lower (below 0.37 M) and higher (above 0.97 M) concentrations of 5-Acl in the depositing reaction mixture, the SFE of the coating was found to be relatively higher in comparison to the selected concentration range (from 0.37 M to 0.97 M), as shown in Fig. 2J . The minimum surface free energy, i.e. , 22 mN m −1 , was noticed for a 5-Acl concentration of 0.37 M. At lower concentrations of 5-Acl, fewer acrylate groups are available to provide β-amino ester cross-linkages through the 1,4-conjugate addition reaction. Hence, the surface free energy remained high. On increasing the concentration of 5-Acl, more acrylate groups are converted to β-amino ester cross-linkages through the 1,4-conjugate addition reaction, thereby lowering the SFE of the coating, whereas at relatively high concentrations of 5-Acl, the amount of unreacted and residual acrylate groups is more (Fig. S7 † ), which is again likely to elevate the surface free energy of the resultant coating. As a consequence, a slight elevation (28 ± 0.88 mN M −1 to 30 ± 0.72 mN m −1 ) in the surface free energy (SFE) of the coating was noticed when increasing the concentration of 5-Acl beyond 1.1 M (Fig. S6 † ). Thus, β-amino ester cross-linkage in the prepared coating derived from RM-III provided a facile basis to alter surface free energy of a solid coating. Thereafter, a separate control study was performed to understand the role of β-amino ester cross-linkages in achieving optimum SFE. In this study, three distinct reaction mixtures were prepared by individually mixing crosslinkers with the other two reactants (PDMS- co -APMS and AEAPTMS) to develop three different coatings for evaluating their slippery behaviour. First, the selected crosslinker, i.e. 5-Acl (0.37 M), was individually mixed with either PDMS- co -APMS (2 mM) or AEAPTMS (0.34 M) to get two different reaction mixtures. On the other side, AEAPTMS (0.34 M) and PDMS- co -APMS (2 mM) were mixed together to prepare a third reaction mixture. The concentrations of the respective reactants were kept identical to the optimized RM-III that provided the desired slippery behaviour with a low SFE of 22 mN m −1 . Interestingly, polymeric coatings derived from these three different reaction mixtures of 5-Acl/PDMS- co -APMS, 5-Acl/AEAPTMS and AEAPTMS/PDMS- co -APMS failed to display slippery properties against the beaded droplets of crude oil. However, the beaded droplets of water slide at comparatively higher tilting angles, as depicted in Fig. 2K–M . This is because of the comparatively higher (∼35 mN m −1 to ∼49 mN m −1 ) SFE of these three coatings, as shown in Fig. 2N . This controlled study supports that the depletion of SFE of the prepared coating derived from RM-III is not just dependent on the amount of 5-Acl, but rather on the β-amino ester bonds that formed through the mutual reaction between the acrylate group of 5-Acl and amine groups of the other two reactants (PDMS- co -APMS or AEAPTMS) attributed to the change in SFE. The content of high β-amino ester bonds in the polymeric coating resulted in a low SFE and allows sliding of both oil and water droplets. To gradually and orthogonally modulate roughness of coatings—keeping their surface free energy unaltered, another set of control studies was introduced. In this context, separate reaction mixtures were prepared by associating different cross-linkers—i.e., 3-Acl and 2-Acl instead of 5-Acl (RM-III), keeping the content of acrylate groups identical. In addition to RM-III, two different coatings that were derived from these reaction mixtures (RM-I and RM-II) successfully slid both beaded droplets of oil and water, as the SFE of all coatings remained low and very similar (<25 mN m −1 , Fig. 3B ). However, the sliding angle of the beaded droplets was noticed to be minimum for RM-III ( Fig. 3A and S8A–O † ). This is likely due to the change in the surface roughness of the resulting coatings. The RMS roughness of the coating derived from RM-III was found to be the least (6 nm), while RM-I provided coating with a relatively higher roughness of 16 nm, as shown in Fig. 3B . Actually, the selected crosslinker having a difference in the crosslinking points (2 acrylate groups in 2-Acl, 3 acrylate groups in 3-Acl and 5 acrylate groups in 5-Acl) is expected to provide polymeric coating with a less or more dense network, as shown in Fig. 3D . Such a difference in the structure (less or more dense) of the polymer network in the prepared coating is likely to control the surface roughness. 75 This study revalidates that (i) low SFE is essential to achieve slippery properties against both water and oil phases and (ii) low roughness improves the sliding angle of beaded liquid droplets on the slippery coating. Thus, both the crosslinking chemistry ( i.e. β-amino-ester linkage) and the structure of the cross-linked network in the polymeric coating control the slippery properties through controlled modulation of roughness and SFE. Fig. 3 (A) Comparing the SCA, SA and CAH of water and crude oil droplets on the coated interfaces that are prepared from different reaction mixtures (RM-I, RM-II, and RM-III). (B) The plot illustrating the change in surface roughness (root mean square (RMS) roughness) and surface free energy (SFE) of coatings that are derived from RM-I, RM-II, and RM-III. (C) Presenting the optical transparency of coating prepared from RM-III, normalized with respect to a bare glass substrate. (D) Schematic illustrating the use of different crosslinkers in achieving a denser polymer network. (E) Graph depicting the SCA and SA of various polar/non-polar liquids and refined/crude oils on the coated interface derived from RM-III. (F) The plot depicting the wettability and SA of beaded droplets of water and crude oil on the coatings prepared from RM-III—following different deposition methods. Such a smooth uniform coating remained appropriate to prevent scattering of light and eventually displayed high optical transparency above 95% at a wavelength of 550 nm, as shown in Fig. 3C , where the optical transparency of the coating is normalized with respect to a bare glass substrate. In addition to water and crude oil, the slippery properties of the prepared solid and dry coating were examined against various other liquids, including polar and non-polar organic solvents and refined oils. The prepared coating remained capable of readily sliding beaded droplets of various types of liquid—including polar (water, DMSO, DMF, glycerol, acetone, hexanol, 1-propanol, methanol, and ethanol), nonpolar (DCE, DIM, toluene, THF, dodecane, and decane) liquids and commercially relevant refined (motor oil, petrol, diesel, and kerosene), crude, and natural (vegetable) oils and fluorinated liquid (Krytox) with a sliding angle well below 20°, as shown in Fig. 3E , S9, S10 and Movie 1, † irrespective of surface tension and viscosity of selected liquids. Thus, the developed coating displayed high optical transparency and liquid independent slippery properties. Interestingly, the simple sol–gel conversion process of the deposited reaction mixture is successfully explored to prepare such anti-fouling interfaces following various standard fabrication methods, including doctor blade, dip coating, paint brush, spray deposition and spin coating without affecting the sliding behavior of beaded droplets of both water and crude oil as shown in Fig. 3F . The deposited solution undergoes a similar sol–gel conversion under ambient conditions, irrespective of the deposition method. Except for air drying under ambient conditions, additional external interventions ( i.e. heat treatment or UV treatment) are not essential to develop the current coating. The RMS roughness of the prepared coating remained very similar (Fig. S11 † )—irrespective of the deposition process, as the depositing solution undergoes the same sol–gel conversion through a 1,4-conjugate addition reaction under ambient conditions. The durability of the prepared coating against different and severe conditions was examined in detail to check its suitability towards its prospective practical applications under outdoor conditions. In the relevant literature, thermal stability of the solid slippery coating remained a concern; often the earlier reported coating failed to survive temperature beyond 200 °C (Table S1 † ). In comparison to earlier literature, the prepared coating derived from RM-III displayed superior thermal stability, as its thermal decomposition was noticed only after exposure to temperature beyond 300 °C, as shown in Fig. 4A . The selection of the crosslinker played an important role in tailoring the thermal stability of the prepared coating as is evident from the early thermal decomposition of the prepared coatings consisting of other crosslinkers, i.e. , 3-Acl and 2-Acl, as shown in Fig. 4A . In the absence of cross-linking, the coating derived from a mixture of PDMS- co -AMPS and AEAPTMS failed to survive temperatures even below 150 °C. Thus, the appropriate selection of cross-linker in the reaction mixture is attributed to improve the thermal stability of the prepared coating—where the crosslinking density through the β-amino ester bond is likely to play an important role. Importantly, the embedded liquid independent slippery properties of the coating remained unaltered even after thermal exposure of the coating to 300 °C. Both the beaded droplets of water and crude oil readily slide off at a tilting angle of <25°, as shown in Fig. 4B . However, the slippery properties were compromised on exposure to 350 °C due to the thermal decomposition of the prepared coating ( Fig. 4B ). Apart from this thermal treatment under dry conditions, the prepared coating was also exposed to extremes of temperature under wet conditions, and it survived the treatment with boiling water (100 °C) and cold water (0 °C) and continued to display slippery properties, as shown in Fig. S12A and B. † Such thermal stability of the coating is attributed to the existence of covalent cross-linkages in the prepared coating. Fig. 4 Durability of liquid independent solid slippery coating. (A) Thermogravimetric analysis of coatings derived from different reaction mixtures without or with selected crosslinkers. (B) Effect of applied temperature on the embedded liquid (water and crude oil) wettability and sliding properties of the prepared coating. (C and D) Stability of the prepared coating under ambient conditions for over 6 months (C) and under UV light exposure ( λ max – 365 nm and 254 nm) for three continuous weeks (D). (E) The plot illustrating the chemical durability of the coating at different and challenging aqueous exposures for 15 continuous days. (F) The plot depicting the physical tolerance of the coating under different physically abrasive exposures—including adhesive tape peeling, tissue paper and cotton rubbing tests. Next, the stability of the prepared coating under ambient laboratory conditions was examined for over 6 months, where the sliding angles of beaded droplets of water and crude oil were measured after every one month, as shown in Fig. 4C . The slippery properties remained unperturbed over the 6 months. The droplets of water and crude oil beaded with static contact angles (SCAs) of ∼105° and ∼30°, respectively and readily slid off on titling the prepared coating at ∼17° and ∼15°. Then, the covalently cross-linked coating was exposed to UV irradiation for 3 weeks and the slippery properties were examined at regular intervals. The beaded crude oil and water droplets readily slid off even after UV light exposure at λ max of 365 nm and 254 nm for 21 days, as shown in Fig. 4D . The prepared coating also displayed tolerance towards different and severe chemical exposures including extremes of pH (1 and 12), river water, artificial seawater, and surfactant contaminated (SDS and DTAB, concentrations of 1 mM) water for prolonged duration (15 days) without perturbing the embedded slippery properties of beaded droplets of water and crude oil, as shown in Fig. 4E . While the recently reported solid slippery coatings suffered from exposures to extremes of pH and other severe chemicals ( Table 1 ), such a covalently cross-linked approach provided a simple basis to achieve thermal, UV and chemical durability. In addition, the prepared coating also sustained different relevant and widely accepted physical abrasion tests including the adhesive tape peeling test, tissue paper rubbing test and cotton rubbing test for multiple cycles (minimum of 50 times) without compromising the embedded liquid independent solid slippery properties ( Fig. 4F and S13A–C † ). Importantly, no delamination of the coating was noted during the adhesive tape test, which supports the existence of strong adhesion between the coating and the substrate. In addition, such slippery coatings prepared following different deposition processes using the same reaction mixture (RM-III) displayed a nearly similar durability against the standard adhesive tape peeling test (Fig. S14 † ). On the other side, the survival of the slippery properties against tissue paper and cotton rubbing tests under an external load of 200 g confirmed the existence of mechanical stability of the prepared coating against relevant physical abrasive exposures. The prepared coating was also tolerant to the sand drop test, where 50 g of sand particles was dropped from a height of 20 cm—however, the prepared coating continued to display slippery properties with effortless sliding of beaded droplets of crude oil and water, as shown in Fig. S15. † Thus, the prepared liquid-independent solid slippery coating with thermal, chemical, and physical durability would be more appropriate for practical applications. In this section, the anti-fouling, anti-smudge, and self-cleaning performances of the prepared coating were examined in detail. The prepared optically transparent coating was individually and completely submerged in various relevant contaminated aqueous phases ( i.e. , water, pH 1, pH 12, juice, cola, and muddy water) and commercially available refined (vegetable oil, motor oil, and kerosene) and crude oils, surfactant (including cationic surfactants (cetyltrimethylammonium bromide (CTAB), 1 mM), anionic surfactants (sodium dodecyl sulfate (SDS), 1 mM) and neutral surfactants (Triton-X 100, 1 mM)) contaminated aqueous phases and crude oil based emulsions (both water-in-crude-oil (2%) and crude-oil-in-water (2%)) as shown in Fig. 5A , S16 and Movie 2. † No trace of liquid was noticed on the prepared coating after removing the coated substrate from the respective liquids. Such self-cleaning performance against a wide range of liquids is attributed to the association of liquid independent slippery properties, unlike the uncoated substrate ( Fig. 5B , S16, S17A and B † ). Next, commercially available oil and water-based permanent markers were manually applied to write on this coated substrate to demonstrate anti-smudge performance as shown in Fig. 5C . Apparently, an immediate shrinkage of deposited inks was noticed on the coated glass due to the embedded anti-fouling properties. Both oil and water-based deposited inks were easily removed from the coated substrate with the application of gentle tissue paper wiping, as shown in Fig. 5C and Movie 3. † However, a completely different outcome was noticed on repeating the same experiment on a bare glass slide, where the selected oil- and water-based inks deposited more and the rubbing with tissue paper failed to completely wipe out the deposited oil- and water-based inks ( Fig. 5D and Movie 3 † ). This simple study validated the existence of anti-smudge performance of the coating, where both water- and oil-based inks can be readily removed with gentle wiping with tissue paper. Such performance is challenging to achieve with earlier reported solid slippery coatings. The preferred surface free energy, smoothness and covalent cross-linking of the prepared coating together contributed to achieving this superior anti-smudge performance. Fig. 5 Anti-fouling, anti-smudge, and self-cleaning properties of the prepared coating. (A and B) Digital photographs of the coated (A) and uncoated (B) interface after immersion and taking out of different aqueous phases and oils. (C and D) Sequential digital photographs depicting the anti-smudge performance of coated (C) and uncoated (D) glass, where both oil- and water-based inks were deposited prior to being wiped out with tissue paper. (E and F) Photographs comparing the self-cleaning of deposited sand, dust, and fly ash particulates on coated slippery (E) and superhydrophobic (F) interfaces. Thereafter, the prepared coating was explored in demonstrating the self-cleaning of deposited relevant solid particulates having different size distributions (Fig. S18A–C † ) including dust, sand and fly ash, and the self-cleaning performance was compared with that of a bio-inspired superhydrophobic coating which is well-recognized for its self-cleaning ability. The prepared liquid independent solid slippery coating displayed absolute self-cleaning ability towards selected solid particles. During the sliding of aqueous droplets on the prepared slippery coating, the deposited solid particles were removed away from the interface to providing an instantly clean and dry interface, as shown in Fig. 5E and Movie 4. † However, the superhydrophobic coating that consisted of hierarchically rough topography failed to completely clean the fine dust particles and fly ash, as shown in Fig. 5F and Movie 5. † Only the deposited sand particles having comparatively large particle sizes (Fig. S18A † ) were self-cleaned on the superhydrophobic interface. As expected, the fine solid particles (particularly fly ash and dust particles; Fig. 5F and S18B and C † ) accumulated in the grooves of the rough topography of the superhydrophobic coating and thus suffered from the incomplete cleaning of the superhydrophobic interface. But the prepared solid slippery coating having an ultra-smooth feature prevented such accumulation of solid particulates and displayed a superior self-cleaning performance ( Fig. 5E ). Taking advantage of the self-cleaning ability and high optical transparency of the prepared coating, we have demonstrated the potential application of this coating on commercially available solar cell modules to keep its performance unperturbed in outdoor settings. The solid slippery coating (SCA = 105.6° and SA = 17° for water and SCA = 55.5° and SA = 16° for vegetable oil; Fig. S19A and B † ) was applied on a solar cell module to achieve (a) effortless sliding of the beaded droplets of oil and water ( Fig. 6A and S19B † ) and (b) self-cleaning of the different deposited solid particulates, as shown in Fig. 6A . As expected, the uncoated solar cell module absolutely failed to (i) slide beaded droplets of water and oil and (ii) self-clean the deposited dust under a similar experimental set-up ( Fig. 6B , S19C and D † ). More importantly, the deposition of this solid slippery coating on the solar cell module barely affects the photovoltaic performance ( Fig. 6C ) as it displays high optical transparency in the visible light spectrum. Thereafter, the coated solar cell module and uncoated solar cell module were individually and consecutively exposed to oil droplets (vegetable oil) and dust particles prior to water exposure ( Fig. 6A and B ). This entire experiment was repeated for 50 cycles, and the output power of the coated and uncoated solar cell modules was measured after every 10 cycles, as shown in Fig. 6D . We noticed a gradual loss of performance of the uncoated solar cell module with increasing self-cleaning cycles due to incomplete removal of oil and dust particles, whereas the coated solar cell module remained successful in keeping the output power unperturbed over the entire 50 cycles under an identical experimental set-up due to its self-cleaning ability. Thus, the prepared coating provided a more appropriate remedy to protect the performance of solar panels from the unavoidable challenges of deposited dust, dirt, and other organic and oily substances. Fig. 6 Impact of the prepared liquid independent solid slippery coating on different substrates. (A and B) Self-cleaning demonstration of deposited dust particulates on coated (A) and uncoated (B) solar cell modules. (C) Photovoltaic performance study of coated and uncoated solar cell modules. (D) The changes in output power of the coated and uncoated solar cell modules during repetitive self-cleaning demonstration 50 times. (E and F) Photographs depicting the sliding of beaded water and crude oil droplets on the coated region (right side of the red color dotted line) of the wrist watch cover (E) and spectacles (F), whereas the uncoated region (left side of the red color dotted line) of the wrist watch cover (sliding angle ∼20°); (E) and spectacles (sliding angle ∼40°); (F) the pinning and spreading of water and crude oil droplets, respectively. (G) Photographs showing the sliding of water and crude oil droplets on the coated aluminium foil (Al foil), plastic, paper, and wood, whereas on the uncoated substrate, water and crude oil droplets pinned and readily spread, respectively. (The red color ‘pause’ sign indicates pinning and spreading of beaded liquid droplets on the uncoated substrate, whereas the green color ‘play’ sign refers to the effortless sliding of beaded droplets of water and crude oil). Next, the optically transparent liquid independent solid slippery coating was successfully applied on other commercially relevant substrates including wrist watch covers and spectacles, where the right half of the selected substrates was coated with slippery coating and the left half was kept uncoated to compare the wettability and sliding behavior of beaded droplets of water and crude oil. As expected, the coated area of the substrate readily slides off the beaded droplets of both water and crude oil without leaving any trace of beaded liquid, whereas the droplets of water and oil strongly adhered and spilled, respectively, on the uncoated portion of the selected substrate as shown in Fig. 6E and F . Importantly, such coating can be successfully applied to many other relevant substrates—including metal, plastic, paper, and wood. On application of the prepared liquid independent coating, all the mentioned oleophilic and hydrophilic substrates (Fig. S20A and B † ) became capable of sliding beaded droplets of both water and crude oil, while the uncoated substrate failed to display such anti-fouling properties ( Fig. 6G ). Additionally, atomic force microscopy (AFM) analysis revealed the presence of similar roughness for different coated substrates, as shown in Fig. S21. † As a consequence, deposited coatings on various substrates displayed very similar slippery properties. The strategically selected 3-(2-aminoethylamino)propyltrimethoxysilane (AEAPTMS) present in the reaction mixture acts as a binding agent and significantly contributes to the adhesive interaction between the coating and underlying substrates. We have investigated the mechanical durability of this developed coating on different substrates where no delamination of the coating was observed after the adhesive tape peeling test and it remained effective in repelling both water and crude oil as shown in Fig. S22. † Thus, the current chemical approach provided substrate-independent, process-independent, optically transparent, and mechanically, chemically, and thermally durable liquid independent solid slippery coating."
} | 12,799 |
35720268 | PMC9204736 | pmc | 8,941 | {
"abstract": "Summary Bioelectrochemical systems (BESs) have made significant progress in recent years in all aspects of their technology. BESs usually work with a membrane or a separator, which is one of their most critical components affecting performance. Quite often, biofilm from either the anolyte or catholyte forms on the membrane, which can negatively affect its performance. In critical cases, the long-term power performance observed for microbial fuel cells (MFCs) has dropped by over 90%. Surface modification and composite material approaches as well as chemical and physical cleaning techniques involving surfactants, acids, hydroxides, and ultrasounds have been successfully implemented to combat biofilm formation. Surface modifications produced up to 6–7 times higher power performance in the long-term, whereas regeneration strategies resulted in up to 100% recovery of original performance. Further studies include tools such as fluid dynamics-based design and plasma cleaning. The biofouling area is still underexplored in the field of bioelectrochemistry and requires systematic improvement. Therefore, this review summarizes the most recent knowledge with the aim of helping the research and engineering community select the best strategy and discuss further perspectives for combating the undesirable biofilm.",
"conclusion": "Conclusion This review outlines several strategies and monitoring approaches oriented towards reducing bioadhesion to the separators used in bioelectrochemical systems. The research was based on doping with carbon materials, coating the surface with polymers, doping with silver nanoparticles, and the synthesis of new membranes with high antifouling potential. The result of these tests was higher resistance to biofouling compared to separators commonly used in bioelectrochemical systems. In addition, a group of physical and chemical methods was identified to regenerate membranes already affected by biofouling. Among them, the chemical cleaning methods proved to be effective and easy to conduct; however, on the other hand, the chemicals used in the process are rather aggressive, may affect the other types of materials in the system, and have to be handled with care. Depending on the type of separator, various strategies can be applied and should take into account not only the efficiency of the method but also its cost-efficiency ( Table 4 ). In general, ceramic membranes are very resistant to aggressive chemical cleaning agents, and some low-cost surface coatings have already been proposed. The most popular ion exchange membranes are also known to be resistant to chemical attack, which makes them easy to clean, whereas their overall high cost also justifies more expensive surface treatments such as nanoparticle modifications. Synthetic polymers were also investigated and seem to be suitable for BES applications. However, their chemical resistance varies, and thus the cleaning agents have to be selected accordingly, whereas their low cost also justifies the replacement, if the BES design allows for it. The most difficult and varied group is composed of natural polymers because of their diverse properties. The safe strategy could be a dedicated surface treatment or carefully selected cleaning agents, whereas Ultrasounds could also be a good alternative for those polymers which present relatively strong mechanical properties. Table 4 Guidelines for choosing the most commonly used membranes in BES and combating biofouling phenomenon Separator type Membrane examples and their cost, EUR/m2 Example membrane durability prior biofouling Suggested strategy References Ceramic Earthenware, 4 Mullite, 16,50 Alumina, 211 81 days for PP80 modified ceramics Low cost surface modification (such as PP coating) and wide variety of chemical cleaning agents, including NaOH, HCl and surfactants, such as SDS and Triton X-100 ( Pasternak et al., 2016a ; 2016b ) ( Pasternak et al., 2021 ) Ion exchange membranes Zirfon, 51 CMI-7000, 340 Nafion 117, 2130 90 days for silica modified Nafion 117 Because of high cost of the membranes, surface modification with gold and silver nanoparticles is justified, chemical cleaning allowed for chemical attack resistant membranes ( Hernández-Flores et al., 2019 ) ( Angioni et al., 2016 ) Synthetic polymers Polypropylene, 0,25 Polystyrene, 0,3 280 days for non-woven fabric polypropylene Low cost surface modification allowed, chemical cleaning adjusted to the type of the polymer, replacement of the separator is economically justified ( Mathuriya and Pant, 2019 ) ( Kondaveeti et al., 2018 ) Natural polymers Mixed cellulose ester, 57 Silk fibroin, 48 60 days for mixed cellulose ester filter Dedicated surface modification, ultrasonic or chemical cleaning ( Wang and Lim, 2017 ) The area of biofouling in BESs is heavily underexplored and techniques derived from other processes may be very useful in combating this problem. Such approaches may involve novel techniques of plasma cleaning, application of electric field, or utilization of computational fluid dynamics to induce shear forces. These techniques have never been tested in bioelectrochemical systems but have proved their applicability to other types of processes. Thus, the topic will certainly benefit from being extended with methods borrowed from other areas of membrane science.",
"introduction": "Introduction Bioelectrochemical systems (BESs) employ live microorganisms involved in various types of electrochemical reactions such as electricity production from wastewater or other types of waste in microbial fuel cells (MFCs) ( Bennetto, 1990 ). In slightly modified reactors, bioelectrochemical synthesis of valuable compounds takes place, known as microbial electrosynthesis or electrofermentation ( Rabaey and Rozendal, 2010 ; Sonawane et al., 2021 ; Roy et al., 2022 ). BESs have also been used for water desalination, electrolysis for the production of hydrogen or methane, and the recovery of metals ( Cao et al., 2009 ; Sleutels et al., 2012 ; Kokko et al., 2017 ; Szydlowski et al., 2022 ). In all of the aforementioned systems, designed for specific applications, the vast majority of the designs are supplied with a membrane or separator. Their purpose is to create a physical barrier that prevents short-circuiting, oxygen and substrate cross-over between cathode and anode electrodes while maintaining the transfer of cations. These membranes are in direct contact with the organic and inorganic compounds, which inevitably leads to biofouling. Biofouling is a phenomenon ( Figure 1 ) based on the aggregation of microorganisms, their metabolites, called extracellular polymeric substances (EPS), and inorganic salts ( Dhar and Lee, 2013 ). Membranes, depending on the type of structural material, are divided into organic, inorganic, and mixed types. The first type is based on polymers, e.g., Nafion or sulfonated polymers. Several other types of polymers have also been investigated. Although the natural polymer-based membranes offer some unique features, they may be susceptible not only to biofouling but also deterioration ( Pasternak et al., 2019 ). In contrast, synthetic polymers such as expanded polystyrene may offer long term durability but also longer start-up times ( Mathuriya and Pant, 2019 ). The inorganic separators group is dominated by ceramic separators, whereas the third group comprises composite membranes ( Dharmalingam et al., 2018 ; Pasternak et al., 2021 ). Ceramic separators offer good power performance but also high porosity, which may lead to high oxygen back-diffusion and substrate crossover, inducing the effects of biofouling ( Pasternak et al., 2016a ; 2016b ). Interactions between chemical compounds that build membranes and the bacteria/EPS matrix result in the formation of a highly adherent coating ( Xu et al., 2020 ). In contrast to biofilm formation on the anode, biofilm on the membranes is not beneficial for the performance of BESs. Such a biofilm layer makes the membrane less permeable for cations and contributes to the increased internal resistance of the system. The decrease in ion conductivity results in lower power density levels in MFCs ( Dharmalingam et al., 2018 ) ( Ji et al., 2011 ). Figure 1 Summary of biofouling layer characterization methods The biofouling layer is mainly composed of microorganisms. Therefore, to mitigate this phenomenon, it is crucial to inhibit the growth of bacteria and the production of their metabolites on the membrane surface. To achieve this objective, various strategies and modifications may be implemented in the BES-based process that could be based on antibacterial components, which kill microorganisms on the membrane surface, or antiadhesion molecules, which prevent the formation of bonds between microorganisms and components of the membrane ( Leong et al., 2013 ). Other membrane physicochemical features that have an impact on bacterial adhesion include hydrophobicity, roughness, and the membrane surface charge ( Pichardo-Romero et al., 2020 ). Although several examples have been published in the field of biofouling prevention in membrane science and technology, only limited knowledge is available for bioelectrochemical systems, and some of these aspects were discussed in a recent review ( Koók et al., 2019 ). Herein, we summarize the most current knowledge in this underexplored field, focusing on biofouling monitoring, assessment, prevention, and removal methods, and discuss possible future tools that may help to combat this phenomenon."
} | 2,375 |
35620795 | PMC9127357 | pmc | 8,942 | {
"abstract": "Silk fibroin is a biobased material with excellent biocompatibility and mechanical properties, but its use in bioelectronics is hampered by the difficult dissolution and low intrinsic conductivity. Some ionic liquids are known to dissolve fibroin but removed after fibroin processing. However, ionic liquids and fibroin can cooperatively give rise to functional materials, and there are untapped opportunities in this combination. The dissolution of fibroin, followed by gelation, in designer ionic liquids from the imidazolium chloride family with varied alkyl chain lengths (2–10 carbons) is shown here. The alkyl chain length of the anion has a large impact on fibroin secondary structure which adopts unconventional arrangements, yielding robust gels with distinct hierarchical organization. Furthermore, and due to their remarkable air-stability and ionic conductivity, fibroin ionogels are exploited as active electrical gas sensors in an electronic nose revealing the unravelled possibilities of fibroin in soft and flexible electronics.",
"conclusion": "4 Conclusions In summary, we explore the synergy between silk fibroin and ILs, through the dissolution and gelation of lyophilised fibroin in selected ILs, giving rise to fibroin ionogels with the lowest water content ever reported, and with unique properties that arise from the combination of both components. The fact that the fibroin polypeptide chains are dissolved in ILs and further allowed to reform thermodynamically stable structures in a high IL content, gave rise to physical ionogels with distinct properties largely dependent on the alkyl chain length moiety of the anion. In fact, the 1-alkyl-3-methylimidazolium chloride ILs act as designer solvents that can tune the induced fibroin secondary structures and the hierarchical organisation of the two components into physical gels. Even though the ILs with larger alkyl chain, such as C 10 mimCl, are known to have their own assembly and crystalline tendency, fibroin enhances the ionogel's mechanical strength despite the absence of β-sheet arrangement, making C 10 F the most stable to air and temperature. In turn, the presence of short alkyl chain length cations has little impact on the fibroin natural assembly, allowing for β-sheet structures to be reformed, which explains the greater mechanical properties of fibroin ionogel using C 2 mimCl when compared to the one with C 6 mimCl, and is also corroborated by the shorter spacings analysed from X-ray scattering patterns. Owing to the characteristics of ILs, the fibroin ionogels were shown not to evaporate and to possess high ionic conductivity, thus creating fibroin sensing layers, in which fibroin is not a passive substrate where active substances are introduced but fibroin is part of the active layer. It is thus possible to produce air-stable fibroin thin films that can be used as gas sensors, in contrary to the fibroin hydrogels that dry out, inhibiting charge mobility. This work sets the ground for establishing fibroin as a much versatile element in flexible and wearable bioelectronic devices.",
"introduction": "1 Introduction The natural polymer silk from Bombyx mori silkworm has a long history in the textile industry and biomedical field due to the unique biodegradability and biocompatibility allied to excellent mechanical properties. These features recently triggered the interest for silk-fibroin based materials in bioelectronics for wearable and flexible devices, albeit still hampered by the limited dissolution of fibroin and by the lack of fibroin-intrinsic conductive properties [ 1 , 2 ]. Silk fibroin, the constituent fibrous protein in the silk fibre core, has a repetitive hexameric motif in its primary structure (Gly-Ala-Gly-Ala-Gly-Ser), with short side chain units closely packed in hydrophobic crystalline regions due to extensive hydrogen bonds. This singular composition contributes to the excellent mechanical properties but also explains the limited solubility in water. In fact, the dissolution and further regeneration of silk fibroin are two challenging steps for which several solvents have been assessed. As an alternative to harsh solvents or aqueous inorganic salts, ionic liquids (ILs) have appeared as effective molecular solvents for the dissolution and regeneration of silk fibroin, exempting subsequent dialysis and significantly reducing the steps of fibroin regeneration [ 3 , 4 ]. ILs are organic salts considered designer solvents due to the versatility in combining anions and cations. Both cation and anion moieties in ILs play an important role in silk fibroin dissolution. After dissolution, the secondary structure of silk fibroin can be altered and transformed back into a water-insoluble structure using coagulation solvents (ethanol, methanol [ 5 ], water [ 6 ] or even protic ILs [ 7 ]). After fibroin regeneration and IL removal, hydrogels [ 8 ], films [ 9 ] or other materials are produced for different applications. As such, ILs have been so far regarded as silk fibroin dissolution and regeneration agents, which are not present (or only partially) in the final fibroin assembled materials [ 10 , 11 ]. Ionogels are generated when ILs are physically entrapped in gelators, such as polymeric matrices. The properties of ILs are typically transferred to the derived ionogels, namely air-stability and ionic conductivity, making ionogels excellent candidates to yield electronic devices [ 12 ]. The research on silk fibroin for flexible electronics and sensing has been so far focused on its use as a substrate [ 2 ] and not as an active component. Composite fibroin materials for use in electronics are obtained by incorporating conducting moieties, namely polymers (e.g. polypyrrole [ 13 ]) and nanomaterials (e.g. carbon nanotubes [ 14 ], silver nanowires [ 15 ] or gold nanoparticles [ 16 ]) into silk fibroin. As an alternative to ILs, ionotronic materials using metal ions and water, are also interesting options to generate silk fibroin conducting materials [ 17 ]. Despite the possible synergetic properties of silk fibroin and ILs, the full potential of this combination for advanced functional materials has not been met. In the present work, the possibility to use fibroin as an ionogelator of methylimidazolium chloride ILs, in the absence of water, was assessed yielding soft materials with unique tunable supramolecular architectures. Furthermore, the resultant air-stable and ionic-conductive fibroin ionogels were assessed as active gas sensing layers for artificial olfaction, widening the impact and applicability of silk fibroin in flexible and wearable bioelectronics and non-invasive sensing devices.",
"discussion": "3 Results and discussion 3.1 Morphology and structure of fibroin ionogels in methylimidazolium chloride ionic liquids Reconstituted silk fibroin presents the repeating motif Gly-Ala-Gly-Ala-Gly-Ser which typically assembles as anti-parallel β-sheets. This arrangement is maintained by the packing of short amino acid side chains of Gly and Ala in hydrophobic crystalline regions. In addition, extensive intra- and inter-molecular hydrogen bond networks between N–H···O \n \n\n<svg xmlns=\"http://www.w3.org/2000/svg\" version=\"1.0\" width=\"20.666667pt\" height=\"16.000000pt\" viewBox=\"0 0 20.666667 16.000000\" preserveAspectRatio=\"xMidYMid meet\"><metadata>\nCreated by potrace 1.16, written by Peter Selinger 2001-2019\n</metadata><g transform=\"translate(1.000000,15.000000) scale(0.019444,-0.019444)\" fill=\"currentColor\" stroke=\"none\"><path d=\"M0 440 l0 -40 480 0 480 0 0 40 0 40 -480 0 -480 0 0 -40z M0 280 l0 -40 480 0 480 0 0 40 0 40 -480 0 -480 0 0 -40z\"/></g></svg>\n\n C from neighbour backbone strands and between Ser OH groups and backbone O C groups are important for the packing [ 21 ]. In the present work, lyophilised regenerated fibroin was used as the starting material in order to meet the challenge of producing fibroin ionogels with the lowest possible water content, as opposed to hybrid gels with 50% w/w of water as previously reported [ 11 ]. When the aqueous solution containing regenerated fibroin is lyophilised, there is a slight modification of the fibroin secondary structure, namely a decrease in random coil and small increase in β-sheet contents, rendering the final lyophilised fibroin sample water insoluble ( Fig.S1 and Table S2 in Supplementary Information). The concept here explored involves the dissolution and gelation of the lyophilised silk fibroin sample in ILs, which represents a different challenge from most reports in which the ILs were used for dissolution and regeneration. The ILs need thus to disrupt the naturally occurring H-bonded network of fibroin, to further allow the formation of other networks of non-covalent interactions between silk fibroin chains and the ILs, giving rise to a physical gel. The identity of both cation and anion IL moieties are important to promote the solubility of polymers in ILs, although it is known that the anion has a much larger effect on this process. Methylimidazolium-based ILs, with chloride as the anion, are known as the most successful for fibroin dissolution and regeneration [ 4 ], and were thus selected for this study. The chloride anion was selected due to its properties. It is a strong H-bond acceptor, known to break inter-strand hydrogen bonds between neighbour backbone polypeptide chains, thus critical for fibroin dissolution, but also able to act as a cross-linker in H-bonds, thus important for gel formation [ 22 ]. Regarding the cation moiety, we selected methylimidazolium cations with varying lengths of the alkyl chain, namely C n mimCl with n = 2, 6, 10. The alkyl chains will likely contribute for hydrophobic interactions, with the potential to disturb the closely packed hydrophobic pockets during fibroin dissolution but also to promote the formation of hydrophobic patches during gel assembly. The selected methylimidazolium chloride ILs dissolved the lyophilised fibroin at high temperature. Upon cooling, we observed the formation of fibroin ionogels at 100, 100 and 70 mg mL −1 of fibroin for ILs C 2 , C 6 and C 10 mimCl ( Fig. 1 ), respectively, while the control fibroin hydrogel was formed at lower concentration (50 mg mL −1 of fibroin) ( Fig. S2 ). Remarkably, the water content of the fibroin ionogels was minimal, between 1 and 7% w/w, mostly attributable to the water already associated to the ILs used ( Table 1 ). It was necessary to add a small amount of water to the fibroin ionogels produced with C 10 mimCl due to the initial low hydration content of the IL. The residual amount of water molecules existent in the final fibroin ionogel materials can contribute to H-bond formation, although the effect should be negligible considering the high IL content (higher than 88% w/w). It should be noted that the fibroin ionogels and controls were produced and then stored for 24 h at room temperature and controlled humidity (RH of 50%) before any characterizations or use. Apart from the detailed analysis that will follow for fibroin ionogels formed with C n mimCl ILs with n = 2, 6 and 10, the mid-term alkyl chains n = 4 and n = 8 were also preliminarily assessed, to conclude that silk fibroin could also gelate C 4 and C 8 mimCl obtaining self-supporting ionogels similar to C 2 and C 10 mimCl, respectively ( Fig. S3 ). Fig. 1 Fibroin ionogels. (A) Schematic representation of fibroin ionogels and proposed predominant secondary structures. After dissolution of lyophilised fibroin and gelation in C 2 , C 6 and C 10 mimCl ionic liquids, different fibroin secondary structures are observed. Scales are exaggerated for clarification. (B) Inverted glass vials containing fibroin ionogels. (C) Atomic Force Microscopy (AFM) topography and (D) Polarised Optical Microscopy (POM) taken with crossed polarisers at 90° of fibroin ionogels. The white line corresponds to 100 μm. Fig. 1 The differences between the silk fibroin ionogels C 2 F, C 6 F and C 10 F containing the ILs C 2 mimCl, C 6 mimCl and C 10 mimCl, respectively, were clear upon morphological characterisation by atomic force microscopy (AFM) and polarised optical microscopy (POM) under crossed polarisers ( Fig. 1 ). The fibroin ionogel C 2 F, containing the imidazolium IL with the shortest alkyl chain, was opaque, similar to the control hydrogel, which similar morphology was also proven by TEM imaging ( Fig. S4 ). C 2 F ionogels presented small aggregates at the surface with RMS roughness of 1.1 nm, whereas fibroin hydrogel also presented aggregates, although larger, with RMS roughness of 5.2 nm ( Fig. 1 and Fig. S2 ). Both C 6 F and C 10 F ionogels were translucent materials (the slight yellow coloration arises from the ionic liquid itself). The C 6 F ionogel presented dense and less homogeneous background with rodlike structures with increased roughness (2.4 nm RMS) when compared to C 2 F ( Fig. 1 ). The C 10 F ionogel exhibited a distinct surface topography of aligned stripes, with a RMS roughness of 3.1 nm and unique birefringence showing a fan-like texture ascribed to the hexagonal liquid crystal phase by POM analysis ( Fig. 1 ). This behaviour arises mostly from the self-assembling properties and molecular order of the IL used, C 10 mimCl [ 23 ], as described below. To assess the contribution of the IL intrinsic self-assembling properties on the final silk fibroin ionogels, the three ILs were subjected to the same processing steps as the fibroin ionogels. The heated/cooled IL controls (C 2 HC and C 6 HC) formed viscous solutions ( Fig. S5 , Supplementary Information), showing that the presence of silk fibroin is essential for gel formation, except for C 10 HC which forms a self-supporting gel on its own. Imidazolium ILs with long alkyl chains have been reported to form lyotropic liquid crystal phases in the presence of water, due to their amphiphilic nature [ [23] , [24] , [25] ]. In particular, C 10 mimCl is reported to present unique self-assembly characteristics [ 23 ]. Moreover, a water content above 3% w/w can promote a H-bonded network and liquid crystalline gel phase with C 10 mimCl [ 26 ], which is the case in our work (water content 6.9% w/w). The C 10 HC gel presented a surface topography of stripes but with a higher RMS roughness (3.2 nm) when compared to C 10 F. These results suggest that the IL self-assembling properties are predominant in the final hierarchical order of the fibroin ionogel, and that fibroin affects the organization of the IL creating smaller ordered clusters, suggesting that fibroin chains are interspersed in the IL supramolecular assemblies. A detailed investigation of the POM images obtained for the heat/cooled IL (C 10 HC) and corresponding fibroin ionogel (C 10 F) ( Figs. S6 and S7 ) confirmed that both materials showed a fan-shaped pattern ascribed to the hexagonal liquid crystal phase, even though a decrease in the size of the fan-shaped structures was observed in the C 10 F fibroin ionogel. The hexagonal phase was recovered upon a heat-cool cycle in which the hexagonal-to-isotropic transition and reverse transition temperatures were similar. The mechanical properties of silk fibroin ionogels and controls were assessed by dynamic frequency sweep measurements ( Fig. 2 A–B and Table S3 from Supplementary Information), after choosing a strain at the linear viscoelastic region from amplitude sweeps ( Fig. S8 as an example). The C 2 F and C 10 F ionogels present viscoelastic behaviour as G’ (10 4 and 10 6 Pa, respectively) is one order of magnitude greater than G’‘. The C 6 F ionogel is the weakest, presenting G′ and G″ in the 10 3 Pa order. The control C 10 HC also became stronger upon stress application and showed high moduli, but the storage and loss moduli are in the same order of magnitude (10 5 Pa), indicating that the presence of fibroin is key to enhance its viscoelasticity. From all tested materials, C 10 F ionogel presented the better mechanical robustness with G′ of 1.3 × 10 6 Pa and G″ of 1.4 × 10 5 Pa. Fig. 2 Mechanical and structural characterisation of fibroin ionogels. (A) Rheology Frequency sweep measurements of fibroin ionogels C 2 F, C 6 F and C 10 F. (B) Rheology Frequency sweep measurements of fibroin hydrogel and heat/cooled C 10 HC. (C) ATR-FTIR spectra (Amide region) of fibroin ionogels C 2 F, C 6 F and C 10 F, using the heat/cooled ILs as background, and compared with fibroin hydrogel, highlighting the Amide I band. (D) Secondary structure content from deconvolution of peaks at the Amide I band of ATR-FTIR spectra for each of the samples. (E) X-ray scattering 2θ scans of fibroin ionogels C 2 F, C 6 F, C 10 F and fibroin hydrogel, with distances in Å annotated on top, and (F) taken from scattering ring intensity analysis. Fig. 2 The ATR-FTIR spectra of the fibroin ionogels tested (using each IL as background) helps to understand how silk fibroin chains could be organised within the gels ( Fig. 2 C–D). Comparing the spectra from lyophilised fibroin, control fibroin hydrogel and fibroin ionogels, it is possible to observe differences at important amide bands ( Fig. S1 , Table S2 and Fig. S9 Supplementary Information). For all the fibroin ionogels tested, the peak at the amide I region was shifted to a higher wavenumber (around 1660 cm −1 ) when compared to the starting material (1624.69 cm −1 ), suggesting alterations in secondary structure [ 27 ]. In turn, the amide II region (1470-1570 cm −1 ) shows a broader appearance, with more than one peak, which was already observable in the lyophilised fibroin. The amide III band (1200-1350 cm −1 ) presents broader peaks at the same wavenumbers as the fibroin hydrogel, which in turn points to β-sheets. In addition, the specific band at 1700 cm −1 , only visible in the control fibroin hydrogel, is stated as indicative of the antiparallel arrangement of fibroin chains in the β-sheet domains [ 28 , 29 ]. The deconvolution of peaks at the amide I region (1575-1800 cm −1 ) indicates the most prevalent fibroin secondary structure in the different materials ( Table S4 ), suggesting the existence of β-sheet (83%) and β-turn (17%) in the control fibroin hydrogel (as expected), and predominant β-turn (66%) and β-sheet (33%) in C 2 F. In turn, C 6 F shows the presence of 3 10 helix (63%), which can be also attributed to β-turns, in the addition to the 3% of attributable β-turns, and 33% of other conformations. Finally, C 10 F presents a strong presence of α-helix (79%), and the existence of β-turn (12%) and other (9%). The materials were also characterized by X-ray scattering. As expected, the commercial fibroin solution showed an amorphous pattern, while the hydrogel presented one peak (2θ angles 23° ( Fig. 2 E and Fig S10 )), and a sharp ring at 4.32 Å ( Fig. 2 F), which probably corresponds to a β-sheet crystalline periodic spacing. These results corroborate ATR-FTIR observations ( Table S2 ), with the amorphous silk fibroin solution silk I re-organising into a more crystalline silk II structure upon mechanical stirring (hydrogel) or lyophilisation [ 6 , 30 ]. The two-dimensional scattering images acquired for the fibroin ionogels showed the presence of diffraction rings around 4 Å (wide angle region) which corresponds to a 2θ angle of around 22°. These diffraction rings were more diffused and less sharp than those observed for the control hydrogel which indicates more scattering and less ordered structures in the fibroin ionogels ( Fig. 2 E–F or Fig. S11 ). It is evident that the spacing corresponding to this scattering ring increases in value as the alkyl chain of the IL increases, visible at 3.71, 4.12 and 4.26 Å for C 2 F, C 6 F and C 10 F, respectively. The value observable for C 10 F approaches the 4.32 Å distance in the control hydrogel. It has been previously reported that attractive van der Waals interactions increase with increasing alkyl chain length on the cation C n mim of the IL, which starts exhibiting amphiphilic character from n = 10 [ 24 ], and ultimately leads to an increase in order and crystal stabilisation [ 31 ]. For the C 6 F ionogel, a second scattering ring is present in the small angle area, yielding a spacing value of 19.74 Å. The C 10 F ionogels exhibit also a sharp scattering in the small angle albeit partially covered by the beamstop, which corresponds to a distance of 28.9 Å ( Fig. 2 E–F). X-ray scattering studies of pure ILs after undergoing a heat/cool cycle (labelled C n HC) showed similar scattering patterns as to the corresponding fibroin ionogels ( Fig. S11-S12 ). Still, the wide-angle region ring shifts to lower spacing in the fibroin ionogels, which points to more compact structures when fibroin is present. The ILs selected for this study provide a multitude of interactions through the rich chemical diversity of cations and anions. When fibroin is dissolved in ILs, the intra- and inter-molecular H-bonds and hydrophobic interactions between fibroin polypeptide chains are reduced, which, after cooling down, enable the formation of thermodynamically stable ionogels that do not exactly follow the typical secondary structure and supramolecular assembly of fibroin hydrogels. The chloride anion is constant among all tested ILs. This anion is hydrophilic and a strong hydrogen bond acceptor [ 22 ], that can undertake multiple H-bonding interactions as doubly ionic [ 32 ] which act as a cross-linker between neighbour polypeptide chains. Regarding the cation moiety, the imidazolium ring is constant. Given the amino acid sequence of silk fibroin, it is expected that this ring mostly contributes as a weak hydrogen bond donor forming hydrogen bonds with hydrogen bond acceptor groups in the protein backbone and Ser side chain. But the most important contribution from the cation moiety is attributable to the alkyl chain that ranges from 2 to 10 carbons. The alkyl chain likely establishes hydrophobic interactions with the hydrophobic side chains of the fibroin, having an important role during dissolution and gelation. Particularly in gelation, the shortest alkyl chain seems to interfere less with fibroin assembly into β-sheets (according to ATR-FTIR) by possibly having little disruption on the hydrophobic packing of fibroin strands. The C 6 F appears as the most disordered material, with less mechanical robustness and with the lack of predominant fibroin secondary structure. In C 10 F we observe a synergistic effect between the strong self-assembling properties of the IL - which alone gives rise to a lyotropic liquid crystalline phase - and the physico-chemical properties of fibroin. After IL dissolution, the latter is forced to acquire a distinct secondary structure, rich in α-helix and β-turns, affecting the organization of the IL itself by creating smaller ordered clusters but still giving rise to birefringent and viscoelastic gels with higher G’ than the control hydrogel and the heat/cooled IL. 3.2 Stability and ionic conductivity of fibroin ionogels Fibroin ionogels acquire interesting properties due to the high content of ionic liquid, namely air and thermal stability, and high ionic conductivity. Analysis of the ionogels’ stability upon storage at ambient conditions, as well as thermal assays, were carried out. When the gels are stored in an open vial at controlled humidity and temperature, the fibroin ionogels adsorb water from the atmosphere, reaching a maximum weight gain of 25, 16 and 10% w/w for C 2 F, C 6 F and C 10 F, respectively, after 30 days of study. This is contrary to the behaviour of the hydrogel, which loses almost 60% of weight by drying out after 30 days ( Fig. 3 A–B). Yao and partners have shown that fibroin/C 2 mimAcetate/H 2 O gel almost maintains the original size and shape after exposed to air for 20 days [ 11 ], even though they have a 40–50% weight loss. That corresponds to the unbound water, as these gels were composed of 10% fibroin, 40% C 2 mimAc and 50% water w/w [ 11 ]. In our work, fibroin ionogels present less than 27% water in their air-equilibrated composition after 30 days of air-storage (see insert of Fig. 3 A). Such behaviour is likely attributable to the high hygroscopy of the ILs containing the chloride anion [ 22 ]. While C 6 F and C 10 F remain gels that can be handled with tweezers after 30 days, C 2 F turned into a liquid state after 1 day of exposure to ambient air, likely due to the low self-assembling propensity of the IL alone. The heat/cooled ILs also gained weight throughout the storage time. It should be noted that C 10 HC remained a self-supporting gel after 30 days ( Fig. S13A-B ). Fig. 3 Stability to air and temperature and ionic conductivity of fibroin ionogels. Stability study of fibroin ionogels C2F, C6F and C10F versus fibroin hydrogel throughout time, upon storage of the open vials at ambient conditions (T ≈ 20 °C; RH ≈ 50%). (A) Weight variance throughout storage time, comparing the mass at each time with the initial mass; Water content after 1 day and 30 days – equilibrated samples in the inset. (B) Macroscopic aspect of the gels after storage for 1 and 30 days, including when picked with the tweezers. (C) TGA analysis of fibroin ionogels versus hydrogel when heating the fibroin ionogels and hydrogel at 10 °C/min. (D) Ionic conductivity spectra of fibroin iono- and hydrogels at ambient conditions. Fig. 3 When comparing the mass loss curves from thermogravimetric analysis, it is clear that fibroin ionogels present larger thermal stability than the fibroin hydrogel, which loses mass abruptly until 150 °C ( Fig. 3 C). Fibroin ionogels lose mass almost entirely at 300 °C (as observed for the control heat/cooled ionic liquids, Fig. S14 ), as opposed to the 60% mass loss for the hydrogel for the same temperature, as previously reported [ 9 ]. Analysing the DSC scans, all fibroin ionogels present an endothermic peak between 77 and 110 °C ( Fig. S15A ), which represents the gel-sol transition. This is due to the reversible supramolecular gel formation that is based on weak physical forces such as H-bonding and van der Waals interactions [ 33 ]. The absence of a glass transition endotherm suggests that the materials are not completely amorphous [ 33 ], even though the X-ray scattering broad peaks point to no ordered structure within the ionogels. When compared to fibroin hydrogel ( Fig. S16C ), the fibroin ionogels present a larger degradation temperature, in addition to much larger enthalpies (T D and ΔH D in Fig. S15B ), which means they require higher temperature and energy to degrade. This increasing thermal stability can be explained by decreasing Coulomb attraction if ideal ionic interaction is assumed, when opposed to hydrogels, where ionic interactions are not relevant [ 34 ]. The exothermic peak at ∼100 °C for the hydrogel, as well as for the fibroin solution (see more detail in Fig. S16B ) coincide with the TGA weight loss at this temperature range ( Fig. S16A ), just before the glass transition (T G values of 120 and 112 °C, respectively, as seen in Fig. S16C ). The crystallisation of fibroin induced by heat was above 250 °C for all the fibroin materials (exothermic peak), as previously reported [ 35 ]. In addition, the following degradation temperatures (T D at which Δ max is achieved) increase when there is less water ( Fig. S16C ). As opposed to amorphous silk fibroin, for which the decomposition has been reported by some researchers to occur at T < 290 °C [ 28 , 36 ], the analysed fibroin ionogels showed decomposition peaks at larger temperatures (T D ) ( Fig. S15B ) – with the exception of C 6 F. The degree of molecular orientation and crystallinity, that give the morphological and physical properties to the sample, are the main responsible factors for this thermal behaviour [ 29 ], which actually confirms the morphological, mechanical and structural analysis ( Fig. 2 ). Intrinsic ionic conductivity of the fibroin ionogels is another unique characteristic endowed by the high IL content. The ionogels’ ionic conductivity is attributed to the mobility of the ILs cations and anions within the gels. The fibroin hydrogel also presented ionic conductivity ( Fig. 3 D), very similar to the one found for C 10 F ionogel due to the presence of water. All ionogels, except C 6 F, presented a maximum ionic conductivity in the range of 10 −3 -10 −2 S cm −1 , which is above the benchmark of 1 mS cm −1 required in electrochemical devices [ 37 ]. It has been reported that increased IL content or decreased silk fibroin content can raise the ionic conductivity [ 11 ]. In this work, the conductivities achieved for C 2 HC and C 10 HC were similar to their corresponding fibroin ionogels C 2 F and C 10 F, with the large error bars from duplicates actually pointing to a larger variability of the controls ( Fig. S17 ), indicating the stabilising effect of fibroin polypeptide chains. As already expected [ 38 ], an increase in the alkyl chain length of the imidazolium cation lowered the ionic conductivity, with C 2 F presenting the largest ionic conductivity. However, the C 6 F showed lower conductivity than C 10 F, which could be explained by the less organised structures within the C 6 F gel, lowering ion mobility. Even though C 2 F ionogel presents the highest conductivity, it has the lowest air-stability with C 10 F having the best compromise between conductivity and air stability. 3.3 Fibroin ionogels as electrical gas sensors The synergy between remarkable air-stability and high ionic conductivity of the fibroin ionogels was here combined to assess a potential application of the materials in the field of artificial olfaction. After proving that fibroin ionogels present ionic conductivity, they were spread as thin films on top of interdigitated gold electrodes ( Fig. 4 A) and used as sensors in our in-house built electronic nose (set-up on Fig. S18 ). Due to the intrinsic ionic conductivity property of the ionogel material, when an alternate voltage is applied between the terminals of the interdigitated electrodes, it causes ions movement within the ionogel, generating an electrical current. Our electronic nose detects that current and converts it to a voltage value that is proportional to the conductance of the ionogel. This is the electrical signal of the material in rest. When we expose the ionogels to vapours of different chemicals or water vapour, we observe changes in their rest electrical signal, which represent changes in ionic movement within the ionogel caused by the interactions established between the incoming vapour molecules and the ionogel. Thus, our ionogels report the adsorption/desorption of gas molecules through the variation of their electrical signal, as shown in Fig. 4 B and C. Even though the hydrogel showed a high ionic conductivity, it did not qualify as electrical gas sensor because it loses water by evaporation and a rigid dry material forms, preventing charges to move. In our VOC sensing experiment, the fibroin sensors' signals were recorded during 22 consecutive cycles of exposure to VOC (5 s) followed by ambient air (15 s) (for recovery of the baseline). Different VOCs have different characteristic signals for each sensor composition ( Fig. 4 B, for C 10 F sensor), which is related with the distinct dynamics and types of interactions that occur during VOC adsorption/desorption to the ionogel. Also, signals are different for each sensor composition upon exposure to the same VOC ( Fig. 4 C, for methanol). For example, regarding exposure to methanol, C 2 F returns relatively quickly (1.6 ± 0.4 s) to its initial conductance, while C 10 F and C 10 HC take longer (5.8 ± 1.6 s and 6.6 ± 0.8 s, respectively) to recover, resembling a more triangular-shape signal. As it is possible to observe from the 22 exposure/recovery cycles in Fig. 4 D (example of C 10 F response to methanol), the sensors were relatively stable throughout the 7.5 min experiment, yielding reversible and repeatable signals after the first 6 cycles. This corresponds to the sensor's stabilisation time of around 2 min (where the signal amplitude variability is 29%), after which the signal amplitude can be considered constant, with a variability lower than 4% for each independent sensor. From all the 10 VOCs tested, chloroform was the only one that clearly damaged films containing fibroin (with the exception of C 10 mimCl-based thin films). The control C 10 HC also presented deterioration after exposure to the tested VOCs, which was not observable for the C 10 F sensor, indicating the important role of fibroin to maintain the integrity of the material. Fig. 4 Application of fibroin ionogels in gas sensing. VOC sensing experiment using the in-house developed electronic nose. (A) Macroscopic aspect of C 10 F films spread on top of a glass slide patterned with interdigitated gold electrodes after used on the electronic nose. (B) Typical cycle signals of a C 10 F sensor upon exposure to different VOCs and water. Each curve represents the average and standard deviation of at least 19 replicate cycles from a same sensor. VOC exposure periods (5 s) are highlighted in grey. (C) Typical cycle signal of the sensors made of fibroin ionogels and heat/cooled ionic liquid C 10 HC when exposed to methanol (5 s, highlighted in grey). The lines and shadow are the average signal and standard deviation of the 2 independent sensors. (D) Representation of all the cycles performed during the 7.5 min experiment with methanol when using 2 independent C 10 F films as sensors. The line and shadow are the average signal and standard deviation of 2 independent sensors. (E) Comparison of correct VOC prediction rates obtained when using each fibroin ionogel and heat/cooled ionic liquid C 10 HC as gas sensors. (F) Overall correct VOC prediction rate for each sensor, given by the average of the correct prediction rate of all the VOCs. Fig. 4 After collecting signals from the sensors upon VOC exposure, we used an automatic classifier based on support vector machines (SVM) that analyses the cycles’ shape. The cycles were normalised (see the mean normalised waves for each sensor in Figure S19-S22 of Supplementary Information ), showing singular signatures for different VOC chemical classes and sensors. The rate of correct VOC predictions (%) was taken from the diagonal of each confusion matrix and presented in Fig. 4 E (from Fig. S23 ). C 10 F correctly identified all VOCs with an overall correct prediction rate higher than 80%, emerging as the most promising gas-sensing film allied to higher robustness. In previous works, we reported similar gas-sensing gel materials, where an optical probe (liquid crystal) was added to the ionogel, resulting in hybrid gels that yield optical signals with different shapes for different VOCs [ 39 ] and have excellent VOC prediction ability (98.9% overall correct prediction rate [ 20 ]). Fibroin ionogel materials still present lower VOC prediction ability (around 80%, Fig. 4 F) than the optical gelatin hybrid gels but are more robust mechanically and simpler to produce because less components are required than for gelatin hybrid gels. The combination of fibroin and C 10 mimCl yielded gels with G′ and G″ in the order of 10 6 and 10 5 , respectively, whereas the reported gelatin ionogels have G′ and G″ in the order of 10 3 and 10 1 , respectively [ 39 ]. The required signal acquisition hardware is simpler in the case of ionogels. The simplicity and improved mechanical properties might be favourable for several applications. Thus, the fibroin ionogel sensing system would benefit from further work to optimize the VOC prediction ability, namely by gathering a larger dataset of signals collected with C 10 F sensors from different batches, providing a more accurate representation of the variability of the signal shape per VOC."
} | 8,972 |
38630303 | PMC11166799 | pmc | 8,943 | {
"abstract": "Due to the loss of photosynthetic ability during evolution, some plant species rely on mycorrhizal fungi for their carbon source, and this nutritional strategy is known as mycoheterotrophy. Mycoheterotrophic plants forming Paris -type arbuscular mycorrhizas (AM) exhibit two distinctive mycorrhizal features: degeneration of fungal materials and specialization towards particular fungal lineages. To explore the possibility that some understory AM plants show partial mycoheterotrophy, i.e., both photosynthetic and mycoheterotrophic nutritional strategies, we investigated 13 green herbaceous plant species collected from five Japanese temperate forests. Following microscopic observation, degenerated hyphal coils were observed in four species: two Colchicaceae species, Disporum sessile and Disporum smilacinum , and two Gentianaceae species, Gentiana scabra and Swertia japonica . Through amplicon sequencing, however, we found that all examined plant species exhibited no specificity toward AM fungi. Several AM fungi were consistently found across most sites and all plant species studied. Because previous studies reported the detection of these AM fungi from various tree species in Japanese temperate forests, our findings suggest the presence of ubiquitous AM fungi in forest ecosystems. If the understory plants showing fungal degeneration exhibit partial mycoheterotrophy, they may obtain carbon compounds indirectly from a wide range of surrounding plants utilizing such ubiquitous AM fungi. Supplementary Information The online version contains supplementary material available at 10.1007/s00572-024-01145-9.",
"conclusion": "Conclusions We conducted microscopic observations and amplicon sequencing on the roots of 13 understory herbaceous photosynthetic plant species that form Paris -type AM. The results showed that degenerated fungal materials were observed in four of the examined plant species, and all species examined did not exhibit specificity for particular fungal lineages. The fungal degeneration suggests the possibility of acquiring carbon compounds from mycorrhizal fungi, i.e., partial mycoheterotrophy, although the fungal degeneration alone does not provide direct evidence of the supply of carbon compounds to the host plant. Hence, further study is necessary to validate partial mycoheterotrophy in these plants. Additionally, our data suggest the presence of ubiquitous AM fungi in forest ecosystems. If the understory plants showing fungal degeneration exhibit partial mycoheterotrophy, they may utilize a wide range of surrounding plants as carbon sources by targeting the ubiquitous AM fungi.",
"introduction": "Introduction The majority of terrestrial plants form arbuscular mycorrhizas (AM) with fungi of the subphylum Glomeromycotina (Spatafora et al. 2016 ; Brundrett and Tedersoo 2018 ). There are two main morphologies of AM: the Arum -type, which is characterized by intercellular hyphae and intracellular arbuscules, and the Paris -type, which is characterized by intracellular coiled hyphae that are often accompanied by intercalary arbuscules (arbusculate coils) (Gallaud 1905 ). The type of AM is primarily determined by the classification of host plant, especially at the family level (Smith and Smith 1997 ; Dickson et al. 2007 ), although in some cases, it can be determined by which AM fungi have colonized the plant (Cavagnaro et al. 2001 ; Dickson 2004 ). It is also confirmed that the number of plant families forming Arum -type AM and those forming Paris -type AM are similar (Dickson et al. 2007 ). Both types of AM enhance host plant growth and share expression patterns of AM-related genes in roots (Tominaga et al. 2022 ). However, their functional differences remain poorly understood. Some plants have lost their photosynthetic capacity entirely and therefore fully rely on mycorrhizal fungi as their carbon source; this nutritional strategy is known as mycoheterotrophy (Leake 1994 ). Among mycoheterotrophic plants, Orchidaceae and Ericaceae plants have been found to associate with Basidiomycota and Ascomycota, whereas other plant families associate with Glomeromycotina (i.e., AM fungi). There are at least 330 species of mycoheterotrophic AM plants in nine angiosperm families (Merckx et al. 2013b ; Cheek et al. 2024 ; Imhof 2024 ), and Paris -type AM have been observed in all plants examined (Imhof et al. 2013 ). Recently, Giesemann et al. ( 2021 ) suggested that partial mycoheterotrophy (mixotrophy), obtaining carbon compounds via both photosynthesis and mycoheterotrophy, may be common among chlorophyllous plants with Paris -type AM based on the enrichment of 13 C and 15 N. Along with the observation that understory plants typically develop Paris -type AM (Brundrett and Kendrick 1990 ; Yamato and Iwasaki 2002 ), it has been suggested that Paris -type AM may be a prerequisite for the evolution of mycoheterotrophy (Imhof 1999 ; Giesemann et al. 2021 ). In general, mycoheterotrophic AM plants exhibit two distinct mycorrhizal characteristics. First, coiled intracellular hyphae develop in their roots and later undergo degeneration, which is thought to be caused by the digestion of the fungus by the host plant (Imhof et al. 2013 ). Degenerated hyphal coils also have been observed in (partial-) mycoheterotrophic plants within the Orchidaceae and Ericaceae. Fungal digestion is the mechanism by which mycoheterotrophic plants are hypothesized to obtain carbon compounds. Indeed, it has been confirmed that carbon is transferred to host plant cells from both living and degenerated fungal hyphal coils, with a larger quantity observed from the latter, in the protocorms of the photosynthetic orchid, Spiranthes sinensis (Kuga et al. 2014 ). In AM-forming green plants, fungal degeneration also has been confirmed in some species (e.g., Rath et al. 2013 ; Yamato et al. 2021 ). Second, AM-forming mycoheterotrophs exhibit specialization toward specific fungal lineages, predominantly the Glomeraceae (e.g. Merckx et al. 2012 ; Ogura-Tsujita et al. 2013 ; Yamato et al. 2014 ; Gomes et al. 2017 ), although the degree of specificity differs among the plant species (Merckx et al. 2012 ). However, it remains unclear whether Paris -type AM-forming green plants, which may be partial mycoheterotrophs, also exhibit specificity toward fungi. Unlike plants in the Orchidaceae and Ericaceae, it can be difficult to identify partial mycoheterotrophy in AM-forming plants by examining their 13 C and 15 N abundances, because the stable isotopic signatures of AM fungi closely resemble those of host plants (Nakano et al. 1999 ; Merckx et al. 2010 ; Courty et al. 2011 ). For example, while Giesemann et al. ( 2021 ) found 13 C enrichment in various Paris -type AM green plants thriving on shady forest grounds, Murata-Kato et al. ( 2022 ) reported that 13 C enrichment was found not only in certain Paris -type AM plants but also in understory Arum -type AM and in nonmycorrhizal plants. Thus, 13 C enrichment in understory plants can be affected by many factors other than mycoheterotrophy. In this study, we used fungal degeneration and fungal specificity rather than stable isotope signatures to explore the possibility of partial mycoheterotrophy in Paris -type AM green herbaceous plants. To do so, we conducted microscopic observations and amplicon sequencing of understory plant species collected from temperate forests in Japan.",
"discussion": "Discussion Mycorrhizal structures In this study, we examined the mycorrhizal structures of 13 understory plant species and found degenerated fungal materials in four of them, D. sessile , D. smilacinum , Gen. scabra , and S. japonica . The presence and ratio of degenerated fungal materials varied among the examined samples in all four species, and these variations may be related to local environmental factors such as light conditions. A negative correlation between light availability and the degree of dependence on fungal carbon sources has been reported for the partial mycoheterotrophic Pyrola japonica (Ericaceae; Matsuda et al. 2012 ). Alternatively, plant growth stages or seasons also may influence degeneration, because samples showing no degenerated fungal materials or low rates were collected earlier in the season. To our knowledge, fungal degeneration in AM-forming green plants has been confirmed in some plant species to which fully or initially mycoheterotrophic plants belong (McGee 1985 ; Kovács et al. 2003 ; Rath et al. 2013 ; Sýkorová 2014 ; Yamato et al. 2021 ). In this study, however, degenerated fungal materials were observed in two Colchicaceae species, D. sessile and D. smilacinum , and this plant family has never been known to have fully mycoheterotrophic AM plants. Notably, Gen. scabra and S. japonica examined in this study belong to the tribe Gentianeae, and the mycorrhizal structures of different Gentianeae species in previous studies are highly similar (Sýkorová 2014 ; Yamato et al. 2021 ). Furthermore, these mycorrhizal structures also resemble those of full mycoheterotrophic Voyria aphylla in the Voyrieae (Imhof 1999 ) as well as photosynthetic Centaurium spp. in the Chironieae (McGee 1985 ). The family Gentianaceae comprises seven tribes, and full mycoheterotrophy within the Gentianaceae has evolved independently at least four times, including in Voyria (Voyrieae), Voyriella (Saccifolieae), and Exochaenium and Exacum (Exaceae) (Merckx et al. 2013a ). Therefore, it is plausible that pre-adaptation for mycoheterotrophy occurred during the family differentiation. Actually, partial mycoheterotrophy in the Gentianaceae has been suggested for some species within the tribe Gentianeae (Cameron and Bolin 2010 ; Suetsugu et al. 2020 ; Giesemann et al. 2021 ). However, some Gentianaceae species, including Gen. scabra and S. japonica , can be pot-cultured, so even if these plants have partial mycoheterotrophy, they may not be highly dependent on fungi. The presence of fungal degeneration in these four species suggests a potential for partial mycoheterotrophy. Degeneration alone, however, does not demonstrate the supply of biologically meaningful amounts of fixed carbon compounds to a host plant. Therefore, further investigation is required to confirm partial mycoheterotrophy in these plants. In this study, many species were collected from a single site within a single day. Hence, the possibility of degeneration cannot be excluded for plant species in which degenerated fungal materials were not confirmed in this study. AM fungal specificity Most plant species investigated in this study had phylogenetically diverse AM fungi that belonged to two or more orders. In the case of L. auratum , nine OTUs within the family Glomeraceae were detected, yet these OTUs belonged to various lineages within the family. Based on the presence/absence of the OTU matrix, we concluded that all plant species examined, including those with degenerated fungal materials, showed no specificity toward AM fungi. AM fungal community The phylogenetic tree revealed that many OTUs were not closely related to sequences from known AM fungal species. Currently, 346 AM fungal species have been described ( http://www.amf-phylogeny.com/amphylo_species.html ), but SSU rDNA sequences have been obtained for only a fraction of them (Öpik et al. 2014 ). Furthermore, molecular analyses of environmental samples have estimated the presence of numerous undescribed AM fungi (Kivlin et al. 2011 ). To date, most of the AM fungi that have been described have originated from human-impacted habitats, and a relatively high number of undescribed species are anticipated in forest ecosystems (Hart et al. 2014 ). The OTUs 001, 002, and 003 were consistently found in most plant individuals, and they correspond to the VTX166, 84, and 80 in Maarj AM , respectively. Furthermore, VTX166 has been identified as Dominikia aurea (Glomeraceae) or a closely related species according to Kusakabe and Yamato ( 2023 ). These VTXs have been widely detected in tree species growing in temperate Japanese forests (Miyake et al. 2020 ; Matsuda et al. 2021 ; Djotan et al. 2023 ). These VTXs also have been detected in phylogenetically independent fully mycoheterotrophic plants (Öpik et al. 2010 ; https://maarjam.ut.ee ); thus, they are likely to be cheating susceptible fungi, as suggested by Perez-Lamarque et al. ( 2020 ). If the understory plants showing fungal degeneration exhibit partial mycoheterotrophy, they may obtain carbon compounds indirectly from a wide range of surrounding plants by utilizing such ubiquitous AM fungi. A previous study also suggested that fully mycoheterotrophic plants preferentially target AM fungi that are well connected to surrounding autotrophic plants (Gomes et al. 2022 )."
} | 3,204 |
34175462 | null | s2 | 8,944 | {
"abstract": "Polyketide synthases (PKS) and nonribosomal peptide synthetases (NRPS) comprise biosynthetic pathways that provide access to diverse, often bioactive natural products. Metabolic engineering can improve production metrics to support characterization and drug-development studies, but often native hosts are difficult to genetically manipulate and/or culture. For this reason, heterologous expression is a common strategy for natural product discovery and characterization. Many bacteria have been developed to express heterologous biosynthetic gene clusters (BGCs) for producing polyketides and nonribosomal peptides. In this article, we describe tools for using Pseudomonas putida, a Gram-negative soil bacterium, as a heterologous host for producing natural products. Pseudomonads are known to produce many natural products, but P. putida production titers have been inconsistent in the literature and often low compared to other hosts. In recent years, synthetic biology tools for engineering P. putida have greatly improved, but their application towards production of natural products is limited. To demonstrate the potential of P. putida as a heterologous host, we introduced BGCs encoding the synthesis of prodigiosin and glidobactin A, two bioactive natural products synthesized from a combination of PKS and NRPS enzymology. Engineered strains exhibited robust production of both compounds after a single chromosomal integration of the corresponding BGC. Next, we took advantage of a set of genome-editing tools to increase titers by modifying transcription and translation of the BGCs and increasing the availability of auxiliary proteins required for PKS and NRPS activity. Lastly, we discovered genetic modifications to P. putida that affect natural product synthesis, including a strategy for removing a carbon sink that improves product titers. These efforts resulted in production strains capable of producing 1.1 g/L prodigiosin and 470 mg/L glidobactin A."
} | 492 |
37440531 | PMC10415592 | pmc | 8,946 | {
"abstract": "Abstract Many aerobic microbes can utilize alternative electron acceptors under oxygen-limited conditions. In some cases, this is mediated by extracellular electron transfer (or EET), wherein electrons are transferred to extracellular oxidants such as iron oxide and manganese oxide minerals. Here, we show that an ammonia-oxidizer previously known to be strictly aerobic, Nitrosomonas communis , may have been able to utilize a poised electrode to maintain metabolic activity in anoxic conditions. The presence and activity of multiheme cytochromes in N. communis further suggest a capacity for EET. Molecular clock analysis shows that the ancestors of β- proteobacterial ammonia oxidizers appeared after Earth's atmospheric oxygenation when the oxygen levels were >10 −4 p O 2 (present atmospheric level [PAL]), consistent with aerobic origins. Equally important, phylogenetic reconciliations of gene and species trees show that the multiheme c-type EET proteins in Nitrosomonas and Nitrosospira lineages were likely acquired by gene transfer from γ - proteobacteria when the oxygen levels were between 0.1 and 1 p O 2 (PAL). These results suggest that β- proteobacterial EET evolved during the Proterozoic when oxygen limitation was widespread, but oxidized minerals were abundant.",
"introduction": "Introduction Many microbes employ diverse energy metabolisms that ensure their survival across a range of environmental conditions, for example utilizing different electron donors and/or acceptors for redox couples ( Berney et al. 2014 ; Koch et al. 2015 ; Bayer et al. 2021 ). One physiological capacity that enables this flexibility is extracellular electron transfer (EET), which involves transferring electrons to exogenous materials outside the cell rather than soluble electron acceptors within the cell ( Shi et al. 2016 ). EET is enabled through a diversity of mechanisms, including redox-active soluble compounds as well as multiheme c-type cytochromes (MHCs), which are anchor proteins that link intracellular energy pathways to redox transformations of extracellular metal ions ( McGlynn et al. 2015 ; Shi et al. 2016 ; Deng et al. 2018 ) or substrates—such as humic acids ( Lovley et al. 1996 ), soluble metal ions ( Lovley et al. 1991 ), dimethyl sulfoxide ( Gralnick et al. 2006 ), as well as poised electrodes ( Bond et al. 2002 ). Transitions in molecular oxygen (O 2 ) concentrations over Earth's history have been a major force shaping modern microbial metabolisms ( Raymond 2006 ). As the availability of O 2 enabled the replacement of many enzymatic reactions central to anaerobic microbial metabolism with aerobic respiratory chains ( David and Alm 2011 ), many lineages have evolved to be obligate aerobes. For example, γ- and β -proteobacterial taxa that oxidize ammonia (NH 3 + ) to nitrite (NO 2 − ) via O 2 reduction are considered to be strict aerobes ( Koops et al. 2006 ). However, aerobic ammonia oxidizers are consistently observed in oxygen-limiting and -depleted environments such as anoxic marine zones ( Garcia-Robledo et al. 2017 ) and sediments ( Freitag and Prosser 2003 ; Mortimer et al. 2004 ), as well as engineered systems ( Yu and Chandran 2010 ). Although a wide range of oxygen affinities for aerobic ammonia-oxidizing bacteria have been reported ( Geets et al. 2006 ), how they are able to persist and survive during oxygen deficiency remains enigmatic. Many groups of aerobic microbes have been shown to relax their dependence on oxygen using alternative energy metabolisms ( Berney et al. 2014 ). This includes EET, where electrons from central metabolism can be transferred to extracellular minerals such as iron and manganese oxide ( Lovley 2012 ). For example, methane-oxidizing bacteria sharing many metabolic genes with aerobic ammonia-oxidizing bacteria ( Khadka et al. 2018 ) can perform EET under anaerobic conditions using MHCs ( McGlynn et al. 2015 ). Many of these anaerobic methane-oxidizing (ANME) clades are capable of performing syntropy via MHC-driven direct electron transfer between cells. The deeply rooted phylogeny of archaeal ANME clades ( Wang et al. 2021 , 2022 ) suggests that MHCs may have a long evolutionary history. To date, a few studies have reported anaerobic metabolisms in aerobic ammonia-oxidizing bacteria, such as nitrite reduction ( Bock et al. 1995 ; Schmidt et al. 2004 ; Shaw et al. 2006 ; Cantera and Stein 2007 ), but those metabolisms were not linked to any exogenous energy-yielding reaction ( Stein 2014 ). It has also been suggested that Nitrosomonas spp. donates electrons to an insoluble electrode in an anoxic electrochemical system, but this, too, has yet to be validated ( Vilajeliu-Pons et al. 2018 ). If aerobic ammonia-oxidizing bacteria can donate extracellular electrons to solid electrodes, they have the phenotypic potential to maintain survival via EET metabolic couplings in the absence of O 2 in natural settings. We, therefore, hypothesize that ammonia-oxidizing bacteria can switch from aerobic metabolism to anaerobic EET metabolism under anoxic conditions. We further hypothesize that this ability would have evolved early in the evolutionary history of ammonia-oxidizing bacterial clades, as is inferred for EET-capable ANME archaea when both widespread anoxia and oxidized mineral surfaces were likely prevalent ( Saito 2012 ). To test these hypotheses, we examined the electrochemical response of a model aerobic ammonia-oxidizing bacteria under anoxic conditions. Cyclic voltammetry (CV) and chronoamperometry (CA) were applied to assess the potential capacity for ammonia oxidizers to donate electrons to an electrode, and cytochrome reactive heme staining and metatranscriptomics were employed to identify the presence and activity of their MHCs. Additionally, we performed molecular clock analysis, integrated with reconciliations of genes associated with EET, to estimate the divergence times of ammonia-oxidizing bacterial groups and EET-performing lineages within these groups. Our results show that 1) Nitrosomonas may be capable of transferring electrons to solid surfaces in the absence of oxygen and 2) EET capacity in β- proteobacterial ammonia oxidizers is ancient, likely acquired by multiple horizontal gene transfers (HGTs) from γ - proteobacteria during the Paleo- and Mesoproterozoic (1,556–2,188 Ma and 1,172–1,936 Ma).",
"discussion": "Results and Discussion Multiheme EET Cytochromes Are Present in the Nitrosomonas Lineage EET often relies on a connection between redox and structural proteins ( Kumar et al. 2017 ). For example, a network of proteins physically associated with periplasmic c-type cytochromes, integral outer-membrane β-barrel proteins, and outer-membrane–anchored c-type cytochromes was shown to facilitate EET in Shewanella oneidensis, Geobacter sulfurreducens, and Rhodopseudomonas palustris ( Shi et al. 2016 ). We searched the NCBI genome database for genes in ammonia-oxidizing bacteria found in model EET pathways to evaluate their potential EET capability ( supplementary table S1, Supplementary Material online). Putative homologs to these known examples were queried using the HMMER search tool NCBI and Ensembl Reference Sequence databases ( Gruen et al. 2019 ). Detected homologs in ammonia-oxidizing bacteria were more similar in sequence to the enzymatic EET machinery of S. oneidensis ( Coursolle and Gralnick 2010 ) than Geobacter and Rhodopseudomonas and were primarily identified in the Nitrosomonas genus ( supplementary fig. S1, Supplementary Material online). Nitrosomonas species possessing the complete EET machinery formed a single clade in the species tree ( fig. 1 ), suggesting that the putative EET metabolism of Nitrosomonas appears to be a shared ancestral trait of this group ( Coleman et al. 2021 ). The γ-proteobacterial ammonia oxidizer Nitrosococcus halophilus was also identified as carrying a full set of EET metabolism genes. No such homology was detected in the genomes of archaeal ammonia oxidizers. FIG. 1. Comparison of phylogenies for species tree and EET metabolism gene tree. Species trees were generated from concatenated alignments of ribosomal protein sequences. EET gene trees were constructed from the concatenated alignments of proteins orthologous to identified EET components in ammonia-oxidizing bacteria, complete MTR pathways, including periplasmic C-type cytochromes (Q8EG35), integral outer-membrane β-barrel proteins (Q8EG34), and outer-membrane-anchored C-type cytochromes (Q8EG33). Ammonia oxidizers with a known complete EET pathway and their phylogenetic distance were colored blue and red, respectively. We then examined MHC containing at least two “C-X-X-C-H” heme-binding motifs in ammonia-oxidizing bacteria and compared the total number of MHC and heme-binding motifs ( supplementary fig. S2, Supplementary Material online), as such components constitute the direct electron transport pathway in S. oneidensis and G. sulfurreducens to reduce extracellular solids ( Deng et al. 2018 ). A total of 25 and 21 MHC carrying 87 and 70 heme-binding motifs were identified in Nitrosomonas communis Nm2 and Nitrosoc occus halophilus Nc4, respectively, comprising homologs of the EET pathway. Other ammonia oxidizers, on average, contained 16 MHC with 57 heme-binding motifs ( supplementary table S2, Supplementary Material online). The high frequency of these homolog motifs suggests that ammonia-oxidizing bacteria Nitrosomonas and Nitrosococcus can transfer electrons to surfaces in a manner similar to model EET strains. To test this hypothesis, N. communis Nm2 and Nitrosoc. halophilus Nc4 cultures were grown and examined via bioelectrochemical incubations under oxygen-deficient conditions. \n Nitrosomonas May Donate Electrons to Solid Electrodes in an Anaerobic Environment We measured the electrochemical response of N. communis and Nitrosoc. halophilus under anaerobic and ammonium-supplemented conditions ( fig. 2 A ). The anodic CA current at 0.3 V versus AgCl was stable at 4.7 ± 2 µA over 12 days in electrochemical incubations of N. communis , whereas abiotic control consistently yielded 2.8 ± 0.7 µA over 12 days of incubation ( fig. 2 B ). Nitrosococcus halophilus , however, did not produce currents that were significantly higher than control incubations ( supplementary fig. S3, Supplementary Material online), indicating that Nitrosoc. halophilus may not be capable of performing EET under the given conditions. The high frequency of MHCs and the presence of a complete model EET pathway were limited only to a single strain, Nitrosoc. halophilus , in the Nitrosococcus clade ( fig. 1 ; supplementary fig. S2, Supplementary Material online); this patchwork taxonomic distribution may indicate the presence of a non-EET function that does not require the complete protein machinery ( Li et al. 2013 ; Goodhead and Darby 2015 ). Future experiments considering varying electric potentials, substrate concentrations, or electrode surface types are needed to reveal the physiology of MHCs in Nitrosoc. halophilus . Our data suggest that the graphite felt electrode served as an electron acceptor for N. communis in the presence of ammonia, generating a constant anodic current at all culture replicates higher than the controls. However, we did not observe an increase in the anodic current of live incubations, which may show that the microbial electroactivity over this time course was insufficient to support cell growth ( Turick et al. 2019 ). It is plausible that N. communis has longer doubling times while using an anaerobic energy metabolism that further limited growth, as previously reported for N. europaea (6.5 days in oxic vs. 9 days in anoxic conditions; Kozlowski et al. 2014 ). The change in cell numbers after 12 days of incubation would likely have been insignificant, given the high initial cell numbers, in line with the results of recent EET incubations with aerobic Desulfovibrio ferrophilus ( Deng et al. 2018 ) and our CA profiles. The stable current may also be related to a limited capacity for EET by N. communis ( Kato et al. 2012 ) under these experimental conditions. In summary, the observed sustained current in N. communis relative to the control, and the lack of elevated current in Nitrosoc. halophilus relative to the control supports the hypothesis that N. communis might be capable of engaging in EET under anoxic conditions, but further work across a variety of conditions is needed to determine whether N. communis can thrive via EET. FIG. 2. Electrochemical characteristics of Nitrosomonas communis on graphite felt electrode. ( A ) Anodic currents were measured using an electrode poised at 0.3 V versus AgCl supplemented with 1 mM NH 4 + . ( B ) Mean anodic current from replicate runs of N. communis (black) with standard deviation (gray) and abiotic control (red). ( C ) Cyclic voltammograms were measured at a scan rate of 1 mV/s 12 days after initiating the incubation. ( D ) Mean cyclic voltammogram from replicates runs of N. communis normalized by subtracting the abiotic control CV as a baseline. The smooth pink layer represents the standard deviation. To determine the redox-active compounds of N. communis, cultures were further analyzed by CV at 1 mV/s scanning rate ( fig. 2 C ). Anodic CV peaks that appeared at the abiotic control incubations were consistently lower than at the live incubations, possibly enabling electron transfer to the anode by N. communis ( Richter et al. 2009 ). Interestingly, an anodic CV peak was observed in live incubations at the potential of 0.25 V, close to the applied potential in the electrochemical experiments ( fig. 2 D ). As all other anodic redox peaks were observed in live and control incubations together, the redox signal at 0.25 V appeared to be affiliated with N. communis ( Chen et al. 2019 ). Such redox response hints at a mechanism that might be responsible for the electrochemical activity of N. communis involved redox compounds or proteins that developed under O 2 -limited conditions. Outer Membrane and Multiheme Cytochromes Were Active in Anode Respiring N. communis Heme staining coupled with TEM imaging was applied to ascertain the presence and distribution of outer membrane heme-containing metalloprotein(s) cytochromes of electro-active N. communis after 12 days of incubation without O 2 ( Marshall et al. 2006 ; Deng et al. 2018 ). In cytochrome-specific 3,3′-diaminobenzidine (DAB)–H 2 O 2 staining, heme metal centers catalyze the formation of a DAB polymer that has a high binding affinity to OsO 4 ( Marshall et al. 2006 ). Thin sections of N. communis showed the apparent formation of heme-bound peroxidase, whereas Nitrosoc. halophilus , which showed no electrochemical response, exhibited no heme-bound peroxidase activity ( fig. 3 A ). This suggests that outer membrane cytochromes of N. communis were produced during the electrochemical incubation and potentially involved in the EET mechanism ( Hartshorne et al. 2009 ). The control sections of N. communis without the amendment of DAB stain yielded no heme-bound peroxidase signal, indicating that DAB successfully reacted with heme centers of N. communis in noncontrol TEM sections. Outer membrane cytochromes are often an essential component of direct EET between microbes and solid surfaces ( Kumar et al. 2017 ); therefore, the detected presence of inducible outer membrane cytochromes further suggests that N. communis transferred its electrons to the solid electrode through direct electron transfer. The cytochrome activity of electrochemically incubated N. communis was further assessed via metatranscriptomics. Among 25 detected multiheme cytochromes (≥2 heme motifs) in the genome of N. communis ( supplementary table S3, Supplementary Material online), 19 were expressed after 12 days of electrochemical incubation without oxygen, in line with electrochemical measurements and heme stain assays ( fig. 3 B ). Furthermore, the transcript library of N. communis revealed the activity of genes affiliated with anaerobic metabolism; the highest expression levels were detected for P460 ( supplementary table S4, Supplementary Material online)—a cytochrome converting NH 2 OH to N 2 O ( Caranto et al. 2016 )—may indicate its potential role in EET activity. In line with the enzymatic mechanism of cytochrome p460 in N. europhea ( Caranto et al. 2016 ), NH 2 OH oxidoreductase activity was also detected, which may suggest p460 dependence on NH 2 OH oxidoreductase activity during EET. Although a future isotopic tracing and a comprehensive transcriptomic effort may ultimately provide a complete understanding of the enzymatic EET pathway of N. communis , our results suggest that cytochrome P460 can be the enzymatic bridge between ammonia oxidation and the extracellular electron release of N. communis . In addition, the low expression of carbon fixation genes ( supplementary table S5, Supplementary Material online) was consistent with the nonincreasing anodic currents from CA results ( fig. 2 A and B ), pointing out that the cell growth was not supported. FIG. 3. ( A ) Transmission electron microscopy images of N. communis and Nitrosococcus . halophilus cells stained with cytochrome-reactive DAB-H 2 O 2 and without DAB. ( B ) Expressed genes of N. communis and their expression levels (the inner blue circle) are shown with their genome position (the outer black circle). MHCs having more than one heme-motif are shown as a net inside the circle. Expressed and unexpressed MHCs are colored as red and black, respectively. Red numbers within the circle represents the number of sequential MHC genes in the given genome position.” β-Proteobacterial Ammonia-Oxidizing Bacterial Lineages Are over 1.7 Billion Years Old Although experimental investigations indicated the active metabolism of EET in Nitrosomonas spp., a complementary phylogenomics approach can reconstruct the history of EET metabolism in ammonia-oxidizing bacteria, revealing clues about its ecological and planetary significance. To this end, a relaxed molecular clock approach was used to estimate divergence times for β -proteobacterial ammonia-oxidizing bacterial lineages inferred to have a shared history of EET metabolisms. We first applied molecular dating to a species tree ( Magnabosco et al. 2018 ; Wolfe and Fournier 2018 ; Gruen et al. 2019 ), including Nitrosomonas spp., to estimate the divergence time of ammonia-oxidizing bacterial clades and compare these ages with other known EET metabolism groups, such as Shewanella . We also directly estimated divergence times for the MtrA protein family tree ( supplementary fig. S4, Supplementary Material online) using the calibrations for Aeromonas , Vibrio, and clade 6 Cyanobacteria ( Moore et al. 2019 ). As evolutionary models often substantially impact the age estimates of molecular clocks ( Dos Reis et al. 2015 ), we used uncorrelated and auto-correlated branch-specific rate models, as well as uniform and birth-death (BD) priors on the relative age distributions of divergences to estimate the uncertainty of age estimates ( Fournier et al. 2021 ). Any divergence time estimates deep within the Tree of Life will be limited by the paucity of deep, informative fossil calibrations, and the inherent uncertainty of evolutionary rate models. Nevertheless, the obtained posterior age estimates can still be broadly informative and potentially discriminate between hypotheses, such as if a lineage has diverged before or after the great oxygenation event (GOE). Refinements of all age estimates are expected with subsequent improvements in rate models, taxonomic sampling, and the availability of reliable fossil calibrations. A model assessment method was applied to determine the most compatible model with detected HGT events ( supplementary fig. S5, Supplementary Material online) as described previously ( Fournier et al. 2021 ). The Cox–Ingersoll–Ross (CIR) process model with a uniform (UNI) prior resulted in the highest compatibility, where 94% of the posterior chronograms tested under CIR + UNI fulfilled HGT constraints ( supplementary table S5, Supplementary Material online). Similarly, the CIR model with BD prior showed 93% compatibility, which is very close to the CIR + UNI; we, therefore, considered estimations that covered the time range of both models in our interpretations. The compatibility of other models ranged from 80% to 23%. Molecular clock estimates under the CIR + UNI and CIR + BD models recover Nitrosomonas and Nitrosospira clades diverging from other β -proteobacterial lineages between 1,518 and 1,400 Ma and between 1,355 and 1,246 Ma, respectively ( fig. 4 ). These divergence times represent a younger bound on the acquisition of EET metabolisms by these groups; older bounds are provided by the inferred ages of the Nitrosomonas and Nitrosospira common ancestors, which we recover as diversifying during the Paleoproterozoic between 2,247 and 1,556 Ma. The origin of β -proteobacterial ammonia oxidizers during this interval is consistent with the appearance of their EET metabolism between 2,246 and1,042 Ma, as indicated by the molecular dating analysis of the MtrA gene tree ( supplementary fig. S4, Supplementary Material online). The Shewanella lineage in possession of EET metabolism was observed to diverge during the Mesoproterozoic between 1,686 and 1,089 Ma. β -Proteobacterial ammonia-oxidizing bacteria are inferred to have evolved after the GOE, when the atmospheric oxygen level was more than >5% present atmospheric level (PAL) ( Holland 2006 ; Planavsky et al. 2014 ; Reinhard and Planavsky 2022 ) consistent with the proposed shared aerobic ancestry for these lineages. These age estimates suggest that bacterial ammonia oxidizers acquired their metabolisms and diversified at different times during the Proterozoic, whereas the archaeal ammonia oxidizer lineage within Thaumarchaeota (including Nitrosocaldus , Nitrososphaera , and Nitrosocosmicus ) had already likely diversified in the Archean, between 2,328 and 3,100 Ma. However, this age estimate is less informed by included secondary calibrations, which are distant from these groups in the species tree and are, therefore, more speculative. FIG. 4. Time-calibrated species tree with ammonia-oxidizing clades highlighted. The depicted chronogram is for the CIR rate model with a uniform distribution, which was selected using the horizontal gene transfer compatibility method ( Fournier et al. 2021 ). Key bacterial clades with putative EET metabolisms are colored from the species tips to their last common ancestral node: Brown-Nitrosomonadaceae, Blue- Shewanella , Gray-Gallionellaceae, and Red- Nitrosococcus . The red-colored taxa names represent the recognized ammonia-oxidizing clades in this study. Nodes used for calibrations are indicated by red-filled circles. Posterior distributions were generated by sampling the Markov chain Monte Carlo analysis every 1,000 generations, with a 25% burn-in. Blue bars show uncertainty (95% CI). The age distributions of key nodes for the timing of the diversification of Nitrosomonadaceae, Gallionellaceae, Shewanella , and Nitrosococcus lineages are provided on the left side graph under six different evolutionary models. The mean age estimates for a selection of key nodes under CIR + uniform and CIR + BD models are provided in the table with 95% CI levels. EET Metabolisms Have Been Distributed across the Tree of Life via Horizontal Gene Transfer The Paleoproterozoic appearance of β -proteobacterial ammonia-oxidizing bacteria raises the possibility that the EET metabolism detected in extant forms has been conserved for a long period of planetary history. This history can be directly traced through the phylogeny of protein families that are diagnostic for EET metabolic function, and associated molecular clock divergence time estimates can further inform the timing of the acquisition of this function by different groups, albeit with less precision than a species-tree molecular clock. We first compared the protein family tree of periplasmic c-type MHC (MtrA; supplementary fig. S5, Supplementary Material online) to a species tree inclusive of represented taxa using reconciliation implemented in ecceTERA v1.2.4, a technique that infers well-supported speciation, duplication, transfer, and loss events ( Libeskind-Hadas et al. 2014 ; Stolzer et al. 2015 ) during the evolution of the EET MHC (35; fig. 5 ). Among all the domain family trees of EET metabolism components, periplasmic MHCs were conserved and widely distributed among the tree of life ( supplementary figs. S1, S6, and S7, Supplementary Material online) and hence used to trace the evolution of EET metabolism. Date estimates of key HGT recipient nodes ( supplementary fig. S8, Supplementary Material online) were inferred under CIR, LN, and UGAM models with UNI and BD priors ( fig. 5 ). FIG. 5. Visualized reconciliation of the electron transfer gene tree (MtrA) onto the dated species tree in this figure constructed from concatenated ribosomal genes. Black lines represent vertical inheritance within the genomes of the species tree, whereas orange lines represent the gene transfer events. Red lines represent the important gene transfer events for bacterial clades and ammonia-oxidizing bacteria (red species-tree tips). Yellow boxes represent atmospheric oxygen levels over time. The yellow box representing the 0.1–1.0% PAL levels within the Proterozoic period is displayed along the reconciliation tree and date summary table to better highlight the evolutionary events during that period. The bottom graph shows the frequency of gene transfer events of the electron transfer gene over time. Taxa are abbreviated as per this figure. A summary of the dates of the reconciled key nodes received the MtrA gene estimated with six evolutionary models is provided on the left. The reconciled roots for periplasmic MHC, MtrA, map to node 424, the last common ancestor of Euryarchaeota and TACK in figure 5 . We further evaluated the EET root position by forcing a posterior root age for the last common ancestor of the MtrA (node 424) in the MtrA gene tree using the age estimates for the crown groups from the species tree as secondary calibrations ( supplementary fig. S9, Supplementary Material online). The molecular clock applied to the MtrA gene tree yielded the posterior age estimate of 3,348–4,010 Ma, which is consistent with the age estimate of the reconciled species tree (3,363–4,045 Ma). These broad posterior age distributions are expected, given the limited information available for constraining such deep divergences. These inferences of deep-rooted ancestry of MtrA from phylogenetic reconciliation are sensitive to both the current sampled diversity of extant sequences and the expected underlying frequencies of gene loss events, as high rates of loss are more compatible with deeper rootings within the species tree. The HGT events and recipients inferred by the reconciliations, on the other hand, are less prone to biases from rooting, reconciliation, and sampling. The reconciliation of the MtrA phylogeny to the species tree suggests that the distribution of MtrA genes in the bacterial tree of life can be explained by major gene transfer events between archaea and bacteria ( fig. 5 , red arrows). The earliest HGTs are mapped from 1) Thermoplasmata to Cyanobacteria and 2) Methanoperedenaceae to γ-proteobacteria. Each of these HGT events is inferred to have occurred after the GOE (2,175 ± 90 Ma to Cyanobacteria and 2,120 ± 266 Ma to γ-proteobacteria) ( fig. 5 ). Reconciliation analysis suggests that β -proteobacteria acquired their periplasmic EET MHC from γ-proteobacteria in multiple HGT events, including one HGT to the common ancestor of Nitrosomonas and Nitrosospira ( fig. 5 ). This HGT to Nitrosomonadaceae consistently occurs during the time of presumed oxygen limitation ( Holland 2006 ; Planavsky et al. 2014 ) in all model estimations ( fig. 5 ). The ancestral β -proteobacterial ammonia oxidizer, therefore, initially acquired the anaerobic EET metabolism early in Earth's history of atmospheric oxygenation, when transient oxygen limitation was likely commonplace. As in Methanoperedenaceae ANME, our study indicates that EET metabolism appears to be still functional in β -proteobacterial ammonia-oxidizers today. Integrating the results of these experimental and phylogenomic studies with the geochemical history of oxygen suggests a period of ecological and metabolic transition during the Proterozoic, somewhat ironically marked by an expansion of anaerobic oxidation metabolisms. Our experimental findings show that a modern aerobic bacterial ammonia oxidizer may survive oxygen-limiting conditions through EET, which enables the oxidation of inorganic solid-phase electron acceptors. Future studies should aim to establish the growth rates of N. communis in anoxic conditions and elaborate on the range of mineral oxides capable of supporting growth. In addition, our analyses reveal that multiple HGT events from γ-proteobacteria to β -proteobacteria and Nitrosomonadaceae are inferred to have occurred during the Proterozoic, providing ammonia oxidizing lineages with archaeal EET metabolisms. The timing of these evolutionary innovations may be due to a regime of fluctuating anoxic–oxic interfaces that persisted until the late Proterozoic (742–542 Ma) ( Saito 2012 ) and thus might explain why aerobic ammonia oxidizers are consistently observed in oxygen-limiting and -depleted environments ( Freitag and Prosser 2003 ; Mortimer et al. 2004 ; Yu and Chandran 2010 ; Garcia-Robledo et al. 2017 ). This ordering of evolutionary events, specifically, HGT of EET encoding genes within groups of aerobic bacterial ammonia oxidizers, hints that electrogenic ammonia oxidation is not ancestral to aerobic ammonia oxidation. This is in line with the vast increase of oxidized minerals after the GOE, which could serve as electron acceptors for EET ( Saito 2012 ). Our homology searches did not identify EET signals in archaeal ammonia oxidizers. One possibility is that these groups have lost their ancestral MHCs following the gain of other metabolic adaptations ( Kraft et al. 2022 ) to cope with O 2 fluctuations and limitations, as ammonia-oxidizing archaea have been consistently detected in marine oxygen-minimum zones and oxygen-deficient sediments ( Molina et al. 2010 ; Stahl and de la Torre 2012 ; Sollai et al. 2019 ). Additional anaerobic pathways may remain to be investigated among other groups of aerobic microbes, which could potentially be revealed using similar electrode-based culture enrichment methods and phylogenomics."
} | 7,721 |
35890447 | PMC9322151 | pmc | 8,947 | {
"abstract": "Several activities in the agriculture sector lead to the accumulation of Nickel (Ni) in soil. Therefore, effective and economical ways to reduce soil bioavailability of Ni must be identified. Five isolates of Rhizobium leguminosarum biovar Viceae (ICARDA 441, ICARDA 36, ICARDA 39, TAL–1148, and ARC–207) and three bacterial strains ( Bacillus subtilis , B. circulance , and B. coagulans ) were evaluated for tolerance and biosorption of different levels of Ni (0, 20, 40, 60, and 80 mg L −1 ). Pot experiments were conducted during the 2019/2020 and 2020/2021 seasons using four inoculation treatments (inoculation with the most tolerant Rhizobium (TAL–1148), inoculation with the most tolerant Rhizobium (TAL–1148) + B. subtilis , inoculation with the most tolerant Rhizobium (TAL–1148) + B. circulance , and inoculation with the most tolerant Rhizobium (TAL–1148) + B. coagulans ) under different levels of Ni (0, 200, 400, and 600 mg kg −1 ), and their effects on growth, physiological characteristics, antioxidant enzymes, and Ni accumulation in faba bean plants ( Vicia faba C.V. Nobaria 1) were determined. The results showed that Rhizobium (TAL–1148) and B. subtilis were the most tolerant of Ni. In pot trials, inoculation with the most tolerant Rhizobium TAL–1148 + B. subtilis treatment was shown to be more effective in terms of growth parameters (dry weight of plant, plant height, number of nodules, and N 2 content), and this was reflected in physiological characteristics and antioxidant enzymes under 600 mg kg −1 Ni compared to the other treatments in the 2019/2020 season. In the second season, 2020/2021, a similar pattern was observed. Additionally, lower concentrations of Ni were found in faba bean plants (roots and shoots). Therefore, a combination of the most tolerant Rhizobium (TAL–1148) + B. subtilis treatment might be used to reduce Ni toxicity.",
"conclusion": "5. Conclusions The effects of several bacterial inoculations on Ni accumulation in faba bean plants grown in various levels of Ni-contaminated soil were studied. Inoculation with the most tolerant Rhizobium TAL–1148 + B. subtilis treatment was more effective in terms of growth parameters (dry weight of plant, plant height, number of nodules, and N 2 content), as evidenced by physiological characteristics and antioxidant enzymes in soil treated with 600 mg kg −1 Ni compared to the other treatments. As a result, during the two growing seasons, the treatment combining the most tolerant Rhizobium (TAL–1148) with B. subtilis could be utilized as an option to reduce Ni toxicity.",
"introduction": "1. Introduction Faba bean ( Vicia faba L.) is one of the most important leguminous crops grown in Asia and the Mediterranean region [ 1 ]. It is high in protein (25–30%) and carbohydrates (55–60%), which contributes to its placement among the popular annually produced grain crops for use among humans and domestic animals [ 2 ]. Green seeds are utilized in fresh vegetable salads during vegetative growth, while dry seeds are used in prepared food, and the entire plant can be fed to farm animals [ 3 ]. Due to a lack of domestic production, Egypt is one of the leading importers of faba bean [ 1 ]. Some stresses, such as heavy metal contamination, have an impact on faba bean productivity. In addition, human, agricultural, and industrial activities all contribute to metal contamination of soils [ 4 ]. As a result of these processes, mineral residues accumulate in agricultural soils, posing a threat to food safety and public health [ 5 ]. Since microbial flora composition and microbial activity are greatly affected by mineral accumulation, soil fertility is lost [ 6 ]. Some metals, while necessary in small amounts for organisms, are toxic in large amounts. One of the most significant environmental and biological issues is nickel (Ni) contamination [ 7 ], which is one of the most common trace metals discharged into the environment by both natural and manmade activities. Anthropogenic activities, such as burning fossil fuels for electricity production, mining, smelting, automobile emissions, steel manufacturing, the cement sector, and domestic, municipal, and industrial waste disposal, all contribute to increased Ni release into the soil [ 8 ]. In the metallurgical and electroplating sectors, Ni is used as a raw material. It is also employed as a catalyst in the chemical and culinary industries, in addition to being used as a battery backup [ 8 , 9 ]. The release of Ni into the environment, including its deposition in agricultural soils, is a major problem [ 8 , 10 ]. Nickel is a common heavy metal found in soil and water, accounting for around 0.08 percent of the earth’s crust [ 11 ]. Nickel toxicity poses a serious threat to agriculture, the environment, and human health [ 12 ]. Excess Ni in plants has become a major issue, posing a serious threat to the sustainability of agriculture. Species and age of plant, growing conditions, Ni concentration, and exposure period in the soil all influence the impact of Ni toxicity on physiological and metabolic functions [ 13 , 14 ]. Nickel is required for the synthesis of hydrogenase in prokaryotes, which catalyzes the oxidation of hydrogen liberated by nitrogenase during the dinitrogen reduction process [ 15 ]. Nickelin (HypB), an accessory protein responsible for Ni supply in rhizobia, has a dual role in Ni mobilization into hydrogenase and Ni storage [ 16 ]. Metals have been shown to negatively affect microorganism growth, morphology, and activity, including symbiotic nitrogen fixation [ 17 ]. This symbiosis has been suggested as a method to remove or fix heavy metals in polluted soil and increase the fertility of soil [ 5 ]. As a result, finding plant growth-promoting rhizobacteria (PGPR) with high heavy metal resistance capacities became a top priority [ 18 ]. Edulamudi [ 14 ] showed that, in soils amended with Ni, horse gram coupled with rhizobia could develop nodules and fix nitrogen, and both root nodules and soil were used to assess the rhizobial strains’ biosorption capability for the removal of Ni from contaminated soils. On the other hand, Bacillus thuringiensis 002, B. subtilis 174, and B. fortis 162 accelerated root elongation and Ni mobility in soil and increased Ni accumulation in Acrasis rosea [ 13 ]. The goal of this study was to examine the Ni stress tolerance and biosorption capability of rhizobia and Bacillus strains in their association with faba bean plants under greenhouse conditions during 2019/2020 and 2020/2021 seasons.",
"discussion": "3. Discussion 3.1. Assessment of Different Rhizobium Isolates and Bacillus Strains for Ni Tolerance These differences in response shown by the studied strains might be due to differences in their inherent tolerance capacities, supported by active Ni efflux mechanisms to avoid dangerous intracellular Ni levels [ 19 ]. Several investigations have found that heavy metals, notably Ni, have a negative impact on symbiotic N fixation; for example, from the nodules of pea and lentil plants cultivated in polluted fields, Ni-tolerant Rhizobium strains (RP5 and RL9) were isolated and showed great tolerance to 350 and 500 mg mL −1 of Ni [ 20 ]. At the lowest dose of 0.2 mM, Rhizobium strains L9 and L19 showed better resistance to Ni than Mesorhizobium L42 and L50 [ 21 ]. In addition, in vitro, the rhizobium HGR-4 isolated from horse gram root nodules could tolerate 1000 mg g −1 Ni [ 14 ]. On the other hand, among the bacteria tested ( B. thuringiensis 002, B. fortis 162, B. subtilis 174, and B. farraginis 354), B. subtilis 174 had the highest Ni tolerance, growing in conditions containing Ni at a concentration of 400 mg L −1 [ 13 ]. 3.2. Biosorption of Ni by Different Rhizobium Isolates and Bacillus Strains For the concentrations examined, the biosorption of Ni by different bacterial strains was significantly increased. The reason for this specific behavior is due to the smaller ionic radius of Ni (0.69 Å). In addition, bacteria can also accumulate metal in their cell walls, as well as protein polyphosphate complexes, polysaccharides, and complex forms with carboxyl groups of peptidoglycans [ 22 ]. Tobin et al. [ 23 ] hypothesized that molecules with a smaller ionic radius sorb more quickly. Biosorption of Ni has been well supported by previous findings based on ionic radius [ 24 , 25 ]. As a result, the aforementioned strains could be employed as potential heavy metal immobilizers in polluted soils. Ajmal et al. [ 26 ] reported that the bacterial strain Citrobacter werkmanii (WWN1) showed maximum net removal of 87% of Ni from an aqueous solution, followed by Enterobacter cloacae (JWM6), which showed 86% net removal of Ni, in a comparison with other studied strains. 3.3. Pot Trial 3.3.1. Parameters of Growth Rhizospheric bacteria have the ability to reduce/detoxify heavy metal stress through a variety of methods, such as metal ions outside the cell, biostimulation, bioaugmentation, metal reduction, and biosorption [ 27 ]. Improved plant development in metal-contaminated soils has been attributed to a bacterial biosorption/bioaccumulation mechanism with plant growth-promoting characteristics [ 28 ]. Metal accumulation in root nodules may be aided by rhizobial nodulation of the host plants. Additionally, different processes of precipitation, chelation, immobilization, and biosorption might lower metal toxicity when microbes remain in the rhizosphere [ 29 ]. Heavy metals such as Ni have a significant impact on plant nodulation growth parameters [ 30 ], and excessive Ni has been found to have negative effects on microorganisms, particularly rhizobia, and therefore on nodule formation in various leguminous species [ 31 ]. At 100 mg kg −1 Ni, more nodules were detected in Vigna cylindrica , while the production of root nodules was substantially hampered in Vigna mungo and Vigna radiata [ 32 ]. A phytotoxic effect was observed at 580 mg Ni/kg soil, which dramatically reduced the number of lentil nodules [ 20 ]. 3.3.2. Photosynthetic Pigments Nickel almost completely destroys the photosynthetic apparatus/machinery, i.e., mesophyll cells and epidermal tissues [ 33 ], and reduces chlorophyll content (chlorophyll a, b, total chlorophyll) at all levels [ 34 , 35 ]. Furthermore, Ni affects the structure of thylakoid membranes and grana, lowering the size of grana and increasing the frequency of non-appressed lamellae [ 36 ]. However, higher levels of nutrients and organic matter in the rhizosphere could explain the rise in chlorophyll and carotenoids in faba bean leaves by bacterial inoculation [ 37 , 38 ]. Several studies have shown that bacterial inoculation accelerates the production of photosynthetic pigments in stressed plants [ 13 , 39 , 40 , 41 ]. 3.3.3. Activity of Antioxidant Enzymes Plants enhance the activity of antioxidant enzymes in their main state in response to abiotic challenges, such as heavy metal stress; this is dependent on plant stress sensitivity as a first line of defense against high antioxidant ROS concentrations [ 42 , 43 ]. According to our findings, antioxidant enzymatic defense systems appear to play a key part in faba bean plant Ni toxicity. This defense can be activated at the transcriptional level, and at the enzymatic activity can help the plant adapt to Ni toxicity. A similar trend was observed in rye [ 44 ], Lemna polyrhiza [ 45 ], Helianthus annus [ 13 ], and lettuce [ 42 ]. 3.3.4. Nickel Content Irrespective of Ni concentrations, the data showed that treating faba bean plants with Rhizobium TAL–1148 + B. subtilis had a better effect than other bacterial inoculation treatments due to the fact that the Ni content was lower. Under varied conditions of Ni stress, the bioconcentration factor (BCF) and translocation factor (TF) of faba bean plants revealed that the application of Rhizobium TAL–1148 + B. subtilis (T4) considerably reduced the accumulation of Ni in plant tissues compared to the control treatment, T1 ( Table 4 ). Hence, the increase in Ni content in the roots of faba bean plants is due to biosorption of Ni by Rhizobium + B. subtilis . Based on these findings, it appears that biosorption by bacterial inoculation is responsible for the change of Ni into insoluble forms [ 14 , 42 ]. Reduced Ni levels in plant organs could be attributed to RL9 strain’s adsorption/desorption, according to research by the authors of [ 20 , 46 ]. The bioinoculant strains lowered Ni levels in the organs of inoculated plants cultivated in soils polluted with various metals [ 18 , 21 ]."
} | 3,149 |
38224956 | PMC10847717 | pmc | 8,949 | {
"abstract": "Abstract Microbiome-based solutions are regarded key for sustainable agroecosystems. However, it is unclear how agricultural practices affect the rhizosphere microbiome, plant–microorganism interactions and crop performance under field conditions. Therefore, we installed root observation windows in a winter wheat field cultivated either under long-term mouldboard plough (MP) or cultivator tillage (CT). Each tillage practice was also compared at two nitrogen (N) fertilization intensities, intensive (recommended N-supply with pesticides/growth regulators) or extensive (reduced N-supply, no fungicides/growth regulators). Shoot biomass, root exudates and rhizosphere metabolites, physiological stress indicators, and gene expression were analyzed together with the rhizosphere microbiome (bacterial/archaeal 16S rRNA gene, fungal ITS amplicon, and shotgun metagenome sequencing) shortly before flowering. Compared to MP, the rhizosphere of CT winter wheat contained more primary and secondary metabolites, especially benzoxazinoid derivatives. Potential copiotrophic and plant-beneficial taxa (e.g. Bacillus, Devosia , and Trichoderma ) as well as functional genes (e.g. siderophore production, trehalose synthase, and ACC deaminase) were enriched in the CT rhizosphere, suggesting that tillage affected belowground plant–microorganism interactions. In addition, physiological stress markers were suppressed in CT winter wheat compared to MP. In summary, tillage practice was a major driver of crop performance, root deposits, and rhizosphere microbiome interactions, while the N-fertilization intensity was also relevant, but less important.",
"conclusion": "Conclusion In our study, we used a long-term field study site and in-field root windows to obtain a holistic view on the impact of agricultural practice (tillage, N-fertilization intensity) on the complex interaction between plant roots and the surrounding microbial community in soil. Tillage practice strongly impacted on the multipartite interaction network with consequences for plant health and stress resilience. CT combined with reduced N-fertilization intensity resulted in a positive plant–microorganism feedback in the RH contributing to an improved plant performance compared to conventional management. However, care should be taken as these observations cannot be generalized as indicated by long-term (2012–2016) higher yields in the conventional (9.6 t ha −1 MP-Int) compared to conservation practice (8.4 t ha −1 CT-Ext). We, therefore, suggest that the observed compensatory effects of conservation practices are more likely to play a role under unfavorable conditions such as pathogen pressure or drought, which are predicted to occur more frequently in a changing climate. Altogether, this study contributes to a holistic understanding of soil–plant–microorganism interactions in agricultural settings.",
"introduction": "Introduction The increasing demands for plant-based products together with the reduced availability of sites for agriculture has led to more intensive farming practice over the last decades (Hoang et al. 2023 ). This intensification, often achieved by high use of agrochemicals, has negative consequences for soil quality and overall ecosystem functions (Kopittke et al. 2019 , Timmis and Ramos 2021 ). To counteract the increasing degradation of soils, less intensive, so-called conservation farming practices including diverse crop rotations, reduced tillage combined with lower pesticide and fertilizer use have been promoted (Hobbs et al. 2008 ). Soil microorganisms play an essential role for soil structure and fertility (Fierer 2017 , Banerjee and van der Heijden 2023 ). Furthermore, soil microorganisms represent the reservoir from which the plant assembles its rhizosphere (RH) microbiome (Philippot et al. 2013 ). The RH, i.e. the carbon-enriched thin layer of soil surrounding roots and influenced by root activity (Berg and Smalla 2009 ), is a hot spot for microbial activity and is considered one of the most complex and diverse ecosystems (Hinsinger et al. 2009 , Raaijmakers et al. 2009 ). The RH microbiome plays a pivotal role in plant development and health (Berendsen et al. 2012 , Mendes et al. 2013 ). For instance, an improved plant tolerance to abiotic and biotic stressors can be the result of beneficial plant–microorganism interactions in the RH (Panke-Buisse et al. 2015 , Mommer et al. 2016 ). Therefore, engineering the soil and RH microbiome is crucial for sustainable agroecosystems (Toju et al. 2018 , Trivedi et al. 2021 ). Plants have evolved various mechanisms to modulate their RH microbiome (Berendsen et al. 2012 , Lareen et al. 2016 ), including the release of root exudates and other organic rhizodeposits, which can account for up to 11% of photosynthetically fixed carbon (Jones et al. 2009 ). Low molecular weight (LMW) root exudates, released either by diffusion or via controlled secretion, comprise the full range of primary metabolites as well as a wide range of secondary plant compounds. Generally, LMW sugars in root exudates represent an easily available carbon source for microorganisms. Exuded carboxylates such as malate and citrate are chemo-attractants and preferential carbon sources for N 2 -fixing RH bacteria. Moreover, they can act as metal chelators and can thereby contribute to the mobilization of micronutrients and sparingly soluble phosphorus (P) in soils. Additionally, carboxylates can neutralize toxic aluminum as well as adaptively modify root architecture (Canarini et al. 2019 , Neumann and Ludewig 2023 ). Amino acids are important nitrogen (N) sources for microorganisms. Furthermore, they can function as precursors for microbial production of phytohormones, signals in adaptations for N acquisition and as metal chelators (Canarini et al. 2019 , Neumann and Ludewig 2023 ). Exuded secondary metabolites comprise also diverse bioactive compounds (Philippot et al. 2013 ), such as benzoxazinoids (BXs; Kudjordjie et al. 2019 , Cadot et al. 2021 ), coumarins (Stassen et al. 2020 ), flavones (Yu et al. 2021 ), triterpenes (Huang et al. 2019 ), and camalexin (Koprivova et al. 2019 ), which were found to contribute to root–microbiome interactions and various cross-kingdom relationships. Previous studies demonstrated that the legacy of agricultural practices affect the RH microbiome (Sommermann et al. 2018 , Babin et al. 2019 , Cerecetto et al. 2021 ), and thereby the performance and health of plants (Chowdhury et al. 2019 , Babin et al. 2021 , Bourceret et al. 2022 , Flemer et al. 2022 ). Using lettuce as a model in minirhizotrons with root observation windows, Neumann et al. ( 2014 ) and Windisch et al. ( 2021 ) showed that the soil type and the fertilization strategy affected the root exudation profiles and accumulation of RH metabolites likely as a result of plant interactions with the soil-specific microbiomes. However, realistic insights into the dynamics of root exudate releases and turnover under field conditions and related interactions with pathogenic and beneficial soil microorganisms remain largely unexplored (Kawasaki et al. 2018 , Oburger et al. 2022 ). Consequently, factors influencing plant–microorganism interactions and processes in agroecosystems are not yet fully understood (Canarini et al. 2019 ). In order to exemplarily address these knowledge gaps and provide a holistic understanding of soil–plant–microorganism interactions in agricultural settings, we installed root windows, similar to large rhizotrons, in winter wheat plots of a long-term field experiment managed under contrasting tillage types [cultivator (CT) vs. mouldboard plough (MP)] and intensities of N-fertilization and pesticide/growth regulator use [intensive (Int) vs. extensive (Ext)]. An interdisciplinary approach enabled us to assess root growth characteristics and RH metabolites in situ along with the soil and RH microbiome. Aboveground, shoot biomass, plant nutritional status, and physiological stress indicators were monitored to assess plant health.",
"discussion": "Discussion Reduced N-fertilization intensity supported wheat root development The root development is strongly influenced by nutrient availability and fertilization (Pierret et al. 2007 ). Bilalis et al. ( 2015 ) showed that reduced nutrient availability stimulates root properties required for nutrient acquisition. In the present study, winter wheat under Ext exhibited a larger root system compared to Int, regardless of the tillage practice, likely supporting the uptake of water and nutrients even under reduced availability. The reductive assimilation of nitrate as the predominant N source in mineral fertilized soils requires the successive activities of nitrate reductase 1 ( TaNR1 ) and nitrite reductase ( TaNIR ) for conversion of nitrate to nitrite and finally to ammonium (Costa-Broseta et al. 2021 ). The higher amount of available N consistently induced higher expression of these genes, including the nitrate transporter gene ( TaNPF7.1 , NRT1-PTR-Family), in the Int compared to Ext treatments ( Figure S4 , Supporting Information ). Aside from K, which was below the deficiency level across all treatments, there were no specific nutrient deficiencies. Consequently, winter wheat plants acquired sufficient nutrient amounts, leading to comparable shoot biomass across treatments regardless of N-fertilization intensity (Table 1 ). This highlights that wheat compensated the reduced N availability (Ext) by extending the root architecture and physiological properties. As wheat under Ext and reduced tillage (CT) produced the same yield like plants under Int and MP, current N-fertilization practices for wheat still appear too high, with potential negative consequences for the environment, due to leakage. Agricultural practice altered RH metabolites and plant–microorganism interactions Root exudates and related RH metabolites are key drivers of interactions at the plant–microorganism–soil interface (Hu et al. 2018 , Kudjordjie et al. 2019 , Oburger et al. 2022 ) influenced by various factors (Neumann and Ludewig 2023 ). The root window setup combined with microsampling of RH soil solutions (Neumann 2006 ) allowed to track spatial variations along different root zones and relate them to the RH microbiome and plant performance. In our study, tillage practice, but not N-fertilization intensity, predominantly influenced RH metabolite patterns, especially in the young apical root zones (Fig. 1B ). Tryptophan was significantly increased in the RH of plants grown under CT (Table 5 ). Many RH microorganisms use tryptophan as a precursor for indole acetic acid (IAA) production (Spaepen and Vanderleyden 2011 , Vurukonda et al. 2016 ) and thereby stimulate the growth of fine lateral roots, as observed also in this study (Table 1 ). Elevated tryptophan concentrations were also positively correlated with an enrichment of Bacillus in the RH (Fig. 4 , Table 6 ), containing strains described to produce IAA (Özdal et al. 2016 ). Interestingly, microbial genes involved in IAA production were not among the differentially abundant genes (Fig. 3 ). However, it has been reported that microorganisms can also improve lateral root formation independent of IAA production (Yu et al. 2021 ) by modulating the hormonal balances of the host plant via changes in plant hormonal metabolism (Moradtalab et al. 2020 ). In this context, also the increased abundance of ACC deaminase genes in RH of CT plants could be relevant for the stimulation of fine root development (Table 1 ) by lowering the plant ethylene level acting as an antagonist (Glick et al. 2007 ). Other RH metabolites, such as succinic acid, trehalose, and asparagine, were higher in the CT treatments and correlated with the increased relative abundance of potentially beneficial microorganisms ( Bacillus and Trichoderma ; Fig. 4 ). Succinic acid acts as a chemoattractant and carbon source for various beneficial microorganisms and is relevant for functions in biocontrol and plant defense responses (Sampedro et al. 2015 ). Trehalose represents a signaling molecule regulating bacterial and fungal growth, development, and virulence (Sharma et al. 2020 ), but it is also produced by microorganisms in high quantities, promoting adaptive responses to abiotic stress in plants (Vurukonda et al. 2016 , Kosar et al. 2019 ). Moreover, trehalose can induce resistance to powdery mildew in wheat (Reignault et al. 2001 ), which is in line with the here observed reduced symptoms of powdery mildew in the CT treatments. The increased abundance of trehalose synthase genes in the RH of CT plants (Fig. 3 ) suggests a microbial origin for the elevated trehalose levels. Apart from some phenolic acids and flavonoids, the predominant secondary metabolites detected in the RH soil solution were different BXs, derived from the young apical root zones particularly of CT plants. These compounds are produced by most cereal crops at an early growth stage and in response to stress events as defense substances with allelopathic, insecticidal (antifeeding), and antimicrobial effects (Hu et al. 2018 , Kudjordjie et al. 2019 , Schandry and Becker 2020 ). Additionally, they can stimulate growth of beneficial soil microorganisms, decrease plant growth of competitors, increase JA signaling and plant defenses, and suppress herbivore performance in the next plant generation (Hu et al. 2018 , Oburger et al. 2022 ). In soils, these highly bioactive substances are rapidly converted into more stable derivates, such as APO, MBOA, MeBOA, and AMPO, through both microbial and nonmicrobial processes (Schütz et al. 2019 , Oburger et al. 2022 ). In the CT treatments, MBOA was predominant, while in the MP treatments, other BXs (MeBOA) dominated, which could indicate differences in microbial degradation between CT and MP tillage practice. The accumulation of MBOA was positively correlated with potentially antagonistic microorganisms ( Bacillus and Trichoderma ) (Tables 6 and 7 ; Fig. 4 ). This, together with the fact that MBOA has toxic effects on various fungal pathogens (Cotton et al. 2019 , Kudjordjie et al. 2019 ), such as Fusarium species (Glenn et al. 2001 ), may explain the reduced relative abundance of putative plant pathogenic fungal genera in the CT-Ext treatment ( Zymoseptoria and Gibellulopsis ; Figure S5B , Supporting Information ). Agricultural practices altered the RH microbiome of winter wheat The RH microbiome strongly depends on the soil microbiome, which is influenced by different factors, such as agricultural practice (Bulgarelli et al. 2013 ). In our study, tillage practice was the main factor affecting the microbiome in the RA soil and RH (Table 4 ), indicating that the complete plant–microorganism–soil system was affected. These observations are in line with results from previous studies investigating wheat soils (Sommermann et al. 2018 , Babin et al. 2019 , Romano et al. 2023 ), which highlights the stable legacy of tillage practice likely caused by differences in physical soil properties (Schlüter et al. 2018 ) as well as differences in chemical composition (e.g. C and N stocks; Table S15 , Supporting Information ). N-fertilization intensity shaped the communities only to a minor extent with a stronger influence on fungi. This confirmed previous studies (Sommermann et al. 2018 , Bziuk et al. 2021 ) and could be related to the availability of N that influences the activity and growth efficiency, especially of saprotrophic fungi (Di Lonardo et al. 2020 ). Clearly, not only plants can influence the microbial community via root exudation, but microorganisms can also alter the exudate composition (Korenblum et al. 2020 ). Our results further support such interdependence of root exudates and the microbiome (Fig. 4 ). The effects of tillage practice on the composition of root exudates are likely related to specific patterns of substrate utilization by the microbiome. Bacterial and archaeal species in the RH of MP plants belonged mainly to Actinobacteria and Acidobacteria (Table 6 ; Table S10 , Supporting Information ), which are typically regarded oligotrophs (Fierer 2017 ). This might indicate that the selective effect of the plant is lower in MP than in CT. The acidobacterial genus RB41 has been frequently isolated from soil and was reported as a tillage responder. In accordance with our results ( Table S10 , Supporting Information ), Kudjordjie et al. ( 2019 ) found a negative correlation between many acidobacterial species and BX compounds in maize roots. BXs have a selective impact on root and RH microbiota across different field locations (Niemeyer 2009 , Kudjordjie et al. 2019 , Cadot et al. 2021 ). Taxa with higher relative abundance in the RH of CT plants compared to MP plants belonged to typical RH genera such as Bacillus, Sphingomonas, Devosia , and Pseudoxanthomonas (Table 6 ; Table S10 , Supporting Information ), which are known to harbor members with plant-beneficial properties (Chowdhury et al. 2019 ). Additionally, many sequences with affiliation to Saccharimonadaceae (Patescibacteria) were enriched in the RH of CT plants. A symbiotic lifestyle and cometabolism interdependencies were proposed for Patescibacteria (Lemos et al. 2019 ), which might favor these taxa in microbial hotspots such as the RH. In summary, this suggests that the driving effect of the plant on the soil bacterial/archaeal community was stronger in soils under CT than MP tillage. In the RH of CT more fungal genera with known plant-beneficial members, such as Trichoderma , were present, whereas potential plant pathogens, like Olpidium , were more abundant in the RH of MP plants. The genus Olpidium harbors typical pathogens for Brassicaceae (Lay et al. 2018 ) like rapeseed, which was the previous crop at the sampling site. Furthermore, Chrysosporium species were enriched in MP and are known in the context of gibberellin production, which can enhance plant growth (Hamayun et al. 2009 ), but is detrimental for plants in high doses (Cen et al. 2020 ). Among the fungal responders in CT were many potential fungal antagonists such as Chaetomium, Penicillium, Trichoderma , and nonpathogenic Fusarium , which were often found in disease-suppressive soils (reviewed by van Bruggen and Semenov 2000 , Mazzola 2002 ). Trichoderma species are well known as plant-growth promoters, mycoparasite and inducers of plant systemic resistance against pathogens (Harman et al. 2004 , López-Bucio et al. 2015 , Hafiz et al. 2023 ) and were previously identified in a growth chamber experiment with soils from the identical sampling site as responders to CT (Babin et al. 2021 ). The class Sordariomycetes was increased in the RH of CT plants with high BXs concentration (Fig. 4 ), which confirms previous studies (Kudjordjie et al. 2019 ). The effect of tillage on microbial communities was not only observed on a taxonomic but also functional level. ACC deaminase activity, siderophore, trehalose, and spermidine production were enriched in the RH of CT plants (Fig. 3 ). ACC deaminase lowers the level of the plant stress hormone ethylene and is, therefore, considered as beneficial (Dubois et al. 2018 ). Genes encoding ACC deaminase were present in several genera including Microbacterium , which was enriched in CT samples and is well-known to harbor plant-beneficial members (Vílchez et al. 2018 , Freitas et al. 2019 ). Moreover, spermidine is a compound with several important functions, e.g. biofilm production, overall bacterial fitness, plant growth promotion, and stress protection (Alavi et al. 2013 , Xie et al. 2014 , Chen et al. 2018 ). Among the classified genera, that encode spermidine production, was the responder genus Mesorhizobium from the RH of CT. In rhizobia, spermidine plays a role in symbiotic interactions and root nodule formation (Becerra-Rivera and Dunn 2019 ). Siderophores are iron-chelating compounds that are involved in pathogen suppression by iron competition (Gu et al. 2020 ) or by inducing systemic resistance (Zamioudis et al. 2015 , Verbon et al. 2019 ). Several genera were associated with siderophore production, but no responder genus was included ( Figure S8 , Supporting Information ). Thus, the increased siderophore production in CT plants seems to be a concerted effect of several beneficial taxa. Comparing amplicon and metagenomics data, responders encoding trehalose synthase genes were found ( Microbacterium and Devosia ; Figure S8 and Table S10 , Supporting Information ). Trehalose produced by Microbacterium sp. 3J1 was previously described to be involved in the protection of pepper plants against drought stress (Vílchez et al. 2018 ). Taken together, these responders could have contributed to the observed improved plant health in CT plants. Reduced tillage practice and N-fertilization intensity enhanced stress tolerance in winter wheat Analysis of stress-related metabolites and genes in wheat leaves highlighted that tillage practice had a pronounced effect on metabolic stress adaptation. In contrast to MP plants, lower concentrations of stress hormones (JA and SA) and stress indicators (T-AO, proline, and APX; Table 3 ) were revealed for CT plants. Moreover, increased abundance of the ACC deaminase gene derived from bacteria in the RH of CT plants (Fig. 3 ) could have also contributed to the reduced stress responses in CT plants (Glick et al. 2007 ). The elevated stress level of MP plants was underlined by the differentially enriched expression of genes involved in stress responses (Fig. 1A ) like the well-characterized pathogenesis-related gene PR1 (β-1,3-glucanase) and Chitinase ( TaCHI ). These genes encode for proteins involved in hydrolysis of glucan and chitin, which are present in fungal cell walls (van Loon et al. 2006 ) and have been shown to be upregulated in Puccinia triticina infected wheat leaves (Casassola et al. 2015 ) and in Pyricularia oryzae infected rice leaves (Cruz et al. 2015 ). In our study, an enhanced expression of other defense-related genes like lipoxygenase ( TaLOX ), defensin ( Tad1 ), and allene oxide synthase ( TaAOS ), which are highly inducible by biotic stress factors (Manners et al. 1998 ), was observed. The cross-talk among SA, JA, and ET in the regulation of plant stress responses has been extensively studied in model plants like Arabidopsis (Pieterse et al. 2009 , Verhage et al. 2010 ). The increased expression of TaSOD, TaCAT , and TaPER genes associated with leaf accumulation of T-AO and increased APX activity in the MP plants indicates an activation of defense mechanisms to detoxify free radicals and to alleviate the oxidative damage associated with the overproduction of reactive oxygen species (Miller et al. 2010 ). Our findings from wheat leaf gene expression suggest that compared to CT, plants grown in MP soil showed enhanced activity of defense signaling pathways, potentially triggered by the presence of a leaf pathogen (i.e. B. graminis ). This observation was supported by an elevated concentration of the stress hormones JA and SA in the shoots (Table 3 ). The described scenario indicates a reduced influence of stress factors on wheat plants grown in CT soil, which was most likely supported by modifications of the interactions with the RH microbiome e.g. via root exudates."
} | 5,869 |
28705169 | PMC5513249 | pmc | 8,950 | {
"abstract": "Moth-eye nanostructures, discovered to coat corneae of certain nocturnal insects, have inspired numerous technological applications to reduce light reflectance from solar cells, light-emitting diodes, and optical detectors. Technological developments require such nanocoatings to possess broadband antireflective properties, transcending the visual light spectrum, in which animals typically operate. Here we describe the corneal nanostructures of the visual organ exclusive in UV sensation of the hunting insect Libelloides macaronius and report their supreme anti-light-reflectance capacity."
} | 148 |
29062933 | PMC5640696 | pmc | 8,952 | {
"abstract": "The rapid development of synthetic biology has conferred almost perfect modification on single cells, and provided methodological support for synthesizing microbial consortia, which have a much wider application potential than synthetic single cells. Co-cultivating multiple cell populations with rational strategies based on interacting relationships within natural microbial consortia provides theoretical as well as experimental support for the successful obtaining of synthetic microbial consortia, promoting it into extensive research on both industrial applications in plenty of areas and also better understanding of natural microbial consortia. According to their composition complexity, synthetic microbial consortia are summarized in three aspects in this review and are discussed in principles of design and construction, insights and methods for analysis, and applications in energy, healthcare, etc.",
"conclusion": "5 Conclusions and perspectives Synthetic microbial consortia are getting more and more attentions with the rapid progress of synthetic biology. Academic authorities including Ron Weiss, Frances Arnold, Pam Silver are all working on the system design and construction, robust research, and dynamic stability analysis, etc. As one of the important aspects in synthetic microbial consortia, signals delivery and metabolites exchange are the basic principles and guidelines, which are reflected in QS 21 , 30 and cross-feeding 39 , 40 , 41 systems. Ecosystems not only contain interaction among strains but also between microbial consortia and external environment, and are wildly used in natural relations simulation. 36 , 37 Evolution is important as well, and is mainly a supporting method in studies such as biodiversity and stability. 42 , 43 , 44 , 45 In this review, current synthetic microbial consortia are divided into three types according to their composition complexity, which are single species, two species or multiple species. Due to their relatively simple relationships, synthetic microbial consortia composed of single species have relatively more thorough understanding about the mechanisms. There are much more principles proposed to describe two species consortia, due to there much more complicated interactions. As for multiple species, breakthroughs have not been made yet; the supplementary metabolites or other signaling chemicals provided by other microbes in the communities are still mysterious. 94 Hence there is a phenomenon that with the increase of species, principles for design and analysis of microbial consortia are getting more special and novel, but the mechanisms are getting less understood, and the strains are more inclined to wild type rather than genetically engineered in application. Several challenges need to be overcome for uncovering the veil of multispecies consortia, the foremost of these is to optimize media compositions that satisfy all the multiple species, which influence population dynamics and further metabolism greatly. 5 Moreover, we need to take advantage of design and computational tools that take biological variability, uncertainty and evolution into account to provide rational guidance. 1 In addition, more novel approaches should be introduced into this field such as micro bead encapsulation, 95 \n 13 C-metabolic flux analysis, 96 synthetic biofilm for sequential layering of microbes. 97 Further, multispecies consortia finally put into application need to strengthen the robustness, especially in environment management or lignocellulose degradation in which survival conditions are tough for microbes, that is probably the reason why few genetically engineered strains are employed. One good solution to this may be to combine modified strains with natural microbial consortia derived strains together and evolve them to obtain a viability-improved synthetic microbial consortia. 98 Therefore, a series of problems need to be addressed urgently, such as: how to expand research objects, jump out of the confine of model microbes; how to build functional pathways in the existing non-model systems with valuable applications; how to deeply illuminate ecological structures, interaction patterns, fluctuating environmental and evolutionary stresses 94 of multiple species, in order to develop more powerful systems and broaden the application scope and depth? Correspondingly, the research methods and train of thoughts can't be limited into synthetic biology, which should also be combined with a systems biology approach. We envision that with the rational guidance of engineering principles, the advantages of synthetic microbial consortia over single strains enable multiple species make breakthrough in design and application of genetically engineered consortia in the future.",
"introduction": "1 Introduction With the rapid development of synthetic biology, designing and constructing synthetic microbial consortia has raised extensive attention, becoming one of the important frontiers for the second wave of synthetic biology, 1 but yet to be an important aspect of in-depth research. 2 As summarized by Ron Weiss and Cynthia Collins, there are three advantages of taking microbial consortia as the research object to engineer specific routes: (1) different strains are functionally divided to fulfill many complex tasks at the same time; (2) relationships between cells are dynamically balanced, leading to stronger adaptability and stability to the fluctuant environment; (3) elements and modules from different sources and with different functions can be built in different strains, reducing the metabolic load on single chassis as well as avoiding the cross-influence of different functions. 3 , 4 There are mainly two ways for designing and constructing synthetic microbial consortia. The first one is to re-engineer naturally occurring microbial consortia, which is a top-down method. 5 That is, based on multiple omics analysis, 6 , 7 , 8 , 9 , 10 , 11 , 12 starting from the macroscopic microbial consortia, parsing the system principles, to explore the molecular mechanisms for the maintained systems. The other one is to design and construct artificial microbial consortia, which is a bottom-up method. 5 That is, based on the genetic elements, modules, circuits and metabolic pathways or networks, 13 , 14 , 15 , 16 with the rational guidance of engineering principles, to obtain microbial consortia with higher efficiency, stability and controllability. Considering the complexity and practicability of synthetic biology, currently the bottom-up method is the mostly used for constructing microbial consortia from simple to complicated. Moreover, about the synthetic systems, there are different statements on the concept: co-cultures, 17 , 18 mixed cultures, 19 microbial consortia, 4 , 20 and so on. Considering that the phrase “microbial consortia” indicates not only living together but also labor division, and covers all of conditions of their composition: by single, two, and multiple species, 2 , 6 , 21 we use “microbial consortia” in this review. This review summarized current synthetic microbial consortia reported in literature from three aspects according to their composition complexity (composed of single species, two species or multiple species) and then discussed their design and construction strategies based on the interactions within microbial communities, their mechanism analysis methods, as well as their applications in many fields such as medicine and energy, etc."
} | 1,879 |
31700196 | PMC6837881 | pmc | 8,953 | {
"abstract": "Microorganisms are critical in mediating carbon (C) and nitrogen (N) cycling processes in soils. Yet, it has long been debated whether the processes underlying biogeochemical cycles are affected by the composition and diversity of the soil microbial community or not. The composition and diversity of soil microbial communities can be influenced by various environmental factors, which in turn are known to impact biogeochemical processes. The objectives of this study were to test effects of multiple edaphic drivers individually and represented as the multivariate soil environment interacting with microbial community composition and diversity, and concomitantly on multiple soil functions (i.e. soil enzyme activities, soil C and N processes). We employed high-throughput sequencing (Illumina MiSeq) to analyze bacterial/archaeal and fungal community composition by targeting the 16S rRNA gene and the ITS1 region of soils collected from three land uses (cropland, grassland and forest) deriving from two bedrock forms (silicate and limestone). Based on this data set we explored single and combined effects of edaphic variables on soil microbial community structure and diversity, as well as on soil enzyme activities and several soil C and N processes. We found that both bacterial/archaeal and fungal communities were shaped by the same edaphic factors, with most single edaphic variables and the combined soil environment representation exerting stronger effects on bacterial/archaeal communities than on fungal communities, as demonstrated by (partial) Mantel tests. We also found similar edaphic controls on the bacterial/archaeal/fungal richness and diversity. Soil C processes were only directly affected by the soil environment but not affected by microbial community composition. In contrast, soil N processes were significantly related to bacterial/archaeal community composition and bacterial/archaeal/fungal richness/diversity but not directly affected by the soil environment. This indicates direct control of the soil environment on soil C processes and indirect control of the soil environment on soil N processes by structuring the microbial communities. The study further highlights the importance of edaphic drivers and microbial communities (i.e. composition and diversity) on important soil C and N processes.",
"conclusion": "5 Conclusions We found that soil bacterial/archaeal and fungal communities were shaped by similar edaphic variables though slightly differing in strength. Not only single edaphic variables but also the combined multivariate representation of the soil environment strongly affected microbial community composition and diversity. Strong relations between bacterial/archaeal community composition and soil processes were also found, with lesser effects of fungal community composition likely due to low activity. Both bacterial/archaeal and fungal diversity showed strong relations with soil N processes but not with soil C processes. Soil enzyme patterns were not affected by the multivariate soil environment or by microbial community composition, but were shaped by microbial richness and diversity. Moreover, stronger effects of the soil environment on combined soil processes than on soil C processes or N processes individually when studied in multidimensional and multi-functional space were apparent. The limitation of our study is that the results of observational studies are correlative and potentially non-causative, but still we provide useful information on how microbial community composition and diversity relate to the soil environment and to soil multifunctionality under “real world” conditions. Combined manipulative and observational approaches are suggested in future studies of environment-microbial community structure-function interactions. In conclusion, this study adds to an integrated understanding of using microbial community structure (i.e. composition, richness and diversity) to improve predictions of multiple soil functions (i.e. enzyme patterns, C and N cycling), and confirms the significance of treating the soil environment as an integrity to predict soil multifunctionality.",
"introduction": "1 Introduction Soils harbor an enormous diversity of microorganisms, among which bacteria, archaea and fungi play pivotal roles for ecosystem functioning, such as regulating organic matter decomposition and soil C dynamics, and mediating nutrient cycling ( Bardgett et al., 2008 ; Singh et al., 2010 ; Wagg et al., 2014 ). As microbial habitats, the soil environment was reported to exert substantial impacts on microbial community structure and diversity ( Lauber et al., 2008 ; Rasche et al., 2011 ; Richter et al., 2018 ). A broad range of edaphic variables such as soil pH, texture, moisture, temperature, organic C and nutrient content were recognized to influence the composition and diversity of soil microbial communities ( Brockett et al., 2012 ; Cookson et al., 2007 ; Rousk et al., 2010a ). At the global scale, soil pH is regarded as the key predictor of soil bacterial community composition and diversity ( Fierer and Jackson, 2006 ; Rousk et al., 2010a ; Zhalnina et al., 2015 ). Soil texture, particularly clay and silt content, is closely related to soil organic C (SOC) content and nutrient availability, and was shown as another key driver of microbial community composition and diversity ( Hansel et al., 2008 ; Kallenbach et al., 2016 ). Microbial community composition and diversity could also be affected by soil nutrient content ( Koyama et al., 2014 ; Pan et al., 2014 ); N and P addition for example were reported to increase bacterial to fungal phospholipid fatty acid ratios ( Dong et al., 2015 ) and change microbial diversity ( Leff et al., 2015 ; Ling et al., 2017 ). Beyond the recorded influence of the soil environment on microbial communities, there is a wealth of studies on edaphic and environmental effects on soil functions such as soil formation, organic matter decomposition and substrate use efficiency (e.g. Bonner et al., 2018 ; Borken and Matzner, 2009 ; Colman and Schimel, 2013 ; Davidson et al., 1998 ; Davidson and Janssens, 2006 ; Hu et al., 2018 ). For instance, temperature, soil moisture, substrate availability and nutrient limitations were suggested to affect soil C metabolism including microbial growth, respiration, C use efficiency and microbial biomass turnover ( Dijkstra et al., 2015 ; Hagerty et al., 2014 ; Manzoni et al., 2012 ; Schindlbacher et al., 2015 ; Takriti et al., 2018 ; Zheng et al., 2019 ). Soil organic nitrogen (N) transformations such as gross protein depolymerization, gross N mineralization and gross nitrification rates can be controlled by temperature, soil pH, resource or enzyme availability and substrate quality ( Booth et al., 2005 ; Cookson et al., 2007 ; Noll et al., 2019 ; Rustad et al., 2001 ; Wallenstein and Weintraub, 2008 ; Wanek et al., 2010 ). Soil functions can also be driven by soil microbial community composition and diversity ( Balser and Firestone, 2005 ; Bonner et al., 2018 ; Creamer et al., 2015 ; Don et al., 2017 ; Schimel and Schaeffer, 2012 ). Microbial growth and CUE were found to be influenced by bacterial versus fungal dominance ( Soares and Rousk, 2019 ). Soil ammonia-oxidizer populations such as bacterial and archaeal nitrifiers can promote gross nitrification rate ( Li et al., 2018 ; Prommer et al., 2014 ; Stieglmeier et al., 2014 ). Soil enzymes activities were found to be shaped by microbial communities ( Gallo et al., 2004 ; Schnecker et al., 2015 ; Waldrop et al., 2000 ). It is undoubtedly important to study links between microbial communities and single soil functions, which provide valuable information on microbial drivers of specific processes. Despite considerable research efforts made into examining how microbial community composition and diversity drives single soil functions, in recent years there is an emerging field of research began to investigate how microbial communities maintain ecosystem multifunctionality based on both observational and manipulative studies ( Bastida et al., 2016 ; Delgado-Baquerizo et al., 2017a , 2017b ; 2016 ; Wagg et al., 2014 ). These studies calculated multifunctionality indices and attempted to investigate how microbial community composition, richness or diversity drive such multifunctionality. Some also accounted for environmental factors ( Delgado-Baquerizo et al., 2016 ; Thakur et al., 2018 ), but most of them focused on dissecting the individual effects of single edaphic factors, and few of them have regarded edaphic factors as an integral construct to represent the multivariate soil environment, nor investigated combined effects of the soil environment on microbial community composition, diversity and C and N processes together. Moreover, most studies focused only on effects of bacterial communities and fewer considered effects of fungal or archaeal communities (alongside bacterial ones) on various soil processes, and thus the latter effects remain elusive, specifically across different soils and for multiple processes ( Graham et al., 2016 ). Hence few studies have investigated the soil environment, microbial community structure, richness and diversity, extracellular enzyme patterns and soil C and N processes cohesively. This represents a major knowledge gap given that soils are complex systems that encompass a wide variety of abiotic and biotic characteristics, which means that no single soil parameter can explain single or multiple soil processes alone. It is therefore important not only to assess the influence of single edaphic factors but also of the combined effects of multiple factors on multiple processes to allow firm conclusions on the environment-microbial community-function coupling. This is particularly important as soils only provide their ecosystem services based on their multifunctional integrity ( Delgado-Baquerizo et al., 2016 ; Wagg et al., 2014 ). The objectives of this study were to test the effects of multiple edaphic drivers, microbial community composition and diversity on soil multiple functions (i.e. soil enzyme activities, soil C and N processes). Towards this end, we examined bacterial/archaeal and fungal community composition using DNA-based sequencing methods (Illumina MiSeq) and linked them to a series of edaphic variables, as well as a wide range of soil processes and soil enzyme activities. We studied individual effects of single edaphic factors on microbial community composition, soil process rates and extracellular enzyme activities, and also investigated the combined effects of soil parameters on soil multiple processes as matrices by Mantel tests, which provides a more comprehensive understanding of using environmental and microbial data to predict the multiple functions of soil ecosystems. Soils from three land uses (cropland, grassland and forest) deriving from two bedrock forms (silicate and limestone) were collected to test for the generality of the patterns.",
"discussion": "4 Discussion 4.1 Edaphic factors shape microbial community composition and diversity in soils differing in land use and bedrock The heterogeneous nature of the soil (micro) environment is thought to maintain highly diverse microbial communities ( Fierer, 2017 ). Here, we explored the relationship between a range of edaphic variables and microbial community composition and diversity across three different land uses and two bedrocks. When considering single edaphic factors, most physicochemical properties (e.g., soil reaction, nutrients and texture; but not SOC and TP) showed a stronger effect on bacterial/archaeal community composition than on that of fungi. One possible explanation might be that bacteria/archaea are fostered to better adapted to local edaphic conditions than fungi due to their different growth strategies, as fungi may access more soil volume due to their hyphal growth and thereby get access to more substrates and nutrients than bacteria/archaea. However, in native soil environments, edaphic variables co-vary and likely interact to regulate microbial community structure, diversity and function, since soil environments are defined by a combination of edaphic and climatic characteristics that microorganisms must adapt to in synchrony ( Schimel and Schaeffer, 2012 ). Treating the edaphic properties as a matrix allowed us to investigate their combined impact on microbial community composition. Here, with respect to the edaphic matrix, significant correlations with both bacterial/archaeal and fungal communities were observed, with slightly stronger responses of the bacterial/archaeal communities. The combined edaphic effects on both bacterial/archaeal and fungal communities were much stronger than the effects of single edaphic variables, illustrating for the first time on a matrix level that the combination between those edaphic factors strengthened the environmental influence on microbial community composition compared to the effect of individual factors. Among all edaphic variables, we found strongest Mantel correlations between bacterial/archaeal as well as fungal communities and soil pH and base saturation ( Table 2 ), both of which are strongly positively related to each other according to PCA (Fig. S3). Soil pH has been widely recognized as a key factor influencing microbial community composition ( Lauber et al., 2008 ; Rousk et al., 2010a , 2010b ). Among the most abundant bacterial phyla, Acidobacteria and Actinobacteria exhibited a strong, inverse responses to soil pH ( Table S4 ), corroborating the fact that members of Acidobacteria (e.g. Subdivision 1 and 3) tend to become more prominent at mildly acidic pH ( Eichorst et al., 2007 ; Foesel et al., 2014 ; Jones et al., 2009 ; Sait et al., 2006 ). Actinobacteria were reported to thrive in soils with neutral pH and to grow best between pH 6 to 9 ( Barka et al., 2016 ), as supported by the observed strong positive correlation between Actinobacteria and soil pH in this study. Soil pH was found to exert different or even contrasting effects on bacterial and fungal communities, i.e. low soil pH was found to decrease bacterial growth while to increase fungal growth ( Rousk et al., 2009 ), which could potentially alter the microbial community structure by favoring low-pH adapted or acidophilic microorganisms. Here, we found that both bacterial/archaeal and fungal communities were affected by soil pH, but the bacterial/archaeal community was more strongly influenced by pH than that of fungi, which might be due to relatively narrow optimal pH ranges for bacterial growth but wide pH ranges for fungal growth ( Rousk et al., 2010a ). Despite the direct influence of soil pH on microbial community structure, soil pH can also shape microbial communities indirectly by other co-varying factors such as nutrient availability and organic C content ( Rousk et al., 2010a ). Additionally, base saturation, representing the percent of the cation-exchange sites occupied by basic cations such as Ca 2+ , Mg 2+ , Na + , and K + , was significantly correlated with both bacterial/archaeal and fungal communities, indicating that base saturation is a global variable that co-explains microbial community dissimilarity. Cations such as manganese (Mn) was found to shape microbial community composition independent of pH ( Whalen et al., 2018 ). The significant impact of base saturation on microbial community composition, however, is most likely explained by the co-variance of soil pH and base saturation in this study, indicating that soils with higher base saturation typically have higher soil pH and generally are more fertile. Moreover, low soil pH might lead to the higher solubility of SOM and altered composition of dissolved organic matter in soils ( Curtin et al., 2016 ), which could trigger changes in energy and nutrient availability for microorganisms and thereby affect microbial abundance and composition. Consistent with previous work ( Li et al., 2012 ; Xu et al., 2015 ), we also found a significant correlation between DOC and bacterial/archaeal community composition, which was mainly explained by the positive correlation between DOC and Acidobacteria . The reported negative responses of Acidobacteria to increased available organic C suggested that members of this phylum are oligotrophic bacteria ( Fierer et al., 2007 ); however, our results suggest that not necessarily all Acidobacteria are oligotrophs, corroborating the fact that some of the Acidobacteria isolates could grow in higher C concentrations ( Kielak et al., 2016 ; Navarrete et al., 2015 ). As indispensable energy and nutrient source for microorganisms, soil organic matter content (as represented by SOC or by soil TN) was reported to play an important role in shaping microbial communities ( Burns et al., 2016 ; Drenovsky et al., 2004 ). For instance, organic C and N amendment experiments revealed significant changes in microbial PLFA composition and in fungal: bacterial ratios ( Drenovsky et al., 2004 ; Ng et al., 2014 ; Zhou et al., 2017 ). The relative abundances of Actinobacteria were reported to increase with soil C and N pool size ( Li et al., 2014 ), in accordance with our finding that Actinobacteria showed positive correlations with SOC and TN. Another dominant microbial phylum, Firmicutes (copiotrophic), was found to be negatively associated with SOC. This contradicts the typically observed positive relationship of Firmicutes with soil C content ( Ling et al., 2017 ; Tsiknia et al., 2014 ), which may be due to differences in the quality and accessibility of SOC (not specifically measured in this study). If there was less biodegradable or bioaccessible SOC, more SOC will not necessarily lead to a greater abundance of copiotrophic microbial communities including Firmicutes . The Deltaproteobacteria and Acidobacteria were also strongly correlated with TN, corroborating with previous research ( Ling et al., 2017 ; Zhang et al., 2013 ). There is no general agreement of the effects of phosphorus (P) - another crucial nutrient - on microbial community composition, as negative, neutral or positive effects of P were found on soil microbes in terrestrial ecosystems ( DeForest et al., 2012 ; Huang et al., 2016 ; Liu et al., 2012 ). In this study, TP was found to be the most crucial edaphic factor in explaining dissimilarities in fungal communities (NMDS), in line with the reported important role of P in structuring soil fungal communities in P addition experiments ( He et al., 2016 ). TP is typically less in forests than in managed ecosystems due to fertilization. We found higher abundances of Eurotiomycetes and Agaricomycetes in forest soils as compared to cropland and grassland soils (both P < 0.05), which was due to negative correlations between TP and the relative abundance of these two fungal classes. Based on SIMPER analysis ( Table S3B ), Eurotiomycetes and Agaricomycetes accounted for 48.1% of the overall dissimilarity between forest soils and cropland soils, and explained 52.2% dissimilarity between forest soils and grassland soils. Therefore, TP might be an important driver in structuring soil fungal communities across land uses, though the exact mechanism currently remains elusive. Despite the influence of land use and bedrock on microbial community composition, we also observed strong effects of bedrock on microbial richness and effects of land use on microbial diversity, which were likely due to the influence of bedrock and land use on soil pH and base saturation ( Table 1 ). Soil pH has a strong impact on microbial diversity across different spatial scales and soil types ( Lauber et al., 2009 ; Rousk et al., 2010b ; Zhalnina et al., 2015 ), corroborating our results that pH was positively correlated with both bacterial/archaeal and fungal diversity ( Table S6B ). The strong positive correlation between base saturation and microbial diversity is likely due to the strong association between base saturation and soil pH (Fig. S3). The impact of C, N and P on microbial diversity was not consistent in previous observational and experimental studies ( Leff et al., 2015 ; Li et al., 2012 ; Ling et al., 2017 ; Lopez-Fernandez et al., 2018 ). Microbial diversity was negatively associated with DOC content here, in line with the previous results obtained at laboratory and field scales ( Li et al., 2012 ), although positive correlations between DOC and microbial diversity were also reported previously ( Lopez-Fernandez et al., 2018 ). A possible explanation might be grounded in the effect of DOC on microbial community composition. For example, the observed positive correlations between DOC content and the dominant bacterial phylum Acidobacteria and fungal class Eurotiomycetes ( Table S4 ) might lead to less competitiveness and less influence by other bacteria, archaea and fungi in the studied soils, and thus may result in negative correlations between microbial diversity and DOC content. There were no significant relationships between microbial diversity and soil N and P content in this study, which were different from previous research that showed negative correlations between microbial diversity and N and P content ( Leff et al., 2015 ; Ling et al., 2017 ). Inconsistent with previous studies ( Lynn et al., 2017 ; Ma et al., 2016 ), we did not find a significant association between microbial diversity and clay content and CEC. Therefore the significant combined effect of the edaphic matrix on microbial diversity demonstrated by Mantel tests ( Table S6A ) is likely induced by the effect of individual edaphic parameters including soil pH, base saturation and DOC content on microbial diversity. 4.2 The influence of edaphic variables, microbial community composition and diversity on soil C and N processes The soil environmental variables are generally regarded as good predictors of soil C and N process rates ( Graham et al., 2016 ). For example, soil pH is often positively linked with substrate and nutrient availability ( Mccauley et al., 2017 ) and is expected to affect soil microbial C and N processes. In this study, we found that soil microbial C and N processes were significantly correlated with individual edaphic variables ( Table S7 ). For instance, we observed a strong negative correlation between soil pH and qGrowth, likely due to the negative influence of pH on DOC concentrations (Pearson R = −0.73, P < 0.001). DOC represents a major labile C and energy source for microbes and was found to positively affect qGrowth in soils ( Zheng et al., 2019 ). It is likely that the strong effects of soil pH, base saturation, CEC and DOC on qGrowth ultimately led to a substantial correlation between the edaphic matrix and the soil C process matrix ( Fig. 3 ). Single edaphic variables also exhibited strong connections to some of the soil N processes or extracellular enzyme activities, e.g. SOC and TN content showed negative connections with gross protein depolymerization and gross mineralization, and TP, pH and base saturation were all negatively associated with qPhenoloxidase and qPhosphatase activities. However, when considered as a matrix, edaphic properties showed no significant effect on the soil N process matrix or extracellular enzyme patterns, indicating no or very weak influences of the combined edaphic properties on soil N processes and soil enzyme patterns. When incorporating all measured soil C and N processes into one soil process matrix ( Fig. 3 ), the connection of the edaphic matrix to this merged soil process matrix became stronger (R = 0.36, P < 0.05) than the connection of the edaphic matrix to the soil C process matrix (R = 0.30, P < 0.05) or to the soil N process matrix (R = 0.23, P > 0.05) individually. This demonstrates that the influence of edaphic properties on soil processes strengthened when more processes were incorporated into the soil process matrix, i.e. the more multifunctional the consideration of soil processes became. This again illustrates the importance of investigating the effects of multiple edaphic factors on multiple soil functions instead of only studying the relation between single soil parameters and single soil processes. Microbial community composition has been variably demonstrated to affect microbial processes ( Becker et al., 2017 ; de Menezes et al., 2017 ; Graham et al., 2016 ). Here partial Mantel tests showed that bacterial/archaeal community composition was significantly affecting single soil C or N processes, i.e. microbial growth, microbial NUE, gross protein depolymerization and gross N mineralization rates ( Table S5 ), corroborating findings of previous studies on soil respiration, net N mineralization and denitrification ( Colman and Schimel, 2013 ; Li et al., 2015 ; Zhou et al., 2011 ). In terms of the dominant archaeal phylum Thaumarchaeota, members of which were found to oxidize ammonia aerobically and contribute to the soil nitrification process ( Brochier-Armanet et al., 2012 ; Pester et al., 2011 ), showed no correlation with nitrification rates in this study. This unambiguously demonstrates the influences of bacterial/archaeal community composition on specific soil processes. Although the bacterial/archaeal community composition was not significantly correlated with the soil C process matrix, its significant correlation with qGrowth highlights that some carbon transformation processes are inherently linked to bacterial/archaeal community composition. Here microbial respiration (as represented by qCO 2 ) was not correlated with microbial community composition ( Table S5 ), in accordance with other short-term studies ( Barnard et al., 2015 ; Leff et al., 2012 ; Placella et al., 2012 ). Only few studies recorded a relationship between microbial respiration and specific bacterial lineages ( Che et al., 2016 ; Fierer et al., 2007 ; Orr et al., 2015 ), but the results were not consistent across studies. Here, no significant correlations between microbial respiration and specific bacterial/archaeal or fungal lineages were detected ( Table S8 ). Almost no studies tested the relationships between microbial respiration and archaeal or fungal lineages ( Che et al., 2016 ), and we did not find substantial correlations between microbial respiration and archaeal or fungal lineages in this study. Additionally, bacterial/archaeal community composition exhibited a strong regulatory effect on soil N processes (matrix-level) likely due to its significant correlations with single soil N processes ( Table S5 ). Similarly, fungal community composition showed no direct influence on combined C or N process matrices possibly due to its weak influences at the single process levels. The reason for this was possibly the low activity of the fungal community, which was not specifically measured in this study, compared to the bacterial/archaeal community across the studied soils. The observed significant correlation between gross N mineralization and bacterial community composition was likely due to the strong correlations between gross N mineralization rate and two dominant bacterial lineages, i.e. Acidobacteria and Deltaproteo-bacteria. Likewise, no significant association between fungal community composition and gross N mineralization rate was found since most abundant fungal classes were not correlated with this process here. Although not all of the single processes were associated with bacterial/archaeal community composition, we still found a strong control of the bacterial/archaeal community composition on soil C and N processes, almost rivaling the direct edaphic effects on merged soil processes. This again highlights that edaphic and microbial controls on soil processes strengthen when considering soil processes in a multifunctional context and edaphic variables not in an isolated but combined form. Despite the significance of microbial community composition in regulating multiple soil processes, soil microbial diversity also plays a pivotal role in maintaining ecosystem multifunctionality ( Delgado-Baquerizo et al., 2017b , 2016 ; Wagg et al., 2014 ), corroborating the strong correlations between bacterial/archaeal/fungal richness/diversity and the soil process matrix observed here ( Table S6A ). Interestingly, no effects of microbial richness or diversity on the soil C process matrix or on microbial respiration or CUE were detected, in accordance with previous field study that showed no relation between basal respiration with bacterial richness ( Delgado-Baquerizo et al., 2017b ). However, a strong correlation between fungal richness and qGrowth was observed, illustrating that microbial richness may play a role in influencing microbial growth. In contrast, we found strong associations between microbial richness/diversity and the soil N process matrix ( Table S6A ), likely induced by strong effects of microbial richness/diversity on gross protein depolymerization ( Table S6B ), which has been rarely reported previously. In general, compared to bacterial/archaeal richness and diversity, fungal richness and diversity seemed to play stronger roles in regulating soil N processes as demonstrated by partial Mantel results. Except for direct influences, microbial communities could also affect soil processes by regulating extracellular enzyme levels. Extracellular enzymes are essential for organic matter decomposition and are primarily produced by fungi and bacteria in soils. Fungi are generally considered to process recalcitrant C and N-poor substrates while bacteria are thought to be more responsive to labile substrates ( Treseder et al., 2016 ; Xu et al., 2015 ). Moreover, fungi are thought to possess a greater capacity to produce extracellular enzymes for decomposition of complex plant organic matter than bacteria, and intermediate decomposition products by fungi can provide labile resources for bacteria ( Romaní et al., 2006 ). In this study, soil enzyme patterns were not significantly correlated with either the bacterial/archaeal or the fungal communities, in contrast to previous studies showing that microbial community composition shaped enzyme patterns ( Gallo et al., 2004 ; Schnecker et al., 2015 ; Waldrop et al., 2000 ). A possible explanation for our finding is that here we only included four extracellular enzymes involved in the decomposition of soil organic C, N and P into the matrix. It is therefore possible that having data on more divergent extracellular enzymes may lead to a stronger impact of bacteria/archaea and fungi on enzyme patterns. Nevertheless, we still found significant correlations of qPhenoloxidase and qPhosphatase with bacterial/archaeal community composition, as well as a substantial effect of fungal community composition on qPhosphatase, in accordance with the reported influence of microbial community composition on soil enzyme activities ( Talbot et al., 2013 ; Waldrop and Firestone, 2006 ). We also observed substantial associations between microbial richness/diversity and soil enzyme patterns and single soil enzyme activities ( Tables S6A and B ), in line with findings from previous soil multifunctionality studies ( Delgado-Baquerizo et al., 2017b , 2017a ). Additionally, soil enzyme activities are influenced by environmental factors such as soil pH, soil texture, and substrate and nutrient availability ( Acosta-Martínez et al., 2007 ; Turner, 2010 ). We also found strong correlations between edaphic factors (e.g. soil pH, base saturation, TP, DOC) and some of the extracellular enzyme activities as well as soil enzyme patterns; however, no significant correlation was found between the edaphic matrix and soil enzyme patterns. This finally indicates that the interactions between edaphic variables could possibly offset their overall effects on enzyme activities compared to the effects of individual edaphic variables."
} | 7,997 |
30524394 | PMC6262304 | pmc | 8,955 | {
"abstract": "The rumen microbial complex adaptive mechanism invalidates various methane (CH 4 ) mitigation strategies. Shifting the hydrogen flow toward alternative electron acceptors, such as propionate, was considered to be a meaningful mitigation strategy. A completely randomized design was applied in in vitro incubation to investigate the effects of replacing forage fiber with non-forage fiber sources (NFFS) in diets on methanogenesis, hydrogen metabolism, propionate production and the methanogenic and bacterial community. There are two treatments in the current study, CON (a basic total mixed ration) and TRT (a modified total mixed ration). The dietary treatments were achieved by partly replacing forage fiber with NFFS (wheat bran and soybean hull) to decrease forage neutral detergent fiber (fNDF) content from 24.0 to 15.8%, with the composition and inclusion rate of other dietary ingredients remaining the same in total mixed rations. The concentrations of CH 4 , hydrogen (H 2 ) and volatile fatty acids were determined using a gas chromatograph. The archaeal and bacterial 16S rRNA genes were sequenced by Miseq high-throughput sequencing and used to reveal the relative abundance of methanogenic and bacterial communities. The results revealed that the concentration of propionate was significantly increased, while the concentration of acetate and the acetate to propionate ratio were not affected by treatments. Compared with CON, the production of H 2 increased by 8.45% and the production of CH 4 decreased by 14.06%. The relative abundance of Methanomassiliicoccus was significantly increased, but the relative abundance of Methanobrevibacter tended to decrease in TRT group. At the bacterial phylum level, the TRT group significantly decreased the relative abundance of Firmicutes and tended to increase the relative abundance of Bacteroidetes . The replacement of forage fiber with NFFS in diets can affect methanogenesis by shifting the hydrogen flow toward propionate, and part is directed to H 2 \n in vitro . The shift was achieved by a substitution of Firmicutes by Bacteroidetes , another substitution of Methanobrevibacter by Methanomassiliicoccus . Theoretical predictions of displacements of H 2 metabolism from methanogenesis to propionate production was supported by the dietary intervention in vitro .",
"conclusion": "Conclusion Theoretical predictions of displacements of H 2 metabolism from methanogenesis to propionate production was supported by the dietary intervention in vitro . A modified dietary formulation strategy can affect methanogenesis by shifting the hydrogen flow toward propionate and partially toward to H 2 . The shift was achieved by a substitution of Firmicutes by Bacteroidetes and another substitution of Methanobrevibacter by Methanomassiliicoccus . In conclusion, the replacement of forage fiber with NFFS in diets may be a meaningful strategy to shift the hydrogen flow toward propionate and further studies need to be conducted to explore if the same microbiota modulation would be observed in vivo .",
"introduction": "Introduction Microorganisms in the rumen can ferment feeds rich in cellulose and can convert plant materials that people can’t utilize directly into meat and milk products. At the same time, the process of hydrolyzing complex compounds is accompanied by the formation of gasses, such as hydrogen (H 2 ) and carbon dioxide (CO 2 ). To keep the fermentation continuing, methanogenic archaea in the rumen produce methane (CH 4 ) by using H 2 and CO 2 to scavenge H 2 and keep the partial pressure of H 2 low ( Moss et al., 2000 ). Methanogenesis from ruminants can result in a significant loss of feed efficiency (2–12%), depending upon the types of diets ( Johnson and Johnson, 1995 ). To mitigate the negative impact on climate change and to improve feed efficiency, various mitigation strategies have been conducted to reduce CH 4 emissions from ruminants, including using essential oils ( Patra and Yu, 2012 ), plant extracts ( Wang et al., 2016 ), ionophores ( Weimer et al., 2008 ), and vaccines ( Williams et al., 2009 ). However, the rumen ecosystem is exceedingly complex and the ability of this system to efficiently convert complex carbohydrates to volatile fatty acids (VFA) is in part due to the effective disposal of H 2 by reducing CO 2 to produce CH 4 . Methanogenesis can be inhibited for short periods, but the ecology of the system is such that it frequently reverts back to the initial levels of methane production through all various adaptive mechanisms ( McAllister and Newbold, 2008 ). On the other hand, the problem with chemical residues, toxicity, and high costs, have greatly limited these strategies utilization in animal production. The type of feed offered to ruminants has a major effect on the profile of VFA and the level of methane production. Kessel and Russell (1996) reported that methane production was completely inhibited at a pH less than 6.0 when feeding a high-concentrate diet. However, when microorganisms in the rumen are exposed to large amounts of fermentable substrates for short periods, the rate of VFA production will exceed the VFA utilization, resulting in subacute ruminal acidosis or acute ruminal acidosis, which has negative impacts on animal health and performance ( Nagaraja and Titgemeyer, 2007 ; Sato, 2015 ). Non-forage fiber sources (NFFS) from high-fiber byproducts usually have limited utility in non-ruminant diets, but ruminant nutritionists can use them to partially replace both forages and concentrates in lactation diets ( Allen and Grant, 2000 ; Stock et al., 2000 ). Although they have different production responses ( Huhtanen, 1993 ; Huhtanen et al., 1995 ; Alamouti et al., 2009 ), NFFS-based diets can maintain or improve the performance of dairy cattle under certain conditions ( Pereira et al., 1999 ; Ertl et al., 2015 ). The strategy of primarily replacing some forage fiber with NFFS for higher-producing cows but only partially replacing some starch for lower-producing cows can optimize nutrient utilization and potentially control feed costs without compromising animal health or productivity ( Bradford and Mullins, 2012 ). Moreover, Pereira and Armentano (2000) reported that low-forage, medium-neutral detergent fiber (NDF) (12.6% forage NDF, 27.5% total NDF) diets and low-forage, high-NDF diets (12.7% forage NDF, 35.7% total NDF) had a lower acetate to propionate ratio and a higher proportion of propionate than the traditional diet (20.1% forage NDF, 25.2% total NDF). The formation of acetate and butyrate results in production of H 2 which can be used to generate CH 4 by methanogenic archaea ( Moss et al., 2000 ). Propionate is an end-product of rumen fermentation that is probably the principal alternative of the H + sink after CH 4 , and the acetate to propionate ratio in the rumen has a relationship with methanogenesis ( Lana et al., 1998 ; Russell, 1998 ). The balance between propionate formation and acetate and butyrate formation has a key role in determining H 2 available in rumen for utilization by methanogenic archaea. Janssen (2010) reported that increases in propionate formation are strongly associated with decreases in CH 4 production. In a meta-analysis, Ungerfeld (2015) found that inhibiting CH 4 production in batch cultures resulted in redirection of metabolic hydrogen toward propionate and H 2 , but not butyrate. In addition, propionate is predominantly used as a glucose precursor in ruminants, and more propionate formation would likely result in a more efficient utilization of feed energy. Maximizing the flow of metabolic hydrogen in the rumen away from CH 4 and toward VFA (mainly propionate) would increase the efficiency of ruminant production and decrease its environmental impact ( Ungerfeld, 2015 ). Therefore, modifying the dietary formulation with NFFS may be an effective measure to shift the hydrogen flow toward alternative electron acceptors such as propionate. The objective of this study was to build a model of metabolic hydrogen shifts in vitro to explore the effects of replacing forage fiber with NFFS in diets on methanogenesis, hydrogen metabolism, propionate production and the methanogenic and bacterial community by high-throughput sequencing.",
"discussion": "Discussion Non-forage fiber sources are generated by several industries, which are high in fiber (like forages) but are rapidly passed from the rumen (like concentrates). The judicious use of NFFS can improve the productivity and health of cattle in all stages of lactation while potentially controlling feed costs ( Bradford and Mullins, 2012 ). Most non-forage fiber is relatively digestible compared with forge fiber, resulting in higher digestibility ( Bhatti and Firkins, 1995 ; Dann et al., 2007 ). In our study, the replacement of forage fiber with NFSS significantly increased DMD, NDFD, and ADFD, but numerically increased the concentration of TVFA. On the contrary, total gas production was numerically decreased, unlike the concentration of TVFA. This may be explained by the fact that non-forage fiber is more digestible, but not better in fermentation than alfalfa fiber, which usually was considered to be the best forage fiber. The production of CH 4 decreased by 14.06%, and H 2 production was numerically increased by 8.45%, followed by significant increases in the concentration of propionate. The formation of acetate and butyrate results in production of H 2 which can be used to generate CH 4 by methanogenic archaea ( Moss et al., 2000 ). In propionate formation, pyruvate is reduced to propionate, while in H 2 formation, protons (H + ) are reduced to H 2 . The two pathways are both electron accepting, so Janssen (2010) thought that propionate formation was an alternative pathway to H 2 formation and was accompanied by decreasing in CH 4 production. The balance between propionate formation and acetate and butyrate formation has a key role in determining H 2 available in rumen for utilization by methanogenic archaea. These results indicated that the replacement of forage fiber with NFFS may reduce the utilization of hydrogen in methanogenesis and shift hydrogen flow from CH 4 to propionate and H 2 by changing the relative abundance of certain archaea or bacteria. Similar to previous studies, inhibition of CH 4 production in batch cultures resulted in the redirection of metabolic hydrogen toward propionate and H 2 ( Ungerfeld, 2015 ). Mitsumori et al. (2012) found that some [H] spared from CH 4 production is redirected to propionate, and part is directed to atypical [H] sinks like H 2 . As the sole producers of methane in the rumen, a correlation between the number of methanogens and methanogenesis might be expected. Wallace et al. (2014) and Veneman et al. (2015) suggested that the number of archaea, rather than the population structure, might be the major driver of methane production in the rumen. Some strategies, including supplementation of essential oils ( Duarte et al., 2017b ) or ionophores ( Shen et al., 2017 ), reduce enteric methane emissions by inhibiting the activity or richness of the microbiota. Inhibition of the microbiota generally results in decreasing feed digestion ( Ungerfeld, 2015 ). However, Morgavi et al. (2010) reported that decreasing methane production did not affected fiber digestibility in several in vitro experiments. Shen et al. (2017) found that supplementation of nisin in diets decreased methane production, while feed digestion was unaffected. This may be explained by shifts in the microbial population. Various methanogen groups have different methanogenic potential ( Leahy et al., 2013 ) and a shift in the methanogen community toward less effective methanogenesis might also explain the differences in methane production. We observed decreased methane production and increased propionate concentration, while dry matter disappearance was increased in the present study. It is possible that changes in the population structure of the microbiota can also affect the methane production, like the inhibition of microbial richness or activity. Belanche et al. (2016) found that ivy fruit saponins reduced the methane production by modifying the structure of the methanogen community and decreasing its diversity. In contrast, chitosan promoted a shift in the fermentation pattern toward propionate production to reduce the methane production, which is achieved by a simplification of the structure in the bacterial community. Therefore, both the richness of the methanogen and the population structure of the microbial community plays an important role in methanogenesis. On the other hand, the richness and diversity of the archaeal and bacterial community were not affected by treatments, together with a similar pH value and TVFA production, also suggesting that the replacement of forage fiber with NFFS in the diets didn’t have significant detrimental effects on the overall rumen fermentation in vitro . Archaea Methane is produced in the rumen as a product of normal fermentation of the feedstuffs, and methanogens, which belong to the domain Archaea and the phylum Euryarchaeota are the only known microorganisms capable of methane production ( Hook et al., 2010 ). However, compared to the number of methanogens, the efficiency of different methanogens is considered to be more important in methanogenesis ( Shi et al., 2014 ). Given that the positive relationship of increased methane production and increased transcripts of mcrA gene, methanogens that can express more mcrA genes are believed to contribute more to methane production ( Freitag and Prosser, 2009 ). In our study, differences between treatments were observed at the genus level, where the relative abundance of Methanomassiliicoccus (belongs to Methanomassiliicoccaceae family) was significantly increased, but the relative abundance of Methanobrevibacter tended to decrease in the TRT group. Danielsson et al. (2017) reported that unclassified Methanomassiliicoccaceae was 1.5-fold more abundant in low CH 4 emitters than that in high CH 4 emitters. Luo et al. (2017) reported that dietary pea fiber increased the diversity of the colonic methanogen community structure of pigs with a shift from Methanobrevibacter to Methanomassiliicoccus and Methanomassiliicoccus -like genus. Hydrogenotrophic pathway, methylotrophic pathway and acetoclastic pathway are the three major pathways of methanogenesis. Methanobrevibacter is one kind of hydrogenotrophic methanogen, that converts H 2 and/or formate to CH 4 ( Leahy et al., 2013 ), while Methanomassiliicoccus , which belong to the novel order Methanomassiliicoccales , has capacity to use methylamine substrates for methanogenesis by H 2 -dependent methylotrophic pathway ( Lang et al., 2015 ; Moissl-Eichinger et al., 2018 ). Although methanogenic archaea can acquire substrates form environment, some species would increase efficiency by forming contacts with protozoa, which produce large quantities of H 2 by their hydrogenosomes ( Embley et al., 2003 ). Methanobrevibacter is considered to be the predominant protozoa-associated methanogens ( Belanche et al., 2014 ), while the relation between Methanomassiliicoccus and protozoa has not been reported. Compared with Methanobrevibacter , Methanomassiliicoccus may be less effective in methane production. Different sources of fiber may stimulate the growth of different microbiota and change the relative abundance of the microbial community. Replacement of forage fiber with NFFS in diets would mitigate CH 4 emission from ruminants by changing the relative abundance of Methanobrevibacter and Methanomassiliicoccus at the archaea level. Methanomassiliicoccus is more abundant in our study than Methanobrevibacter , which was believed to be the most predominant genus in a previous study ( Janssen and Kirs, 2008 ). In another recent study ( Danielsson et al., 2017 ), Methanobrevibacter was also observed as the most predominant genus. Danielsson et al. (2017) used the same primers of both bacteria and archaea to construct 16S rRNA amplicon libraries, resulting in an average of 505 archaeal sequences per sample (61434 archaeal sequences per sample in our study). Different sequencing depths may be responsible for the difference between our study and others. Similar to our study, Paul et al. (2015) also reported a high abundance of Methanomassiliicoccaceae present in the rumen of Nili-Ravi buffalo by 16S rDNA analysis of archaea. Bacteria In the present study, the rumen microbiota was dominated by Bacteroidetes and Firmicutes , which are considered to be the predominant phyla in most studies ( Kim et al., 2010 ; de Menezes et al., 2011 ; Martinez-Fernandez et al., 2016 ; Duarte et al., 2017a ). The Bacteroidetes are considered net H 2 utilizers whereas the Firmicutes phylum includes H 2 producers ( Stewart et al., 1997 ). Belanche et al. (2016) reported that supplementing chitosan in the control diet promoted a shift in the fermentation pattern toward propionate production, which explained about a third of the decrease in methanogenesis, which was achieved by the substitution of fibrolytic ( Firmicutes and Fibrobacteres ) by amylolytic bacteria ( Bacteroidetes and Proteobacteria ). In another study, a shift in the microbiota with an increase in the Bacteroidetes to Firmicutes ratio was accompanied by a 30% decrease in methanogenesis and increase in propionate production, using chloroform as a methane inhibitor ( Martinez-Fernandez et al., 2016 ). Kittelmann et al. (2013) observed a positive correlation between the occurrence of methanogens and fibrolytic bacteria. In the present study, the TRT group had a higher abundance of Bacteroidetes (mainly amylolytic bacteria) and a lower abundance of Firmicutes (mainly fibrolytic bacteria) compared with the CON group. This substitution of fibrolytic by amylolytic bacteria may result in the higher concentration of propionate as fermentation products in the TRT group. At the genus levels, all bacterial genera whose relative abundance changed ( P < 0.1) belonged to the Firmicutes phylum. Most of these genera have higher relative abundance in the CON group, except Marvinbryantia , Hydrogenoanaerobacterium , and Christensenella . Marvinbryantia belongs to the Lachnospiraceae family, which degrades complex polysaccharides to short chain fatty acids, including acetate, butyrate, and propionate ( Biddle et al., 2013 ). Hydrogenoanaerobacterium belong to the Ruminococcaceae family, which contains a large number of healthy gut-associated butyrate-producing bacteria ( Morissette et al., 2017 ). A recent study suggests that the presence of Christensenella in the gut, a low abundant (less than 0.001%) and highly heritable (transmissible from parent to offspring) bacterial genus, decreases body weight gain in obese mice ( Goodrich et al., 2014 ). There are few references about these genera and whether they participate in the metabolism of propionate is unknown. However, as described above, these genera are all involved in energy metabolism and maybe have certain relationships with shifting hydrogen flow toward propionate."
} | 4,825 |
32888315 | null | s2 | 8,956 | {
"abstract": "Artificial selection is a promising approach to manipulate microbial communities. Here, we report the outcome of two artificial selection experiments at the microbial community level. Both used \"propagule\" selection strategies, whereby the best-performing communities are used as the inocula to form a new generation of communities. Both experiments were contrasted to a random selection control. The first experiment used a defined set of strains as the starting inoculum, and the function under selection was the amylolytic activity of the consortia. The second experiment used multiple soil communities as the starting inocula, and the function under selection was the communities' cross-feeding potential. In both experiments, the selected communities reached a higher mean function than the control. In the first experiment, this was caused by a decline in function of the control, rather than an improvement of the selected line. In the second experiment, this response was fueled by the large initial variance in function across communities, and stopped when the top-performing community \"fixed\" in the metacommunity. Our results are in agreement with basic expectations from breeding theory, pointing to some of the limitations of community-level selection experiments that can inform the design of future studies."
} | 330 |
36252042 | PMC9618036 | pmc | 8,957 | {
"abstract": "Significance Some species interactions, termed higher-order interactions, can only emerge when there are many species in an ecological community. These interactions are likely frequent in nature, although their role in shaping the coexistence of species is poorly explored. Here we incorporate higher-order interactions into a mathematical model of the dynamics of diverse communities and show that many of the rules governing the effects of pairwise interactions on coexistence extend to the higher-order case. Our theory requires only a small number of parameters to predict the number of species coexisting at equilibrium. As a result, empiricists can use our framework to generate expectations for how higher-order interactions influence species coexistence in nature.",
"discussion": "Discussion Through the analysis of models for two competing species, ecologists have derived simple rules for species coexistence (spelled out in the Introduction) ( 22 , 23 ). We know that these rules do not formally apply to systems with more than two species, including those with purely pairwise interactions ( 26 ). Nonetheless, our findings here suggest that these simple rules may strongly guide expectations for the interpretation of coexistence in large systems, even those organized by higher-order interactions, as long as the network of interactions has a random structure. Moreover, the cavity method can be used to develop theory for how higher-order interactions impact species coexistence in such systems. The central question of our study was how the strength and variability in higher-order interactions influence species coexistence (question 1 from the Introduction). We found that as higher-order interaction strengths become more variable between the species, fewer species coexisted. When interactions are heterogeneous and randomly assigned to species, species differ in their sensitivity to competition, and the poorest competitors get excluded. This behavior is directly analogous to results from pairwise interactions ( 27 – 31 ). The average strength of higher-order interactions, on the other hand, exhibited a more complex effect on coexistence. When species differed considerably in their intrinsic growth rates and interaction strengths had little variation, more harmful interspecific higher-order interactions generated less coexistence. This result follows from the two-species rule that more harmful interspecific interactions relative to intraspecific regulation are destabilizing ( 30 , 31 ). However, when the variation in higher-order interactions was large relative to the variation in intrinsic growth rates, we found the opposite dependence—more harmful higher-order interactions counterintuitively produced more coexistence. Even here, though, the two-species rules prove useful. Less harmful mean higher-order interactions introduced more mutualistic interactions, which even in two-species systems can cause abundances to grow without bound when they overwhelm self-regulation. The subset of species engaged in this mutualistic rise were the most abundant ( SI Appendix , section 3.D ) and greatly harmed species that happened to engage in harmful higher-order interactions with these species. When the strength of higher-order interactions instead saturated as a function of species abundance, more harmful higher-order interactions once again produced less coexistence because the likelihood of strong mutualistic interactions, and hence groups of highly dominant species, was reduced. While variation in higher-order interactions harmed coexistence regardless of whether or not these interactions saturated with species densities, the effect of the mean interaction strength depended strongly on the model form. As a result, increased variation in both pairwise and higher-order interactions reduced coexistence, but the strength of linear higher-order interactions had qualitatively new effects on coexistence relative to pairwise interactions, thereby answering question 2 in the Introduction. In principle, higher-order interactions likely saturate with species densities in natural communities ( 42 – 45 ), but it is unclear whether species abundances in nature lie in a regime where a linear functional response is a reasonable description of these saturating curves. It is worth noting that the higher-order interactions currently fit to data usually involve this linear assumption (mainly as a byproduct of very reasonable data limitations), and if it is valid, our theory suggests that more harmful higher-order interactions may favor coexistence ( 19 ). However, this linear description of higher-order interactions may not be a good one, in which case we suspect that the predicted dynamics from these fitted models would not be realistic ( 19 , 65 ). If indeed, better data supported higher-order interactions that saturate with species abundances or are tightly coupled to pairwise interaction strengths, more harmful higher-order interactions could favor fewer not more coexisting species. The possibility of empirical support for higher-order interactions constrained by the pairwise effects is interesting given that such constraints are central to previous theoretical work showing widespread coexistence resulting from higher-order interactions ( 17 , 66 ). All of this points to the fact that determining both the parameter values and the functional forms of higher-order interactions supported by empirical data is a crucial next step in this research area. Thus far, we have argued that higher-order interactions with specific functional forms and constraints can favor coexistence but that more generic, randomly sampled higher-order interactions have similar effects on coexistence as pairwise interactions. This latter message also holds when exploring how species richness affects opportunities for coexistence. Consistent with classic studies modeling pairwise interactions ( 27 – 29 ), we found a loss of coexistence with increasing diversity in our model, for both pairwise and higher-order interaction systems. Importantly, this effect arose from fewer species having positive equilibrium abundance rather than an increasingly unstable equilibrium with all species present. Previous theoretical studies have also found that feasibility is lost before stability in Lotka–Volterra models ( 33 , 63 , 64 ), and we have found the same behavior when incorporating higher-order interactions. Although these feasibility- and stability-based approaches differ quantitatively in their requirements for the coexistence of all species, they have identified the same qualitative relationship between interaction variability and species richness—namely, that communities tolerate less variability in pairwise interspecific interactions as they become more diverse ( 27 – 29 ). This makes the recent findings of Bairey et al. ( 34 ), showing that species diversity has no effect on the variability of three-way, higher-order interactions required to disrupt coexistence, particularly surprising. In contrast, not only did we find that the critical variability of both pairwise and higher-order interactions declines with species richness, this decrease was more severe with higher-order interactions. We believe the discrepancy lies in the different modeling frameworks. In the replicator equation used by Bairey et al. ( 34 ), all abundances must sum to one, and thus, higher-order interactions become weaker as the number of species increases because the products of relative abundances near zero quickly become very small. In the generalization of the Lotka–Volterra model we consider, every species has an abundance that is fixed by its intrinsic growth rate and its self-regulation. As a result, the variability in higher-order interactions and species richness affects opportunities for coexistence in the same qualitative way that pairwise interactions do, answering question 3 from the Introduction. Our results also suggest that the number of interactions in a community plays an important role in determining their effects on coexistence. When we removed the scalings which accounted for the larger number of higher-order than pairwise interactions, we found that higher-order interactions had a stronger impact on coexistence simply because there were more of them. This fact suggests that higher-order interactions involving more than three species should have even smaller critical variabilities than those we predicted for three-way higher-order interactions. On the other hand, if in nature the measured strength of higher-order interactions tends to decrease as a function of the number of species involved, then our theory that scales out the number of interactions may be a more accurate representation of real systems. In this case, it is less clear how the order of the interactions (i.e., the number of species they involve) will affect the critical variability because the clear effect of the number of possible interactions is muted. The relationship between the order of an interaction and its empirically derived strength is therefore an important outstanding question for both theoreticians deriving higher-order interactions from mechanistic underpinnings and empiricists tackling the problem in nature. We have focused here on three-way higher-order interactions, both to maintain analytical tractability and because interactions of larger orders are exceedingly difficult to measure empirically ( 19 ). A principal direction for future work is to understand which interaction orders ought to be included in phenomenological models and how the orders of these interactions impact macroecological properties. One important caveat of our cavity method results that they are only valid when species coexist at a stable equilibrium ( 67 ). Species may instead coexist in limit cycles ( 68 ) or exhibit chaotic dynamics ( 69 , 70 ), in which case it is no longer clear how the mean and variance of the interactions affect coexistence. In the parameter regimes we focused on, nonequilibrium dynamics were rare (but see Materials and Methods and SI Appendix , section 3.B for a complete discussion of where they can appear). Nevertheless, complex dynamics with widespread coexistence have been shown to emerge in diverse models with randomly sampled interactions when intraspecific competition is similar to interspecific competition ( 71 ) or in the regime with multiple equilibria when there is also external immigration ( 59 ). We did find multiple equilibria when higher-order interactions are saturating ( Materials and Methods and SI Appendix , section 3.B ), suggesting that nonequilibrium coexistence may appear in model communities with higher-order interactions of specific functional form. Our theory generates a null expectation for how higher-order interactions influence species coexistence assuming they are on average harmful (mutualistic, nonsaturating higher-order interactions simply cause abundances to explode), and there is no structure to the higher-order interaction network. Indeed, we have shown with the cavity method that when higher-order interactions are sampled at random, they do not generate ecosystems with perfect coexistence. However, ecological interactions in nature are likely to be nonrandom. If the network of higher-order interactions has some complex structure, then it may have a fundamentally different effect on coexistence than suggested here. For example, we assumed that higher-order interactions involving the square of abundances [the intraspecific higher-order interactions ( 19 )] follow the same distribution as all other higher-order interaction terms. If instead the intraspecific higher-order interactions are stronger than their interspecific counterparts, they might be broadly stabilizing ( 39 ). Similarly, higher-order interaction strength may be correlated with the underlying pairwise interactions in the system and thereby give rise to more or less coexisting species than predicted here. At this point, however, it is unclear how to impose additional constraints on the parameters of the model we consider without specifying a mechanism for the interactions in the ecosystem ( 72 , 73 ). Moreover, deviations from truly random interactions may not alter the qualitative conclusions we have focused on. If specific interaction structures were found to change our main conclusions, it is possible to incorporate these structures into the cavity method ( 37 , 61 ), allowing one to understand the mechanisms by which nonrandom interaction structures benefit or harm coexistence. In this context, a central challenge in this field is to derive phenomenological higher-order interaction parameters either from 1) nature or 2) an underlying mechanistic process in a model. Although both approaches could refine the conclusions we have derived based on randomly sampled interactions, an empirically determined interaction network can be used to interrogate specific patterns in the structure of the interactions. At the same time, the number of possible higher-order interactions grows quickly with the number of species and the order of the interactions themselves, making it very difficult to estimate all possible interactions experimentally and necessitating new empirical approaches to circumvent this challenge. This is where the cavity method may prove particularly useful in an empirical context. To predict coexistence with the cavity method, one only needs estimates of the mean and variability of the interactions ( 61 ). In other words, not every interaction needs to be measured. As a result, the cavity method provides a powerful framework for empiricists to compare the potential effects of higher-order interactions across different ecosystems. The theory can be used to generate a baseline level of coexistence expected from randomly assigned higher-order interactions, and thus, deviations from such predictions can be indicators of more complex ecological structure in nature."
} | 3,506 |
35157025 | PMC9004645 | pmc | 8,960 | {
"abstract": "Abstract Motivation Constraint-Based Reconstruction and Analysis (COBRA) is a widely used approach for the interrogation and stratification of microbiome samples, yet applications to large-scale cohorts are hampered by limited scalability and efficiency of simulations. Results We substantially improved the computation speed and scalability of a previous implementation for the construction and interrogation of personalized constraint-based microbiome models as well as implemented additional functionalities for analysis and visualization. Availability and implementation Microbiome Modelling Toolbox and tutorials are freely available as part of the COBRA Toolbox at https://git.io/microbiomeModelingToolbox .",
"introduction": "1 Introduction The Constraint-Based Reconstruction and Analysis (COBRA) approach is a mechanistic, bottom-up systems biology method that relies on manually curated genome-scale reconstructions of metabolism that can be converted into mathematical models ( Palsson, 2006 ). In recent years, COBRA has been used in >100 studies to interrogate the metabolism of microbial communities and microbiomes, yielding valuable insight into microbial community structure and function ( Heinken et al. , 2021 ). A notable application of COBRA modelling is the generation of personalized human microbiome models and their stratification based on their structure and function, which has been applied to, e.g., inflammatory bowel disease and colorectal cancer ( Heinken et al. , 2021 ). We have previously developed the Microbiome Modelling Toolbox, a MATLAB-based suite for the construction and interrogation of microbe–microbe and personalized microbiome models ( Baldini et al. , 2019 ). Here, we present an updated version, the Microbiome Modelling Toolbox 2.0. Compared with its predecessor, computation times have been greatly reduced by taking advantage of parallelization. Moreover, the toolbox has been expanded by additional functions for targeted analysis, statistical analysis and visualization.",
"discussion": "4 Discussion Recent cohort studies have generated an unpreceded amount of publicly available metagenomic sequencing data of human microbiomes varying, e.g., in health status, diet, and ethnicity. Yet, the interpretation of this wealth of data is lagging. The increasing availability of strain-resolved metagenomic data, as well as of curated genome-scale reconstructions, such as the AGORA resource of 773 reconstructed human gut microbes ( Magnusdottir et al. , 2017 ), and its expansion, AGORA2, now containing over 7,000 microbial reconstructions ( Heinken et al. , 2020 ), allow for the construction of personalized microbiome models with increasing coverage and hence, size. The Microbiome Modelling Toolbox 2.0, due to its improved scalability and efficiency, provides the computational tools for the large-scale interrogation of hundreds ( Hertel et al. , 2021 ) or even thousands of microbiomes. For instance, it enabled the comprehensive prediction of the fecal metabolome for 644 microbiome models of colorectal cancer patients and controls containing up to ∼150 species and ∼240,000 reactions ( Hertel et al. , 2021 ), as well as the construction of over 14,000 personalized microbiome models (A.Heinken et al. , in preparation). Personalized models generated by mgPipe can also be integrated with a whole-body model of human metabolism ( Thiele et al. , 2020 ), hence, enabling constraint-based modelling of human–microbiome interactions with unpreceded scope."
} | 870 |
29488286 | null | s2 | 8,961 | {
"abstract": "Atmospheric nitrogen (N) deposition has enhanced soil carbon (C) stocks in temperate forests. Most research has posited that these soil C gains are driven primarily by shifts in fungal community composition with elevated N leading to declines in lignin degrading Basidiomycetes. Recent research, however, suggests that plants and soil microbes are dynamically intertwined, whereby plants send C subsidies to rhizosphere microbes to enhance enzyme production and the mobilization of N. Thus, under elevated N, trees may reduce belowground C allocation leading to cascading impacts on the ability of microbes to degrade soil organic matter through a shift in microbial species and/or a change in plant-microbe interactions. The objective of this study was to determine the extent to which couplings among plant, fungal, and bacterial responses to N fertilization alter the activity of enzymes that are the primary agents of soil decomposition. We measured fungal and bacterial community composition, root-microbial interactions, and extracellular enzyme activity in the rhizosphere, bulk, and organic horizon of soils sampled from a long-term (>25 years), whole-watershed, N fertilization experiment at the Fernow Experimental Forest in West Virginia, USA. We observed significant declines in plant C investment to fine root biomass (24.7%), root morphology, and arbuscular mycorrhizal (AM) colonization (55.9%). Moreover, we found that declines in extracellular enzyme activity were significantly correlated with a shift in bacterial community composition, but not fungal community composition. This bacterial community shift was also correlated with reduced AM fungal colonization indicating that declines in plant investment belowground drive the response of bacterial community structure and function to N fertilization. Collectively, we find that enzyme activity responses to N fertilization are not solely driven by fungi, but instead reflect a whole ecosystem response, whereby declines in the strength of belowground C investment to gain N cascade through the soil environment."
} | 520 |
29488286 | null | s2 | 8,962 | {
"abstract": "Atmospheric nitrogen (N) deposition has enhanced soil carbon (C) stocks in temperate forests. Most research has posited that these soil C gains are driven primarily by shifts in fungal community composition with elevated N leading to declines in lignin degrading Basidiomycetes. Recent research, however, suggests that plants and soil microbes are dynamically intertwined, whereby plants send C subsidies to rhizosphere microbes to enhance enzyme production and the mobilization of N. Thus, under elevated N, trees may reduce belowground C allocation leading to cascading impacts on the ability of microbes to degrade soil organic matter through a shift in microbial species and/or a change in plant-microbe interactions. The objective of this study was to determine the extent to which couplings among plant, fungal, and bacterial responses to N fertilization alter the activity of enzymes that are the primary agents of soil decomposition. We measured fungal and bacterial community composition, root-microbial interactions, and extracellular enzyme activity in the rhizosphere, bulk, and organic horizon of soils sampled from a long-term (>25 years), whole-watershed, N fertilization experiment at the Fernow Experimental Forest in West Virginia, USA. We observed significant declines in plant C investment to fine root biomass (24.7%), root morphology, and arbuscular mycorrhizal (AM) colonization (55.9%). Moreover, we found that declines in extracellular enzyme activity were significantly correlated with a shift in bacterial community composition, but not fungal community composition. This bacterial community shift was also correlated with reduced AM fungal colonization indicating that declines in plant investment belowground drive the response of bacterial community structure and function to N fertilization. Collectively, we find that enzyme activity responses to N fertilization are not solely driven by fungi, but instead reflect a whole ecosystem response, whereby declines in the strength of belowground C investment to gain N cascade through the soil environment."
} | 520 |
37756392 | PMC10530074 | pmc | 8,963 | {
"abstract": "Fermentation is a type of metabolism pervasive in oxygen-deprived environments. Despite its importance, we know little about the range and traits of organisms that carry out this metabolism. Our study addresses this gap with a comprehensive analysis of the phenotype and genotype of fermentative prokaryotes. We assembled a dataset with phenotypic records of 8350 organisms plus 4355 genomes and 13.6 million genes. Our analysis reveals fermentation is both widespread (in ~30% of prokaryotes) and complex (forming ~300 combinations of metabolites). Furthermore, it points to previously uncharacterized proteins involved in this metabolism. Previous studies suggest that metabolic pathways for fermentation are well understood, but metabolic models built in our study show gaps in our knowledge. This study demonstrates the complexity of fermentation while showing that there is still much to learn about this metabolism. All resources in our study can be explored by the scientific community with an online, interactive tool.",
"introduction": "INTRODUCTION Fermentation is a major type of metabolism carried out in the absence of oxygen. During fermentation, organic molecules (e.g., glucose) are catabolized and donate electrons to other organic molecules. In the process, adenosine 5′-triphosphate (ATP) and organic end products (e.g., lactate) are formed. Because fermentation forms ATP without using O 2 , prokaryotes in the environment use it as one alternative to aerobic respiration. The gut ( 1 , 2 ), sediments ( 3 ), and anaerobic bioreactors ( 4 ) are just some environments where oxygen is scarce and fermentative microbes are common. Fermentation is also important because of the end products it forms. These products are metabolized by human and animal hosts ( 1 , 5 , 6 ), present in food ( 7 ), and valuable as biofuels or other chemicals ( 8 , 9 ). Fermentation is thus important in many contexts. Despite the importance of fermentation, we know little about the range of prokaryotes that carry it out and their traits. There are excellent reviews of fermentation ( 10 – 15 ), but their focus is on a few model organisms and their biochemical pathways. Information on more organisms is available in journal articles or book chapters ( 16 , 17 ), but each covers just a few (usually related) organisms. With no central resource for information, it is hard to answer even simple questions about the prokaryotes carrying out fermentation. Our laboratory and others have started to collect information on fermentative prokaryotes. Our laboratory has cataloged prokaryotes that carry out fermentation and which form one end product (acetate) ( 18 , 19 ). Another group has cataloged end products of fermentation, but the scope is limited to bacteria of the human gut ( 20 ). Other groups have collected information on fermentation when building databases on microbial phenotypes ( 21 , 22 ). Given the scope of these databases, information specific to fermentation tends to be less complete. Although limited in scope or completeness, these resources provide a good starting point and, if expanded, could give a full picture of fermentative prokaryotes. Here, we assemble a large dataset on fermentative prokaryotes and use it to explore the phenotype and genotype of such organisms. This dataset includes phenotypic records on n = 8350 organisms (prokaryotes) as well as n = 4355 genomes and n = 13.6 million genes. With it, we have answered simple but important questions about fermentation. We also built an interactive tool for the microbiology community to explore our dataset and make predictions about organisms of interest.",
"discussion": "DISCUSSION Fermentation is a major type of metabolism, and it is important in microbial ecology, host health, food production, and industry. Despite this importance, there has been no systematic study of fermentative prokaryotes and their properties. Reviews of fermentation have been based on information from model organisms ( 10 – 15 ), which may not capture the full diversity of this metabolism. Some work, including our own, had started to accumulate information on more prokaryotes ( 18 , 19 , 21 , 22 ), but a full picture has still been lacking. By using a dataset of n = 8350 organisms (28% of which are fermentative), the current study paints a fuller picture. It shows that fermentative prokaryotes are both abundant and widespread. It reveals key insights into their genotype and phenotype and thus the concept of fermentation as a whole. Some of the insights we reach make sense in context of earlier work, while others are unexpected. Some are both expected and unexpected at the same time. Given that fermentation does not use oxygen, it is expected that many organisms were reported as anaerobes. Fermentation was first described as “la vie sans air” (life without air) ( 46 ), and it is still regarded as a principally anaerobic metabolism ( 10 – 15 ). It is thus all the more unexpected that 18% of fermentative prokaryotes were reported as aerobes. These organisms may be more oxygen tolerant than previously realized. One important insight is fermentation is complex and forms many end products. Historically, fermentations have been named by the major end product they form—e.g., alcohol fermentation forms ethanol ( 10 – 12 , 14 , 15 ). This is a long-standing practice ( 47 , 48 ) and remains useful for teaching, but our dataset shows that it does not match reality. Nearly all fermentations formed multiple products and in nearly 300 combinations. Our work reveals a complexity to fermentation not fully apparent before. With the rise of genome sequencing, it is common to use an organism’s genome to predict its metabolic pathways and fermentation products ( 20 , 36 – 38 ). This practice is especially important when an organism is uncultured and known only by a genome sequence ( 37 , 38 ). Our study shows that this practice is useful but has limits. We used genomes of n = 406 organisms to build metabolic models of fermentation. Some end products were predicted with low specificity or low sensitivity. Low specificity means that more organisms are predicted to form a product than observed. It could be due to many factors, such as a product being formed only under certain growth conditions [often the case for lactate ( 49 )]. Alternatively, the product could be used for anabolism [often the case for formate ( 50 )] and not leave the cell. Low sensitivity means that fewer organisms are predicted to form a product than observed, which represents a different issue. One approach for raising sensitivity of predictions is gap filling or adding enzymatic reactions apparently missing from models ( 51 ). This approach is common and used by a study predicting end products for bacteria from the human gut ( 20 ). Our study identified reactions that are often missing, and adding these would have raised sensitivity. However, it was not always clear which reaction was missing, much less the reason. If anything else, missing reactions show areas of metabolism needing further study; such study has led to previously unknown pathways for fermentation being discovered ( 18 ). To maximize the value of our work to the microbial community, we built an interactive tool called Fermentation Explorer. This tool has many applications. One is for identifying organisms for producing end products for biotechnological purposes (e.g., biofuel production). With data on 55 fermentation end products formed in nearly 300 combinations, our tool can pinpoint the best organism for an application. Such an organism could be used outright, or it could be used as a source of genes to genetically engineer other organisms ( 52 – 54 ). Another application is predicting fermentative traits of prokaryotes present in a user’s sample. Users can predict traits in two different ways—either from an organism’s genome or its taxonomy. We showcase this ability with four datasets, including one with uncharacterized prokaryotes that was generated for this study. Because fermentation is widespread, the ability to make these predictions will be useful to microbiologists working in many systems. Fermentation has been studied for 185 years [since the time of Theodor Schwann ( 55 ) and Louis Pasteur ( 47 , 48 )], and our study fills key gaps in our knowledge of this metabolism. It also shows that there is much to learn. It shows common genes in fermentative prokaryotes and that some genes have no defined function. The latter are targets for further study, and their abundance in fermentative prokaryotes may help narrow down possible roles. In one case, a gene with no defined function was confirmed to have a role in fermentation (transport of succinate) ( 34 ). Our study shows a wealth of information exists on fermentative prokaryotes, but it speaks little on eukaryotes. Both unicellular and multicellular eukaryotes carry out fermentation ( 13 ), and they merit further study. The next 185 years of study will be illuminating."
} | 2,249 |
28348844 | PMC5320584 | pmc | 8,966 | {
"abstract": "The majority of Acinetobacter baumannii isolates that are multiply, extensively and pan-antibiotic resistant belong to two globally disseminated clones, GC1 and GC2, that were first noticed in the 1970s. Here, we investigated microevolution and phylodynamics within GC1 via analysis of 45 whole-genome sequences, including 23 sequenced for this study. The most recent common ancestor of GC1 arose around 1960 and later diverged into two phylogenetically distinct lineages. In the 1970s, the main lineage acquired the AbaR resistance island, conferring resistance to older antibiotics, via a horizontal gene transfer event. We estimate a mutation rate of ∼5 SNPs genome − 1 year − 1 and detected extensive recombination within GC1 genomes, introducing nucleotide diversity into the population at >20 times the substitution rate (the ratio of SNPs introduced by recombination compared with mutation was 22). The recombination events were non-randomly distributed in the genome and created significant diversity within loci encoding outer surface molecules (including the capsular polysaccharide, the outer core lipooligosaccharide and the outer membrane protein CarO), and spread antimicrobial resistance-conferring mutations affecting the gyrA and parC genes and insertion sequence insertions activating the ampC gene. Both GC1 lineages accumulated resistance to newer antibiotics through various genetic mechanisms, including the acquisition of plasmids and transposons or mutations in chromosomal genes. Our data show that GC1 has diversified into multiple successful extensively antibiotic-resistant subclones that differ in their surface structures. This has important implications for all avenues of control, including epidemiological tracking, antimicrobial therapy and vaccination.",
"introduction": "Introduction Acinetobacter baumannii is one of the ESKAPE pathogens ( Rice, 2008 ) – the six main agents of hospital-acquired antibiotic-resistant infections recognized by the Infectious Diseases Society of America. A. baumannii are intrinsically resistant to chloramphenicol; however, isolates resistant to a wide array of antibiotics, including sulphonamides, tetracycline, ampicillin, kanamycin, gentamicin and streptomycin, have been observed since the 1970s ( Devaud et al. , 1982 ; Bergogne-Bérézin & Towner, 1996 ). Amplified fragment length polymorphism typing ( Dijkshoorn et al. , 1996 ) and later MLST revealed that the majority of such isolates belong to one of two clones ( Diancourt et al. , 2010 ), which are now globally disseminated and known as global clones GC1 and GC2 ( Nigro et al. , 2011a ). In most GC1, resistance to the older antibiotics is now known to reside in a single chromosomal locus – the AbaR resistance island ( Fournier et al. , 2006 ; Post & Hall, 2009 ; Adams et al. , 2010 ; Krizova & Nemec, 2010 ; Post et al. , 2010 , 2012 ; Krizova et al. , 2011 ; Nigro et al. , 2011b ; Hamidian et al. , 2014c ; Holt et al. , 2015 ); however, one isolate contained a different transposon at the same site, suggesting an independent history ( Hamidian & Hall, 2011 ). Resistance to newer drugs, including fluoroquinolones, third-generation cephalosporins and carbapenems, emerged in the 1980s, associated with a wide variety of genetic mechanisms, including DNA substitutions, transposition, recombination and plasmid acquisition ( Bergogne-Bérézin & Towner, 1996 ; Zarrilli et al. , 2013 ; Antunes et al. , 2014 ; Nigro & Hall, 2016 ). More recently, variation in the regions responsible for surface polysaccharides has been reported in both GC1 and GC2 ( Adams et al. , 2008 ; Snitkin et al. , 2011; Hu et al. , 2013 ; Kenyon & Hall, 2013 ; Wright et al. , 2014 ; Kenyon et al. , 2015 ). MLST has shown that A. baumannii is made up of distinct clones of which only GC1, GC2 and a handful of others are responsible for the majority of antibiotic-resistant human infections, indicating that A. baumannii lineages vary in terms of their pathogenic potential ( Diancourt et al. , 2010 ; Zarrilli et al. , 2013 ; Antunes et al. , 2014 ). More recently, whole-genome comparisons yielded insights into the evolution of pathogenicity in A. baumannii and the genus Acinetobacter , uncovering wide diversity in gene content, including variation in virulence determinants ( Kenyon & Hall, 2013 ; Sahl et al. , 2013 ; Eijkelkamp et al. , 2014 ; Kenyon et al. , 2014b ; Touchon et al. , 2014 ; Wright et al. , 2014 ). Genomic analysis of intra-clone diversity over the period in which antibiotics have been used have been utilized to examine the microevolution of clones of multiple antibiotic-resistant bacterial pathogens, including the more recently emerged ESKAPE pathogens, such as Escherichia coli ST131 ( Petty et al. , 2014 ) and Klebsiella pneumoniae ST258 ( Gaiarsa et al. , 2015 ). However, genomic studies of intra-clonal variation in A. baumannii have been limited to small or highly localized isolate samples ( Adams et al. , 2010 ; Sahl et al. , 2015 ). Here, we used genomic approaches to dissect the evolution of A. baumannii GC1, providing insights into the ongoing evolutionary trajectory of this important human pathogen.",
"discussion": "Discussion Our analysis indicates that the MRCA of A. baumannii the GC1 clonal complex arose around 1960 and later diverged into two phylogenetically distinct lineages. In the mid-1970s, the main lineage acquired resistance to older antibiotics via a single event creating the AbaR0 resistance island in the chromosome and giving rise to the multiply antibiotic-resistant lineage 1. Later, a sublineage carrying AbaR3, identifiable by a small deletion in intI1 , emerged ( Hamidian et al. , 2014c ). Both sublineages of lineage 1 have since given rise to multiple successful subclones, by losing some of the resistance genes in AbaR and accumulating resistance to newer antibiotics through various genetic mechanisms, including the acquisition of plasmids and transposons or acquisition of mutations in chromosomal genes. Ultimately, this has given rise to isolates that are extensively antibiotic-resistant, potentially belonging to many different sublineages. Lineage 2 currently includes only a few military isolates, indicating they are likely to have originated in Afghanistan or Iraq, and has acquired resistance via different routes. In the future, detailed tracking of the spread of GC1 within hospitals, cities, countries and globally will need to entail tracking of specific lineages, and the subclones and sublineages of them. PCR assays to distinguish different gene clusters at the K locus similar to those reported for the OC locus ( Kenyon et al. , 2014a ) should assist this. More detailed information on the plasmids carrying antibiotic resistance genes will also be valuable. Capsule replacement has been extensively studied in Streptococcus pneumoniae , where it is associated with immune evasion and vaccine escape. However, the capsular exchange detected here within the recently emerged A. baumannii GC1 clone adds to the occasional exchanges reported previously in GC1 ( Adams et al. , 2008 ; Kenyon & Hall, 2013 ; Hamidian et al. , 2014b ; Kenyon et al. , 2015 ), bringing the total distinct KL gene clusters to eight, similar to that reported previously in the GC2 clone ( Snitkin et al. , 2011 ; Hu et al. , 2013 ; Kenyon & Hall, 2013 ; Wright et al. , 2014 ). The number of capsule replacement events in these A. baumannii groups is significant amongst Gram-negative epidemic clones. O-antigen or capsule replacement has recently been reported in lineages of E. coli , including 10 capsular types within E. coli ST131 ( Iguchi et al. , 2015 ; Alqasim et al. , 2014 ; Riley, 2014 ), and a capsule replacement event has been noted within K. pneumoniae epidemic clone ST258 ( DeLeo et al. , 2014 ; Wyres et al. , 2015 ). Notably, our analysis indicates that the process of replacement of the gene cluster at the KL in GC1 did not begin until after the emergence of the two successful lineages 1 and 2, following the independent acquisition of multiple antimicrobial resistance determinants into the chromosome of both lineages. It was recently reported that the evolution of multidrug-resistant O12 Pseudomonas aeruginosa involved a change from the O4 serotype via recombination ( Thrane et al. , 2015 ), which also introduced novel antimicrobial resistance genes; we speculate that further exchanges are likely to occur as this clone diversifies. The extensive KL and OCL replacement detected in our collection is suggestive of selection for phenotypic variation in exopolysaccharides expressed by GC1; however, the evolutionary drivers of capsular exchange in A. baumannii are not yet clear. It is tempting to speculate that host immunity is a key driver of capsular exchange and this could help explain the apparent increase in capsular changes over time in the GC1 population as it adapts to the new niche of a human-associated hospital pathogen following the acquisition of multiple antibiotic resistance. However, the variation we observed may be associated with factors unrelated to host immunity, including diversifying selection from predatory bacteriophage and amoeba that recognize specific capsule types ( Adiba et al. , 2010 ), or with subtle differences in antimicrobial susceptibility that have also recently been linked to capsular variation ( Geisinger & Isberg, 2015 ). Whatever the drivers, it is likely that similar selective pressures are at play in the more recently emerged multidrug-resistant epidemic clones E. coli ST131 and K. pneumoniae CC258, in which relatively limited capsular exchange has so far been documented. This has important implications for the prospect of capsule-targeted vaccines and phage therapy, which have been proposed as a control measure for highly drug-resistant hospital outbreak-associated clones of A. baumannii and K. pneumoniae ( Ahmad et al. , 2012 ; García-Quintanilla et al. , 2013 ; Russo et al. , 2013 ). Our analysis traces in fine detail the myriad microevolutionary events that have accompanied the emergence of multidrug-resistant A. baumannii GC1 over the last 65 years as it accumulated resistance to first-line antimicrobials, then fluoroquinolones, third-generation cephalosporins and carbapenems. The revelation of extensive capsule replacement during this period, resulting in a diversity of GC1 subclones with distinct surface polysaccharides and antimicrobial resistance phenotypes, has significant implications not only for epidemiological tracking and hospital infection control, but also for the development of novel vaccines, therapeutics and diagnostics targeting this extremely drug-resistant and globally distributed clone. Further, these patterns provide a glimpse into the future evolutionary trajectory of the much more recently emerged epidemic clones of Enterobacteriaceae , which show similar signs of capsular diversification and accumulation of complex resistance determinants."
} | 2,767 |
31624556 | PMC6787799 | pmc | 8,967 | {
"abstract": "Abstract We hypothesized that population diversities of partners in nitrogen‐fixing rhizobium–legume symbiosis can be matched for “interplaying” genes. We tested this hypothesis using data on nucleotide polymorphism of symbiotic genes encoding two components of the plant–bacteria signaling system: (a) the rhizobial nod A acyltransferase involved in the fatty acid tail decoration of the Nod factor (signaling molecule); (b) the plant NFR5 receptor required for Nod factor binding. We collected three wild‐growing legume species together with soil samples adjacent to the roots from one large 25‐year fallow: Vicia sativa , Lathyrus pratensis , and Trifolium hybridum nodulated by one of the two Rhizobium leguminosarum biovars ( viciae and trifolii ). For each plant species, we prepared three pools for DNA extraction and further sequencing: the plant pool (30 plant indiv.), the nodule pool (90 nodules), and the soil pool (30 samples). We observed the following statistically significant conclusions: (a) a monotonic relationship between the diversity in the plant NFR5 gene pools and the nodule rhizobial nod A gene pools; (b) higher topological similarity of the NFR5 gene tree with the nod A gene tree of the nodule pool, than with the nod A gene tree of the soil pool. Both nonsynonymous diversity and Tajima's D were increased in the nodule pools compared with the soil pools, consistent with relaxation of negative selection and/or admixture of balancing selection. We propose that the observed genetic concordance between NFR5 gene pools and nodule nod A gene pools arises from the selection of particular genotypes of the nod A gene by the host plant.",
"introduction": "1 INTRODUCTION One of the earliest studied types of symbiosis, the host–parasite interaction, was described by Flor's Gene‐for‐Gene concept (Flor, 1971 , 1942 ) and, in fact, the first mathematical model of coevolution was explicitly based on the assumption of a Gene‐for‐Gene (GFG) interaction (Mode, 1958 ; Thompson & Burdin, 1992 ). Further analyses of host–parasite interactions revealed concepts, namely matching‐allele (MA) (Frank, 1994 ), inverse‐matching‐allele (IMA) (Otto & Michalakis, 1998 ), and inverse‐gene‐for‐gene (IGFG) (Fenton, Antonovics, & Brockhurst, 2009 ), which together with the GFG represent the opposite end of the same continuum of host–parasite specificity (Agrawal & Lively, 2002 ). These theoretical concepts, initially developed for antagonistic systems, found their reflection also in mutualistic symbiotic systems (Cregan, Sadowsky, & Keyser, 1991 ; Lewis‐Henderson & Djordjevic, 1991 ; Parker, 1999 ; Sachs, Essenberg, & Turcotte, 2011 ; Sadowsky et al., 1991 ). One of the possible consequences of the above‐mentioned concepts is that matching between symbionts could be observed not only on the gene sequence level but also on the population structure level. We proposed that coordinated population diversity of symbionts can be a significant aspect of symbiotic interactions in a row with the difference in evolutionary rates between interacting species as considered in the Red Queen and the Red King dynamics (Bergstrom & Lachmann, 2003 ; Pal, Maciá, Oliver, Schachar, & Buckling, 2007 ; Paterson et al., 2010 ; Van Valen, 1973 ). Previous studies have demonstrated the matching population diversities of symbionts. For example, the analysis of the symbiosis between Neorhizobium galegae and its host plant Galega indicated correspondence of population diversity levels between microsymbionts and the host Galega species (Andronov et al., 2003 ; Österman et al., 2011 ). In particular, a more genetically diverse Galega orientalis population harbors a more diverse root nodule rhizobial population, while its less diverse sympatric counterpart Galega officinalis forms symbiosis with a less diverse rhizobial population. This observation is related to the well‐studied phenomenon of shaping the genetic structure of the rhizobial population through the selection of specific rhizobial genotypes by the host plant (Depret & Laguerre, 2008 ; Heath & Tiffin, 2007 ; Laguerre, Louvrier, Allard, & Noelle, 2003 ; Paffetti et al., 1998 ). Moreover, it has been shown that the topology of the nod A gene tree follows the corresponding host plant tree more strictly than the 16S rRNA‐based rhizobial phylogeny (Dobert, Breil, & Triplett, 1994 ; Suominen, Roos, Lortet, Paulin, & Lindstro, 2001 ). Therefore, we expect that the interplay of symbiotic populations leads to concordance between the diversity levels in their symbiotic genes. In this study, we focused on two symbiotic genes that can be considered interacting as both encode the essential components of the rhizobium–legume signaling system; these are associated with each other through a lipochito‐oligosaccharide called Nod factor (NF) (Figure 1 ). The first component is the rhizobial nod A gene which encodes an acyltransferase enzyme essential in NF biosynthesis, specifically in the attachment of the long‐chain fatty acid tail to the oligosaccharide backbone (Dénarié, Debellé, & Promé, 1996 ; Esseling & Emons, 2004 ; Oldroyd, 2013 ). The second component is one of the plant symbiotic receptor genes, NFR5 , which is a homologue of LjNFR5 , MtNFP , PsSym10 genes. Its product recognizes NFs (signaling molecules) by three extracellular LysM domains and triggers the formation of root nodule primordia giving the green light to the process of bacterial infection (Oldroyd, 2013 ). The NFs are major determinants of host specificity: rhizobia produce NFs with different structures, and host plants percept only those NFs that have a certain composition (Mergaert & Montagu, 1997 ). The variation of NFs structure is observed not only between rhizobia species but also at the intra‐species level (Spaink, 2000 ); one rhizobia species produces a mixture of NFs that vary in the fatty tail modifications. As proposed, the nod A product can vary in its fatty acid specificity, thus contributing to the bacterial host range (Dénarié et al., 1996 ; Moulin, Béna, & Stępkowski, 2004 ; Ritsema, Wijfjes, Lugtenberg, & Spaink, 1996 ; Roche et al., 1996 ). It is logical to assume that the nod A gene diversity in a rhizobial population can reflect the structural variation of NFs produced by this population. Indeed, it has been shown that minor differences in the structure of fatty acids tail can affect intra‐species host specificity (Li et al., 2011 ). On the host plant side, NFs are recognized by high‐affinity legume receptors (Broghammer et al., 2012 ; Moulin et al., 2004 ). Studies on the model legumes revealed NFR5 as one of the major receptors to percept NFs (Radutoiu et al., 2007 ). Mutant analysis showed that single amino acid differences in one domain of the NFR5 receptor change recognition of NF variants (Broghammer et al., 2012 ; Radutoiu et al., 2007 ). Such mediation of NFs between rhizobial nod A and legume NFR5 genes make them good candidates for testing the hypothesis that population diversities of partners in nitrogen‐fixing rhizobium–legume symbiosis are matched. Figure 1 A part of the signal transduction system that governs the rhizobium–legume symbiosis. The rhizobial nod A gene encodes the acyltransferase that participates in the attachment of the hydrophobic long‐chain fatty acid tail to the Nod factor core. Plant NFR5 gene encodes the symbiotic receptor recognizing the rhizobial Nod factor followed by symbiosis formation We tested the hypothesis on symbiotic systems of three wild‐growing legume species ( Vicia sativa , Lathyrus pratensis and Trifolium hybridum ) with their rhizobial microsymbionts. Sampling of the experimental material was performed uniformly on the one large natural fallow (more than 25 years) field in order to avoid the influence of ecological factors. We collected 30 plant individuals for each of three species and, for each individual, collected (a) leaves, (b) nodules, and (c) soil samples. After the pooling, we obtained nine samples (3 species × 3 types of materials) each containing aggregated information of 30 samples (Figure S1 ). Vicia and Lathyrus species represent the same cross‐inoculation group nodulated with Rhizobium leguminosarum bv. viciae strains, while Trifolium belongs to a separate group nodulated with R. leguminosarum bv. trifolii . One of the important traits of the rhizobium–legume symbiosis is the annual cycle of rhizobia, consisting of nodule formation with consequent amplification of rhizobia inside of the nodule, followed by a release of the nodule rhizobia back into the soil after nodule degradation leading to an increase of the frequency of this rhizobial genotype in the soil (Spaink, Kondorosi, & Hooykaas, 1998 ). Therefore, we analyzed both soil and nodule populations of rhizobia, which affect each other. Testing the hypothesis of matching population diversities required comparison of structural (topological) characteristics of plant and rhizobia populations. Traditionally, the topological similarity between two populations is estimated as the congruence of two respective labeled trees (Leigh, Lapointe, Lopez, & Bapteste, 2011 ). Here, we propose a novel method to compare topologies of two gene trees with unlabeled leaves. The method is based on the gCEED approach (Choi & Gomez, 2009 ) that translates each population to the Gaussian mixture model in a K‐dimensional space. This method can be classified as a kind of beta‐diversity metric, which, by analogy with taxonomic (Jost, Chao, & Chazdon, 2011 ) and phylogenetic methods (e.g., UniFrac, Lozupone, Lladser, Knights, Stombaugh, & Knight, 2011 ), could be denoted as “topological beta‐diversity.” We apply it to show that the tree structures are concordant between the two symbiont species.",
"discussion": "4 DISCUSSION Symbiotic interactions represent a special case of ecological interactions when one of the partners provides an “environment” for another. In On the Origin of Species (Darwin, 1872 ), Charles Darwin proposed that “the life of each species depends in a more important manner on the presence of other already defined organic forms, than on climate.” This is particularly true for organisms in deeply integrated symbiotic systems. Here, we traced the coordination in levels of population diversities between partners within the essential components of the rhizobium–legume signaling system: plant symbiotic receptor gene NFR5 and Rhizobium symbiotic gene nod A involved in the synthesis of signaling molecules Nod factors (NFs), ensuring the first stage of partner recognition (Oldroyd, 2013 ). The matching was detected in two phenomena. The first is the monotonic relationship between the diversity of plant gene pools and the diversity of nodule rhizobial gene pools (Spearman correlation = 0.89). The second is the higher topological similarity between plant gene pool with nodule gene pool than with soil gene pool. The last phenomena were demonstrated using the developed method to compute “topological beta‐diversity”—the difference in topological structures of two population sets (plant and rhizobia) of gene sequences. The observed results allowed us to accept the hypothesis that population diversities of partners in nitrogen‐fixing rhizobium–legume symbiosis are matched. We characterized the most pronounced characteristics of the mechanism underlying the matching population diversities. First, the analysis of the selection imposed by plants revealed significantly increased nonsynonymous diversity (p N ) and Tajima's D values in the nodule gene pools (Table 1 ). This may be indicative of weaker negative selection in a nodule gene pool in a comparison with the respective soil gene pool, but is also consistent with a contribution of balancing selection or presence of stronger population structure in the former. In the previous study, it was shown that in symbiotic systems, besides the above‐mentioned types of selection, negative frequency‐dependent selection in favor of rare genotypes during the competition of rhizospheric bacteria for root nodulation (Amarger & Lobreau, 1982 ) may also play an important role (Andronov, Igolkina, Kimeklis, Vorobyov, & Provorov, 2015 ; Provorov & Vorobyov, 2000 , 2006 ). Second, trees of nodule gene pools contained unique clades of genotypes, which were not detected in soil pools likely due to the low frequency of the genotypes in soil. These genotypes are probably responsible for increased topological similarity between plant and nodule rhizobia gene pools, so that a nodule population is selected by the host plant to supply some needs of the latter. In other words, our results demonstrated the transformation of the initial soil nod A pool by the template of the host plant receptor pool, and this conclusion is in line with the numerous works studying the interplay between diversities of host plant and rhizobia (Andronov et al., 2003 ; Bailly, Olivieri, Mita, Cleyt‐Marel, & Bena, 2006 ; Barrett, Zee, Bever, Miller, & Thrall, 2016 ; Bena, Lyet, Huguet, & Olivieri, 2005 ; Depret & Laguerre, 2008 ; Österman et al., 2011 ; Paffetti et al., 1998 ; Rangin, Brunel, Cleyt‐Marel, Perrineau, & Gilles, 2008 ; Vuong, Thrall, & Barrett, 2016 ). Finally, there are some suggestions on the molecular mechanism involved in this process. In our recent study, we modeled the 3D sandwich‐like structures of the NFR5‐K1 heterodimeric receptor with its ligand Nod factor and observed the mutually polymorphic areas in the contact zone between NFR5 and K1 that were overlapped with known structural variation of Nod factor (in the fatty acid part) produced by R. leguminosarum bv. viciae (Igolkina, Porozov, Chizhevskaya, & Andronov, 2018 ). These results demonstrate the possible specificity of host plant receptors to variations in NF structure likely resulting in matching population diversities between nodA and NFR5 gene pools. The observed matching between nodule rhizobial nod A gene pools and plant NFR5 receptor gene pools revealed the hierarchical organization of effective interaction: two symbionts should be genetically compatible at the single organism level and also at the population level. The process of forming this interaction could be explained metaphorically as an evolutionary molding: shaping the population structure of one symbiont using the population structure of another symbiont as a “matrix.” The important point in this shaping is the difference between evolutionary rates in plants and bacteria. The bacteria have a significantly higher evolutionary rate than plants; therefore, the diversity of the nod A gene in bacterial populations, like the flexible genetic material in the evolutionary molding, reflected the shape of more “rigid” diversity of the NFR5 receptor gene in plant populations. We hypothesize that under the evolutionary molding effect, two symbiotic populations tend to relax the incoordination of genetic diversities between two parts of the symbiont–host signaling system, which is mostly achieved by a faster evolving partner, rhizobia in our case. We proposed that according to the effect described, the relationship in population diversity between rhizobia and host plant may be observed not only within the pair of nod A‐ NFR5 genes (which are related through the NF) but also within any pair of interplaying genes from plant and bacterial sides, and that genome‐wide scanning for “matching” genes can be an extension to the traditional methods of functional analysis of genes."
} | 3,897 |
38495150 | PMC10943344 | pmc | 8,969 | {
"abstract": "Given the challenges imposed by climate change and societal challenges, the European Union established ambitious goals as part of its Farm to Fork (F2F) strategy. Focussed on accelerating the transition to systems of sustainable food production, processing and consumption, a key element of F2F is to reduce the use of fertilisers by at least 20% and plant protection products by up to 50% by 2030. In recent years, a substantial body of research has highlighted the potential impact of microbial-based applications to support crop production practices through both biotic/abiotic stresses via maintaining or even improving yields and reducing reliance on intensive chemical inputs. Here, we have characterised the ability of a new soil-borne free-living bacterium strain Ensifer adhaerens OV14 (EaOV14) to significantly enhance crop vigour index by up to 50% for monocot (wheat, Triticum aestivum L., p < 0.0001) and by up to 40% for dicot (oilseed rape, Brassica napus L., p < 0.0001) species under in-vitro conditions ( n = 360 seedlings/treatment). The beneficial effect was further studied under controlled glasshouse growing conditions ( n = 60 plants/treatment) where EaOV14 induced significantly increased seed yield of spring oilseed rape compared to the controls (p < 0.0001). Moreover, using bespoke rhizoboxes, enhanced root architecture (density, roots orientation, roots thickness etc.) was observed for spring oilseed rape and winter wheat, with the median number of roots 55% and 33% higher for oilseed rape and wheat respectively, following EaOV14 seed treatment compared to the control. In addition, EaOV14 treatment increased root tip formation and root volume, suggesting the formation of a more robust root system architecture post-seed treatment. However, like other microbial formulations, the trade-offs associated with field translation, such as loss or limited functionality due to inoculum formulation or environmental distress, need further investigation. Moreover, the delivery method requires further optimisation to identify the optimal inoculum formulation that will maximise the expected beneficial impact on yield under field growing conditions.",
"conclusion": "5 Conclusions It is clear from the literature that integrated approaches are required to support sustainable crop productivity goals [ 74 , 75 ]. In this regard, the goal of this study was to determine the growth-enhancing potential of the soil-borne bacterium strain E. adhaerens OV14. The results show that when applied as a seed treatment, EaOV14 has the potential to enhance the development of both an important mono and dicot species. These findings indicate that EaOV14 represents a suitable candidate with the potential to contribute to reducing reliance on chemical fertilisers in line with the very ambitious F2F European goals. In conclusion, EaOV14 had a minimal impact on seed germination but exhibited a significantly positive effect on the seedling vigour index. EaOV14 showed a positive response for both spring and winter OSR varieties studied and displayed varietal dependency in the case of the wheat varieties examined. This observation highlights the need to test the efficiency of microbial biostimulants on the varieties listed on the annual recommended list and select the optimal species for the varieties recommended for cultivation. Based on the glasshouse studies, EaOV14 significantly enhanced the root architecture of the oilseed rape variety Ability and wheat variety Rockefeller. Moreover, oilseed rape variety Ability recorded a significant increase in seed yield in response to EaOV14 treatment compared to the controls. Considering that insignificant changes between EaOV14 and controls were observed for the pod number and thousand seed weight (TSW) one can conclude that an increased seed yield is a response to EaOV14 treatment on the pod filling process. This work highlights the biostimulant potential of EaOV14, with the positive response on plant development recorded through both aerial and root development. While the results are limited to controlled optimal growing conditions ( in-vitro and glasshouse), the first stage of proof-of-concept is now confirmed. This will serve as a benchmark for follow on studies that seek to investigate the field performance of E. adhaerens OV14 as a plant biostimulant. Funding This research work was conducted with the financial support of 10.13039/501100001604 Teagasc (Project No. 0777) and through the Teagasc Walsh Scholarship Programme (Grant no. 2019035).",
"introduction": "1 Introduction The ambition of the EU's Green Deal and Farm to Fork (F2F) strategies in agriculture is to reduce the use and risk of synthetic agents for crop production by 20% for nutrients and up to 50% for plant protection products by 2030. Coupled with the increasing impacts of volatile weather patterns linked to climate change [ 1 ], it is clear that significant advancements are required to deliver integrated strategies that support crop resilience. This is especially the case with crop production, where plants must adapt to multiple biotic and abiotic stresses [ 2 , 3 ]. From the perspective of abiotic stress, European climate predictions suggest that more extreme events such as heatwaves, drought, and heavy precipitation can be expected [ 4 , 5 ], even within a single growing season [ 1 ]. Indeed, the weather events in the past decade suggest that the timeline for these events to occur has been accelerated beyond what models predict [ 1 , 6 ]. In the 21 st century, the increase in daytime temperatures due to greenhouse gas emissions and atmospheric change has negatively influenced global wheat and maize production [ 7 ]. Moreover, since 2000, an increase of CO 2 levels in the atmosphere correlates with a rise in atmospheric ozone, which is responsible for approximately a 10% loss in wheat and soybean yield and up to 5% loss in rice and maize production, with severe impacts in Asian countries [ 7 , 8 ]. Plant biostimulants represent a promising solution to increase the resilience of crop production systems and overcome the current agricultural sector's limitations in the face of future challenges. It is well known that microorganisms are omnipresent on all organisms and surfaces, contributing to an ecosystem's well-being [ 9 ]. In plants, it has been shown that many rhizosphere bacteria positively influence nutrient availability [ 10 ]. Plant growth-promoting bacteria influence plant development via direct (facilitating nutrient acquisition) and indirect (biocontrol) mechanisms of action [ 11 ]. Direct mechanisms include phosphate/potassium solubilisation, nitrogen fixation, phytohormone synthesis (indolyl-3-acetic acid and cytokinin), and ACC deaminase production. Indirect mechanisms are represented by activating the induced systemic resistance (ISR) in the presence of pathogens and releasing in the environment inhibitory substances such as allelochemicals or lytic enzymes [ [11] , [12] , [13] , [14] , [15] ]. Ensifer represents a genus of Gram-negative α-proteobacteria with budding multiplication and a specific predatory characteristic for other bacteria. Ensifer and Sinorhizobium are taxonomic terms describing the same genus, with Ensifer first described by Casida in 1982 and Sinorhizobium by Chen, Yan and Li in 1988 [ 16 ]. When supplemented with the pCambia5105 plasmid, Ensifer adhaerens OV14 strain has been shown to successfully transform potato [ 17 ], rice [ 18 ], oilseed rape [ 19 ], and cassava [ 20 ]. Furthermore, several studies on alternative strains of E. adhaerens have already described the species’ capability to promote plant growth via nutrient mineralisation [ 21 ], neonicotinoid insecticide (thiamethoxam) degradation [ 22 ], and indeed act as a biocontrol agent [ 23 ]. A previous study has indicated that E. adhaerens OV14 possesses genetic networks to indicate a possible ability to improve plant growth and enhance stress resilience (salicylic acid metabolism and quorum sensing communication system via N -acyl homoserine lactone metabolism) [ 24 ]. However, tangible evidence to support this hypothesis is lacking. Recently, through comparative genomic analyses, it has been established that species from the Ensifer genus are separated phylogenetically into two clades: symbionts and non-symbionts, with E. adhaerens OV14 located in the non-symbiont group [ 25 ]. In this context, the beneficial effect on improving plant growth that E. adhaerens OV14 might possess falls under the latest biostimulants definition stating that the microorganism must “ stimulate natural processes to benefit nutrient uptake, nutrient efficiency, tolerance to abiotic stress, and/or crop quality, independently of its nutrient content ” [ 26 ]. The goal of this study was to test the hypothesis that the wild-type E. adhaerens OV14 has indeed plant growth-promoting activity and could be utilised as a biostimulant for economically significant monocot ( Triticum aestivum L.) and dicot ( Brassica napus L.) species. For an in-depth understanding of the effect that E. adhaerens OV14 induces on plant development, in-vitro experiments looked at the early stages of development with a focus on seed germination and seedlings’ vigour index. The beneficial effect was further confirmed under controlled glasshouse conditions with in-vivo seed-to-seed experiments for oilseed rape variety Ability and real time root system development observation using bespoke rhizoboxes.",
"discussion": "4 Discussion In the agricultural sector, a new ′green revolution′ is required to sustain the continuously growing population [ 32 ] and counter the socio-economic challenges the world is facing [ 33 , 34 ]. Identifying and validating a low-input, cost-effective alternative that can maintain or even improve plant yield while enhancing stress resilience is essential [ [35] , [36] , [37] , [38] ]. An important step towards sustainable crop production was the observation that naturally soil-borne organisms positively influence plant development, entering the plant nutrient cycle and actively enriching nutrient availability, representing a continuous source of nutrients for the developing plant [ [39] , [40] , [41] , [42] , [43] , [44] , [45] ]. Previous research has looked at the biostimulant potential of E. adhaerens under stressful environmental conditions, where it was able to remediate heavy metal-contaminated soil [ 46 ] and biodegrade thiamethoxan, a neonicotinoid insecticide [ 22 ]. Neonicotinoid insecticides are the most widely seed-applied insecticides and have proven to be harmful to wild bees [ 47 ] and in response, the EU limited the use of some compounds from this class, thiamethoxan included [ 48 ]. Furthermore, the strain E. adhaerens SZMC 25856 isolated from soil improved tomato seedlings’ development under in-vitro conditions and induced high tolerance to salinity, drought, and heavy metals [ 49 ]. There is still a lack of knowledge though on the ability of E. adhaerens to extend its beneficial impact into important agricultural crop cultivars. In this regard, the goal of this work was to determine the growth-enhancing potential of the soil-borne bacterium strain E. adhaerens OV14 and identify if applied as a seed treatment, whether EaOV14 has the potential to enhance the development of an important mono and dicot crop species. The findings of this work showed that EaOV14 had a minimal effect on seed germination yet induced a strong positive effect on the seedling vigour index. EaOV14 showed a positive response for both spring and winter OSR varieties studied and displayed varietal dependency in the case of the wheat varieties examined. Genotype dependency for the efficiency of microbial biostimulants was previously observed for wheat [ 50 ] and rice [ 51 ]. Previous studies on Pseudomonas sp. strains [ 52 ] or consortium of Pseudomonas sp. and other bacteria strains ( Pseudomonas sp. strain B14, Sphingobacterium sp. strain B16, and Microbacterium sp. strain B19) [ 53 ] isolated from oilseed rape rhizosphere showed enhanced plant biomass under glasshouse-controlled conditions. However, it was observed that the biostimulant effect of rhizobacteria on oilseed rape seed yield under glasshouse conditions is insufficiently studied for optimal growing conditions. This work shows that, under glasshouse conditions, oilseed rape variety Ability plants pre-treated with EaOV14 present higher seed yield compared to the controls (H 2 O and CSC), even though the number of pods and thousand seed weight (TSW) were similar across treatments ( Fig. 4 F–H). These observations suggest that applying EaOV14 as a seed treatment could contribute in part to an integrated nutrient management strategy in support of sustainable agricultural practises. The glasshouse experiments showed that EaOV14 significantly enhanced the root architecture of the oilseed rape variety Ability and wheat variety Rockefeller. These changes in the root system architecture are similar to the findings of Sakthivel et al. [ 54 ] that evaluated the impact of Bacillus altitudinis FD48 on rice growth. This study observed that seedlings inoculated with FD48 presented higher number of roots, increased lateral root formation and overall root thickness as response to FD48 modulating the expression of genes in the auxin metabolism pathway ( IAA1, IAA4, IAA11, IAA13 ). Other studies also highlighted the positive impact of plant growth-promoting bacteria on root development through modulating hormone production [ [55] , [56] , [57] , [58] ] and have been linked to drought stress alleviation capabilities [ 59 ]. Strong and healthy root systems are indicators of thriving plants [ 60 ]. Biologically, roots are divided into two classes: shallow and deep roots. The shallow roots inhabit the topsoil, where they absorb immobile nutrients such as potassium and phosphorous. The deeper roots absorb nutrients available at more depth or the mobile water-soluble nutrients that travel with the water, such as nitrates [ 61 ]. In this context, studying how biostimulants modulate root system architecture becomes essential to fully understand the extent of their potential benefit on plant development [ 62 ]. The evolution of technology, together with the rise of computer sciences, has led to significant improvements in the root phenotyping field with high-throughput facilities now available in Europe [ 63 ]. Moreover, the accessibility to deeply understand dynamics of root architecture has also been improved by the release of free software sources (e.g. RhizoVision Explorer) [ 29 ]. Nonetheless, for this work, the difficulty in sourcing accessible phenotyping tools drove the design and building of low-cost rhizoboxes that allowed the study of the changes EaOV14 induces on root systems in real time. ‘Steep, cheap, and deep’ represents the ideal root structure for resilient crops in the current agricultural challenges as it requires minimum energy costs to access nutrients at different levels in the soil [ 64 ]. Shallow root angles (steep) and branching represent cost-effective metabolic solutions to facilitate the uptake of topsoil nutrients such as potassium and phosphorous [ [64] , [65] , [66] ]. Nonetheless, crops with deeper roots have increased access to nutrients and water, especially when they are available at depth, in scarce conditions such as drought [ 65 ]. This work, under controlled conditions, clearly highlights that pre-treatment of seed with E. adhaerens OV14 stimulates oilseed rape and wheat to develop root systems following the ‘steep, cheap, and deep’ pattern indicating the stress resilience enhancing potential of E. adhaerens OV14. The primary challenges associated with the use of beneficial soil bacteria include selecting the right inoculation method, ensuring adequate shelf life, and successfully translating laboratory findings to field applications [ 67 ]. Studying microbial biostimulants requires particular attention to optimising the inoculation method. Several inoculation methods have been assessed in the last decade: soil application, foliar application, and seed application. The latter represents the most accessible method to ensure uniform and persistent microbial coverage [ 27 , 28 , 68 , 69 ]. Moreover, the plant gets access to the beneficial microbe at the early stages of development, while the bacteria gain a head start in the competition for root colonisation [ 67 ]. In this work, seed coating was selected as the inoculation method and optimised for wheat and oilseed rape. For oilseed rape, the concentration selected was adapted after Lally et al. (2017) to 100% of bacteria at 0.8 OD 600 with 10 min of exposure to the inoculum, while for wheat, 4-h exposure to a concentration of 60% of bacteria inoculum showed the highest beneficial impact on seedlings development. This unique approach highlights the importance of optimising delivery methods even for single bacteria strains. With the delivery method selected for this study, the results suggest significantly increased seed yield for oilseed rape plants treated with EaOV14 when grown in controlled environmental conditions (10.8 ± 2.9 g of seed per plant compared to 9.47 ± 3.16 g of seed per plant for H 2 O and 8.95 ± 3.55 g of seed per plant for CSC control treatments). Nonetheless, further optimisation would be required to ensure successful field application, especially for winter crops where bacteria might lose efficiency after the vegetative stage during the winter months. When translated from lab to field, the lack of consistency represents the bottleneck of microbial plant biostimulants. Although the beneficial effect is highly successful under lab and glasshouse conditions, even when non-sterilised compost is used, the effects are often lost under field growing conditions [ 67 ]. This happens primarily because of the high variability and competition of the field environment alongside the soil's physical properties and reduced shelf life of the bacteria. Considering that E. adhaerens OV14 is a gram-negative bacterium, its viability on the seed could be compromised by drying processes [ 70 ] and shifts in temperature [ 71 ]. In this work, the inoculum formulation included 7% ¼ Ringer solution, an osmolarity regulator aiming to protect EaOV14 against desiccation [ 52 ]. This approach allowed EaOV14 to induce a higher vigour index of oilseed rape seedlings compared to the control, even after the coated seeds were stored for 14 days at 4 °C (data not shown). Some of the limitations that EaOV14 could face under field conditions could be overcome if a consortium including EaOV14 with other beneficial microorganisms were considered, their synergistic activities inducing beneficial effects on the target crop while maintaining cell viability under field conditions. Recently, Chaparro-Rodríguez et al. [ 72 ] showed that hydrogel encapsulation of several gram-negative plant growth-promoting bacteria allowed viability of up to 10 7 CFU/g capsules for up to three months of storage at 18 °C. Baliyan et al. [ 73 ] demonstrated that sugarcane straw ash conserves the viability of the consortium Ensifer adhaerens MSN12 and Bacillus cereus MEN8 for up to 12 months at ambient temperature. Taken together, it is clear that further work is required to elucidate the optimum approach that maximises the potential impact of E. adhaerens OV14 and its role as a biostimulant."
} | 4,880 |
31758021 | PMC6874579 | pmc | 8,970 | {
"abstract": "Nanoscale memristive phenomena are of great interest not only to miniaturize devices and improve their performance but also to understand the details of the underlying mechanism. Herein, we utilize conductive atomic force microscopy (C-AFM) as a non-invasive method to examine the nanoscale memristive properties of individual noble metal alloy nanoparticles that are sparsely encapsulated in a thin SiO 2 dielectric matrix. The measurement of current-voltage hysteresis loops at the level of individual nanoparticles, enabled by the nanoscopic contact area of the C-AFM tip, indicates reliable memristive switching for several hours of continuous operations. Alongside the electrical characterization on the nanoscale, the method of C-AFM offers the potential for in situ monitoring of long term operation induced morphological alterations and device failure, which is demonstrated at the example of nanoparticle-based devices with additional Cr wetting layer. The application of alloy nanoparticles as reservoir for mobile silver species effectively limits the formation of stable metallic filaments and results in reproducible diffusive switching characteristics. Notably, similar behaviour is encountered on macroscopic nanocomposite devices, which incorporate multiple stacks of nanoparticles and offer a high design versatility to tune switching properties and engineer scalable memristive devices with diffusive switching characteristics. No additional forming step is required for the operation of the presented alloy nanoparticle based memristive devices, which renders them very attractive for applications.",
"conclusion": "Conclusion In this work nanoscale memristive switching is examined in memristive thin film devices, which rely on noble metal alloy nanoparticles of the system AgAu or AgPt that are embedded in a SiO 2 dielectric matrix. Applying C-AFM as a non-invasive method and making use of the nanoscopic contact area of the tip, we studied the electrical characteristics at the level of individual nanoparticles and observed reliable memristive switching for several hours of continuous operations. In these nanoscale junctions, reliable diffusive memristive switching with a reasonably narrow distribution of SET and RESET voltages and clear operation window in between has been found. The observation of diffusive memristive switching implies that the formation of stable filaments and bipolar switching characteristics is efficiently suppressed by limiting the reservoir of potentially mobile silver species to the alloy nanoparticles. Besides the nanoscale electrical characterization, the method of C-AFM allows to monitor long term operation induced morphological alterations and device failure in situ , which is demonstrated at the example of nanoparticle-based devices with an additional Cr wetting layer. Herein, during continuous IV hysteresis measurement over a time period of two days, severe morphological alterations on the microscale originating from the migration and oxidation of Cr were detected by the C-AFM method. In addition to the investigations on memristive action in individual alloy nanoparticles, the concept of nanoparticle-based memristive switching was extended to nanocomposites featuring assemblies of multiple stacks of nanoparticles. Notably, the diffusive memristive properties were found to be preserved in such multi-stack devices and the respective switching voltages exhibit a narrow distribution and a clear operation window. Accordingly, the underlying concept of embedding alloy nanoparticles as reservoirs for mobile metal cations in a dielectric matrix possesses a high versatility, which makes it highly promising for the future design of forming-free memristive switches with tailored diffusive switching properties.",
"introduction": "Introduction With the postulation of the experimental realization of a memristor in 2008 1 , Strukov et al . related resistive switching phenomena in sub-stoichiometric oxide thin films to the theoretical model of a memristor as initially proposed by L. Chua in 1971 2 , and initiated a huge increase in research interest in this field. While the memristor as a fundamental element has been under severe debate recently 3 , the innovative power of the use of memristive switching phenomena remains unquestioned. Within the past decade, a broad variety of device concepts was reported in the context of memristive switching, which range from electro-chemical metallization (ECM) over valance change mechanism (VCM) and phase change materials (PCM) and beyond 4 – 7 . Memristive devices are commonly discussed as promising devices for an application as novel memory 8 , for beyond-von-Neumann logics 9 and in the context of neuromorphic engineering 10 – 14 . Among the various reported devices, different switching characteristics are commonly observed, including bipolar, unipolar and diffusive memristive switching 4 , 15 , 16 . While in the context of the application as memory device typically bipolar and unipolar switching characteristics are preferred, diffusive memristive devices offer the potential of being used as selector devices or as true random number generators 17 , 18 . Amongst the various device classes, special interest is paid to memristive devices relying on ECM, i.e. the reversible formation of a conductive path upon field-driven motion of mobile metal cations (e.g. silver cations) between two electrodes. Typical setup of such devices consists of a dielectric layer, which is sandwiched between two planar electrodes of which one serves as a reservoir for mobile metallic cations (e.g. Cu or Ag). The underlying mechanisms that lead to the reversible changes in resistivity trace back to local rearrangement of atoms and ions on the nanoscale, even in macroscopic memristive devices 19 . As such, recently there is a high interest to progress from planar electrodes towards nanoscale or nanostructured electrodes. In this context, inert Pt nanoparticles dispersed in SiO 2 matrix are discussed as efficient means to predefine switching channels and locally increase electrical fields and resistive switching is reported in networks of Au nanoparticles 20 , 21 . For an optimization of switching uniformity in ECM memristive devices, nanostructured electrodes (e.g. nanocones) have been successfully prepared and quantum-dot electrodes have been applied for well-defined local field enhancement at the nanoscale 22 – 25 . Instead of nanostructured bulk electrodes, also nanoparticles as reservoirs for the mobile metallic species are under investigation, e.g., Ag nanoparticles embedded in dielectric matrices such as a-Si, SiO 2 , TiO 2 , HfO 2 or MgO 15 , 18 , 26 , 27 . This transition towards nanoparticles for mediating memristive switching is a consequent step as it combines the advantages of local enhancement of the electrical field by the nanoparticles in the dielectric matrix and the pre-definition of the location of memristive switching. In this work, we substantially extend the concept of nanoparticle-based memristive switching by using gas phase synthesis of alloy nanoparticles and sequential deposition to prepare nanoparticles with controlled size, composition and coverage and embed them into a SiO 2 matrix in a controlled manner. Compared to earlier studies in this field, in which nanoparticles were mainly formed by self-organization in a co-deposition process, the gas phase synthesis approach offers the capability to independently vary filling factor and size of the nanoparticles. Moreover, the application of alloy nanoparticles instead of pure Ag NPs allows controlling filament formation by limiting the amount of mobile silver species while simultaneously the nobler alloy component may act as a stable anchor in the matrix for enhanced reliability. This work is devoted to the investigation of memristive switching at the level of individual alloy nanoparticles, which are embedded in a dielectric SiO 2 matrix. In such nanoscale arrangements, the thorough experimental assessment of memristive switching renders rather challenging. Although there are a variety of reports on observations of filament formation by in situ TEM 28 , the high demands on sample preparation as well as the resulting severe changes in sample surface and the considerable effect of electron beam irradiation on the electrical properties of dielectric matrices impose certain restrictions to such TEM methods in the context of memristive devices 29 . In this work, we apply a facile, non-invasive nanoscale method to study the memristive action at the level of individual nanoparticles and visualize in situ any possible structural degradation. In this method we utilize a conducting atomic force microscope (C-AFM) operated in a mixed feedback loop to measure the nanoscale current-voltage (IV) characteristics of nanoparticle-based memristive devices against both structural and geometrical variations. By using a sharp PtIr tip (of radius 2 nm) as scanning electrode, the C-AFM method proved to be advantageous to test the local properties of nanoparticle-based memristive devices as it allows to perform measurements on only one nanoparticle at a time. To ensure this possibility, the contact force between the tip and the sample must be kept below 1.2 nN during electrical measurements to yield contact area of roughly 7 nm 2 30 . Furthermore we report on the scalability of the nanoparticle-based approach towards multilayer nanocomposites and investigate limiting factors for device stability and reliability, such as the impact of adding an additional Cr contact layer. In the following sections, we first (section 2.1) discuss nanoscale memristive switching with diffusive switching characteristics as observed utilizing C-AFM method at the level of individual noble metal alloy nanoparticles. Moreover, to achieve robust memristive action, devices must be subjected to a stress test in order to find the conditions under which failure occurs. Interestingly, C-AFM offers the possibility to monitor in situ signatures of plastic deformation and the subsequent device failure, which will be studied in terms of device stability and degradation against prolonged operations especially for devices with a Cr wetting layer in section 2.2. Finally, in section 2.3 the feasibility of expanding the concept of nanoparticle-based memristive devices to multi-stack nanocomposites will be covered and we will show that the transition towards multi-stack nanocomposites is a versatile approach to design robust memristive devices while preserving the diffusive switching characteristics of individual nanoparticles.",
"discussion": "Results and Discussion In this work we investigate memristive switching relying on nanoparticle assemblies, which consist of noble metal alloy nanoparticles sandwiched between dielectric layers. The typical setup of individual SiO 2 /NP/SiO 2 stacks as well as multi-stack nanoparticle-based devices is depicted schematically in Fig. 1 . Figure 1 Schematic depiction of the typical setup of nanoparticle-based memristive devices in cross-sectional view, including approximate dimensions of the characteristic features. For a detailed assessment of memristive action of single nanoparticles, single stack SiO 2 /NP/SiO 2 devices (with and without an additional Cr wetting layer) are characterized by C-AFM. The transition towards multi-stack arrangements allowed for reliable contacting of nanoparticle-based memristive devices with macroscopic electrodes. As essential components, two types of noble metal alloy nanoparticles were investigated in the context of nanoparticle-based memristive switching, namely AgPt and AgAu nanoparticles. In both cases, the alloy nanoparticles exhibit a narrow size distribution with the mean diameter being roughly 11 nm (in case of AgAu) or 9 nm (in case of AgPt). TEM bright field micrographs of the respective AgAu and AgPt NPs are depicted in Fig. S1 in the supplementary data. The composition of the respective nanoparticles was determined by XPS (as depicted in Fig. S2 in the supplementary data) and the quantification yields a mole fraction of Ag of roughly 0.33 in case of AgAu nanoparticles and 0.73 in case of AgPt nanoparticles. More detailed investigations on AgAu nanoparticles deposited by an identical approach are shown in previous work 31 . Single nanoparticles for diffusive memristive switching Based on the aforementioned alloy nanoparticles, single SiO 2 /NP/SiO 2 stacks were prepared and the electrical characteristics were recorded by C-AFM technique at the location of individual nanoparticles. The following discussion is devoted to the memristive switching properties of AgPt NPs in a SiO 2 /AgPt NP/SiO 2 stack (nominal thickness of bottom and top oxide layer is 8 nm and 2 nm respectively), which is chosen as an example to illustrate the diffusive memristive switching behaviour observed in alloy NPs. The IV characteristics of this device are depicted in Fig. 2 . A representative hysteresis loop of a full switching cycle is depicted in Fig. 2(a) . Continuous measurements of 70 consecutive switching cycles are shown in Fig. 2(b) . Figure 2 Diffusive memristive switching is observed by AFM measurements on an individual AgPt nanoparticle using a conductive tip. In a single hysteresis loop ( a ) the device shows a SET (switching towards LRS) and RESET (switching towards HRS) event for both, positive and negative polarity. For the reliable determination of the respective switching voltages, the current threshold of 5 nA is selected for a SET and 0.5 nA for a RESET. The comparison of 70 consecutive hysteresis loops ( b ) implies a certain distribution of the respective switching voltages. The individual hysteresis cycles are colour coded (first cycles: red colour, last cycles: blue colour). The IV characteristics as depicted in Fig. 2(a) exhibit diffusive memristive switching (also termed threshold switching), thus for both polarities there is a transition from HRS to LRS (SET) and from LRS to HRS (RESET) and upon zero crossing, the device always is in its HRS. The full hysteresis loop of such nanoparticle-based memristive device can be described as follows: In the initial state without bias, the nanoparticle device is in its HRS, which results in a current in the order of 100 pA, corresponding to the limit of detection. Upon increasing the voltage to a certain threshold, the device switches to its LRS and the IV curve is mainly dominated by the serial resistance of 101 MΩ (applied in order to limit the current through the C-AFM tip). When the applied voltage is subsequently reduced, the LRS is preserved until reaching a certain threshold voltage at which the device switches back into its HRS. A similar diffusive switching cycle with transitions from HRS to LRS and vice versa is observed at reversed polarity. In the following evaluation of the statistics of multiple cycles of diffusive memristive switching, the corresponding switching voltages are referred to as “SET+” and “RESET+” or “SET−” and “RESET−” for positive and negative polarity respectively. In contrast to the diffusive memristive switching observed in individual alloy nanoparticles, the IV characteristics recorded on a pure SiO 2 layer exhibits no indication for any switching event (cf. Fig. S6 ). The origin of this diffusive memristive switching is expected to be related to the mechanism of electrochemical metallization (ECM) 32 . In the presence of an electrical field silver cations are released from their reservoir (in this case the individual nanoparticle), are transported through the SiO 2 matrix and form a metallic filament upon being reduced. Due to the nanoscopic thickness of dielectric layer, even the limited amount of mobile silver species released from a single nanoparticle allows for the formation of a metallic filament, describing the transition from HRS to LRS above a certain threshold voltage. For a thorough explanation of the RESET step, two aspects have to be considered. On the one hand, in case the nanoparticle-based device is in its LRS, a conductive filament is formed across the device and the potential drop is mainly over the serial resistor, which is applied to limit the current in the C-AFM measurement (cf. Fig. S9 ). The current flow through the metallic nanoparticle-based connection results in Joule heating and electromigration, which is typically associated with a RESET due to rupture of the metallic filament. On the other hand, the incorporation of alloy nanoparticles instead of bulk electrodes limits the amount of available silver species. Consequently, in our nanoparticle-based memristive devices the filament cannot grow to the full extent and is inherently unstable, which results in diffusive memristive switching. This is in contrast to conventional ECM devices relying on bulk electrodes, which offer an (almost) unlimited reservoir of mobile silver species and typically exhibit stable bipolar memristive switching. Recently, Wang et al . reported a significant dependency of the filament lifetime on the diameter of the metallic filament, which is mainly motivated by the disintegration of a thin filament due to surface diffusion 33 . Similarly, our nanoparticle-based device can be put into the context of these considerations on filament lifetime by using the following assumptions: In case of a AgPt nanoparticle with a mole fraction of silver of roughly 0.73 and a diameter of 9 nm and a dielectric thickness of 8 nm would result in a filament diameter (under the assumption of a cylindrical filament) of less than 2.3 nm, which would result at zero bias, following the argumentation of Wang et al . 33 , in a filament lifetime of less than some tens of microseconds. Realistically, due to entropic considerations (entropy of mixing) it is unlikely that the whole amount of silver would be released from the respective nanoparticle and it is expected that the filament does not form in a perfectly cylindrical shape with constant diameter. Accordingly, the diameter and consequently the lifetime of the real filament are expected to be even lower, which immediately explains the observed diffusive switching and the instability of the LRS in the low voltage regime. The IV characteristics were recorded at the location of an individual nanoparticle for 70 consecutive hysteresis cycles and are depicted in Fig. 2(b) . In general, diffusive memristive switching is observed for each cycle and the respective switching voltages for the SET and RESET switching are distributed over a certain range. For a proper evaluation of the statistical distribution of switching voltages, the SET and RESET voltages are defined as the voltage at which the current raises above 5 nA or falls below 0.5 nA respectively. Based on these evaluation criteria, the switching voltages are extracted from the 70 hysteresis loops and are depicted by means of a cumulative switching probability plot (a) and a histogram (b) in Fig. 3 . Figure 3 Statistical evaluation of the switching voltages obtained from 70 consecutive hysteresis loops measured for a SiO 2 /AgPt NP/SiO 2 stack. The probability plot ( a ) and histogram ( b ) shows a general trend of higher SET voltages for positive polarity. In general, the SET+ voltage (3.60 ± 0.42 V) is shifted to higher voltages and exhibits a narrower distribution compared to the corresponding SET− process at opposite polarity (−2.65 ± 0.57 V). The observation of a higher SET+ voltage is in line with the expectation based on the asymmetry of the SiO 2 separation layers (8 nm and 2 nm as bottom and top layer respectively). The histogram of the distribution of switching voltages implies that there is a clear separation between the SET and RESET voltages, especially at positive polarity. Within this operation window, both resistance states (LRS and HRS) are stable and the presence of a particular state depends on the history of applied voltage. Considering an interval of three standard deviations (1.26 V for SET+ and 0.54 V for RESET+) around the mean values (3.60 V and 0.62 V respectively), the corresponding operation window exhibits a width of 1.18 V with 99.7% confidence (under the assumption of a Gaussian distribution of the respective switching voltages). Essentially, memristive switching on the basis of individual alloy nanoparticles was observed to be stable and reproducible switching behaviour was detected for many consecutive cycles by C-AFM method. For illustration, the switching voltages (as extracted from the individual hysteresis measurements) corresponding to 2000 consecutive cycles of a representative measurement on the SiO 2 /AgPt/SiO 2 stack are depicted in Fig. 4 . In general, the switching voltages are found to be statistically distributed as described in detail for 70 cycles in Fig. 3 . In addition, for a small number of cycles (e.g. around cycle 1100), no memristive switching was observed and the detected switching voltages consequently turn out to be very low. A representative IV hysteresis loop for a cycle without distinct switching events is shown in Fig. S10 . These occasional deviations in memristive behaviour may be attributed to the limitations of the C-AFM measurement, which is operated at ambient atmosphere and temperature. However, more importantly, no time-dependent, systematic drift of the switching voltages is observed, which indicates the high stability of memristive switching based on individual noble metal alloy nanoparticles. Figure 4 Overview over the switching voltages as extracted from individual hysteresis loops for 2000 switching cycles in a SiO 2 /AgPt/SiO 2 stack, measured by C-AFM on an individual AgPt nanoparticle. While occasionally variations in the switching voltages occur due to limitations of the AFM setup (room temperature, ambient air), no systematic drift is observed. Considering the insights gained by C-AFM measurements, nanoparticle-based memristive switching appears highly promising in the context of designing memristive devices with diffusive switching characteristics. For this purpose, two main design routes will be explored in the next sections, namely (1) the incorporation of a Cr wetting layer for a better conformity of the dielectric layer and (2) the transition towards multiple stacks of nanoparticles allowing for additional degrees of freedom for tailoring the switching parameters. Long-term stability of nanoparticle-based memristive switching in the presence of a Cr wetting layer In thin film technology, transition metals such as Cr or Ti are widely applied to enhance the adhesion between different materials like SiO 2 and Pt. In order to investigate the impact of the addition of a Cr layer on the electrical properties, a Cr/SiO 2 /AgPt/SiO 2 thin film stack with SiO 2 separation layer thickness of 2 nm was characterized by C-AFM. Over the whole measurement period of two days, IV hysteresis loops were recorded continuously and exhibited qualitatively similar behaviour (cf. Fig. S3 in supplementary data for a comparison of hysteresis loops recorded within the first hour and after two days). While the electrical characteristics are preserved, severe morphological alterations of the nanoparticle thin film are observed. Initially, the surface is smooth and does not exhibit significant irregularities regarding roughness and topography. After the two-day measurement, a severe structural deformation is observed (Fig. 5 ), ranging with a radius in the order of 20 µm around the location of the tip. Within this area there are two dominating features: A dome-like elevation is located at the centre (red and yellow colour, diameter of roughly 20 µm) and radially surrounded by fluctuating height distributions (diameter of roughly 40 µm). Considering the nanoscopic size of the AFM tip, such morphological modifications on the microscale are particularly surprising. Figure 5 Morphological alterations of the thin film surface on the micrometre scale are induced by the migration of chromium during a two-day continuous IV-hysteresis measurement: The AFM topography map ( a ) as well as the corresponding SEM top view micrograph ( b ) indicate severe changes of the thin film morphology on a circular area with a diameter of roughly 40 µm. The migration and oxidation of Cr is revealed as the origin of these structural changes by SEM EDX spectroscopy maps ( c ) of a selected area (black rectangle). In order to uncover the origin of these morphological changes, SEM and SEM EDX were applied to image and characterize the respective region. The overall appearance of the structural deformation as observed in AFM topography map is well reproduced in the SEM top view micrograph (Fig. 5(b) ). A selected rectangular region, containing the dome-like structure (left) as well as the radial fluctuations (middle) and an undisturbed region (right) was investigated by SEM EDX. The occurrence of the elements oxygen, chromium and gold is depicted in terms of elemental maps in Fig. 5(c) (high colour saturation corresponds to high signal). While the dome-like structure shows strong signal corresponding to Cr and O and considerable signal corresponding to Au, the undisturbed region contains Cr and Au, but considerably less O. The presence of signal corresponding to Au is attributed to the conducting thin film stack on the substrate, which mainly consist of Au. Within the intermediate region, the stripe-like features correlate to a radial depletion of Cr. Within this region, the strong Cr and O signals overlap. Judging from the results of SEM EDX investigations, the morphological changes are attributed to the migration and oxidation of Cr, which is brought to the surface of the Cr/SiO 2 /AgPt/SiO 2 thin film stack in the form of chromium oxide and results in the dome-like feature as well as the radial height fluctuations. Notably, these morphological alterations evolve over time. While in the early stages (e.g. after one hour of continuous IV hysteresis measurement) already first indications of dome-like features are present (see AFM topography map in Fig. S3(a) in supplementary data), the radial features are growing at later stages. Alongside a steady change in the morphology, the electrical characteristics are qualitatively preserved over the whole measurement period of two days (as shown in Fig. S3(b,c) in Supplementary Data). Representative consecutive hysteresis loops for two thin film stacks with either AgPt or AgAu nanoparticles are depicted in Fig. S4 in the supplementary data. In contrast to similar stacks without Cr wetting layer, in these devices no diffusive memristive switching is observed within the investigated voltage range. The respective hysteresis loops remind of a typical cyclic voltammetry measurement and exhibit a non-zero crossing (no pinched hysteresis) as well as several peaks corresponding to oxidation and reduction processes. Although qualitatively the overall shape of the IV hysteresis loop remains similar for consecutive cycles, changes in peak position and height of the individual peaks are strong indications for instabilities and can be related to a change in active area due to the reported morphological alterations. In essence, at the example of long-term measurement induced migration of Cr, C-AFM has proven as an efficient method to monitor device stability and degradation during prolonged operations. Due to the detected instability, the wetting layer of Cr is not considered to be feasible for the development of multi-stack memristive devices as described in following section. Memristive switching in multiple stacks of nanoparticles The scalability of memristive switching devices is one key aspect concerning hardware implementation. The nanoscopic dimensions of the individual SiO 2 /NP/SiO 2 layers (with the dielectric being only a few nanometres thick) make reliable contacting by conventional probes very challenging. Thus, we expand our investigation from single nanoparticles towards multi-stack devices, which consist of multiple stacks of nanoparticles embedded in a dielectric SiO 2 matrix. The transition from individual layers towards multiple stacks results in an increase in overall device layer thickness and consequently reduces the risk of short circuiting by pin holes or due to mechanical failure (pinching). The multi-stack samples discussed in this section comprised of 5 layers of individual AgAu and AgPt nanoparticles separated by thin SiO 2 layers in between. While in case of the AgAu NP multi-stack device the nominal layer thickness of the separating SiO 2 layers was selected to be 2 nm, the AgPt NPs were nominally separated by 4 nm of SiO 2 . The different SiO 2 separation layer thickness was chosen due to the difference in the silver concentration in the respective nanoparticles. Accordingly, for the design of a multi-stack device relying on nanoparticles two general degrees of freedom open up: On the one hand the composition of the respective alloy nanoparticles and on the other hand the width of the dielectric separation layer, which is deposited in between the deposition of the individual nanoparticle layers, can be tailored. For the electrical characterization of the multi-stack devices, the top contact was realized by a soft Pt wire (combined with a serial resistance of 1 MΩ, see method section). As the Pt wire has a diameter of 125 µm, the effective contact is expected to be significantly larger than in case of the C-AFM investigations on single nanoparticles. Thus, the contact area expands from individual nanoparticles (in case of C-AFM measurements) towards a larger nanoparticle assembly. However, as shown in Fig. 6 , the corresponding multi-stack devices featuring AgAu (a) and AgPt (b) nanoparticles show similar diffusive memristive switching, which demonstrates that upon upscaling from single nanoparticles to a multi-stack device the fundamental switching characteristics are preserved. Interestingly, no distinct electroforming step at higher voltages is required to initialize memristive switching in the nanoparticle-based devices, which underlines their application potential. For both, the AgAu and AgPt nanoparticle-based device, the IV hysteresis loops exhibit reproducible diffusive memristive switching over multiple consecutive cycles with a narrow distribution of the SET and RESET voltages, which underlines the fact that macroscopic contact hosts large number of independent nanoscale memristive devices. A closer look at the distribution of the switching voltages (cf. histograms in Fig. 6 ) indicates for both devices a distinct separation between the SET and RESET, which results in a stable operation window. The main differences between the AgAu and AgPt multi-stack device are found in the HRS resistance and the magnitude of the switching voltages. Figure 6 Multi-stack nanoparticle-based memristive devices relying on AgAu (left) and AgPt (right) nanoparticles exhibit diffusive memristive switching characteristics. ( a ) The switching characteristics are depicted for 20 consecutive cycles (top) of an AgAu nanoparticle device with 2 nm SiO 2 separation layers. The corresponding histogram (bottom) shows a narrow distribution of SET (around 0.89 V) and RESET (around 0.23 V) voltages with a clear separation in between. ( b ) For a AgPt nanoparticle-based multi-stack device with SiO 2 separation layers of 4 nm each, the switching characteristics are depicted for 60 consecutive cycles (top) and the corresponding histogram (bottom) shows a narrow distribution of SET (around 0.61 V) and RESET (around 0.32 V) voltages with a clear separation in between. While the AgAu device exhibits a HRS resistance in the order of 70 MΩ, a much higher resistance is observed for the AgPt device (current in HRS is below limit of reliable detection). This difference can be attributed to the SiO 2 separation layer thickness, which is 2 nm in case of the AgAu device and 4 nm in case of the AgPt device. While the switching voltages observed for the AgAu device are around 0.89 ± 0.06 V (SET) and 0.23 ± 0.03 V (RESET), the AgPt device exhibits a lower SET voltage around 0.61 ± 0.03 V and a higher RESET voltage around 0.32 ± 0.03 V. A comprehensive overview over the evaluated switching voltages is given in Table S1 in the supplementary data. Considering the higher SiO 2 separation layer thickness in case of the AgPt device, the observed trend in the SET voltage at first glance seems rather counterintuitive, as the higher separation width is expected to result in a lower electrical field at identical applied voltage. However, the availability of Ag in case of AgPt nanoparticles (with Ag mole fraction of roughly 0.8) is much higher than in the AgAu device (with Ag mole fraction of roughly 0.3). Accordingly, the higher availability of silver species facilitates the filament formation (and as such the SET process). In a similar approach, Wang et al . recently reported diffusive memristive switching in MgO x :Ag, SiO x N y :Ag and HfO x :Ag thin films, which were fabricated by co-sputtering in reactive atmosphere, and attributed the instability of the LRS to the coalescence of individual nanoparticles due to a minimization in surface energy 15 . The diffusive memristive switching characteristics of the multi-stack devices are very well competitive to these devices, especially with respect to the distribution of switching voltages as well as the operation window and switching stability. Unlike the multi-stack nanoparticle-based memristive devices, diffusive memristive devices prepared by Wang et al . incorporate Ag as mobile species in pure Ag nanoparticles, which are most likely formed by self-organization during co-sputtering. Following the concept of multi-stack nanoparticle-based memristive devices as reported in this work, the individual alloy nanoparticles as building blocks are already fully formed in the gas phase with a well-defined composition and size synthesis and are subsequently embedded into the dielectric, which grants multiple degrees of freedom (e.g. tailored filling factor and alloy composition) in the design of memristive devices."
} | 8,558 |
37890135 | PMC10647011 | pmc | 8,971 | {
"abstract": "Genetic engineering allows fine-tuning and controlling\nprotein\nproperties, thus exploiting the new derivatives to obtain novel materials\nand systems with improved capacity to actively interact with biological\nsystems. The elastin-like polypeptides are tunable recombinant biopolymers\nthat have proven to be ideal candidates for realizing bioactive interfaces\nthat can interact with biological systems. They are characterized\nby a thermoresponsive behavior that is strictly related to their peculiar\namino acid sequence. We describe here the rational design of a new\nbiopolymer inspired by elastin and the comparison of its physicochemical\nproperties with those of another already characterized member of the\nsame protein class. To assess the cytocompatibility, the behavior\nof cells of different origins toward these components was evaluated.\nOur study shows that the biomimetic strategy adopted to design new\nelastin-based recombinant polypeptides represents a versatile and\nvaluable tool for the development of protein-based materials with\nimproved properties and advanced functionality.",
"conclusion": "4 Conclusions A new ELP sequence was\ndesigned and fabricated to improve cyto-\nand tissue compatibility and to extend the feasibility of this class\nof recombinant biopolymers and derived materials to the veterinary\nfield while maintaining typical thermoresponsive properties. The new\nUELP construct was successfully prepared, and the expression product\nwas characterized, focusing on the comparison of its physicochemical\nbehavior to that of the previously described biopolymer HELP. Our study highlights the effect of elastin-like sequences mimicking\nthe different hydrophobic domains of human elastin interspersed with\nthe cross-linking domains, leading to the realization of biomimetic\nelastins that, in addition to phase transition properties, exhibit\nsignificantly different features in thermoresponsive behavior. These\nresults indicate that our recombinant platform is a valuable tool\nto further elucidate the physicochemical properties of elastin and\nrelated sequences. The new UELP polypeptide showed an improved\nability to promote\nthe adhesion of cells from different origins to nonadhesive surfaces\ncompared to the biopolymer HELP. Overall, our system, which ensures\ntight control over the bioinspired structure of the polypeptides,\nprovides a powerful means to analyze how the extracellular environment\ncan influence and potentially control cell response. These results\ndemonstrate that our approach can lead to the production\nof biomimetic components that have at least two valuable aspects that\ncan be exploited. One relates to their application for the development\nof biocompatible materials with advanced functionality, and the other\nrelates to their use as specific and customizable tools to study and\nelucidate the interaction at the interface of materials and biological\nsystems at the molecular level.",
"introduction": "1 Introduction Elastin is one of the\nmain structural components of tissues that\nundergoes countless cycles of expansion and contraction during the\nlifetime of vertebrates. For this reason, it represents a valuable\nmodel to get inspiration for the design and realization of biomaterials\nwith advanced functionality and properties. 1 Elastin-like polypeptides (ELPs) are recombinant proteins\nmodeled\nafter elastin, mimicking its repetitive structure. Resembling the\nbovine elastin exon 18 sequence, the ELPs are constituted by long\nstretches of the regularly repeated VPGVG pentapeptidic motif, which\nis responsible for the outstanding inverse phase transition behavior\nthat characterizes elastin and these polypeptides. 2 In the past decade, our group focused on the human\nelastin homologue\nthat shows a regularly repeated stretch of hexapeptidic rather than\npentapeptidic motifs, these last being less represented and interspersed\nthroughout its primary structure. With the aim to realize something\nbetween a protein and a polymer, following a biomimetic approach,\nwe adopted the exon 23 and 24 amino acid sequences as the basic monomer\nto be reiterated. The former corresponds to a cross-linking domain,\nand the latter consists of the repeated hexapeptidic VAPGVG stretch,\nresulting in the human elastin-like polypeptide (HELP) family. 3 These versatile biopolymers were described and\ncharacterized, and a method to obtain a hydrogel matrix was set up. 4 HELP was also further modified by clonal fusion\nwith different bioactive domains, representing a valuable carrier\nto increase the yield of difficult-to-express or active peptides. 5 The HELP and its modifications showed no pro-inflammatory\nactivity and good cytocompatibility, especially toward myoblast cells. 5a , 6 However, cell-type-dependent adhesion on HELP-based substrates was\nobserved. 6 , 7 Although the HELP-derived hydrogel matrices\nshowed no cytotoxicity, the cell adhesion on the HELP-based scaffold\nwas improved by the addition of pro-adhesive sequences. 6 , 8 Moreover, some issues may arise because the HELP elastin-like sequence\ncharacterizing the human homologue may elicit an immune response in\nother organisms, like animal models being used to evaluate the compatibility\nof biomaterials where this sequence is not present. 9 For example, antibodies that recognize the VAPGVG motif\nwere successfully raised in mice. 10 Last,\nthe chemotactic activity of this same motif is well-known, 11 and this should be considered for the development\nof new biomaterials intended for prolonged contact with tissues and\norgans. The perspective to broaden the compatibility toward as many\ncell types as possible and, more generally, toward different organisms\nstill maintaining immunotolerance and the potential as carrier fusion\npartners delineated our approach. Thus, to further extend the properties\nof the biopolymer and, hence, those of the derived materials, we undertook\nthe assembly of a new ELP biopolymer. In this paper, we describe\nthe design of the sequence and the production\nof this construct, as well as its physicochemical characterization.\nThe behavior of this biopolymer was compared with that of the previously\ndescribed HELP prototype by analyzing it with different techniques,\nsuch as turbidimetric analysis, circular dichroism, dynamic light\nscattering, and nuclear magnetic resonance. The response of cells\nto surfaces conditioned with these recombinant biopolymers was also\nevaluated.",
"discussion": "3 Results and Discussion 3.1 Structure of the Recombinant Biopolymers Inspired\nby Human Elastin The design of new human elastin homologues\nstarted almost two decades ago, and it was initiated with a view to\nprepare materials with advanced functionality based on components,\npossibly combining some features of the synthetic polymers, like the\nvery regular structure and the controlled composition, with those\nof the living organisms, like the biotic origin. Back then, collagen\nwas a well-established paradigm, while elastin and the pentapeptidic\nmotif showing temperature-dependent inverse phase transition behavior\nwas an emerging model. 2b 15 At the time, most of the studies\nwere undertaken to adopt a “reductionist approach” since\neach elastin exon encodes an independent domain with its own structure\nso that it could be studied and characterized by the use of synthetic\npeptides resembling its sequence. 16 However,\nthe opportunity to reiterate the same domain in long chains offered\nby genetic engineering allowed us to magnify the physicochemical features\nof a single domain, especially regarding thermoresponsive behavior. 17 Thus, following a biomimetic strategy,\nBandiera and co-workers focused their attention on the most regularly\nrepeated region of the human elastin homologue. At difference with\nmost of the other elastin-like polypeptides described in the literature\nat the time, a construct comprising both the cross-linking domains\nas well as the hydrophobic domains was produced to obtain an ELP biopolymer\nbetter resembling the elastin structure. This construct was named\nHELP (human elastin-like polypeptide). 12 To characterize the physicochemical properties, a second prototype\nwas also produced 3 as a reference more\nclosely related to most of the other described ELPs, which were composed\nof just long stretches of pentapeptidic repeats without any cross-linking\ndomain. 18 VAPGVG, the hexapeptide-based\nhydrophobic HELP domain characterizes the primate elastins, 9 and recently, these sequences were described\nto improve skin elasticity and reduce wrinkles. 19 However, the hexapeptidic motif and its permutations are\ndescribed as matrikines. 20 Although the\nHELP turned out to be a valuable component in obtaining hydrogel matrices\nand a versatile carrier for bioactive domains, this factor may limit,\nto some extent, the applications of this biopolymer. For this reason,\na more accurate analysis of the elastin sequence led to the selection\nof another monomer to build a construct that overcomes these constraints\nwhile maintaining the desired properties. The attention was focused\non a regularly repeated as well as much conserved hydrophobic domain\namong the different organisms in the view of producing a new human-based\nelastin-like polypeptide with broad compatibility and robust immune\ntolerance while maintaining the potential as a carrier fusion partner.\nAligning several vertebrate elastin amino acid sequences, a highly\nconserved region is observed, corresponding to part of the exon 26\nof the human homologue, which is shown in Figure 1 . Figure 1 Comparison of part of the exon 26 sequence of\nelastins from different\nspecies. (A) Porcine (XP_020941438.1), ovine (XP_042096308.1), bovine\n(AAA30505.1), feline (XP_019676153.1), canine (XP_048967017.1), murine\n(NP_031951.2), rat (NP_036854.1), and human (AAC98395.1) homologues\nare aligned. In gray are the residues that are the most conserved\namong these species and that represent the consensus sequence for\nthis region. Boxed, the pentapeptidic motif is followed by a tetrapeptidic\nblock, thus forming the nonapeptidic repeat that characterizes this\nregion. (B) Sequence of UELP hydrophobic domain. Gray, residues corresponding\nto the consensus; black, residues that are found in the human sequence\nand were maintained; white, residues that correspond to the consensus\nand differ from those of the human sequence and that were maintained\nto enhance the regularity of the repeated sequence; italics, motifs\nthat were repeated to obtain a 50 amino acid domain; boxed, the elastin\npentapeptidic repeats. Comparing the sequences, a consensus of 40 amino\nacids, differing\nin only five positions with respect to the human sequence, can be\noutlined, evidencing a nonapeptidic repeat composed of the pentapeptidic,\nVPGL/FG, and the tetrapeptidic, L/VGAG, motifs ( Figure 1 A). Interestingly, exon 26 was described\nto have a dominant role in the temperature-driven self-assembly of\nelastin. 21 On this basis, a 50 amino acid\nrepeated sequence identical to the human one except for three positions\nand one additional nonapeptidic repeat was designed, maintaining the\nsame length of the HELP hydrophobic domain ( Figures 1 B and 1S ). Adopting\nthe same sequence of the HELP cross-linking domains, a new gene that\nwas named “universal” ELP (UELP) with eight reiterated\nmonomers and a length comparable to that of HELP was assembled. In Figure 2 A, the schematic\nprimary structures of the two recombinant biopolymers derived from\nhuman elastin are compared. They represent a system that allows the\namino acid sequence ( Figure 1S , Supporting\nInformation) to be correlated with the behavior of the biopolymer\nas well as with the features of the derived materials and with any\nbiological interaction. Figure 2 Comparison of the structure of the polypeptides\ninspired by the\nelastin human homologue. (A) Schematic representation of the primary\nstructure of the UELP and HELP recombinant proteins. Black, his-tag;\ngray, cross-linking domains; and white, hydrophobic elastin-like domains.\n(B) Prediction of the secondary structure of the two biopolymers obtained\nby I- TASSER simulation. Purple, coil; light blue, helix; and gray,\nβ-strand. 3.2 Macromolecular Features of UELP The\ndistribution of secondary structures in the UELP polypeptide was predicted\nusing GOR IV based on the amino acid sequences. The results, compared\nwith those obtained for HELP, are shown in Figure 2 B and Table 1 . Table 1 Comparison of the Main Parameters\nand Distribution of Secondary Structures of UELP and HELP Biopolymers\nas Predicted Using GOR IV Based on Amino Acid Sequences pI a.a. Mw % polar a.a. % charged\na.a. α % β % rc % UELP theor 11.7 520 43050 2 4.5 25 24 51 CD 17 23 60 HELP theor 11.7 536 44885 2 4.3 26 4 70 CD 29 10 61 An average α-helix content of 25% for the UELP\nsequence,\nvery close to the corresponding value for the HELP one, was predicted\nsince, in both biopolymers, the polyalanine stretch is present in\nthe cross-linking domains ( Figure 1S ).\nBased on the same calculations, the hydrophobic domains of UELP were\npredicted to have a mixed, partially disordered structure consisting\nof 24% β-sheet and 51% random coil regions. The β-sheet\nfraction of the UELP sequence is significantly higher than that calculated\nfor HELP (4%), which rather possesses a higher fraction of random\ncoil sequences (70 vs 51% of UELP). For both biopolymers, it was predicted\nthat β-sheets occur only in the hydrophobic regions (gray fractions\nin Figure 2 B). Table 1 also shows\nthe distributions of secondary structures for the UELP and HELP biopolymers\nobtained by deconvolving the spectra of CD measured below the T t ( Figure 3 A,B, blue line), showing consistency between theoretical\nand experimental data. 22 Typical negative\nbands around 200 and 222 nm (ππ* and nπ* transitions,\nrespectively) were observed. The difference between UELP and HELP\nin the CD signal, mainly around λ = 207 nm ( Figure 3 ), is likely due to the large\npositive contribution of the β-structure/β-turns domains\nof the UELP sequence compared to HELP ( Table 1 ), which resulted in a band with a less negative\nvalue (cf. Figure 3 A with 3 B, blue lines). Interestingly, the\nUELP biopolymer spectra showed a marked dependence on temperature\n( Figure 3 A) with a\nsignificant increase of [θ] above the T t temperature (>20 °C). This is likely due to the stabilization\nof the β-structure assembly after the water removal. On the\ncontrary, this trend is not evident for the HELP biopolymer since,\nincreasing the temperature, the CD spectra remained relatively constant,\nsuggesting a predominantly random coiled structure of the hydrophobic\ndomain ( Figure 3 B). Figure 3 CD spectroscopic\nanalysis of the two elastin-inspired polypeptides\nUELP (A) and HELP (B) at a concentration of 0.1 mg/mL as a function\nof temperature: blue line: 15 °C; purple line: 20 °C; green\nline: 35 °C; orange line: 40 °C; and red line: 45 °C. A snapshot of the two UELP and HELP protein structures\n( Figure 4 ) was generated\nusing\nmultidomain I-TASSER-MTD algorithms on the online platform server. 23 The high-quality three-dimensional (3D) model\npredictions of the proteins were calculated by deep-learning contact-map\nprediction and multiple threading alignments starting from the primary\nstructure. Figure 4 clearly shows the larger proportion of β sheet domains of\nUELP compared to the HELP polypeptide, resulting in a more compact\nstructure, as also supported by the calculated average gyration radii, R G , from the structures obtained in I-TESSER-MTD\nsimulations, which give R G = 7.3 and R G = 9.0 nm for UELP and HELP, respectively. Figure 4 Model\nof the minimized secondary structure of UELP and HELP obtained\nby the I-TASSER – MTD simulation. 3.3 Physicochemical Properties of UELP and HELP 3.3.1 Turbidimetric Analysis The inverse\nthermal transition of UELP in solution was studied by turbidimetric\nand calorimetric measurements, comparing its behavior with that of\nthe polypeptide HELP in the absence and presence of a nearly physiological\nsalt concentration. It is known that the presence of cross-linking\ndomains among the hydrophobic sequences of elastin strongly influences\nits thermoresponsive behavior. A near-physiological NaCl concentration\nis required for optimal coacervation of these types of primary structures. 2b , 7 , 24 On the other hand, for ELPs,\nwhich in most cases do not have cross-linking domains, the addition\nof salt lowers T t , so this condition is exploited for the\npurification of these polypeptides. 15 , 18 , 24b , 25 Thus, salt concentration\nlikely plays an awkward role in modulating the phase transition of\npolypeptides that have alternating hydrophobic and cross-linking domains\nin their sequence, mimicking the primary structure of elastin. The\nhydrophobic folding and self-assembly processes of UELP and HELP were\nfollowed at a specific temperature scanning rate, as described in Section 2 . Figure 5 shows the results of the turbidimetric\nanalysis of UELP compared to the biopolymer HELP, which was previously\ncharacterized. 7 Figure 5 Turbidimetric analysis\nof the human elastin-derived biopolymers\nas a function of temperature. UELP (A) and HELP (B) were solved at\n2 mg/mL in 10 mM Tris buffer (open symbols) and in Tris/NaCl (solid\nsymbols). Cooling turbidity profiles (in blue) were analyzed in Tris/NaCl\nbuffer. Strikingly, in the absence of salt, the 2 mg/mL\nUELP biopolymer\nsolution ( Figure 5 A,\nopen symbols) shows a negligible turbidity variation. The T t of about 27 °C was determined by fitting\nthe transition curve with a Boltzmann sigmoidal function. On the other\nhand, the HELP sample shows an increase in turbidity of the solution\nwith a T t of 32 °C under the same\nconditions ( Figure 5 B, open symbols). The addition of 0.15 M NaCl to the UELP biopolymer\nsolutions resulted\nin a significant and sharp increase in turbidity at a T t of approximately 22 °C ( Figure 5 A, filled symbols), indicating full recovery\nof the transition phase property. In the case of HELP, the addition\nof a near-physiological salt concentration tended to increase the T t to about 35 °C ( Figure 5 B, filled circles). However, this is\nconsistent with our previous observation on dilute\nsolutions of the biopolymer HELP. 7 A polypeptide\nconsisting of the same HELP hydrophobic hexapeptidic sequences but\nlacking the cross-linking domains showed significantly higher T t with respect to HELP and was not affected\nby the addition of a near-physiological salt concentration. 7 In contrast, the addition of the same salt concentration\nto the HELP solution resulted in an increase in T t , suggesting that HELP, once the effect of the presence\nof the cross-linking domains is attenuated by a near-physiological\nsalt concentration, tends toward the T t of the sequence without the cross-linking domains. 7 The behavior of the UELP biopolymer was markedly\ndifferent from\nthat described above for HELP, suggesting that the presence of the\ncross-linking domains alternating with the elastin-like regions based\non the nonapeptide repeats of exon 26 had a dramatic effect that nearly\nabolished the ability of UELP to phase transition. However, the addition\nof salt at near-physiological concentrations fully restored the thermoresponsive\nbehavior of the UELP biopolymer, which exhibited a sharper transition\nat a much lower T t with respect to that\nof HELP, confirming that this salt concentration is essential to avoid\nhampering the temperature transition process of the elastin-like sequences\nin the presence of the cross-linking domains. The reversibility of\nthe phase transition of UELP and HELP was analyzed in the presence\nof a near-physiological salt concentration by cooling the samples\nafter the transition. A clear difference between the two biopolymers\ncan also be seen in this process ( Figure 5 A,B, see the blue lines). In the case of\nUELP, the curve obtained by cooling almost overlaps with the aggregation\ncurve, while HELP heating and cooling ramps lead to two different,\nless steep curves that exhibit some hysteresis, suggesting a more\nstable supramolecular configuration as a function of temperature. Taken together, these results indicate different self-assembly\nbehaviors of the two biopolymers. The sharper transition of UELP and\nits prompt reversal compared with the slower HELP turbidity increase\nwith hysteresis during cooling suggested two different aggregation\nand dissolution mechanisms. The observed different values of the average\ngyration radii calculated above, which are lower for UELP than for\nHELP suggest different compaction capacities of the two different\nhydrophobic sequences. On the other hand, the presence of the cross-linking\ndomains in the biopolymers may also contribute to explaining the different\nhysteresis observed. Thus, in addition to the interactions among the\nhydrophobic elastin-like domains, an interplay among the cross-linking\ndomains may be expected. 26 In the case\nof UELP, the hydrophobic sequences derived from the exon 26 are optimized\nto strongly promote the self–assembly to a more compact structure, 27 likely overcoming all other possible interactions.\nConversely, the delayed HELP coacervation process may allow further\ninteractions beyond the hydrophobic aggregation, 26 leading to a more stable final configuration. 3.3.2 Differential Scanning Calorimetry DSC experiments were performed to compare and further verify the\ninverse phase transition properties of UELP and HELP biopolymers.\nThe results are shown in Table 2 . The measurements were performed under the same conditions\nas the turbidimetric analyses, and the behavior of the biopolymers\nwas analyzed in the same Tris buffer solution with and without 0.15\nM NaCl. Except for UELP in the absence of salt, an endothermic asymmetric\npeak was always observed. Table 2 Thermodynamic Results of the DSC Analysis\nof 8 mg/mL UELP and HELP in 10 mM Tris Buffer, pH = 8, in the Absence\nand Presence of 0.15 M NaCl T peak Δ H tr kJ/mol Δ S tr J /mol K UELP TRIS ND ND ND TRIS/NaCl 23 29.0 98 HELP TRIS 29 198.0 655 TRIS/NaCl 34 35.0 114 According to the turbidimetric analyses, UELP in the\npresence of\nNaCl exhibited the lowest peak T t (23\n°C) and showed a greater tendency to transition compared to HELP.\nAs previously reported, 7 Δ H tr can be a useful method for studying the relative\nhydrophobicity of polypeptides because the lower the transition enthalpy,\nthe lower the hydrophobicity of the polypeptide. Prediction from the\nsequence data showed that UELP and HELP had similar proportions of\npolar and charged groups (6.5 and 6.3%, respectively, Table 1 ), resulting in similar Δ H tr (29 and 35 kJ/mol, respectively) and Δ S tr values (98 and 114 kJ/mol K, respectively),\nalthough UELP always had the lowest values, indicating lower hydrophobicity\ncompared with HELP. The DSC data in Table 2 show good agreement between the T t values and those obtained by turbidimetric\nanalysis under the same conditions ( Figure 5 ). According to these analyses, the data\nin Table 2 show a significant\ndifference in T peak temperatures between\nUELP and HELP proteins, probably due to the higher proportion of β-structures\nin the UELP sequence. It is likely that, although HELP shows a higher\nhydrophobicity with respect to UELP, this latter has a higher propensity\nto adopt the β-structure, making it the most efficient in promoting\nthe hydrophobic interactions and the supramolecular assembly. 27 , 28 3.3.3 Dynamic Light Scattering Characterization By using the DLS technique, we measured the hydrodynamic diameters\nof the biopolymers in solution and the dimensions of the aggregate\nsizes as a function of temperature. Figure 2 S shows the intensity and volume size distribution\nof the hydrodynamic diameter ( D h ) for\nUELP and HELP at different salt concentrations at 15 °C. The\nsize distribution, determined as the scattering intensity, showed\na multimodal pattern over a wide dimensional range, indicating the\npresence of particles of various sizes, most of which were centered\naround 10 nm, as confirmed by the volume size distribution ( Figure 2 S). This indicates\nthat, below the transition temperature, the smallest biopolymer particles\nwere predominant at room temperature, while the proportion of the\nlargest self-assembled particles was low despite the total scattering\nintensity being the highest. Figure 6 shows the average diameter values, D h , of UELP ( Figures 6 A,B, black symbols) and HELP ( Figure 6 C,D, red symbols) in the absence\nand presence of a near-physiological NaCl concentration as a function\nof temperature. Figure 6 DLS diameters (intensity-based calculated values) for\nUELP (black\nsymbols) and HELP (red symbols) in 10 mM Tris (A, C, respectively)\nand in 10 mM Tris/NaCl buffer (B, D) at a concentration of 2 mg/mL\nas a function of temperature ranging from 10 to 60 °C at a scanning\nrate of 0.5 °C/min. The vertical dashed bars show the respective T t values; the horizontal arrows show the predominant\nsize distribution. The percentages of the peak areas ( Figure 6 A–D, in the insets),\nas well as the\nparticle size values, were determined from scattering intensity distribution. T t was determined at the inflection point of\nthe DLS curve for each sample and is evidenced in Figure 6 (vertical dashed bars). In the absence of salt and below T t ,\na multimodal size distribution was observed for both biopolymers\nat a concentration of 2 mg/mL ( Figure 6 A,C). A four-modal size distribution (average D h of 10, 60, 300, and 3500 nm) was observed\nfor the UELP biopolymer ( Figure 6 A), with a prevalence (65–100%) of the D h = 300 nm-sized particles. Under the same conditions,\nthe HELP biopolymer ( Figure 6 C) showed a similar four-modal size distribution as well,\nwith the main fraction (36–100%) consisting of particles with\na D h = 600 nm. Interestingly, although\nthe two biopolymers showed different behavior above the T t , both exhibited a monomodal particle size distribution,\nwith an average particle size of about 150 nm at the highest temperature\nstudied (60 °C, Figure 6 A,C). However, despite the temperature increase, the UELP\nparticle size remained constant ( Figure 6 A), whereas the HELP particle size gradually\ndecreased with the temperature rise ( Figure 6 C). In the presence of 0.15 M NaCl and below T t , the UELP biopolymer showed a three-modal\nparticle size distribution ( Figure 6 B), with a prominent fraction of D h = 600 nm (75%, filled triangles) and two smaller fractions\nof D h = 10–15 nm (6–17%,\nopen squares) and D h = 5000 nm (3–4%,\nopen diamonds). Above T t , again, a monomodal\nparticle size distribution was observed, with a tendency to stabilize\naggregates with a D h of about 3000 nm\n( Figure 6 B, filled\ntriangles with 100% scattered light). Below T t , the HELP biopolymer ( Figure 6 D) showed a four-modal distribution with a main fraction\n(about 50%, filled triangles) with a D h of 250 nm. Above the T t , a further temperature\nincrease resulted in a monomodal particle size distribution with a\ngradually increasing D h up to about 3000\nnm ( Figure 6 D, filled\ntriangles, 100% of scattered light). These results show that\nin the absence of salt and above T t , the\nHELP sample has a tendency to gradually\ndecrease in particle diameter, suggesting a change from expanded to\ncontracted structures as a function of temperature as previously described\nfor these hexapeptidic sequences. 24b In\ncontrast, under these conditions, the UELP particle size stabilized\naround a value that remained constant despite the temperature increase\n(compare Figure 6 A\nwith 6 C), suggesting prompt and optimized particle\nassembly. It can be surmised that for the HELP biopolymer, the structural\ntransition occurred gradually over a temperature range of 30 °C\n( Figure 6 C), which\ncould be due to the higher chain flexibility of the HELP compared\nto the UELP biopolymer. This is also confirmed by the secondary structure\nanalysis ( Figure 2 B\nand Table 1 ), which\nshows a higher proportion of random coil sequences in HELP compared\nwith UELP (70 and 51%, respectively). HELP may, therefore, undergo\na progressive molecular collapse associated with a realignment of\nwater molecules and a restructuring of hydrogen bonding networks (i.e.,\npeptide–peptide hydrogen bonds replace water–water hydrogen\nbonds in the nearest solvation shells), gradually displacing water\nfrom the hydrophobic moiety and leading to a decrease in particle\nsize. 24b On the other hand, a significant\npresence of β-domains in the hydrophobic sequences of UELP is\nexpected ( Figure 2 B\nand Table 1 ), and this\nlikely leads to a more efficient structural collapse process in the\nlocal secondary structure and to a rapid rearrangement of water once\nthe critical T t threshold is reached. 29 According to our previous observations\nand the results of turbidimetric\nanalyses, the decrease in T t of UELP upon\naddition of salt ( Figure 7 A) and the previously observed increase in T t of HELP upon addition of salt ( Figure 7 B) confirmed the expected critical role of\nphysiological salt concentration in restoring the thermoresponsive\nproperties of elastin-like sequences when inserted between cross-linking\ndomains. Figure 7 DLS diameter (volume-based calculated values) as a function of\ntemperature. Calculated values of particle distribution in Tris (open\nsymbols) and Tris/NaCl buffer (filled symbols) at a concentration\nof 2 mg/mL for UELP (A) and for HELP (B). The effect of salt addition not only masks the\neffect of cross-linking\ndomains but also leads to a different interaction between ions, the\nhydrophobic thermoresponsive sequence, and water molecules in the\nnearest hydration shells. Ions diffusing into the nearest hydration\nshell of the polypeptide can interact strongly with the peptide chain\nand facilitate the structural folding of the hydrophobic domain. 30 In addition, the ions can disrupt the hydrogen-bonded\nwater network around the protein and promote the formation of hydrogen\nbonds within the hydrophobic sequence moiety while displacing solvation\nwater molecules from the nearest hydration shell. In the presence\nof salt and above the T t , both biopolymers\nshowed the ability to form particles with larger dimensions than in\nthe absence of salt. Above T t , the UELP\nbiopolymer, during the temperature increase, showed a constant particle\nsize with a large D h of about 3500 nm\nduring the temperature increase ( Figure 6 B), while the particles of HELP showed a\ngradual trend of increasing diameter from about 300 nm up to 4000\nnm under the same conditions ( Figure 6 D), again indicating greater chain flexibility (higher\nentropy) requiring higher temperature to stabilize the particle size. Figure 7 shows the particle\ndiameters determined by DLS as the percent particle number distribution\n(N%) for the two biopolymers at a concentration of 2 mg/mL. In the\nabsence of NaCl and below T t , the particle\ndiameters for the biopolymers were about 6 and 10 nm for UELP and\nHELP, respectively ( Figure 7 , open symbols), which most likely corresponds to a single\nchain size in solution. It is interesting to note that the values\nof the hydrodynamic diameter D h , which\nare calculated from R G ( 31 ) using the equation resulted in a D h of 9.7 nm and 12.0 nm for UELP and HELP, respectively, thus showing\nvalues in agreement with the DLS diameters measured for the temperature\nbelow the T t ( Figure 7 ). In the absence of NaCl and above T t , the UELP biopolymer formed particles that\nstabilized at a D h greater than 200 nm,\nwhile HELP formed larger particles 500–800 nm in diameter.\nThe addition of salt at near-physiological concentrations had a remarkable\neffect on the diameter of UELP particles, which promptly increased\nfrom a value of about 6 nm in the absence of salt and near T t ( Figure 7 A, open symbols) to about 5000 nm in the presence of\nNaCl ( Figure 7 A, filled\nsymbols). This value, which stabilizes as a function of temperature\nat about 3000 nm, is significantly larger than the value observed\nin the absence of salt (above 200 nm). In the presence of salt, HELP\nalso showed a remarkable change in particle diameter around T t , shifting from 10 to 15 to 5000 nm ( Figure 7 B, filled symbols) but stabilizing at about\n1200–1700 nm as a function of temperature. However, in the\ncase of HELP, particle sizes remained comparable in the presence and\nabsence of salt ( Figure 7 B, see the filled and open symbols). 3.3.4 1 H NMR Spectroscopy The arrangement of UELP and HELP biopolymers in solution was studied\nby 1 H NMR spectroscopy in D 2 O to evaluate differences\nin the polypeptide supramolecular arrangements occurring upon thermally\ninduced coacervation. Figure 8 shows, as an example, the NMR spectra of HELP and UELP in\na D 2 O solvent. The characteristic resonances of some protons\nof the amino acid residues at 10 °C, i.e., under the conditions\nof maximum solubility, are shown in Table 3 . In particular, the signals of −CH 3 protons of leucine and valine at 0.76 ppm and −CH 3 of alanine were clearly visible ( Figure 8 ). Figure 8 Overlay of 1 H NMR spectra\nof UELP (A) and\nHELP (B) in D 2 O (5 mg/mL) at 10, 30, and 60\n°C. Arrows indicate the resonance peaks of the following amino\nacid residues: leucine + valine, proline, alanine, and phenylalanine\n+ histidine. Table 3 Total Number of Amino Acid Residues\n(n res) and Relative Protons (nH) of UELP and HELP a UELP HELP theoretical NMR theoretical NMR n res nH δ (ppm) nH n res nH δ (ppm) nH L + V 109 654 0.76 658 129 774 0.76 860 A 130 390 1.03–1.38 412 159 477 0.97–1,46 590 P 48 48 4.40 43 72 72 4.42 75 F + H 29 127 6.55–7.54 127 14 52 6.57–7.55 52 a Chemical shifts (δ) and proton\nnumber (nH) of both biopolymers determined by NMR analysis. The formation of supramolecular aggregates by thermally\ninduced\nself-assembly was studied by 1 H NMR at a variable temperature.\nUpon heating, a significant decrease in the resonance peak areas was\nobserved ( Figure 8 ),\nalong with their downward shift. The latter is clearly visible in Figure 3 S, where the chemical\nshift of the resonance peak was plotted as a function of the temperature\nfor each amino acid residue. A nearly linear trend with an increasing\ntemperature was observed for all proton groups, suggesting that the\nincrease in temperature weakens the hydrogen interactions between\nthe polar amino acid groups of the polypeptide and the water and decreases\nthe solvation and electron shielding at the hydrogen nuclei. 32 In addition, the ratio of the absolute integral\nat a given temperature ( T x ) to the integral at 10 °C ( I Tx y / I 10 °C y ) was calculated for each proton resonance peak and plotted\nas a function of temperature ( Figure 9 ). It can be noticed that most of the peak integrals\ngradually decreased with temperature increase, with no evidence of\nsharp transitions associated with the occurrence of T t . A similar trend in UELP and HELP integrals was observed\nfor the proton peaks of alanine, leucine, and valine, suggesting that\nthese residues exhibit progressively stronger hydrophobic interactions\nupon heating, reaching a signal decrease of about 33–41% at\n60 °C, with a slightly larger decrease for residues in HELP than\nthe analogues in UELP. Figure 9 I y Tx / I 10 °C y as a function\nof\ntemperature for UELP (A) and HELP (B), as determined by 1 H NMR in D 2 O (5 mg/mL) in the range between 10 and 60\n°C. Notably, the greatest decrease was observed for\nUELP phenylalanine\nand histidine signals ( Figure 9 A), which may be attributed to the aromatic side chains and\nthe higher proportion of phenylalanine residues in this polypeptide.\nInterestingly, a striking trend was observed for proline protons.\nIn fact, the intensity ratio of UELP prolines in Figure 9 A decreased by only 5% at 60\n°C, indicating that strong interactions with water molecules\npersist when particle aggregation occurs. Since prolines are known\nto be present mainly in the β-sheet structures, which are generally\ninvolved in self-association and subsequent coacervation, 28 this behavior suggests that the UELP β-sheet\nstructures are still stable and solvated after polypeptide self-assembly.\nIn this context, the observed slight decrease in the level of the\nproline signal is attributed to the rearrangement of the proline residues\nnot involved in the β-sheet structures after self-assembly. A different trend in the proline signal intensity was observed\nfor HELP. Figure 9 B\nshows a decrease in proline intensity (up to 24%) as a function of\ntemperature, suggesting that in this case, the proline residues are\nactively involved in the coacervation process of HELP, whereupon they\nare buried in the hydrophobic moiety. As previously reported, 24b temperature-driven coacervation of highly hydrophobic\nelastin-like proteins may occur by decreasing the hydrodynamic radius\nand expelling water to reduce the hydrophobic-solvent interaction\nas the temperature increases. From this point of view, proline, as\nwell as other residues belonging to the hydrophobic domains of HELP\n(alanine, valine, and leucine), could be involved in these temperature-driven\nstructural changes so that their peaks show a larger decrease in HELP. In summary, NMR analysis is consistent with previous analyses and\nhighlights a different thermally driven coacervation mechanism for\nthe two biopolymers due to the peculiar local secondary structure\nof their hydrophobic sequences. 3.4 Cytocompatibility Evaluation HELP\nbiopolymers have been used as substrates for the culture of human\ncells of various origins. However, it was found that in some cases,\ncell adhesion after 24 h varied depending on the cell line used and\nthe thickness of the biopolymers on the surface. 6 , 12 , 33 To compare the cell adhesion ability of\nthe new UELP versus the biopolymer HELP, tissue-culture-treated polystyrene\n(TP) was coated with each biopolymer by adsorption, as described in Section 2 . MG-63 human osteoblast-like\ncells and NIH3T3 mouse fibroblasts were seeded, and after 24 h, no\nsignificant differences in adhesion were observed for either cell\nline on each biopolymer coating compared with the TP surface ( Figure 10 ). Interestingly,\nwhen the same coating procedure was performed on an untreated polystyrene\nmicrotiter plate (NP), a notable difference in adhesion was seen for\nboth cell lines after 24 h ( Figure 11 ). The cells were not able to adhere to the uncoated\nsurface NP as expected ( Figure 11 , panels A and D). Cells seeded onto the HELP-coated\nsurface NP also behaved similarly to cells observed on the uncoated\ncontrol surface NP: They showed a rounded morphology and formed small\naggregates, suggesting poor adhesion to the surface at this time point\n( Figure 11 , panels\nB and E). In contrast, cell adhesion on the UELP-coated surfaces of\nNP in both cell lines was comparable to that observed in the TP control\n(compare Figure 11 , panels C and F, with Figure 10 , panels A and D). Figure 10 Representative phase-contrast images\nof cell cultures on coated\nand uncoated tissue-culture polystyrene wells (TP). MG-63 and NIH3T3\ncell lines of human and murine origin, respectively, were seeded on\nuncoated TP wells (panels A and D) and on TP wells coated with HELP\n(TP -H, panels B and E) and UELP (TP -U, panels C and F) and grown\nunder standard conditions. Images were acquired 24 h after seeding.\nThe bar is 100 μm. Figure 11 Representative phase-contrast images of cell cultures\non coated\nand uncoated nontissue culture polystyrene (NP). MG-63 and NIH3T3\ncell lines of human and murine origin, respectively, were seeded on\nthe uncoated NP wells (panels A and D) and on the NP wells coated\nwith HELP (NP -H, panels B and E) and UELP (NP -U, panels C and F)\nand grown under standard conditions. Images were acquired 24 h after\nseeding. The bar is 100 μm. The crystal violet adhesion test confirmed this\nobservation ( Figure 4 S) and confirmed\na promoting effect on cell adhesion. However, after a longer time,\ne.g., 48 or 72 h, depending on the cell line, cells were able to cover\nall coated surfaces of NP and show their characteristic morphology,\nindicating that the presence of the biopolymers has no toxic effect\n(data not shown). In addition, coatings were prepared by decreasing\nthe concentration\nof the biopolymer solutions used for adsorption on NP. No significant\ndifference was observed for the HELP-coated surfaces, whereas a dose-dependent\ncell response was observed on UELP coatings. This effect correlated\nwith the amount of UELP biopolymer present in the solution used to\nprepare the coatings. Cell metabolic activity was evaluated 24 h after\nseeding by the WST-1 assay ( Figures 5 S and 6 S). This analysis showed\nthat the UELP and HELP coatings have no toxic effect on both cell\nlines, and the cell adhesion-promoting effect of UELP was confirmed\n(see the Supporting Information ). Remarkably, UELP and HELP have the same structure with alternating\nelastin-like and cross-linking domains, the same length, and very\nsimilar composition, whereas only the amino acid sequence of the elastin-like\ndomain differs ( Figure 1 ). The data presented here suggest that the sequence of the elastin-like\ndomain, the sequence inspired by exon 26 rather than human exon 24,\npromotes the adhesion of cells of different origins to nonadhesive\nNP surfaces. Although tropoelastin has long been considered an unstructured\nprotein, the 3D shape of the human homologue has been described using\nan unconventional approach. 34 According\nto this model, the region encoded by exon 26 was found to have the\nhighest protease susceptibility, indicating that this sequence is\nexposed. 34 Thus, this region could also\nbe readily accessible to cells organized in the extracellular matrix\nof the tissue. This could be one of the possible explanations for\nwhy this highly conserved region was well tolerated by the cells and\nmay even represent a point of cell attachment. On the other hand,\nthe exon 24-derived region is also exposed, being located in the so-called\n“spur” of the tropoelastin structure. 34 However, it can be considered that the sequence of this\nregion, being peculiar to the human, and more in general, primate\nhomologue and also having a recognized signaling role, 20 is less likely to represent a stable adhesion\npoint for the cells within the extracellular matrix."
} | 10,613 |
35136855 | PMC8819722 | pmc | 8,972 | {
"abstract": "Flexible electrodes that allow electrical conductance to be maintained during mechanical deformation are required for the development of wearable electronics. However, flexible electrodes based on metal thin-films on elastomeric substrates can suffer from complete and unexpected electrical disconnection after the onset of mechanical fracture across the metal. Here we show that the strain-resilient electrical performance of thin-film metal electrodes under multimodal deformation can be enhanced by using a two-dimensional (2D) interlayer. Insertion of atomically-thin interlayers — graphene, molybdenum disulfide, or hexagonal boron nitride — induce continuous in-plane crack deflection in thin-film metal electrodes. This leads to unique electrical characteristics (termed electrical ductility) in which electrical resistance gradually increases with strain, creating extended regions of stable resistance. Our 2D-interlayer electrodes can maintain a low electrical resistance beyond a strain in which conventional metal electrodes would completely disconnect. We use the approach to create a flexible electroluminescent light emitting device with an augmented strain-resilient electrical functionality and an early-damage diagnosis capability.",
"conclusion": "Conclusion We have shown that a 2D-interlayer can improve the durability of electromechanical functionality of metal-based flexible electronics. The addition of an atomically-thin interlayer between a metal thin film and flexible substrate results in unique strain-resilient electrical characteristics — electrical ductility — through the modulation of in-plane fracture modes of metal thin-films from unperturbed straight fractures with brittle behaviour to progressive tortuous fractures with ductile behaviour via buckle-guided fracture mechanism. The 2D-interlayer electrodes maintain electrical conductivity beyond the failure strain of conventional metal electrodes and further augment the strain-resilient electrical performance with resistance locking characteristics. To illustrate the capabilities of our 2D-interlayer approach in flexible electronics, we created a flexible electroluminescent light emitting device integrated with metal-2D interlayers. The device exhibits strain-resilient electrical performance under a high degree of multimodal deformation and an early damage diagnosis capability. Our approach is not limited to specific combinations of metals and 2D materials, and could be incorporated into industrial applications that use multilayer-laminated structures for flexible and wearable electronics, including conformable and implantable bioelectrodes and foldable/rollable personal electronic devices."
} | 669 |
33016314 | PMC7705324 | pmc | 8,973 | {
"abstract": "ABSTRACT Drought and agricultural management influence soil microorganisms with unknown consequences for the functioning of agroecosystems. We simulated drought periods in organic (biodynamic) and conventional wheat fields and monitored effects on soil water content, microorganisms and crops. Above the wilting point, water content and microbial respiration were higher under biodynamic than conventional farming. Highest bacterial and fungal abundances were found in biodynamically managed soils, and distinct microbial communities characterised the farming systems. Most biological soil quality parameters and crop yields were only marginally affected by the experimental drought, except for arbuscular mycorrhizal fungi (AMF), which increased in abundance under the experimental drought in both farming systems. AMF were further strongly promoted by biodynamic farming resulting in almost three times higher AMF abundance under experimental drought in the biodynamic compared with the conventional farming system. Our data suggest an improved water storage capacity under biodynamic farming and confirms positive effects of biodynamic farming on biological soil quality. The interactive effects of the farming system and drought may further be investigated under more substantial droughts. Given the importance of AMF for the plant's water supply, more in-depth studies on AMF may help to clarify their role for yields under conditions predicted by future climate scenarios.",
"introduction": "INTRODUCTION Soil microorganisms are of crucial importance for soil functions and the provisioning of ecosystem services (Bardgett and Van Der Putten 2014 ; Nielsen, Wall and Six 2015 ). Abiotic stressors, such as severe droughts and intensive agricultural management, may negatively influence the abundance, diversity and functioning of microbial communities (Cavicchioli et al . 2019 ). Climate models foresee increasingly frequent and severe droughts in southern and most of central Europe along with reduced amounts of summer precipitation (Pachauri et al . 2014 ). Given these projected climatic conditions, it is a research priority to understand how soil microorganisms react to drought. The effect of drought on microbial communities is complex since it is modified by numerous factors, including the frequency, intensity and duration of the drought, the impact of drought on higher-trophic-level soil organisms, resource preferences of microorganisms and their specific adaptive potential (Naylor and Coleman-Derr 2018 ; Schimel 2018 ). Furthermore, in the agricultural context, soil and crop management may influence the ultimate effects of droughts. More specifically, the effects of drought on soil microorganisms may differ between organic and conventional farming systems. These systems follow profoundly different concepts of fertilisation and crop protection, which in turn influence physical, chemical and biological soil properties (Mäder et al . 2002 ; Birkhofer et al . 2008 ; Lori et al . 2017 ). Soils in organically managed fields are, for example, characterised by higher levels of soil organic carbon (SOC) compared with soils under conventional farming with mineral fertilisers (Gattinger et al . 2012 ). High levels of SOC can improve the soil structure, thereby enhancing water infiltration and soil water retention (Rawls et al . 2003 ; Huntington 2006 ) and may ultimately buffer soil organisms from being exposed to drought. Organically managed soils with high SOC levels are further characterised by higher microbial abundance, activity (Lori et al . 2017 ) and increased microbial diversity (Hartmann et al . 2015 ; Harkes et al . 2019 ). The resistance of microbial communities to disturbances is suggested to be linked to diversity (Bardgett and Caruso 2020 ) because diversity can increase the variability of species’ responses to environmental stress and may thus buffer essential ecosystem functions against environmental fluctuations (Naeem and Li 1997 ; Yachi and Loreau 1999 ). Under controlled conditions, Lori et al . ( 2018 ) found evidence for a more stable nitrogen provisioning under drought, which correlated closely to the higher functional gene diversity of the underlying proteolytic community in soils under organic compared to conventional farming. Moreover, plant biomass production under drought was less impaired under organic compared to conventional management (Lori et al . 2018 ). While this study underpins the role of local soil properties and agricultural management in the context of a controlled drought, this needs to be proven under field conditions. To date, most field experiments have explored how agricultural management can modulate the effects of experimental drought on microbial communities in grasslands (De Vries et al . 2012 ; Karlowsky et al . 2018 ; Fuchslueger et al . 2019 ; Siebert et al . 2019 ) but not in arable production systems with annual crops (cereals). Here, we report on the results of a field experiment in which we simultaneously studied the effects of experimental drought and agricultural management on soil water content, properties of microbial communities, crop growth and yields. We conducted the study in the DOK experiment, one of the oldest farming system comparison trials worldwide (Mäder et al . 2002 ; Krause et al . 2020 ), using replicated field plots of the biodynamic and conventional farming systems under winter wheat production. The soils in the biodynamic and conventional farming systems are known to differ in physical, chemical and biological soil parameters (Mäder et al . 2002 ; Fliessbach et al . 2007 ; Birkhofer et al . 2008 ) and therefore allowed to study the effects of drought under contrasting agricultural management and soil properties, respectively. In both farming systems, we established rainout shelters along with controls (Kundel et al . 2018 ) and analysed microbial properties together with basic soil characteristics and plant traits, including above- and belowground biomass production. To understand the dynamics of responses to summer drought, we took the majority of measurements at three sampling dates across the main growing season. Based on the above-mentioned contrasting physical and biological soil characteristics resulting from different soil management practices, we expected to find a higher soil water content in the biodynamic compared with the conventional farming system. Furthermore, we assumed that the experimental drought changes microbial respiration, diversity and community composition, especially under conventional management. Given the complex interactions between microbes and drought-induced effects on the plant and other members of the soil food web, we did not have an a priori hypothesis regarding the effect of drought on bacterial and fungal abundance. Finally, we expected that the experimental drought would have adverse effects on the plant (root biomass, cereal and straw yields), especially under conventional management.",
"discussion": "DISCUSSION According to global climate models, summer months in central and southern European countries will be characterised by increasingly frequent and severe droughts (Pachauri et al . 2014 ) with predicted negative consequences for agricultural production across Europe (Webber et al . 2018 ) and worldwide (Daryanto, Wang and Jacinthe 2017 ). The enhanced resistance of soils mediated through high levels of SOC and improved soil biological quality achieved through extensive management has been proposed to counteract the adverse effects of climate change (Goh 2011 ). Here, we investigated the influence of organic (biodynamic) and conventional farming systems on the response of microbial communities, wheat growth and yields to short-term drought periods under field conditions, a subject rarely investigated before. Agricultural production under future precipitation levels may require specific actions beyond organic farming We hypothesised that the soils under long-term biodynamic management generally contain more water than soils under conventional management. This assumption was based on the high SOC levels in organically managed soils (Gattinger et al . 2012 ) and the positive effects of SOC on plant available water content (Huntington 2006 ). Indeed, we found enhanced SOC contents in the biodynamic compared with the conventional farming system along with higher soil water content at times when soil water was not limiting (T1 and T2). However, in both farming systems, soil water content dropped to similarly low levels on the driest sampling date (T3), and the relative reduction in soil water content (roof vs control) was comparable for the two farming systems. The ultimate effect of SOC on soil water content is complex and depends not only on the quantity of SOC but also its physical and chemical properties and the texture of a given soil (Rawls et al . 2003 ; Huntington 2006 ). In general, however, the influence of SOC on soil water content seems to decrease with decreasing water potential (Rawls et al . 2003 ; Huntington 2006 ; Minasny and McBratney 2018 ), which is also reflected in our findings. Our results indicate that, in addition to careful carbon management, other measures specifically tailored to reduce soil evaporation, transpiration and excessive evapotranspiration may be needed to protect soils from drying. Such measures may include a surface cover with plant residues or living mulches, agroforestry or intercropping in combination with the cultivation of water-efficient crops (Lal and Francaviglia 2019 ). Short-term drought impairs basal respiration and promotes the abundance of arbuscular mycorrhizal fungi Microbial basal respiration depends strongly on soil water content because of the water's vital role in substrate diffusion, which in turn directly impacts on the availability of nutrients to microbes (Manzoni et al . 2012 ). Therefore, the higher basal respiration rates on T2 compared with T1 indicate that soil moisture did not decrease to levels that exposed microorganisms to a stressful situation. Between T2 and T3, however, soil moisture dropped to values around the wilting point and, as expected, respiration rates decreased; however, the decline in respiration did not differ between the farming systems. The soil water content was critically low on T3, and, contrary to our assumption, did no longer differ between the two farming systems, hence substrate diffusion likely restricted microbial respiration in both systems equally. A higher respiration in the biodynamic compared with the conventional farming system was only found under optimal water content, thus, our findings emphasise the need to prevent soils from drying out to benefit from the positive effects of biodynamic farming on basal respiration. Bacterial and fungal abundances as assessed by PLFA remained largely stable throughout the experiment and were not affected by the drought treatments. Severe drought may lead to a decline in microbial biomass (Homyak et al . 2017 ; Ren et al . 2018 ), e.g. due to enhanced microbial mortality. However, as mentioned, in our study, soil moisture levels dropped to a critical threshold (wilting point) only after the second sampling. To adapt to moderate or short-term drought, microbes can form spores or resting structures (Sharma and Gobi 2016 ; Schimel 2018 ) without suffering severe declines in biomass. Moreover, the adverse effects of drought on sensitive predators of microbes (e.g. bacterivorous nematodes: Kardol et al . 2010 ; Landesman, Treonis and Dighton 2011 ; or protists: Geisen et al . 2014 ) can reduce predation pressure (Schimel 2018 ) and may counteract the direct adverse effects of drought on microbial biomass. The abundance of AMF increased under the experimental drought, in line with previous findings (Augé 2001 ; Karlowsky et al . 2018 ; Mackie et al . 2019 ). AMF associations can play a crucial role in the plants’ access to water (Khalvati et al . 2005 ), and plants can promote the association with the fungus via their carbon allocation (Simard and Austin 2010 ; Pagano 2014 ). The relative increase in AMF abundance (roof compared with control) was comparable for the two farming systems, yet, only the biodynamic farming system promoted AMF abundance in addition to the experimental drought. Differences in AMF abundances in the two farming systems could be related to the quantity and quality of the applied fertilisers (Mäder et al . 2000 ; Oehl et al . 2004 ) or the higher weed prevalence in the biodynamic compared with the conventional farming system, given that weeds can act as additional hosts. The additive, positive effects of the experimental drought and the biodynamic farming system resulted in almost three times higher AMF abundance in the roof subplots of the biodynamic compared with those of the conventional farming system at times of the most severe drought (T3). Interestingly, AMF abundance was not related to the crop's plant performance under drought. Several factors can explain this observation: (i) the duration of the drought may have been too short such that the increased AMF abundance could have been reflected in the plant-related data or, (ii) the effect of the increased AMF abundance was reflected in plant-related parameters other than biomass and yield, e.g. changes on the physiological or cellular level. Finally, the reason that the plants did not respond to the experimental drought may be precisely the increased AMF abundance, in the sense that the increased AMF abundance helped to prevent a possible negative drought effect on the plant. Further analyses using more specific methods, may shed light onto the role of AMF in buffering yield losses during drought periods in differently managed farming systems. Such methods may include amplicon-based sequencing approaches (e.g. Schlaeppi et al . 2016 ; Symanczik et al . 2017 ) in bulk soil but also in root samples where the actual symbiotic relationship between the plants and fungi is established. Such data will help to illuminate the effects of the farming system and drought on the proportion of AMF that directly interact with crops and may better depict the consequences for plant growth and final yield. Microbial diversity and community composition are stable under simulated drought Bacterial and fungal Shannon diversity (alpha diversity) as assessed from amplicon-based sequencing was not affected by the experimental drought on any of the sampling dates. However, independent of farming system or experimental drought, across the season, bacterial diversity was highest on the driest sampling date and lowest on the wettest sampling date. In contrast, no such relationship with soil water over time was observed for fungi. Carson et al . ( 2010 ) demonstrated that low pore connectivity caused by low water content promoted Shannon diversity of soil bacteria. These authors argued that dry pore spaces create the isolated habitats and niches that shelter less competitive bacteria. Seaton et al . ( 2020 ) further showed that fungi are less constrained by their physical environment compared with bacteria, which might be related to the hyphal system that allows them to bridge dry pore spaces (Tecon and Or 2017 ). Like alpha diversity, the composition of bacterial and fungal communities (beta diversity) was not affected by changes in soil water content as created by the roof. However, the farming system was a relevant factor shaping microbial community properties, which is in line with earlier findings (Hartmann et al . 2015 ; Bonanomi et al . 2016 ; Lori et al . 2017 ; Lupatini et al . 2017 , 2019 ; Hartman et al . 2018 ; Harkes et al . 2019 ). Moreover, changes in soil water content across the season were among the most relevant drivers of the composition of microbial communities. Our findings indicate that the alpha diversity of bacteria and community composition of both bacteria and fungi react to substantial changes in soil water content; in our study, such changes were created only across the growing season. However, shifts in soil water contents over time co-occurred with changes in other environmental variables, including soil and air temperature and the plants’ growth stage. Given this, our data do not allow us to directly relate the observed patterns in microbial alpha and beta diversities across the season to changes in soil water contents. If we could maintain substantial differences in soil water contents between rainout shelters and control treatments at times of severe drought, we could compare community properties on the same sampling date and, therefore, separate changes in soil water from other potentially influencing factors. This separation could be achieved by irrigating the control subplots in times with overall low precipitation levels (Beier et al . 2012 ). We regarded irrigation as too artificial and, for practical reasons, not feasible in our study. Nonetheless, watering the control subplots should be considered in future studies with passive rainout shelters during times of drought and when the soil water content is at risk of falling below a critical threshold. Indicator species analyses Among the most prominent families within the identified bacterial indicators in the biodynamic farming system were the Planctomycetaceae within the phylum Planctomycetes . This phylum has previously been found to be characteristic for organic farming systems (Lupatini et al . 2017 ), and its importance for the decomposition of soil organic carbon (Wang et al . 2015 ) may explain the prominent role in the organically fertilised soils in our study. In the biodynamic farming system, the genus Flavobacterium had the highest sequence abundance of all indicator OTUs. This bacterium has previously been found to be prominent in organic farming systems (Bonanomi et al . 2016 ; Armalytė et al . 2019 ) and organic-rich soils in general (Bernardet and Bowman 2006 ). Finally, the Peptostreptococcaceae , a genus within the Firmicutes appeared specifically in the organically managed system, in line with earlier reports in which Firmicutes were found to be associated with organic farming systems (Hartmann et al . 2015 ; Bonanomi et al . 2016 ; Hartman et al . 2018 ; Lori et al . 2018 ). In the ConMin system, most indicator OTUs were assigned to the family Acidobacteriaceae (Subgroup 1) and Solibacteraceae (Subgroup 3), which both belong to the phylum Acidobacteria . Members of Acidobacteria seem to be predominant in environments with moderately acidic pH conditions (Sait, Davis and Janssen 2006 ); however, our knowledge of the ecological role of the numerous subgroups within the Acidobacteria is still a field of current research (Kielak et al . 2016 ). The Glomeromycota did not appear on the list of fungal indicators, as they are only represented by very few sequences in the fungal data set (152 total sequences in the filtered data). More specific investigations on AMF may be required with primers designed to target this specific group (e.g. Schlaeppi et al . 2016 ). Only very few bacterial and fungal OTUs were associated with the samples from the drought subplots, and only a few of these drought indicator OTUs could be assigned to genus level, making it hard to extract information on their ecology or habitat preferences. Crop biomass and final crop yields are stable under short-term droughts Grain yields are usually around 20% lower in organic compared with conventional farming (Mäder et al . 2002 ). In line with this, grain yields in our study were around 13% lower in the biodynamically managed fields; however, the uncertainty around this result was considerable, likely because of the relatively small size of the sampling area (0.1 m 2 ). Yield levels in the current study are also higher as usual in the DOK trial (Mäder et al . 2002 ; Mayer et al . 2015 ). Although losses from threshing, separating and cleaning with modern machinery are nowadays relatively small, they might exceed those of the completely manual harvest in our current study. Furthermore, we removed neighbouring plants at each sampling date, which probably reduced competition and increased final yields. The nitrogen-fixing properties of soybean, the preceding crop, could also have promoted overall yield levels. However, we were interested in examining the relative differences between drought treatment levels, and the higher yield levels are not particularly relevant to our study. For more practice-oriented grain and straw yields from the DOK trial, we refer to earlier studies (Mäder et al . 2002 ; Mayer et al . 2015 ). Contrary to expectation, the simulated drought had no direct influence on the measured plant parameters (root and shoot biomass, straw and grain yields) in any of the farming systems, possibly because of the overall short duration of the simulated drought or the mentioned increased AMF abundance in the roof subplots. Implications and outlook Understanding the functioning, potential and limitations of farming systems under the projected rainfall reductions is essential to adapt agricultural strategies and guide policy intervention. Drought-induced effects in the current experiment were small, hindering our ability to study the interactive effects of farming systems and drought. Still, we observed patterns with potential implications for successful crop production in a changing climate. Overall, our data suggest that organic (biodynamic) agriculture enhances the soil's water storage capacity. Current climate models predict drought phases in summer to be preceded by heavy precipitation in spring. A high water storage capacity will be essential to replenish soil water reservoirs in spring and prevent surface run-off (Minasny and McBratney 2018 ). Having said this, the limited ability of SOC to enhance soil water contents under dry conditions should not diminish the importance of careful carbon management but rather encourage the implementation of additional strategies tailored to maintain soil water content under dry conditions. The interactions between farming systems and drought on microbial communities should be investigated under more substantial, extended and repeated droughts. The potential of AMF to help plants survive droughts can be further investigated in root samples from managed soils using more targeted methods. Such studies may contribute to the development of agricultural systems that remain productive even under predicted reduced rainfall."
} | 5,665 |
23528237 | null | s2 | 8,974 | {
"abstract": "Biotechnological production of high value chemical products increasingly involves engineering in vivo multi-enzyme pathways and host metabolism. Recent approaches to these engineering objectives have made use of molecular tools to advance de novo pathway identification, tunable enzyme expression, and rapid pathway construction. Molecular tools also enable optimization of single enzymes and entire genomes through diversity generation and screening, whole cell analytics, and synthetic metabolic control networks. In this review, we focus on advanced molecular tools and their applications to engineered pathways in host organisms, highlighting the degree to which each tool is generalizable."
} | 173 |
35017613 | PMC8752620 | pmc | 8,975 | {
"abstract": "Increasing yeast robustness against lignocellulosic-derived inhibitors and insoluble solids in bioethanol production is essential for the transition to a bio-based economy. This work evaluates the effect exerted by insoluble solids on yeast tolerance to inhibitory compounds, which is crucial in high gravity processes. Adaptive laboratory evolution (ALE) was applied on a xylose-fermenting Saccharomyces cerevisiae strain to simultaneously increase the tolerance to lignocellulosic inhibitors and insoluble solids. The evolved strain gave rise to a fivefold increase in bioethanol yield in fermentation experiments with high concentration of inhibitors and 10% (w/v) of water insoluble solids. This strain also produced 5% ( P > 0.01) more ethanol than the parental in simultaneous saccharification and fermentation of steam-exploded wheat straw, mainly due to an increased xylose consumption. In response to the stress conditions (solids and inhibitors) imposed in ALE, cells induced the expression of genes related to cell wall integrity ( SRL1 , CWP2 , WSC2 and WSC4 ) and general stress response (e.g., CDC5 , DUN1 , CTT1 , GRE1 ), simultaneously repressing genes related to protein synthesis and iron transport and homeostasis (e.g., FTR1 , ARN1 , FRE1 ), ultimately leading to the improved phenotype. These results contribute towards understanding molecular mechanisms that cells might use to convert lignocellulosic substrates effectively.",
"conclusion": "Conclusions The presence of insoluble solids and lignocellulose-derived inhibitors synergistically increased their inhibitory potential exerted on S. cerevisiae F12, especially when using xylose as major carbon source. After subjecting S. cerevisiae F12 to an ALE, the resulting evolved cells showed better fermentation performance in terms of higher xylose fermentation efficiency and ethanol yield than the parental strain. Differential gene expression analysis revealed the induction of genes related with cell wall integrity and the response to stress, as well as the repression of protein biosynthesis and the iron transport and homeostasis as main biological processes responsible for the improved phenotype. These results pointed out the necessity of further developing yeast strains less susceptible to the effects caused by all the stress agents present during the conversion of lignocellulosic materials, providing some molecular insights of the mechanism that yeast uses to face these stressors.",
"introduction": "Introduction Lignocellulose is present in agricultural residues such as rice straw, wheat straw, olive pruning, and gardening wastes. It is a renewable energy reservoir and a sustainable feedstock for chemicals and fuels. The efficient use of lignocellulosic resources will significantly boost the transition towards a bio-based economy. In this sense, the extensive research progress during the last decades has promoted the construction of several industrial-scale plants for lignocellulosic ethanol production 1 . Conversion of lignocellulose under high gravity conditions (i.e., high substrate concentrations) is crucial to achieve high ethanol titers and reduce distillation costs. However, high-gravity technology is still very challenging due to the increase in complexity of the corresponding medium (insoluble solids, inhibitors, etc.). These difficulties associated to the use of high substrate loadings negatively influence cell performance during the fermentation. Biotechnological conversion of lignocellulose into bioethanol involves pretreatment, enzymatic hydrolysis, fermentation and product recovery as major steps. Pretreatment is required to alter the physicochemical properties of lignocellulosic biomass and ease the accessibility of the hydrolytic enzymes to carbohydrates. Most common pretreatment technologies lead, however, to biomass degradation and formation of several compounds, which may inhibit the subsequent saccharification and fermentation steps. In particular, the effects that these inhibitory compounds exert on yeast have been widely explored 2 – 5 , and many different studies have targeted the overcoming of such effects 6 – 9 . Along with the inhibitors, insoluble solids are also present in the media during simultaneous saccharification and fermentation (SSF) and consolidated bioprocesses (CBP). These configuration strategies have been claimed as two promising options to produce lignocellulosic ethanol due to the costs saving potential resulting from the integration of the saccharification and fermentation steps. The integration of these stages reduces the required equipment, decreases the overall process length, and increases the fermentation efficiency 10 , 11 . However, the presence of insoluble solids may also influence the fermentation performance of yeast cells as well as yeasts tolerance to inhibitory compounds 12 , especially at the initial fermentation stages when the concentration of solids is high (solids concentration is diminished along the time due to enzymatic hydrolysis of carbohydrates). In the particular case of CBP processes, hydrolysis of cellulose usually exhibits low rates 13 , thus implying the presence of insoluble solids at high concentrations for longer periods than in SSF. Solid insoluble particles produce shear stress, induce damage in brewing yeast, promote changes in gene expression and accumulation of intracellular reactive oxygen species 12 , 14 . Notwithstanding, the potential effects that insoluble solids have on bioethanol producing yeasts have been frequently underestimated. Several studies have demonstrated the tolerance of yeast cells towards lignocellulose-derived inhibitors during fermentation of liquid prehydrolysates while the same concentration of inhibitory products completely inhibited cells in SSF processes 15 , 16 . Thus, determining the impact of insoluble solids on yeasts is therefore crucial to identify future research lines for the development of more robust and efficient strains with potential applications at industrial scale. The present work aims at evaluating the effect exerted by insoluble solids on the tolerance of yeast cells to inhibitory compounds, which is of great relevance in SSF/CBP processes at high gravity. For this purpose, the fermentation performance of the yeast Saccharomyces cerevisiae F12, a recombinant xylose-fermenting strain successfully used in SSF processes 8 , 10 , was investigated in presence and absence of lignocellulosic insoluble solids and/or inhibitors to determine its tolerance towards these stressors. Since, adaptive laboratory evolution (ALE) is effective for obtaining novel yeast strains better adapted to the challenging bioethanol production conditions 8 , 17 – 19 , S. cerevisiae F12 was subjected to an ALE procedure in the presence of both lignocellulosic degradation compounds and insoluble solids. Subsequently, the genetic changes for facing such challenging environment were identified. In evolutionary procedures, cells are forced to replicate under certain restricting conditions during long periods of time. The modulation of the environment during evolution increases the rate of spontaneous mutagenesis and so, designing an appropriated evolution strategy is crucial for the success of the process. Overall, this study reports for the first time the evolution of yeast cells on insoluble solids and inhibitors to better adapt them to high gravity technology. This work also reveals the most important variations in gene expression that take place during the evolution process. Results presented herein will pave the way for identifying new strategies to develop novel strains to be efficiently applied in high-gravity lignocellulosic conversion processes (i.e., with inhibitors and insoluble solids) at the industrial scale.",
"discussion": "Results and discussion Effect of WIS and/or inhibitors on yeast fermentation This study assessed how the presence of inhibitors and WIS may influence yeast fermentation under the conditions stated in Table 2 . As shown in Fig. 1 A, no differences were observed in terms of glucose consumption rates or residual glucose in fermentation experiments with 50% (v/v) inhibitor mix or 5–10% (w/v) of WIS when compared to control assays without insoluble solids and inhibitors. In these cases, no lag phase was detected and glucose was exhausted within the first 5 h of fermentation. This result agrees with Koppram and co-workers that showed no differences in the consumption of 20 g/L glucose when control fermentation (with no WIS in the medium) was compared to fermentations in the presence of 2, 5, 10, and 12% WIS (w/w) 26 . The presence of 100% (v/v) of inhibitor mix reduced, however, the glucose consumption rates, reaching glucose exhaustion at 24 h (Fig. 1 A) and corroborating the well-known effect that high concentration of inhibitors exerts on yeast cells, which in turns hampers glucose utilization 27 , 28 . Figure 1 Time-course for ( A ) glucose and ( B ) xylose consumption during fermentation assays in presence of different concentrations of WIS and lignocellulose-derived inhibitors. In contrast to glucose conversion, the presence of lignocellulose-derived inhibitors exhibited a strong inhibition effect during the xylose conversion phase (Fig. 1 B). In this case, the addition of 50% and 100% (v/v) of inhibitor mix resulted in restricted xylose assimilation by cells, which only consumed 18% and 12% of the initial xylose concentration, respectively (Table 3 ). The higher susceptibility of xylose fermentation to lignocellulose-derived inhibitors compared to that of glucose fermentation has already been shown in several studies 29 , 30 . Since xylose utilization has been proven to provide less energy in the form of ATP compared to glucose 31 , and response to inhibitors requires high energy levels, the presence of inhibitors may have a stronger effect on yeast when xylose is the utilized carbon source. Furthermore, it is likely that the genetic modifications needed to construct xylose-fermenting yeasts alter their cell metabolic homeostasis affecting the inhibitor tolerance 2 . Table 3 Glucose and xylose consumption and ethanol yields during fermentation assays at different inhibitors and WIS concentrations. Assay Strain Glucose consumption (%) Xylose consumption (%) Y ETOH (g/g) CONTROL Parental S. cerevisiae F12 100 ± 0 60 ± 1 0.28 ± 0.01 I50 100 ± 0 18 ± 1 0.22 ± 0.00 I100 100 ± 0 12 ± 0 0.19 ± 0.04 WIS5 100 ± 0 82 ± 3 0.20 ± 0.00 WIS10 100 ± 0 74 ± 1 0.21 ± 0.01 I50_WIS5 100 ± 0 22 ± 6 0.22 ± 0.02 I50_WIS10 100 ± 0 22 ± 1 0.19 ± 0.01 I100_WIS5 77 ± 2 8 ± 3 0.16 ± 0.00 I100_WIS10 18 ± 4 0 ± 1 0.05 ± 0.01 I100 Evolved S. cerevisiae F12 100 ± 0 64 ± 1 0.25 ± 0.04 WIS10 100 ± 0 59 ± 1 0.24 ± 0.01 I100_WIS10 100 ± 0 21 ± 3 0.24 ± 0.01 By contrast, the presence of 5% (w/w) or 10% (w/w) WIS slightly increased xylose consumption when compared to control assays (Fig. 1 B). Tricarboxylic acids (TCA) cycle was identified as one of the targets of transcriptional regulation to optimize xylose utilization. Thus, intensive TCA cycle was assigned to be important for xylose metabolism in xylose-recombinant S. cerevisiae strains 32 . In the same context, regulation of the stress response and amino acid metabolism have been shown as two important strategies for an effective xylose utilization in a recombinant xylose-fermenting S. cerevisiae strain 32 , 33 . Strikingly, Moreno and co-workers identified amino acids biosynthesis and carboxylic acid metabolic processes among the major overexpressed biological processes in S. cerevisiae F12 grown in glucose media with insoluble solids 12 . Thus, WIS may affect yeast cells by promoting xylose utilization when no other lignocellulose-derived inhibitor is present. Despite the increase in xylose consumption, ethanol yields in presence of WIS were 0.20–0.21 g/g. This value was 25–30% lower than the obtained in control assays (0.28 g/g) (Table 3 ). Lower ethanol yields are commonly linked to an increase in xylitol production 34 . Nevertheless, similar xylitol concentrations (< 0.1 g/L) were found in control and fermentation assays with only WIS. Thus, slight differences in cell growth in presence of WIS or redistribution of metabolic fluxes to cope with the challenging conditions imposed by WIS may result in lower ethanol yields. As mentioned before, Koppram and co-workers 26 did not observed differences in ethanol yields when adding up to 12% (w/w) of WIS to fermentation media with 20 g/L glucose, reaching ethanol yields of 0.32 g/g. However, when adding 40% (w/w) and 60% (w/w) insoluble solids, Moreno and colleagues 12 showed a decrease in ethanol yield in glucose media from 0.37 g/g without solids to 0.35 g/g and 0.22 g/g, respectively. It is worth mentioning that previous studies only utilized glucose as carbon source. In spite of promoting xylose consumption in presence of 5% (w/w) and 10% (w/w) of WIS, the reduced ethanol yields obtained in this study indicated that xylose fermentation was more prone to be affected by stressful conditions. Lower ethanol yields than those obtained for control assays were also found when lignocellulosic inhibitors were present, reaching 0.22 g/g and 0.19 g/g with 50% (v/v) and 100% (v/v) of the inhibitor mix, respectively (Table 3 ). As previously commented, less than 20% of the initial xylose concentration was consumed by non-evolved yeast cells (Fig. 1 B). In addition, when increasing the inhibitor content from 50% (v/v) to 100% (v/v), the glucose consumption rates decreased by threefold (from 1.8 g/L h to 0.6 g/L h) at the initial stages of the fermentation process (5 h) (Fig. 1 A). This result is indicative of the high inhibitory potential of lignocellulose-derived inhibitors, especially during the xylose assimilation phase. Besides the detrimental effect that the presence of WIS exhibited on ethanol yields in fermentation experiments with 10 g/L glucose and 10 g/L xylose, the influence that the presence of WIS has on the inhibitory tolerance of S. cerevisiae F12 was also studied. For such a goal, 50% (v/v) or 100% (v/v) inhibitor mix were combined with 5% (w/v) or 10% (w/v) of WIS in different fermentation tests. As it is shown in Fig. 2 A, when using 50% (v/v) of inhibitor mix, glucose was exhausted within the first 24 h, and 22% of the xylose was consumed after 48 h of fermentation. In this case, the ethanol yield was 0.22 g/g and 0.19 g/g with 5% (w/v) and 10% (w/v) of WIS, respectively (Table 3 ). These ethanol yields were similar than those obtained when only 50% (v/v) of inhibitor mix was added (Table 3 ), indicating that yeast tolerance was not significantly affected by the presence of WIS at low inhibitor concentration. On the other hand, when 100% (v/v) of the inhibitor mix was combined with either 5% or 10% (w/v) of WIS neither glucose nor xylose were exhausted in 48-h long fermentation (Fig. 2 B). Furthermore, marked differences were observed in ethanol yield in comparison with only 100% (v/v) of the inhibitor mix (Table 3 ). When 5% WIS (w/v) were added together with 100% (v/v) of the inhibitor mix, about 80% of the initial glucose and 10% of the initial xylose were consumed after 48 h of fermentation, reaching an ethanol yield of 0.16 g/g. However, 10% (w/v) of WIS together with 100% (v/v) inhibitor mix resulted in 80% less ethanol when compared to only 100% (v/v) inhibitor mix. The lower ethanol concentrations were directly linked to a completely hampered xylose consumption and to a limited glucose consumption. These results clearly showed a synergistic effect when combining both lignocellulose-derived inhibitors and WIS and pointed out to the presence of WIS as a crucial factor when yeast cells have to deal with high concentrations of inhibitory compounds. Figure 2 Fermentation assays with ( A ) 50% and ( B ) 100% (v/v) inhibitor mix in presence of 5% and 10% (w/w) WIS. In the present work, an increase in xylose uptake was observed when 50% (v/v) of inhibitor mix was combined with WIS compared with only 50% (v/v) inhibitors (Table 3 ). This result supported the hypothesis that the presence of insoluble solids may promote xylose consumption in absence of biomass degradations compounds or when inhibitors are present at low concentrations. In this sense, Koppram and co-workers 26 studied the effect of steam-pretreated birch WIS on the glucose consumption and yeast tolerance to either HMF (1 g/L), furfural (1 g/L), syringaldehyde (0.8 g/L) or acetic acid (9 g/L). These authors reported higher glucose uptake rates when low concentrations of these compounds were simultaneously present with WIS compared to those obtained in the absence of solids 26 . In the same study, a proteomic analysis revealed up-regulation of glycolytic enzymes and ATP synthases in the presence of acetic acid and WIS, strongly indicating an increased generation of energy in the presence of both stressors (WIS and inhibitors) which could be the reason for the increased sugar consumption. The ALE procedure in WIS-rich and inhibitor-rich media (Table 1 ) resulted in an evolved S. cerevisiae F12 with improved abilities to cope with the combination of both inhibitors and WIS. When compared with the parental strain, a decrease in the xylose consumption was observed when only WIS (10% w/v) was present in the fermentation broth (Table 3 ). However, in presence of 100% (v/v) inhibitor mix, xylose consumption increased from 12% with parental S. cerevisiae F12 to 64% with evolved cells which was also translated in an increase of ethanol yield from 0.19 g/g to 0.25 g/g. These results suggest that evolution procedure primarily favored changes to increased tolerance to inhibitors that could be detrimental to cope with the sole presence of insoluble solids. The success of ALE was evident when comparing parental and evolved S. cerevisiae F12 performance at the most challenging conditions (i.e. 100% (v/v) of inhibitor mix and 10% (w/v) of WIS). In this case, parental S. cerevisiae F12 did not consume any xylose and ethanol yield was as low as 0.05 g/g. On the other hand, xylose consumption and ethanol yield increased to 21% and 0.24 g/g, respectively, when using the evolved strain proving the effectiveness of ALE as strategy to increase tolerance to a combination of stressors. Simultaneous saccharification and fermentation at high substrate loading Parental S. cerevisiae F12 was used in SSF to evaluate its fermentation performance and cell robustness under high substrate loading. When using the whole slurry at a concentration of 20% TS (w/v), no ethanol was produced during SSF processes (data not shown). Although parental cells were able to cope with 100% (v/v) inhibitory mix in absence of WIS (Fig. 1 ), the presence of solids and inhibitors in SSF of slurry led to complete cell inhibition. This fact pointed to a reduced tolerance to inhibitors in presence of high solids content. In this case, the progressive liquefaction of the solids during the first hours of SSF was not sufficient to overcome the effect that WIS had on yeast tolerance to inhibitors. Nevertheless, when using 20% WIS (w/v) supplemented with xylose (i.e. absence of inhibitors), parental S. cerevisiae F12 was capable of fermenting both glucose and xylose, reaching a maximum ethanol concentration of 39.3 ± 0.4 g/L (Fig. 3 ). Figure 3 SSF of steam-exploded wheat straw (WIS supplemented with xylose), using the parental (P) and evolved (E) S. cerevisiae F12. In SSF from WIS, S. cerevisiae F12 assimilated glucose immediately upon enzymatic hydrolysis, thus maintaining a low glucose concentration during the fermentation process (Fig. 3 ). In contrast, limited xylose consumption was shown within 72 h of SSF. Recombinant S. cerevisiae cells use the same transport systems to incorporate both glucose and xylose inside the yeast cell 35 , 36 . The uptake of xylose through the transport system has been reported to have significantly lower affinities for xylose than for glucose 37 . In this sense, the xylose uptake is strongly inhibited when glucose is present. This fact is decisive in mixed sugar fermentations with recombinant S. cerevisiae strains because this yeast does not utilize xylose unless glucose is significantly depleted. In this case, glucose concentration was below 0.5 g/L during SSF process, and the limited xylose consumption could be therefore explained due to the stressful fermentation conditions. The robustness of the evolved strain was evaluated under the same SSF conditions than the parental strain. Similar to the parental S. cerevisiae F12, the evolved strain was totally inhibited during SSF processes of the whole slurry at 20% TS (w/v) (data not shown). However, in the SSF from WIS, the evolved strain produced a maximum ethanol concentration of 41.5 ± 0.5 g/L, which was 5% higher ( P < 0.01) than the obtained by the parental strain (Fig. 3 ) and represented 50% of the theoretical maximum ethanol that could be obtained in SSF (yield estimated considering the total glucose and xylose that can be potentially available during SSF process and a maximum sugar-to-ethanol conversion yield of 0.51 g/g). The evolved cells also exhibited improved xylose uptake rates, which increased the xylose consumption by about 10% (32% of xylose was consumed after 72 h of SSF). The high xylose:glucose ratio utilized during ALE was decisive for the success of the process since the utilization of xylose as carbon source during the evolution procedure is a key factor to increase the yeast affinity for this sugar. This improved xylose fermenting capacity could be due to improved xylose transport kinetics 38 , 39 . As a matter of fact, increased expression of hexose transporters was reported in evolved xylose-utilizing yeasts 39 – 41 , as may be the case for the resulting evolved strain in this study as well. Differential gene expression of the improved phenotype A total of 196 genes were found upregulated (130 genes) or downregulated (66 genes) in evolved cells in the presence of both solids (20% w/w) and inhibitors (80% v/v of inhibitory mix) (Fig. 4 A). These conditions of solids and inhibitors were the most challenging conditions to which cells were evolved in the ALE and thus they were selected for differential gene expression analysis. The differences between parental and evolved cells were also analyzed by hierarchical clustering, which clearly plotted two different groups (Fig. 4 B): i) one corresponding to parental cells and ii) another one corresponding to evolved cells. This result supported the differences between S. cerevisiae F12 and the corresponding evolved strain. Figure 4 Differential expression analysis between parental and evolved S. cerevisiae F12 in terms of ( A ) induced and repressed genes and ( B ) hierarchical clustering. Piano Software [ http://biomet-toolbox.chalmers.se ]. Differentially expressed genes (parental vs evolved) were subsequently analyzed by gene ontology (GO) analysis to determine the biological processes induced and repressed. This analysis highlighted cell cycle (e.g., cytokinesis, regulation of cell cycle, reproductive process) and cell wall organization or biogenesis (e.g., fungal-type cell wall organization, sexual sporulation) as major upregulated biological processes, while maltose metabolic process, transport (e.g., ion transport, amino acid transport, water transport) and homeostatic process (e.g., iron ion homeostasis) were the main biological processes downregulated (Table 4 ). In spite of identifying several biological processes induced and repressed in the improved phenotype, enrichment analysis identified no metabolic pathway statistically upregulated or downregulated. It is also important to remark that a significant number of identified upregulated (53 genes, ca. 40%) and downregulated (19 genes, ca. 30%) genes had an unknown molecular function (Supplementary Table S1 ). Furthermore, about 90% of these genes have a Log2-fold change above one order. These results might indicate the potential role of these genes during the cell response to insoluble solids, and therefore, they should be further investigated. Table 4 Upregulated and downregulated biological processes in evolved S. cerevisiae F12 cells. Biological Process Enriched P-value a Genes GO term Upregulated Cell cycle 1.99E-08 YBR038W, YBR098W, YDL055C, YDL101C, YDL222C, YER095W, YGL021W, YGL116W, YGR044C, YGR108W, YGR221C, YHR023W, YHR061C, YHR152W, YHR153C, YHR172W, YIL050W, YIL131C, YIL158W, YJR092W, YKL096W, YML027W, YML052W, YML085C, YMR001C, YMR029C, YMR032W, YMR078C, YMR117C, YMR199W, YNL196C, YNR009W, YOL069W, YOL132W, YOR026W, YOR301W, YOR315W, YOR372C, YOR373W, YPL256C, YPL257W, YPR119W GO:0,007,049 Cell wall organization or biogenesis 1.70E-06 YBR038W, YBR067C, YBR076W, YDL055C, YDL222C, YDR261C, YER011W, YHL028W, YHL043W, YHR143W, YIL123W, YJL158C, YKL096W, YKL096W-A, YKL164C, YKL187C, YML052W, YMR215W, YMR305C, YNL283C, YOL030W, YOL132W, YOR247W GO:0,071,554 Downregulated Maltose metabolic process 2.25E-05 YBR297W, YBR298C, YBR299W, YDL247W, YGR287C GO:0,000,023 Transport 6.68E-03 YAL067C, YBL042C, YBR068C, YBR069C, YBR298C, YDL247W, YEL065W, YER145C, YGR055W, YGR295C, YHL035C, YHL040C, YHL047C, YKL220C, YKR093W, YLL038C, YLL048C, YLL051C, YLL052C, YLL053C, YLR047C, YLR214W, YLR237W, YNL328C, YOR382W, YOR384W, YPL265W GO:0,006,810 Homeostatic process 1.65E-02 YEL065W, YER145C, YHL040C, YHL047C, YKL220C, YLL051C, YLR047C, YLR136C, YLR214W, YOR382W, YOR384W, YPL156C GO:0,042,592 a Multiple testing was analyzed by Holm-Bonferroni test correction. The results obtained by GO analysis regarding induced and repressed biological processes were also supported by the protein–protein interaction networks resulting from STRING analysis. STRING revealed cell cycle process, response to stress and cell wall organization as the main upregulated processes, while homeostasis, ribosome biogenesis and transport were highlighted as major downregulated processes (Table 5 , Fig. 5 ). From these analyses, it is important to highlight the upregulation of genes specifically related with DNA damage and the cell response to stress. These genes included for instance CDC5 , CTF18 , HTA1 , MMS4 , PLM2 , RNR1 , RAD51 , DUN1 , SSA3 , TRR2 , CTT1 , ALD3 , ALD2 , PAI3 , SIP18 , and GRE1 . CDC5 is known to prevent the cell-cycle arrest induced by the DNA damage checkpoint, allowing cell division and promoting the adaptation of cells to this cell state 42 . Simultaneously, DUN1 , CTF18 , RNR1 and RAD51 genes were also induced in the evolved S. cerevisiae F12 strain. These genes are also related with the DNA damage replication checkpoint and DNA repair mechanisms 43 – 45 . The overexpression of these genes might prevent cells from having an excess of mutations during cell adaptation, thus encouraging cell survival. The response to stress was also induced through the overexpression of genes involving the protection against oxidative stress ( TRR2 , CTT1 ), heat shock ( SSA3 , SPG4 ) and osmotic stress ( PAI3 ), as well as genes related to the general response to stress ( GRE1 , SIP18 , ALD2 , ALD3 ). It is worth highlighting that the overexpression of CTT1 improved xylose utilization in recombinant strains 32 , supporting the overexpression of this gene after ALE that may be responsible of the increased xylose consumption in the evolved S. cerevisiae F12. Table 5 STRING analysis of induced and represses genes after evolution of S. cerevisiae F12. Biological process Genes a Upregulated Cell cycle process BUB3, CDC5, CDC20, CDC21, CHS2, CLB1, CLB2, CLN1, CLN2, CTF18, DUN1, FDO1, FKH1, HHO1, HOF1, HTA2, KIN3, MMS4, MYO1, NDD1, NRM1, NUD1, NUF2, PCL7, PLM2, RAD51, RNR1, SPC24, SPC97, SPO12, TUB1, YOX1 Response to stress ALD2, ALD3, CTT1, FMP45, GRE1, HBT1, HXT5, PAI3, PHM7, SIP18, SPG4, SSA3, TRR2, YEF1 Cell wall organization CIS3, GAS5, GIC1, SCW10, SIM1, SRL1, TOS1, TOS2, (CWP2, WSC4, WSC2) Sporulation RME1, SGA1 Cell division BUD4, RAX1 Mannitol assimilation DSF1, HXT13 Nitrilase NIT1, YIL165C Downregulated Iron ion homeostasis and transport ARN1, ARN2, ENT4, FIT2, FRE1, FRE2, FRE5, FRE6, FRE8, FTR1, SIT1, TIS11 Ribosome biogenesis, RNA processing CMS1, ECM2, FAL1, FCF2, HGH1, NOP14, NOP7, ROK1, YCR016W, YNL050C Maltose metabolic process IMA1, MAL32, MAL31, MAL33 (MPH2) GTP/GMP biosynthetic process IMD1, IMD2, IMD3 Peptide transport BAP2, PTR2, (TAT1, MUP1, DIP5) Water transport AQY2, YLL053C a Upregulated and downregulated genes with similar functions and highlighted by GO analysis are listed in brackets. Figure 5 STRING analysis showing protein–protein interactions between induced and repressed genes. STRING software v11 [ https://string-db.org/ ]. Specific genes (8 in total) related with cell wall organization were also induced (Tables 4 and 5 ). Among them, SRL1 , CWP2 , WSC2 and WSC4 encode important proteins for the stabilization of the cell wall 46 – 48 . The overexpression of these genes might specifically be related with the yeast response against the stress promoted by solids. The presence of insoluble solids during yeast growth promotes the formation of cavities that cause a change in the external morphology of cells from a round-turgid shape to a highly wrinkled morphology 12 . Overexpression of the aforementioned cell wall proteins might counteract this effect and maintain cell wall integrity under the stress conditions. Major downregulated biological processes include ribosome biogenesis and RNA processing, as well as the transport of specific molecules including iron, peptides and water (Table 5 ). Repression of protein synthesis is one of the first cell responses upon stress exposure (heat shock, osmotic and oxidative stress), as it is a highly energy consuming process 49 , 50 . Nevertheless, although having the general protein synthesis process repressed, cells can simultaneously induce the translation of stress-related genes to face the adverse environmental conditions 51 . This was also the case for the evolved S. cerevisiae F12 in this work. The second main downregulated biological process was transport. Most of the transport-related genes are associated to peptide/amino acid transport and to iron ion transport and homeostasis (Tables 4 and 5 ). In this work, repression of peptide/amino acid transport genes might be linked with the downregulation of protein biosynthesis upon stress exposure. On the other hand, it is highly remarkable the relatively high number of genes (up to 12 genes) that are involved in iron ion transport and homeostasis, including the transporter-encoding genes FIT2 , FTR1 , SIT1 , ARN1 and ARN2 , and genes encoding different ferric reductases ( FRE1 , FRE2 , FRE5 , FRE6 , FRE8 ). Iron is an essential element required for different biological processes such as respiration, synthesis of nucleic acids, carbon metabolism, as well as photosynthesis and nitrogen fixation 49 . However, iron may be toxic for cells due to its oxidative capacity in the ferrous form, which increases the importance of having a tight control of the iron metabolism. A high intracellular concentration of reactive oxygen species (ROS) under oxidative stress conditions represents a potential threat since the interaction between ROS and iron may end up in the formation of new hydroxyl radicals with increased prooxidant capacity 52 . The simultaneous presence of both insoluble solids and lignocellulose-derived inhibitors during fermentation processes causes a severe oxidative damage in yeast cells, which greatly increases the intracellular ROS levels 12 . This high ROS concentration might be responsible for repressing the corresponding iron-related genes as a way to reduce the risks associated to a marked oxidative stress. Yeast cells (and other multicellular organisms) usually promote iron depletion to prevent metal toxicity and the irreversible damage under oxidative stress conditions 52 . Overall, these results clearly show the complex inhibitory environment that cells have to face during lignocellulosic biomass conversion. In response to a single stressor, specific genes and pathways have been identified as key components to increase yeast robustness. For instance, ZWF1 has been identified as a key element during oxidative stress in S. cerevisiae upon exposure to a wide variety of chemical and environmental stress agents 53 . During a heat shock, changing ergosterol by fecosterol alters membrane fluidity rendering thermotolerance in yeast 54 . The general response to stress and the cell cycle arrest have been identified as important processes to face a high concentration of insoluble solids 12 . By contrast, in lignocellulose-conversion processes cells must simultaneously deal with a bunch of chemical inhibitors and a high concentration of insoluble solids. To cope with such adverse conditions, this study demonstrate that cells should be capable of maintaining cell membrane integrity and preventing oxidative damage. Therefore, upregulation of membrane-related genes (e.g. SRL1 , CWP2 , WSC2 and WSC4 ) and induction/repression of genes and pathways involving the oxidative stress and the general response to stress (e.g. CDC5 , DUN1 , CTT1 , GRE1 , FTR1 , ARN1 , FRE1 ) can be targeted in future studies to evaluate cell robustness in lignocellulose-related bioprocesses."
} | 8,365 |
32831858 | null | s2 | 8,978 | {
"abstract": "One approach to understanding gut microbiome-host interactions, described in this review, is to examine how natural variation in a model organism, where environmental factors can be controlled, affects the microbiome and, in turn, how the microbiome is associated with physiological or clinical traits. A variation of this approach, termed \"systems genetics\" is to characterize both the microbiome and the host using various high throughput technologies, such as metabolomics or gene expression of the microbiome and the host. By relating variation in the microbiome and host functions to such \"molecular phenotypes\", hypotheses can be generated and then experimentally tested. To model human gut microbiome-host interactions in this way, the mouse is particularly useful given the extensive body of genetic resources and experimental tools that are available."
} | 215 |
37653415 | PMC10468875 | pmc | 8,979 | {
"abstract": "Background Cold-adapted archaea have diverse ecological roles in a wide range of low-temperature environments. Improving our knowledge of the genomic features that enable psychrophiles to grow in cold environments helps us to understand their adaptive responses. However, samples from typical cold regions such as the remote Arctic and Antarctic are rare, and the limited number of high-quality genomes available leaves us with little data on genomic traits that are statistically associated with cold environmental conditions. Results In this study, we examined the haloarchaeal genus Halorubrum and defined a new clade that represents six isolates from p olar and d eep earth environments (‘PD group’ hereafter). The genomic G + C content and amino acid composition of this group distinguishes it from other Halorubrum and the trends are consistent with the established genomic optimization of psychrophiles. The cold adaptation of the PD group was further supported by observations of increased flexibility of proteins encoded across the genome and the findings of a growth test. Conclusions The PD group Halorubrum exhibited denser genome packing, which confers higher metabolic potential with constant genome size, relative to the reference group, resulting in significant differences in carbon, nitrogen and sulfur metabolic patterns. The most marked feature was the enrichment of genes involved in sulfur cycling, especially the production of sulfite from organic sulfur-containing compounds. Our study provides an updated view of the genomic traits and metabolic potential of Halorubrum and expands the range of sources of cold-adapted haloarchaea. Supplementary Information The online version contains supplementary material available at 10.1186/s12864-023-09597-7.",
"conclusion": "Conclusions By adding four isolates from deep salt mines to a clade anchored by the well-studied psychrophilic Hrr. lacusprofundi strains HLS1 and DL18, we have expanded the range of sources of cold-adapted Halorubrum species – which were previously limited to Antarctica – to include deep-earth environments. We also analysed the genomes of new PD group Halorubrum isolated from subterranean salt mines and reconstructed their C, N and S cycling capacities. In comparison to the reference group, the PD group Halorubrum possessed distinct genomic signatures consistent with their representation in low-temperature environments, and more compact genomes. In the era of next-generation microbiology, two advances will improve our understanding of the genetic basis of environmental adaptation: (i) increasing the availability of multiple genomes sharing similar environmental conditions [ 21 ]; and (ii) minimizing the phylogenetic distance between target groups and reference groups [ 35 , 53 ]. In this study, we defined a cold-adapted clade in Halorubrum harbouring 10 non-redundant genomes, for which phylogenetic noise was reduced as much as possible by using all other Halorubrum genomes as a reference group. Thus, an important step has been taken towards achieving the two advances that will improve our understanding of the environmental adaptation of microbes.",
"discussion": "Discussion A body of studies has revealed that Halorubrum harbours diverse species, and there are members of Halorubrum that are well adapted to low temperatures and are abundant in cold saline lakes such as Deep Lake [ 11 , 33 ]. Halorubrum -related sequences were also found to be abundant in the 2 m sample of the permafrost from the Canadian high Arctic [ 24 ]. Despite the competitiveness of Halorubrum in different cold environments globally, it is challenging to grow them at temperatures lower than 4 °C in the laboratory, and Halorubrum can grow at temperatures higher than 40 °C [ 2 , 25 ]. Indeed, it is difficult to ascertain how well-adapted and ecologically important a microorganism is based on laboratory temperature-dependent growth curve tests [ 34 ]. Thus, there is a lack of knowledge regarding the genetic boundary between the cold-adapted Halorubrum species and their counterparts that thrive at higher temperatures. In our analysis of the pangenome of Halorubrum , we found that the core genes exhibited a similar degree of functional diversity to the shell genes and cloud genes. This may confer on each member of Halorubrum the functional capacity to colonize a wide range of habitats. Having an open pangenome also indicates that Halorubrum is beginning to expand in terms of function and exploring new ecological niches [ 35 ]. There is an emerging view that the ecological theory developed for animals and plants may apply to Bacteria and Archaea [ 36 ]. Thus, the ability to occupy diverse and geographically distant habitats may be one of the reasons why Halorubrum is one of the largest haloarchaeal genera and has rapidly changing variation of its populations [ 37 ]. With respect to the high intrageneric diversity of Halorubrum , a clade containing 60% isolates from deep subterranean salt mines and Deep Lake was identified in the phylogenomic tree (i.e. the PD group). Although the ambient temperatures (~ 15 ℃) of the deep salt mines are not as low as those of Deep Lake (< 15 ℃ all year and < 0 ℃ for ~ eight months of the year), they can be considered low-temperature environments relative to saline lakes and solar salterns, where temperatures are around 20–30 ℃ [ 27 , 33 ]. We hypothesize that this clade represents a low-temperature-adapted ecotype in Halorubrum . This is generally supported by the growth tests described in this study and in a previous study by Williams et al., (2017), both of which found that isolates from the PD group grew well at low temperatures and outperformed the reference isolates. To further test our hypothesis, we then analysed the DNA G + C content of the PD group. For Bacteria and Archaea, the G + C content of genomic elements, especially RNAs, is a good proxy for temperature adaptation [ 38 ]. The lower G + C content of genomic DNA and RNA genes in the PD group, relative to the reference group, corresponds well to the improved ability of members of the PD group to survive at lower temperatures. The PD group is located in the middle of the phylogenomic tree shown in Fig. 1 , and both its genomic and RNA G + C content are lower than those of the upper and lower clades, further supporting the notion that the lower G + C content is correlated with low-temperature adaptation rather than phylogenetic divergence. The optimization of amino acid composition in the PD group provided stronger evidence that the PD group represents a low-temperature adapted ecotype in Halorubrum . In a comparison of the amino acid composition of the PD and reference groups, significant changes in the proportions of 15 of the 20 standard amino acids were observed. Significant decreases in the proportions of Arg and Pro, and significant increases in Lys and Asn, all of which represent well-established signatures of cold adaptation, were identified in the PD group [ 6 , 39 , 40 ]. By clearly delineating the cold-adapted ecotype of Halorubrum , we are now able to summarize, in statistical terms, the overall amino acid optimization of Halorubrum in response to low-temperature environments. We identified a bias in amino acid composition toward Lys, Gln, Ile, Asn, Trp, His, Cys, Met, Tyr, Ser and Glu and against Pro, Arg, Val and Ala. Our findings in the PD group were consistent with trends identified in psychrophilic Arthrobacter , a genus of bacteria in the Actinomycetes family; which reported similar findings for eight of the eleven amino for which an increase was observed (Asn, Lys, Met, Ile, Ser, Gln, Trp and His) and three of the four for which a decrease was observed (Ala, Pro, and Arg) [ 41 ]. The optimization of protein amino acid composition would enhance the activity of enzymes at low temperatures via a reduction in the number and strength of salt bridges (i.e. Asp-Arg salt bridge to Asp-Lys salt bridge) and would confer conformational flexibility and reduce activation energy [ 17 , 42 ]. A comparison of the average flexibility between the PD group and the reference group further supported the idea that amino acid optimization has enabled genome-scale cold-environment adaptation in the PD group [ 6 , 39 ]. The substitution of Lys for Arg may also help to reduce the amount of nitrogen needed for cell replication, as Lys has lower nitrogen content [ 43 ]. It is worth noting that the amphipathic amino acid content (for all three – Trp, Met and Try) was higher in the PD group; this indicates that the amphipathic amino acids may present a novel signature of cold adaptation that has not been noted in previous studies. We also observed that the optimization of amino acid composition by the PD group had not resulted in an increase in isoelectric point, which was thought to be incompatible with cold adaptation [ 44 ]. We speculate that the PD group Halorubrum are adapted genetically to the cold but that other unknown growth requirements prevent them from growing at temperatures < 4 °C. Although it is clear that the optimization of amino acid composition to increase protein flexibility is a good indicator of cold adaptation in both archaea and bacteria, there is no general trend when classifying the amino acids based on their chemical characteristics only. For example, the hydrophobic amino acids Ile and Met were increased while Pro and Ala content were decreased in the cold-adapted clades of Halorubrum and Arthrobacter ; Lys and Arg both have positive charges at neutral pH values but showed opposite trends in adapted proteins [ 41 ]. The trend of decreased Leu content identified in previous studies was not seen in the cold-adapted clades of Halorubrum or Arthrobacter [ 9 , 41 ]; thus, based on statistical analyses of multiple closely related genome data sets, Leu may not be the key amino acid in low-temperature adaptation. The contrasting trends observed for some amino acids in different cold-adapted taxa probably result from a balancing of the overall amino acid composition. The PD group was found to have higher functional potential with constant genome size relative to the reference group. This suggests that the PD group had higher substrate- and energy-use efficiency, enabling these species to drive the biogeochemical cycle in the oligotrophic cold polar and deep-earth environments. We further compared the functional traits between the PD group and the reference group by dividing genes into different functional categories. The PD group was shown to differ from the other Halorubrum in terms of overall gene content and specific functional genes involved in carbohydrate metabolism, the nitrogen cycle and the sulfur cycle. Functional differentiation between the PD group and the reference group further supports the idea that the PD group represents a low-temperature adapted ecotype in Halorubrum . The denser packing of genes indicates that the PD group may have undergone stronger positive selection of related genes [ 35 ]. We can explore the specific biogeochemical role of this cold-adapted clade using the reverse ecology principle, which states that the genome of an organism includes identifiable adaptational features to its native environment [ 36 ]. In our analysis of the nitrogen cycle, genomic data indicated that Halorubrum were able to reduce NO 3 – to N 2 or NH 4 + but were not able to fix nitrogen or oxidize ammonia; this is consistent with the physiology of Halorubrum [ 45 ]. The genes nirS/K , norB and nasA were significantly enriched in the PD group, suggesting enhanced reduction of NO 3 – by the cold-adapted Halorubrum species in polar and deep-earth hypersaline environments [ 45 ]. Our result is consistent with the findings that most of the genes involved in the denitrification pathway could be detected in Arctic permafrost, but the relative gene abundances for N 2 production were low, leading to the accumulation of N 2 O, another greenhouse gas [ 46 , 47 ]. The cold-adapted Halorubrum isolates encoded a number of key genes involved in both organic and inorganic sulfur transformation, and were especially enriched in genes involved in organic sulfur transformation. This suggests that the cold-adapted Halorubrum species prefer organic sulfur to generate energy for cellular activity and growth. Our results corroborated the findings of previous studies, in which strong psychrophilic adaptation of the sulfate reducers was identified in the Arctic sediment, and psychrophilic Arthrobacter were characterized as harbouring a complete mycothiol (MSH, a sulfur-containing compound) biosynthesis pathway [ 41 , 48 ]. The capture of advantageous genes – such as those discussed here that confer on the PD group Halorubrum the ability to explore new ecological niches (i.e. deep subterranean salt mines and polar lakes) – can lead to the expansion of genomes. The fact that the genome sizes in the PD group Halorubrum remained constant suggests that the capture of new genes in this group might have overridden the selection for genome streamlining [ 35 , 49 ]. This also implies that the genome content of the PD group Halorubrum is optimized such that maximum metabolic complexity is achieved without the cost of having increased the number of regulatory genes [ 50 , 51 ]. Ordering genomes from geographically distant locations with similar low-temperature conditions into ecologically cohesive units helps to improve our understanding of the genomic features that are statistically associated with particular environmental conditions. However, it is difficult to identify a strict monophyletic group in which all isolates are from cold environments (e.g. polar, high alpine, and deep-earth environments) [ 41 ]. In this study, the PD group was found to harbour four isolates that were not from polar or deep-earth environments; however, these isolates formed a mixed clade with the polar and deep-earth isolates and shared conserved genomic traits. The benefits of defining the PD group were achieved at the expense of including the four non-cold-environment-derived isolates. However, there are in principle strict limits to what can be achieved by any simple system of classification; for example, in the classification of terrestrial climate, some locations may simultaneously satisfy the criteria for more than one category [ 52 ]."
} | 3,614 |
37628597 | PMC10454618 | pmc | 8,980 | {
"abstract": "The evolution of endosymbionts and their hosts can lead to highly dynamic interactions with varying fitness effects for both the endosymbiont and host species. Wolbachia , a ubiquitous endosymbiont of arthropods and nematodes, can have both beneficial and detrimental effects on host fitness. We documented the occurrence and patterns of transmission of Wolbachia within the Hawaiian Drosophilidae and examined the potential contributions of Wolbachia to the rapid diversification of their hosts. Screens for Wolbachia infections across a minimum of 140 species of Hawaiian Drosophila and Scaptomyza revealed species-level infections of 20.0%, and across all 399 samples, a general infection rate of 10.3%. Among the 44 Wolbachia strains we identified using a modified Wolbachia multi-locus strain typing scheme, 30 (68.18%) belonged to supergroup B, five (11.36%) belonged to supergroup A, and nine (20.45%) had alleles with conflicting supergroup assignments. Co-phylogenetic reconciliation analysis indicated that Wolbachia strain diversity within their endemic Hawaiian Drosophilidae hosts can be explained by vertical (e.g., co-speciation) and horizontal (e.g., host switch) modes of transmission. Results from stochastic character trait mapping suggest that horizontal transmission is associated with the preferred oviposition substrate of the host, but not the host’s plant family or island of occurrence. For Hawaiian Drosophilid species of conservation concern, with 13 species listed as endangered and 1 listed as threatened, knowledge of Wolbachia strain types, infection status, and potential for superinfection could assist with conservation breeding programs designed to bolster population sizes, especially when wild populations are supplemented with laboratory-reared, translocated individuals. Future research aimed at improving the understanding of the mechanisms of Wolbachia transmission in nature, their impact on the host, and their role in host species formation may shed light on the influence of Wolbachia as an evolutionary driver, especially in Hawaiian ecosystems.",
"conclusion": "5. Conclusions This study sheds light on the infection status and coevolutionary history of Wolbachia endosymbionts within their Hawaiian Drosophilidae hosts. Co-phylogenetic reconciliations and comparative phylogenetic analyses indicate that the transmission patterns of Wolbachia is best explained by both co-speciation and host-switching events. Future studies that survey Wolbachia from a greater breadth of native Hawaiian arthropod taxa, as well as introduced arthropod invasive taxa, may help to improve our understanding of how Wolbachia transmission has occurred in Hawaiian ecosystems. Insights into Wolbachia infections and strain types could help guide conservation programs, possibly enhancing translocation efforts, impacting host behavioral response to temperatures, and conferring host thermal tolerance.",
"introduction": "1. Introduction The Hawaiian Drosophilidae, long recognized as a striking example of adaptive radiation, are of considerable interest as model systems for understanding the underlying mechanisms of insular speciation [ 1 ]. Comprised of up to 1000 species in two major genera ( Scaptomyza and Drosophila ), which are believed to have diverged within the Hawaiian archipelago approximately 23.4 million years ago, this taxonomic grouping represents approximately 10% of the insect fauna endemic to the Hawaiian Islands [ 2 , 3 ] and one third of the world’s Drosophila species [ 4 ]. Numerous mechanisms have been proposed to explain the explosive lineage diversification of Hawaiian Drosophilidae, including isolation, niche availability [ 5 ], sexual selection [ 6 ], and host plant and substrate shifts [ 1 , 3 ]; however, data are lacking on the potential role of symbiont pressures, despite recognition that symbionts, especially those associated with reproduction, could be a major contributor to insect species formation [ 7 ]. In particular, a growing body of empirical evidence suggests that the reproductive endosymbiont Wolbachia may play a role in the speciation process of some arthropods [ 8 , 9 , 10 ], including Drosophila [ 11 ]. Wolbachia is a widespread and common α-proteobacterium (order Rickettsiales) that infects arthropods and nematodes [ 12 ]. The relationship between Wolbachia and its host can span from parasitism to facultative or obligate mutualism to ultimate mutualism, and in some cases, beneficial and detrimental effects can be simultaneously conferred [ 13 ]. Wolbachia strains possess a remarkable ability to significantly alter the reproductive functions of its host in ways that serve to enhance the rate of Wolbachia ’s transmission, be it through cytoplasmic incompatibility, male-killing, feminization of genetic males, increased fecundity of host, and parthenogenesis [ 13 , 14 ]. Thus, through multiple mechanisms, Wolbachia possess the means to give rise to reproductive isolation barriers, which could contribute to the divergence of populations into new species [ 15 ]. Consistent with that notion, cytoplasmic incompatibility is known to have a direct effect on gene flow and can serve as a mechanism of reproductive isolation between populations [ 11 , 16 , 17 ]. The primary mode of Wolbachia infection is vertical transmission to the host’s progeny through the cytoplasm of the egg [ 14 ]. Horizontal transmission is believed to occur as well, especially in arthropods, as evidenced by the widespread distribution of Wolbachia and its potential to infect new host species [ 8 , 18 ], phylogenetic incongruence between hosts and endosymbionts [ 12 , 19 ]), and evidence for species sweeps [ 20 , 21 ]. In contrast, within filarial nematodes hosts, strict vertical inheritance of Wolbachia endosymbionts is evidenced by high levels of co-phylogenetic concordance for certain clades [ 22 , 23 ]. At present, the community-level interactions required for Wolbachia strains to be successfully transmitted horizontally and become stable within a new host species remain largely unknown, but in some cases, they are believed to involve transfer through plant tissues or parasitoids of insects [ 24 , 25 ]. Molecular methods have been invaluable for the study of Wolbachia because of an inability to culture it outside of its host or host cells, owing to its obligate intracellular status [ 14 ]. Based on molecular diversity analysis, the genus Wolbachia is subdivided into at least 17 possible supergroups [ 26 , 27 ], with terrestrial arthropods most commonly infected by Wolbachia belonging to supergroups A and B [ 28 ]. Estimates for the incidence of Wolbachia in terrestrial arthropod species worldwide range between 40–76% [ 13 , 29 , 30 ], whereas within-species estimates for Wolbachia incidence indicate that infection rates tend to be either exceedingly high (>90%) or considerably low (<10%), depending on the surveyed insect system [ 13 , 30 ]. In native Hawaiian insects, the overall incidence of Wolbachia infection at the species level was estimated to be ~14%, and for native Dipteran species (e.g., Drosophilidae and Calliphoridae), 12% [ 2 ]. Although many mechanisms have been proposed to explain the rapid and extensive diversification of the Hawaiian Drosophilidae, the potential contribution of Wolbachia as a driver of speciation and patterns of Wolbachia transmission have yet to be examined. Using a single gene marker, Wolbachia surface protein ( wsp ), Bennett et al. [ 2 ] found the incidence of infection within Hawaiian Drosophilidae, including genera Drosophila and Scaptomyza , was ~18%. Wolbachia ’s presence in the Hawaiian Islands, and the knowledge of the potential impacts that it can have on host reproductive strategies, give rise to the question: could Wolbachia have played a role in the diversification of the native Hawaiian insects? To begin to address this larger question, in this study we conducted genetic analyses of Wolbachia and its Hawaiian Drosophilidae hosts to examine: (1) the Wolbachia strain diversity and phylogenetic affiliations; (2) the co-phylogenetic diversification patterns of Wolbachia and hosts; and (3) Wolbachia host-switching mechanisms through stochastic character trait mapping to construct host ancestral traits.",
"discussion": "4. Discussion Our assessment of Wolbachia within the Hawaiian Drosophilidae family contributes to the understanding of endosymbiont transmission and its potential role in speciation. Using a modified MLST strain typing protocol, and through phylogenetic analyses, we found evidence for both coevolution and horizontal transmission of Wolbachia within Drosophila sampled across the Hawaiian archipelago. Our study complements the singular previous broad-scale study of Wolbachia within natural populations of Hawaiian insect taxa by Bennett et al. [ 2 ], in which strain diversity was characterized using a single gene marker, wsp . These studies differed by taxonomic scope, in that our primary focus was to investigate Wolbachia strain diversity among members of native Hawaiian Drosophilidae (and select invasive insects), and we used a modified version of the MLST strain typing scheme developed by Baldo et al. [ 34 ]. Despite study design differences, findings across studies were largely concordant, with Bennett et al. [ 2 ] determining the species-level incidence of Wolbachia infection for native Hawaiian Drosophilidae to be 18.1%, compared to our finding of 20.0%. Across all samples screened, we found an infection rate of 10.3%, which is lower than Bennett et al.’s [ 2 ] incidence of infection at 18.1%. That difference in infection rate can be attributed to the sampling of different taxa, along with uneven sample numbers within individual species. We caution that many species considered in this study were represented by only a single individual; thus, infection status is not representative of the species as a whole. Indeed, we found strong differences in percent infection rate within individual species having data available for five or more individuals. Additionally, although our efforts to re-design Wolbachia MLST primers improved amplification efficiency and increased the number of confirmed infections, the amplification and sequencing of Wolbachia alleles still proved to be difficult and infection rates may thus be an underestimate. A few of the species (namely D. claytonae and D. setosifrons ) are also represented only by older specimens with poor DNA extractions, which may not have yielded enough to detect Wolbachia . If specimens with PCR bands only (absent sequencing results) were to be counted as positive infections, the incidence of Wolbachia at both the species and individual level would increase to 28.1% and 16.3%, respectively. Between supergroups A and B, the majority of Wolbachia strains in Hawaiian Drosophilidae were determined to belong to supergroup B (at 68%), consistent with previous screens in native Hawaiian insect taxa, using wsp , at ~75% [ 2 ]. Among the species included in Bennett et al.’s [ 2 ] study, and also screened here, the Wolbachia supergroup designations were concordant for endosymbionts of D. basimacula , D. nr. basimacula , D. redunca , and D. ancyla , which harbored Wolbachia from supergroup B, and D. nigrocirrus , which harbored Wolbachia from supergroup A. With regards to invasive Drosophila, Bennett et al. [ 2 ] found that D. suzukii was infected only by Wolbachia belonging to supergroup A, whereas we found individuals harboring infections belonging to supergroups A ( n = 5) and B ( n = 3). Interestingly, we observed that a Wolbachia infecting a D. suzukii individual collected from Hawai‘i shared at least two identical alleles ( coxA and hcpA ) with the non-native species D. simulans that was also collected from Hawai‘i by Ellegaard et al. [ 38 ]). 4.1. Mechanisms of Wolbachia Transmission In the case of purely vertical transmission of Wolbachia within the Hawaiian Drosophilidae, the expectation is that Wolbachia strains would be most similar between closely related host species and that phylogenetic reconstructions of the host and endosymbiont would be fully congruent [ 18 ]. The alternative hypothesis is that host-switching may play a role in transmission, in which case host and endosymbiont phylogenies would be discordant. Using co-phylogenetic reconciliation analysis, we found that optimal solutions generated by JANE consistently showed co-speciation (i.e., vertical transmission) and duplication with host switching (i.e., horizontal transmission) events as significant parameters despite the costs associated with them. Further evidence for both scenarios—vertical and horizontal transmission—are evidenced through strain typing results. For example, the distantly related species D. seclusa and S. caliginosa possessed seemingly identical Wolbachia strains, and conversely, individual hosts belonging to the same species harbored differing Wolbachia strains (e.g., D. engyochracea ). Mechanisms for horizontal transmission are suggested by stochastic character trait mapping results, which revealed a positive association between phylogenetic patterns of Wolbachia and their hosts’ ancestral trait preferred host ovipositional substrate, a trait that is more evolutionarily conserved than affiliations with host plant families [ 3 , 31 ]. For preferred ovipositional substrate, in general, Hawaiian Drosophilidae from the genus Scaptomyza use flowers or rotting fruits (as well as many unusual substrates, such as living Cyrtandra leaves), the AMC clade (i.e., antopocerus , modified-tarsus , ciliated-tarsus ) utilizes rotting leaves, the picture wing species group uses rotting bark or sap-flux, and the modified mouthparts clade (e.g., D. nigrocirrus and D. large spots ) uses a range of ovipositional substrate types [ 31 ]. High posterior probabilities for ancestral states of host ovipositional substrate indicated associations between the trait ‘bark’ and ‘sap flux’ for supergroups A and A/B and the trait ‘leaf’ for supergroup B. This pattern was consistent even for the single D. large spots specimen doubly infected by Wolbachia strains belonging to supergroups A and B. Notably, the only other Wolbachia belonging to supergroup A isolated from Hawaiian Drosophila was isolated from D. nigrocirrus , also a member of the modified mouthparts sub-group. The host plant and substrate are unknown for both of these species. Bennett and colleagues [ 2 ] noted that phylogenetically, wsp alleles amplified from Hawaiian taxa tended to group closely together, and they found evidence for sharing of identical or similar wsp alleles between close and distantly related Hawaiian insect species. They postulated that this observation can be explained by Wolbachia infections persisting through speciation, as well as horizontal transmission occurring between host taxa. An association of Wolbachia supergroup B with the decaying leaf substrate could play a role in one of the evolutionary puzzles of Hawaiian Drosophilidae, namely, why there are so many closely related, sympatric species utilizing the same host substrate. This is most readily seen in the spoon tarsus subgroup on Hawai’i and the bristle tarsus subgroup on Kaua’i. The latter is represented here by six members of the D. basimacula–perissopoda species complex, which can be distinguished by the number and arrangement of thickened bristles on the modified front tarsus of the male. Each was found to carry a different strain of Wolbachia , or none. Novel infection or loss of infection may initiate the localized equivalent of “founder events”, leading to rapid speciation and maintenance of species boundaries when combined with the sexual selection for which Hawaiian Drosophila are well known [ 53 ]. Consistent with our findings, plants are thought to play key roles in the horizontal transmission of Wolbachia strains between infected and uninfected individuals, as well as between diverse insect species. For example, Sintupachee et al. [ 54 ]) found that distantly related species of arthropods found to co-occur on pumpkin leaves harbored Wolbachia with similar wsp sequences, and Li et al. [ 25 ] showed under a controlled experimental laboratory setting that a stable Wolbachia infection could be attained by uninfected whitefly individuals through feeding on the same leaf substrate previously exposed to Wolbachia infected individuals. In that study, Wolbachia was documented as dispersing to adjacent leaves within just a few days of the initial plant infection, where it remained within the phloem of the plant for a minimum of 50 days [ 25 ]. In Hawaiian insects, Bennett et al. [ 2 ] found that nearly identical Wolbachia wsp alleles were shared between some Diptera species (e.g., Drosophila forficata ) and Hemiptera ( Nesophrosyne craterigena ), which they propose is explained by a reliance of both Drosophila and Nesophrosyne species on shared host plants across their ranges. Together, plant utilization and feeding habits may help explain why most native Drosophilidae species were infected with Wolbachia from supergroup B, why some members were infected with supergroup A (modified mouthparts group), and why identical alleles were shared between some distantly related taxa. Our findings are thus congruent with Bennet et al. [ 2 ], who proposed that horizontal transmission of Wolbachia occurs between Hawaiian taxa at multiple taxonomic scales. Insects that possess piercing-sucking mouthparts may be more apt to transmitting Wolbachia to plants through feeding [ 19 , 54 ], and Wolbachia has been found to exist within insect salivary glands in addition to other somatic tissues [ 24 , 55 ]. Additionally, honeydew and infected leaves have been implicated in previous studies as a potential means of horizontal transmission [ 25 , 56 ]. Most non-native Drosophila included in this study were infected with supergroup A; however, infection by supergroup B Wolbachia within non-native D. suzukii individuals could be explained by their occasional use of native plants [ 31 ]. Full strain typing profiles, if available, could be used to test this idea. In other biological systems, although extremely rare, Wolbachia strains have been known to rapidly displace other strains, often in association with insect invasions. For example, the Wolbachia variant w Ri rapidly displaced w Au within their host D. simulans [ 57 ], and horizontal transmission occurred for Wolbachia endosymbionts and their host silverleaf whitefly ( Bemisia tabaci ), in which a host shift event occurred in China from indigenous members of the complex to the invader as well as from the invader to indigenous relatives [ 24 ]. An alternative explanation to plant-mediated horizontal transfer of Wolbachia is through non-lethal probing of infected nymphs and uninfected nymphs by parasitoid wasps ([ 24 ], reviewed by Sanaei et al. [ 58 ]). That mechanism for transmission is consistent with Bennett and colleagues [ 2 ] who postulated parasitoids to be a potential mechanism of horizontal transmission for Wolbachia in Hawaiian taxa, in addition to plant associations. They found that parasitoids, along with native and non-native Drosophila species, were grouped closely together based on the phylogenetic reconstruction of the wsp gene. 4.2. Discrepancy in Supergroup Designation of Loci Whether supergroups can recombine has been the subject of debate. Ellegaard et al. [ 38 ] proposed that Wolbachia supergroups are irreversibly separated, and that barriers other than host-specialization are able to maintain distinct clades in recombining endosymbiont populations. Their conclusion was based on naturally occurring double-infections of Wolbachia strains w Ha and w No endosymbionts of D. simulans . Recent findings from a survey of 33 genome-sequences for Wolbachia strains belonging to supergroups A–F found that strains maintained a supergroup relationship across 210 conserved single-copy genes, yet an analysis of interclade recombination screening revealed that 14 inter-supergroup recombination events had occurred in six of the 210 core genes (6/210 = 2.9%) [ 59 ]. Consistent with recombination events, Baldo et al. [ 60 ]) found evidence for recombination between gatB and fbpA alleles, and intragenic re-combination was detected by comparing patterns of gltA to other housekeeping genes [ 60 ]. In this study, among the 44 Wolbachia strains isolated from Hawaiian Drosophilidae hosts, conflicting supergroup designations were observed for 20.4% of the strains (with data available at two or more genes), which in some cases resulted in an intermediate phylogenetic placement between supergroups A and B. In particular, coxA and hcpA alleles exhibited discordance between supergroup placement, congruent with discordance in supergroup designation for coxA and hcpA alleles observed within Lepidoptera species collected from West Siberia [ 61 ]. Although we cannot fully rule out that allelic discordance across strains may be a result of preferential amplification of certain alleles by primers in the presence of multiple infections—for example, double infections by strains belonging to supergroups A and B were observed to occur within w208 D. apodasta and w215 D. nr. perissopoda —the majority of individuals with conflicting alleles lacked evidence for the presence of a double infection. Therefore, the discrepancy in supergroup assignment between alleles may have resulted from a recombination event that occurred within a doubly infected host species and subsequent fixation of alleles. Further research could help to elucidate the complex interactions of endosymbionts and host taxa occurring within Hawaiian insect communities. 4.3. Conservation Implications The rapid diversification of Hawaiian Drosophila results from a combination of evolutionary-time scale island isolation, rugged topography, and development of novel host plant associations that have persisted for millions of years [ 3 ]. Many species are single-island endemics with narrow ranges and are restricted to the natural distribution of their host plants, which makes populations especially vulnerable habitat degradation and climate change. At present the US Fish and Wildlife Service lists 13 Hawaiian Drosophilds as endangered ( D. aglaia , D. differens , D. digressa , D. hemipeza , D. heteroneura , D. montgomeryi , D. mulli , D. musaphilia , D. neoclavisetae , D. obatai , D. ochrobasis , D. sharpi , D. substenoptera , and D. tarphytrichia ) and one as threatened ( D. musaphilia ). These listed species represent 14.4% of all insects, and 4.8% of all listed invertebrates, within the USA (ECOS Environmental Conservation Online System https://ecos.fws.gov/ecp , accessed on 5 March 2023). Given Wolbachia ’s impacts on reproduction, consideration of host–symbiont relationships and infection status might increase success of breeding programs and ensure that translocation efforts do not suffer from effects of cytoplasmic incompatibility. With regards to climate change, experimental data for Hawaiian Drosophila has demonstrated that species are locally adapted [ 62 , 63 ], thus, resilience to warming temperatures could perhaps be enhanced by manipulation of the host microbiomes, including Wolbachia endosymbionts. Endosymbiont-mediated responses to temperature stress are known to include transcription response and behavior [ 64 , 65 ]."
} | 5,916 |
31547633 | PMC6843645 | pmc | 8,981 | {
"abstract": "The phosphogypsum (PG) endogenous bacterial community and endophytic bacterial communities of four plants growing in phosphogypsum-contaminated sites, Suaeda fruticosa ( SF ), Suaeda mollis ( SM ), Mesembryanthmum nodiflorum ( MN ) and Arthrocnemum indicum ( AI ) were investigated by amplicon sequencing. Results highlight a more diverse community of phosphogypsum than plants associated endophytic communities. Additionally, the bacterial culturable communities of phosphogypsum and associated plant endophytes were isolated and their plant-growth promotion capabilities, bioremediation potential and stress tolerance studied. Most of plant endophytes were endowed with plant growth-promoting (PGP) activities and phosphogypsum communities and associated plants endophytes proved highly resistant to salt, metal and antibiotic stress. They also proved very active in bioremediation of phosphogypsum and other organic and inorganic environmental pollutants. Genome sequencing of five members of the phosphogypsum endogenous community showed that they belong to the recently described species Bacillus albus ( BA ). Genome mining of BA allowed the description of pollutant degradation and stress tolerance mechanisms. Prevalence of this tool box in the core, accessory and unique genome allowed to conclude that accessory and unique genomes are critical for the dynamics of strain acquisition of bioremediation abilities. Additionally, secondary metabolites (SM) active in bioremediation such as petrobactin have been characterized. Taken together, our results reveal hidden untapped valuable bacterial actors for waste remediation.",
"conclusion": "5. Conclusions Despite the serious PG negative environmental impact involving drawbacks on human health, there is no bio/phytoremediation schemes to deal with this deleterious waste. PG and plant-associated endophytes microbiomes offer a credible alternative towards efficient management. A prerequisite for this is the characterization of these microbiomes and their functional investigation. Using metagenomic analysis and culture-based approaches, we describe unique communities thriving in this extreme environment. PG and plant-associated endophytes microbiomes proved to be endowed with an impressive battery of metabolic xenobiotic biodegradation capacities and genomic plasticity allowing them to adapt to these extreme environments. The results of this study will probably ultimately allow efficient development of bio/phytoremediation schemes of phosphogypsum.",
"introduction": "1. Introduction When using rock phosphate as raw material for the production of phosphoric acid, phosphogypsum (PG) is the main waste generated. Phosphogypsum, currently considered a NORM (naturally occurring radioactive material), contains numerous hazardous materials such as natural radionuclides and heavy metals [ 1 ]. Management of phosphogypsum is challenging in numerous countries. In Tunisia, when discharged on the marine environment in the Gulf of Gabes, phosphogypsum severely impacts the ecosystem where environmental conditions can be considered as critical [ 2 ]. Its use as a fertilizer, while environmentally and economically sound, is hindered by its high toxicity to crops and earthworms [ 3 , 4 , 5 , 6 ]. Therefore, there is an urgent need to remediate the millions of tons of PG that weaken ecosystem functions and represent serious threats to the environment and human health. While traditional mitigation technologies failed to treat the high volumes of waste, a more sustainable and eco-friendly mean consists of the use of the PG microbiome able to degrade PG [ 7 , 8 ]. Plants also form associations with diverse beneficial microorganisms that can provide them with selective benefits [ 9 , 10 , 11 , 12 , 13 , 14 , 15 ]). Among them, bacterial endophytes can support plant growth, prevent plant diseases and alleviate abiotic stresses [ 16 , 17 , 18 , 19 , 20 ]). Considerable interest is therefore drawn actually to describe endophytic communities from plants that are subjected to diverse types of stress [ 21 , 22 , 23 , 24 ]. Under contaminated environments where plants thrive, endophytes can alleviate pollutant-induced stress by producing indole-3-acetic acid (IAA), a plant hormone that promotes their growth and development [ 10 , 25 ]. Endophytes can also solubilize phosphate and nitrogen, which are considered among the elements most limiting to plant growth and development [ 13 , 15 ]. They are also able to release 1-aminocyclopropane-1-carboxylate (ACC) deaminase, responsible for a relevant decrease of ethylene production [ 10 ]. It is believed that plants thriving with endophytes endowed with ACC deaminase activity have longer roots and shoots. They are also more resistant to growth inhibition by a variety of ethylene-inducing stresses [ 21 ]. HCN production by endophytes is beneficial for plant hosts as suggested by Rijavec and Lapanje [ 26 ] through the sequestration of metals and the consequential indirect increase of nutrient availability. Siderophore production by endophytes enables PGP indirectly and are, therefore, considered beneficial for plants thriving under environmental pollution [ 27 ]. Taken together, all these elements lead to the proposal that endophytes endowed with PGP potential and contaminant-degrading abilities would be optimal means for the full development of bio- and phyto-remediation to efficiently clean up wastes and contaminants [ 21 ]. In this study, to unravel the potential of use of the phosphogypsum microbiome and the potential of endophytic plants thriving in this waste for its remediation, we investigated through cultivation independent (using amplicon sequencing technology) phosphogypsum bacterial microbiome as well as bacterial endophyte microbiomes of four plants SF , SM , MN and AI thriving in this waste. Simultaneously, the culturable community was also recovered and their PGP potential, stress tolerance and bioremediation potential were studied. Finally, genome mining of five phosphogypsum endogenous bacteria allowed us to shed the light on their stress tolerance and bioremediation potential at the genomic level.",
"discussion": "4. Discussion Phosphogypsum, a by-product of the production of fertilizer from phosphate rock, is stored in large stacks. PG discharge into the sea has been practiced in Tunisia with dramatic consequences to marine ecosystems [ 2 ]. PG contains toxic components harmful to ecosystems and human health; these include heavy metals and radionuclides [ 1 ]. PG use as a fertilizer has also been limited by its toxic effect on plant growth and development and earthworms [ 3 , 4 , 5 , 6 ]. Its use as a construction material is also seriously limited by its radioactivity [ 39 ]. PG used in our study shows high metal content that has been linked to its ecotoxicity [ 4 ]. Our ICP-OES analysis shows different toxic metal concentrations according to PG provenance [ 7 , 8 ]. PG toxicity warrants the development of ecofriendly smart remediation means of the million tons piled on stacks. Here, we take advantage of PG and associated plant endophytic microbiomes to develop environmentally sound means for bioremediation of PG. In a first step, we analyzed the PG and SF, SM, MN and AI endophytic microbiomes by Illumina high throughput sequencing. Our results document more diverse bacterial microbiomes in PG than in plant endophyte microbiomes. The SF, SM, MN and AI endophytic bacterial microbiomes were significantly less diverse (low richness) and more equal (high evenness) than PG communities, a result that is in agreement with the study of Marasco et al. [ 40 ] on desert spear grasses. The PG bacterial community was dominated by firmicutes (39.3%), proteobacteria (24.2%) and actinobacteria (20.4%). This is in agreement with the study of Zouch et al. [ 8 ]. SF, SM, MN and AI endophytic microbiomes were dominated by protebacteria (89.6%) and firmicutes (10.4%); proteobacteria (98.5%); proteobacteria (96.7%) and proteobacteria (99.8%), respectively, in agreement with the reports of Gonzalez et al. [ 41 ] and Hassani et al. [ 42 ]. Similar results have also been reported for the microbiome of arugula (Eruca sativa Mill.) by Cernava et al. [ 43 ], Vitis vinifera [ 40 ], Apple [ 44 ] and Trifolium pratense [ 45 ]. For PG bacterial community bacilli (38.3%) dominated the firmicutes with main genera being Bacillus (20.7%) and Enterococcus (17.6%). Similar results have been reported by Kolekar et al. [ 46 ] for atrazine exposed soil in microcosm experiments. Alpha proteobacteria (18.8%) dominated the proteobacteria and actinobacteria were dominated by the genus Kocuria (15.2%), known to occur in diverse high pollution load wastes [ 47 ]. SF and SM endophytic microbiomes were dominated by Alpha proteobacteria (85.9% and 95.2%, respectively), while MN and AI endophytic microbiomes were dominated by Gamma proteobacteria (96.6% and 95.5%, respectively) with the main genera being Enterobacteriaceae genera (50.9%) undescribed genera and Halomonas (44.8%). All these genera have been frequently described as inhabitants of plant roots [ 44 ]. High specificity of taxa to their origin or host was observed (136), while only two taxa were common to PG and plant endophytic microbiomes. Network analysis revealed two main co-occurrences groups: a first group represented by Clostridium gasigenes , Prevotella copri , Cesiribacter adanamensis and Shewanella algae and a second group represented by Paenibacillus aminolyticus , Carnobacterium viridans , Bacillus formainis , Pseudomonas fragi and Chromohalobacter salixigens . These findings are of paramount importance to understand how bacterial consortia are recruited for efficient bio or phytoremediation. Metagenome functional prediction documented no clear difference between PG and plant endophytic microbiomes despite their diverse compositions. This result is in agreement with microbiomes being selected according to their functional content as suggested by Hassani et al. [ 42 ]. Along with the main functional categories, metabolism (49.4%), genetic information processing (16.3%), unclassified (14.8%) and environmental information processing (14.7%), xenobiotics, biodegradation and metabolism (2.3%), metabolism of terpenoids and polyketides (2%) and biosynthesis of other secondary metabolites (1%) are also represented. Similar findings were reported in Li et al. [ 48 ] for plant adaptation to adverse environments with high calcium contents. Given these findings, it was relevant to recover culturable population and to test single bacterial isolates metabolic capacities. The culturable PG community was dominated by Bacillus spp. belonging mainly to the BC group. The BC group is widely linked to bioremediation [ 42 , 49 ] and the endophyte culturable microbiome of SF, SM. MN and AI were more diverse than PG and lumped representants of 11 different genera. All of them are widely associated with a plant endophyte life style and efficient phytoremediation potential [ 10 , 15 ]. The PG and plant microbiomes were endowed with huge metabolic capacities. SF, SM, MN and AI endophytic communities have strong PGP activities reminiscing their endophytic life style [ 10 ]. While, PG and plant microbiomes displayed bioremediation and stress tolerance traits. Numerous studies reported similar results with different plants endophytes [ 15 , 43 , 50 ]. Interestingly, waste degradation potential was not limited to PG but extended to other recalcitrant wastes including TWW and OWW, insecticides such as imidacloprid, permethrin and dimethoate and the herbicide glyphosate. This result is of critical importance and is supposed to stimulate more studies into endogenous waste and associated plants microbiomes. Given the importance of these cultivable PG and associated plants endophyte microbiomes metabolic capacities, we decided to sequence the genomes of PG 1, PG 9, PG 17, PG 18 and PG 26 highly effective in the degradation of, TWW, PG, metals, insecticides and OWW. The five sequenced species were all identified as BA using the gold standard for bacterial species identification based on phylogenomics, GGD and ANI inputs for definition of species boundaries [ 10 , 51 ]. Moreover, using the concatenated amino acid sequences of core genome derived from the five genomes of BA to reconstruct phylogenetic relationships among the BA genomes, we confirmed the results obtained using GGD and ANI analysis suggesting that isolates belong to BA. BA has previously been isolated from the tailings of Panzhihua mining area and has high tolerance to vanadium (BA strain N35-10-2, GenBank accession: MAOE00000000) and Silt in tailing reservoir area (BA strain PFYN01, GenBank accession: CP034548). Comparative genomics analysis of BA PG 1, PG 9, PG 17, PG 18, PG 26, PFYN01 and N35-10-2 document their status as different strains of BA. These differences have been further confirmed by analysis of the different strains synteny and conserved and unique gene families. A species core genome, represented by gene sets shared by available genomes, describes the common metabolic and functional features of the species [ 10 , 15 ]. While pan genome mirrors full potentialities of considered species. Therefore, studying core and pan genome functional content is of paramount importance to decipher major intra species trends and main lifestyles [ 10 ]. Comparative genomics of BA isolates allowed showing that the species pan-genome might be an open pan-genome experiencing frequent changes through gene gains and losses or lateral gene transfers for efficient environmental adaptations [ 15 ]. Genome mining for detoxification and degradation of organic pollutants allowed conclusion that BA has an impressive molecular tool box for environmental bioremediation. Additionally, secondary metabolites have been suggested as relevant actors in the biodegradation of organic pollutants [ 10 ]. Genome mining of the PG BA isolates allowed to shed the light on relevant SM already reported for their bioremediation activity such as petrobactin [ 52 ]. Studying functional content of core and pan genome is of paramount importance to decipher major trends of intra species evolution and lifestyles [ 10 , 50 , 53 ]. In BA, while, the core genome was enriched with basic metabolic functions such as translation, ribosomal structure and biogenesis as well as coenzyme and nucleotide transport and metabolism, functional genes related to secondary metabolites biosynthesis, xenobiotic degradation, transport, and catabolism and defense mechanisms have been enriched in the accessory genome. A unique genome was enriched in cell wall, membrane and envelope biogenesis and replication recombination and repair along with genes of unknown or general function prediction only. We speculate that given the lifestyles of bacteria used in this study basic metabolic functions have been concentrated in the core genome while metabolic functions such as repair, membrane and envelope biogenesis, biosynthesis of SM and xenobiotic degradation have been allocated to accessory and unique genomes of strains to allow them to adapt to specific niches such PG in this study. More genome sampling is needed to infirm or confirm this hypothesis."
} | 3,817 |
34365153 | null | s2 | 8,982 | {
"abstract": "Bacteria grown on a mixture of carbon substrates exhibit two utilization patterns: hierarchical utilization (HU) and simultaneous utilization (SU). How and why cells adopt these different behaviors remains poorly understood despite decades of research. Recent studies address various open questions from multiple viewpoints. From a mechanistic perspective, it was found that flux sensors play a central role in the regulation of substrate utilization, accounting for the known dependences on single-substrate growth rates, substrate concentrations, and the point where the substrate enters central metabolism. From a physiological perspective, several recent studies suggested HU or SU as growth-optimizing strategies through efficient allocation of essential proteome resources. However, other studies demonstrate that a significant fraction of the proteome is dedicated to functions apparently unnecessary for growth, casting doubt on explanations based on slight efficiency gains. From an ecological perspective, recent theoretical studies suggest that HU can help increase species diversity in bacterial communities."
} | 280 |
31771141 | PMC6956225 | pmc | 8,984 | {
"abstract": "Multifunctionalities linked with the microbial communities associated with the millet crop rhizosphere has remained unexplored. In this study, we are analyzing microbial communities inhabiting rhizosphere of kodo millet and their associated functions and its impact over plant growth and survival. Metagenomics of Paspalum scrobiculatum L.(kodo millet) rhizopshere revealed taxonomic communities with functional capabilities linked to support growth and development of the plants under nutrient-deprived, semi-arid and dry biotic conditions. Among 65 taxonomically diverse phyla identified in the rhizobiome, Actinobacteria were the most abundant followed by the Proteobacteria. Functions identified for different genes/proteins led to revelations that multifunctional rhizobiome performs several metabolic functions including carbon fixation, nitrogen, phosphorus, sulfur, iron and aromatic compound metabolism, stress response, secondary metabolite synthesis and virulence, disease, and defense. Abundance of genes linked with N, P, S, Fe and aromatic compound metabolism and phytohormone synthesis—along with other prominent functions—clearly justifies growth, development, and survival of the plants under nutrient deprived dry environment conditions. The dominance of actinobacteria, the known antibiotic producing communities shows that the kodo rhizobiome possesses metabolic capabilities to defend themselves against biotic stresses. The study opens avenues to revisit multi-functionalities of the crop rhizosphere for establishing link between taxonomic abundance and targeted functions that help plant growth and development in stressed and nutrient deprived soil conditions. It further helps in understanding the role of rhizosphere microbiome in adaptation and survival of plants in harsh abiotic conditions.",
"conclusion": "4. Conclusions Understanding how different microbial communities in the rhizosphere influence plant performance and productivity using metagenomics opens new avenues for devising eco-friendly ways to cater benefits from microbe-mediated agricultural technologies. Millet crops are in center of attention across the world as they ably grow under nutrient deprived soil conditions, reflect environmental robustness, possess disease resistance and remediation ability, and are high in food nutritional value. Accumulating evidences suggest that crop plants in their rhizosphere microenvironment are largely supported by the belowground microbial communities. Metagenomic analysis of kodo rhizosphere revealed high taxonomic diversity with actinobacterial dominance. Further analysis of the metabolic capabilities of microbial communities associated with the kodo rhizosphere has been established with the observations that gene sequences linked with normal physiological pathways, carbon fixation, nutrient cycling and acquisition, stress and defense response, secondary metabolism, xenobiotic degradation, and bioremediation were abundantly identified in the metagenome. With such metabolic functions, the microbial communities are supposed to support growth, development and survival of the crop in the soil under tough environmental conditions. These results established that a rich gene pool is associated with the kodo rhizosphere for: (i) various secondary metabolite pathways associated with synthesis of bacteriocins or ribosomally synthesized antibacterial peptides; (ii) resistance against diverse antimicrobial compounds; and (iii) detoxification of xenobiotic compounds and metals. Knowing these facts, either new culturable strategies can be devised to isolate such microbial strains that can show robust behavior in the adverse condition or model organisms can be manipulated with such genes to harvest novel functional benefits. The information from mining of metagenome of neglected but agro-ecologically robust and nutritionally sound plants is helpful to identify novel genes and proteins of varied functions. This is also helpful in mapping metabolome of kodo rhizosphere to explore novel small molecules with proven functions of agricultural implications. Conclusively, the availability of genes associated with different important biological processes indicates how the inhabiting microbial communities adopt and respond in the rhizosphere microclimate at both the community and organism level and exhibit metabolic capabilities to support growth and development of kodo plants.",
"introduction": "1. Introduction Crop plant rhizosphere harbors a huge collection of mutualistic microbial population which encodes metabolic activities supporting the growth and development of the host and associative organisms [ 1 ]. Soil bacteria in close propinquity to the plant roots, i.e., the rhizosphere exhibit deep impact on nutrient management and plant defense against biotic and abiotic stresses [ 2 ]. Rhizosphere associated microbial communities play a key role in different biogeochemical cycles [ 3 ]. A vast microbial majority with interactive functions in the natural habitats still remains uncharacterized due to the limitations of culturability on media conditions [ 4 , 5 ]. This is specifically true in the dynamic biological systems like rhizosphere, which harbors complex microbial diversity and metabolic functions [ 6 , 7 ]. Therefore, for characterizing complex rhizosphere communities and linking functionalities, metagenomics has provided access to the rich pool of genomes in a particular microenvironment [ 8 ]. Understanding how different microbial communities in the rhizosphere influence plant performance and productivity using metagenomics can open new avenues for devising eco-friendly ways to cater benefits from microbe-mediated agricultural technologies [ 9 ]. Paspalum scrobiculatum (kodo or Indian crown grass) is among the ancient grain millets grown in many parts of India, Philippines, Indonesia, Thailand, and West Africa [ 10 ], where it is consumed as nourishing healthy and vitality foods in rural areas [ 11 ]. As a drought-tolerant and hardy monocot crop especially confined to semi-arid regions, kodo is grown on about 907,800 ha of land annually with the approximate annual production of 310,710 tons [ 12 ]. The crop grains possess high-value proteins (11%), carbohydrates (66.6 g per 100 g of grains equivalent to 353 kcal), low fat (3.6 g per 100 g) with iron (25.86 to 39.6 ppm), calcium (27/100 mg) and antioxidant free-radical scavengers [ 13 ]. Kodo plants exhibit medicinal attributes like antidiabetic and antirheumatic activities, cures wounds and possesses a tranquilizing effect [ 12 , 13 ]. As against rice and wheat, which contain 0.2% and 1.2% fiber content, kodo is fiber rich (9%) and thus, a beneficial food source for subsistence farming communities in many regions in India and Africa. Having said that the plant rhizosphere is dynamic and live ecosystem inhabited by diverse microbial communities with apparent multifunctions [ 14 ], focused attention is required to decipher inhabitants of the millet rhizosphere and link communities with the multifunctionalities that favor plant and soil health in such difficult ecological conditions. We analyzed microbial communities and functions in the kodo millet rhizosphere metagenome and identified overall taxonomic abundance of communities, their functional pathways and metabolism in this rhizosphere and establish their role in stress responses, adaptation to abiotic stresses, nutrient recycle, xenobiotic degradation, carbon fixation, plant growth promotion, and disease resistance. The study indicated multi-functions of the microbial communities that help plant growth and development under water deficit drought stress in the rhizosphere. It further extends our understanding on the role of rhizosphere microbiome in adaptation and survival of plants growing under nutrient deprived conditions.",
"discussion": "3. Results and Discussion Millet crops have gained worldwide attention due to their intrinsic resistance against diseases, nutritional value to feed subsistence rural population, ability to grow under dry and harsh conditions, and environmental robustness. Physicochemical analysis of kodo rhizosphere suggested that the soil was low in carbon (0.49%), nitrogen (available N 195.7 kg/ha),and phosphorus (available P 9.46 kg/ha) content. The soil was almost normal with pH 7.15 and moderate in potassium (available K 167.2 kg/ha) content. The soil analysis revealed that the kodo millet plants were growing well in low carbon and nutrient deficient soils in the water deficient conditions. 3.1. Sequencing and Annotation of Proteins A total of 2.6 GB data was obtained for kodo rhizosphere metagenome with 10,669,925 sequences. Out of the total sequences, 590,010 (5.53%) failed to pass the QC pipeline. Furthermore, 516,927 sequences were identified as artificial duplicate reads. Of the sequences that passed quality control, certain sequences (11,748) were predicted as ribosomal RNA genes (0.13%) while 33.13% (3,086,627) were identified as predicted proteins with known functions and 66.75% (6,218,676) as predicted proteins with unknown functions. 3.2. Taxonomic Microbial Diversity in the Kodo Rhizosphere The taxonomic classification of genes was carried out through Best Hit Classification algorithm of MG-RAST against the M5NR database [ 16 ]. A total of 9,317,051 sequences were assigned to various taxonomies. There were also a number of sequences that could not be assigned to the highest taxonomy levels with an average of 15.5% of the reads and they were tagged as either unassigned, unclassified, or ‘others’. Over all, bacteria dominantly accounted for 98.12% of the total assigned reads followed by Eukaryota (1.21%) and Archaea (0.58%), while ‘unclassified sequences’ and ‘other sequences’ accounted only for 0.06 and 0.01% respectively. Viral sequences were least abundant in the rhizosphere sample with only 0.01% fraction. The alpha diversity for the kodo rhizobiome was calculated to be 381 reflecting the presence of significant number of species. The rarefaction curve predicted the taxonomic diversity and reflected significantly high level of community variability in the kodo rhizosphere ( Figure 1 ). 3.3. Community Composition and Abundance A total of 65 different phyla were identified for the reads along with those characterized as ‘unclassified sequences’ (derived from Archaea, Bacteria, Eukaryota, Fungi, other sequences, unclassified sequences or viruses). Among all the phyla, Actinobacteria (42.22%) and Proteobacteria (23.72%) were the most dominating communities with almost 66% of total reads. Other dominant bacterial phyla included Chloroflexi (7%), Firmicutes (5.08%), Acidobacteria (4.65%), Bacteroidetes (4%), Verrucomicrobia (3.7%), Planctomycetes (2.32%), and Cyanobacteria (1.95%). Rest of the phyla possess less than 1% of total reads ( Figure 2 ). At class level, 205 different classes were identified. Actinobacteria was the most dominant class occupying 42.22% of the total assigned reads followed by Alphaproteobacteria (12.57%), Betaproteobacteria (4.45%), Ktedonobacteria (4.42%), Acidobacteria (3.61%), Gammaproteobacteria (3.48%), Deltaproteobacteria (3.05%), Clostridia (2.33%), Planctomycetacia (2.32%), Bacilli (2.29%), unclassified (derived from Cyanobacteria) (1.92%), Spartobacteria (1.90%), Sphingobacteria (1.6%), Thermomicrobia (1.23%), Chloroflexi (1.18%), Verrucomicrobiae (1.12%), and Cytophagia (1.02%). Less than 1% of the entire reads was individually assigned to rest of the classes which cumulatively accounts for 9% only ( Figure 2 ). At the order level, hits were obtained for 554 different taxa with maximum hits for Actinomycetales (36.87%). Only 16 orders occupied more than 1% of the reads though rest of the orders cumulatively accounted for 22.54% of the total distribution ( Figure 2 ). Family-level taxonomy indicated 1073 identified families. However, only 23 families were with more than 1% of the total read distribution. Most of the dominantly present families were observed for the order Actinomycetales (26.03%) including Streptomycetaceae (9.45%) and 10others (Frankiaceae: 3.80%, Pseudonocardiaceae: 2.91%, Mycobacteriaceae: 2.70%, Nocardiaceae: 2.33%, Micromonosporaceae: 1.96%, Streptosporangiaceae: 1.43%, Catenulisporaceae: 1.37%, Nakamurellaceae: 1.24%, Nocardioidaceae: 1.2%, and Actinosynnemataceae: 1.05%). We noticed that 42.78% of the total reads were assigned to rest of 1050 families with less than 1% of reads. Similarly, at genus level reads were assigned to 2115 different genera with only 17 genera having more than 1% reads. Rest of the genera cumulatively accounted for 55.75% distribution ( Figure 2 ). In these 17 genera, Streptomyces (9.37%) was the most dominant community while nine other genera also belonged to the order Actinomycetales (Frankia, Mycobacterium, Rhodococcus, Micromonospora, Streptosporangium, Catenulispora, Amycolatopsis, Nakamurella, and Actinosynnema). Actinomycetales is the taxonomic order of Actinobacteria with largest taxonomic units amongst 18 identified lineages within the bacteria [ 24 , 25 ]. The members are referred to Actinomycetes, the species of which are known for producing prominent antimicrobial compounds—such as streptomycin, actinomycin, and streptothricin of immense agricultural importance [ 26 , 27 ]. The order Streptomycetales, especially the genus Streptomyces synthesizes almost 80% of the total metabolites known today as compared to other unicellular bacteria except Bacillus and Pseudomonas species (16%), cyanobacteria (3.7%), and myxobacteria (1.8%) [ 28 ]. These communities serve as valuable sources of novel secondary metabolites with multiple biological functions such as antagonism, anti-infection, anticancer, and antibiotics [ 29 , 30 , 31 , 32 ]. The dominance of Actinobacteria in the kodo rhizosphere reflects significant attributions with respect to the crop robustness against diseases, and that too under stressed environment. These communities have a proven role to protect plants under oxidative stress conditions [ 32 , 33 ], their dominance indicates their supportive functions for the kodo crop being grown in dry environment. Apart from this, the revelations on the dominance of Streptomycetales community in the kodo rhizosphere may invite attention for the isolation and identification of antibiotic-producing cultivable actinobacteria using culturable strategies. The second most dominating family and genus of Actinomycetales was Frankia , a N-fixing actinomycete forming root nodules [ 34 ]. These communities fix nitrogen under free-living and symbiotic conditions [ 25 , 35 , 36 ]. Since kodo is grown in fertility-deprived soil and the crop requirement for N as external input is low (40 kg N per ha) ( http://vikaspedia.in/agriculture/crop-production/package-of-practices/cereals-and-millets/finger-millet-and-kodo-millet ; website visited on 17.9.2019), the dominance of N-fixer Frankia species in the rhizosphere reflects prominent role of these communities in supporting N-demand of the plants under low nitrogen conditions. 3.4. Metabolic Multifunctionalities in the Kodo Rhizosphere Microbial communities inhabiting rhizosphere soil play crucial biogeochemical role in the root microenvironment [ 37 ]. Functional characterization of the rhizobiome thus becomes crucial for the understanding of microbial support to the plants in nutrient-poor, abiotic stressed and disease prone conditions [ 38 , 39 ]. Protein function in the dataset was identified through evidence-based annotations (COG, KEGG, SEED SubSystem) classified into diverse hierarchies i.e. particular genes, protein families and cellular processes. Identified proteins revealed community-linked metabolic potentials and functional activities of the kodo rhizosphere. COGs classification reflected that ‘Metabolism’ (48.33%) was the most abundant functional category followed by ‘Information Storage and Processing’ (20.45%) and ‘Cellular Processes and Signaling’ (16.65%) ( Figure 3 ). ‘Poorly characterized’ (14.57%) category was also noticed. KEGG also showed ‘Metabolism’ (61.37%) as the most abundant category followed by ‘Genetic Information Processing’ (20%), ‘Environmental Information Processing’ (13%), ‘Cellular Processes’ (3.74%), ‘Human Diseases’ (1.5%), and ‘Organismal Systems’ (0.43%) ( Figure 3 ). Hierarchical analysis of Level 1 of SEED Subsystems again reflected different prominent functions of microbial communities in the rhizopshere. Sequences associated with carbohydrate metabolism, amino acids and derivatives, protein metabolism, cofactors, vitamins, prosthetic groups, pigments and RNA and DNA metabolism were abundant ( Figure 3 ). Metaproteomics [ 40 , 41 ] and metatranscriptomics studies [ 42 , 43 , 44 , 45 ] have already been reported for the presence of such functional categories in different soil, sediment and water ecosystems. These functions were shown to be linked with the maintenance and regulation of basic cellular processes that support growth and metabolism of microbial communities under various environments [ 46 , 47 ]. We speculate that with the abundance of these functions, the communities harboring kodo rhizosphere maintain and regulate their own cellular functions and metabolism. 3.5. Carbon Fixation The analysis indicated that the genes related to the pathways involved in the central carbohydrate metabolism and energy generation (Entner–Doudoroff pathway, glycolysis and gluconeogenesis, and pentose phosphate pathway) were significantly present in the dataset. Abundant hits were observed for carbon dioxide fixation along with the pathways of Calvin–Benson cycle, carboxysome, CO 2 uptake, and photorespiration (oxidative C2 cycle). Different level 2 stages, their associated pathways and enzymes related to carbohydrate metabolism including amino sugars (GlcNAc) 2 catabolic operon, chitin and N-acetylglucosamine utilization, N-acetyl-galactosamine and galactosamine utilization, neotrehalosadiamine ((NTD) Biosynthesis Operon); central carbohydrate metabolism (including glycolysis, gluconeogenesis) were identified. In the kodo rhizosphere, the communities that utilize amino sugars, polysaccharides, organic acids, one-carbon compounds, and sugar alcohols as sole source of carbon and energy were observed. The communities that participate in the central carbohydrate metabolism, fermentation, and hydrolysis were also identified for their food and energy related needs. This is eventually helpful for survival of kodo plant as biochemical analysis reflects low organic content of soil. It reflects that rhizosphere microbial communities are helping the plant to meet their demand for carbon through different metabolic pathways as soil exhibits low carbon content. 3.6. Mineral Metabolism The dataset was analyzed for different hierarchies (level 2, level 3, and functions) with the SEED subsystems to explore genes linked with the major functions in nitrogen, phosphorus, sulfur, and iron metabolism 3.6.1. Nitrogen Metabolism Reads related to ammonia assimilation (58%) occupied a maximum of the total sequences of N metabolism followed by ammonification (28%) and denitrification (5%). The proportion of the reads linked with N fixation was low (1% only) ( Figure 4 ). A minor fraction of the reads matched with the processes like allantoin utilization and cyanate hydrolysis. The abundance of reads linked with ammonia assimilation in the plant rhizosphere followed by those associated with nitrate and nitrite ammonification is indicative of such processes that enhance nitrogen use efficiency (NUE) in the plants [ 48 ] that grow under low N availability [ 49 ]. Since ammonia can be directly assimilated in to amino acids, few pathways like glutamate, alanine, or aspartate and other cellular components are known for its assimilation. Enzymes like glutamate dehydrogenase (GDH), glutamine synthetase (GS), and glutamate synthase are the major catalyzing agents for these reactions. Reads associated with the enzymes glutamate synthase (EC 1.4.1.13), glutamate-ammonia-ligase adenylyltransferase (EC 2.7.7.42), nitrogen regulation protein (NR(I) and NR(II)), nitrogen regulatory protein (P-II), and ammonium transporter indicate prominent assimilation of ammonia in the rhizosphere inhabiting microbial communities. Certain bacteria possess the ability to reduce nitrate and/or nitrite to ammonium (NH 4 + ) without nitrous oxide as an intermediate. The process, known as nitrate/nitrite ammonification improves NUE because the end product, i.e., ammonia is retained in the soils for utilization by the plants. The reads related to the nitrate/nitrite ammonification (28%) were dominant in the kodo rhizosphere. The enzymes such as nitrate ABC transporter, nitrate/nitrite transporter, nitrite reductase (EC 1.7.1.4), Respiratory nitrate reductase (EC 1.7.99.4), nrfE, NrfC protein, response regulator NasT responsible for these processes were identified in the rhizosphere metagenome. Functionally, the dominance of these processes due to dominant microbial communities with such functionalities may enrich soil N content. We further explored the reads for different enzymes that help incorporation of nitrogen in the plants [ 50 ]. Prominent enzymes allantoate amidohydrolase (EC 3.5.3.9), allantoicase (EC 3.5.3.4), allantoinase (EC 3.5.2.5), ureidoglycolate dehydrogenase (EC 1.1.1.154), and ureidoglycolate hydrolase (EC 3.5.3.19) related to allantoin utilization were identified in the dataset. Sequences linked with the methylobacterium, which is known for allantoin utilization [ 51 ] are present significantly ( Figure 4 ). Presence of such communities and their processes are therefore, indicative of improving N economy in rhizosphere through enhanced NUE under nitrogen limitations. Rhizosphere soil analysis has indicated deficiency of N, which seems to be compensated by the presence of N fixing and assimilating microbial communities. Thus, the microbial communities are helping the plants to cope up with less N content through making environmental nitrogen available. The presence of different cyanate ABC transporter proteins, cyanate hydratase (EC 4.2.1.104) and Cyn operon transcriptional activator involved in cynate hydrolysis was traced. Cyanate is generally formed spontaneously inside the cells from urea and carbamoylphosphate [ 52 , 53 ] or appear in the environment as a result of physicochemical decomposition of urea or cyanide [ 54 , 55 ]. Certain marine cyanobacteria [ 56 , 57 ] and only one identified organism, Nitrososphaera gargensis [ 58 ] utilize cyanate as N source for energy under N-limiting conditions [ 59 ]. The presence of the reads linked with the cyanate metabolism in kodo rhizosphere may be an interesting finding. Different enzymes including nitrite reductase (EC 1.7.2.1), nitric-oxide reductase (EC 1.7.99.7), nitrous-oxide reductase (EC 1.7.99.6), transcriptional regulator and maturation protein for denitrification were identified. Though denitrification is a process of losing N from the soils, the presence of enzymes with denitrifying activities, even in low proportion (5%) reflects a naturally balanced ecosystem, where microbial communities normally return fixed N to the atmosphere [ 60 ]. For N fixation, reads linked to homocitrate synthase (EC 2.3.3.14), nitrogenase, NifA and VnfA were identified. Certain reads were also identified for the enzymes involved in the processes of N metabolism like nitrosative stress (NorR, NnrS), dissimilatory nitrite reductase (Cytochrome c551 NirM), nitric oxide synthase (putative cytochrome P450 hydroxylase), and nitrilase (Plant-induced nitrilase; EC 3.5.5.1). Altogether the results generate an insight that in the kodo rhizosphere, nitrogen economy is mainly maintained by the processes like ammonia assimilation, nitrate/nitrite ammonification, allantoin utilization, and N fixation ( Figure 4 ). The soils in which these plants grow are usually N deficient and the N fertilizer usage in kodo crop is very limited [ 49 ]. In the rhizosphere, plants, microbial communities, and other soil inhabitants interdependently depend on the naturally managed low N resources for their nitrogen requirements. This has major implications for kodo plants because N is a crucial element for the growth and development. 3.6.2. Phosphorus Metabolism Phosphorus (P) is an essential macronutrient. It also manages low pH stress through cytoplasmic buffering of hydrogen ions [ 61 ]. Limited availability of P in the soils, freshwater, and marine ecosystems influences primary and heterotrophic bacterial productivity [ 62 ]. The rhizosphere of the kodo is low in P as is evident from the soil analysis. Microorganisms acquire inorganic and organic forms of reduced P compounds like phosphonate, phosphite, and hypophosphite [ 63 ]. The most abundant gene pool (71%) for P metabolism in the dataset included different Phn proteins, phosphate metabolism (different phosphatase, NAD(P), transhydrogenase and various enzymes (EC 3.1.3.1, EC 3.6.1.11, EC 3.6.1.1, EC 1.6.1.2, EC 2.7.4.1, EC 3.6.1.1, EC 1.6.1.1), phosphoenolpyruvate phosphomutase, phosphonate metabolism (different ABC transporter) proteins along with phosphate-binding DING proteins ( Figure 4 ). Different enzymes prominently related to high-affinity phosphate transporter and control of PHO regulon (16%), P-uptake (10%), and alkylphosphonate utilization were indicative of enhanced plant P availability, P-solubilization, and mineralization through the acquisition of P from phosphonates with the help of rhizosphere microbial communities, as is evident from earlier studies [ 64 ]. 3.6.3. Sulfur Metabolism In the kodo rhizosphere, 48% genes were linked with inorganic sulfur assimilation and those involved in galactosylceramide, sulfatide metabolism, and sulfur oxidation. Enzymes known for inorganic sulfur assimilationlike ABC-type probable sulfate transporters, adenylylsulfate reductase, ferredoxin, oxidoreductase, sulfate adenylyltransferase, sulfate transport system, and permease proteins were identified. Genes related to galactosylceramide and sulfatide metabolism, sulfate reduction-associated complexes, sulfur oxidation, and thioredoxin-disulfide reductase were also detected. For organic sulfur assimilation, genes and pathways related to alkanesulfonate assimilation, DMSP breakdown, L-Cystine uptake/metabolism, and utilization of taurine and glutathione as a sulfur source were identified ( Figure 4 ). Of the two sulfur oxidation pathways, the Sox is involved in complete oxidation of reduced sulfur compounds to sulphate while the APS involves adenosine-5-phosphosulphate as an intermediate [ 65 , 66 ]. A completely functional Sox complex includes SoxB (key component), SoxXA, SoxYZ, and SoxCD components [ 64 , 65 ]. Reads linked with sulfur oxidation (14%) showed SoxB along with SoxA, SoxX, and SoxY suggesting the occurrence of sulfur oxidation processes in the rhizosphere. Sulfur-oxidizing bacterial communities include members from Alpha-, Beta-, Gamma- and Epsilon-proteobacteria, Chlorobia and Chloroflexi along with the photo- and chemoautotrophic bacteria [ 65 , 66 ] while the sulfur-reducing bacteria are mostly from Deltaproteobacteria [ 66 , 67 , 68 , 69 ]. Interestingly, a wide assemblage of these communities inhabited kodo rhizosphere as is evident from their taxonomic abundance ( Figure 2 ). Apart from inorganic sulfur assimilation and sulfur oxidation, reads linked with alkanesulphonate assimilation (13%), utilization of glutathione as sulfur source (8%), thioredoxin-disulfide reductase, and L-cystine uptake and metabolism (both 6%) were also present( Figure 4 ). The role of the enzymes associated with sulfur metabolism have been reported from microbial communities inhabiting various habitats [ 70 , 71 , 72 , 73 ]. Their presence in metagenome reflects a balanced sulfur metabolic capability of microbial communities associated with the kodo rhizosphere. 3.6.4. Iron Acquisition and Metabolism Iron (Fe) is a crucial micronutrient for the living organisms for activating metabolic enzymes and pathways as prosthetic group constituent [ 74 ]. High-affinity Fe transport systems involving biosynthetic chelates, the siderophores help microorganisms and plants to tolerate Fe stress. Transport systems allow microorganisms to competitively obtain Fe as siderophores, to which plants utilize under varied soil conditions. We identified gene sequences related to iron acquisition and metabolism in the kodo rhizosphere metagenome through SEED subsystem alignment at different levels ( Figure 4 ). Sub-categorization of these sequences further revealed that most of them were associated with siderophore activity plus some other functions, e.g. ABC transporter, heme, hemin uptake and utilization systems (gram negative and gram positive both), hemin transport system, Iron(III) dicitrate transport system, iron acquisition in Vibrio , iron scavenging cluster in Thermus , iron metabolism in Campylobacter , and iron transport ( Figure 4 ). A large number of siderophore related sequences were involved in the siderophore assembly i.e. ABC-type Fe 3+ -siderophore transport system, Ferric hydroxamate ABC transporter (EC 3.A.1.14.3), Isochorismate synthase (EC 5.4.4.2) of siderophore biosynthesis, Siderophore biosynthesis protein, Siderophore synthetase component and TonB-dependent proteins. Different siderophores linked gene sequences that resembled pyoverdine (generally produced by the members of the family Pseudomonaceae, i.e., Azotobacter , Azomonas , Pseudomonas , and Rhizobacter ) [ 75 ] , achromobactin (siderophore produced by Pseudomonas syringe ) [ 76 ]; yersiniabactin (siderophore of the pathogenic bacteria Yersinia pestis , Yersinia pseudotuberculosis , and Yersinina enterocolitica ) [ 77 ]; bacillibactin (siderophore synthesized by the genus Bacillus ) [ 78 ]; enterobactin and pyochelin (siderophore synthesized by Pseudomonas aeruginosa ) [ 79 , 80 ] were traced in the dataset. We speculate that the dominant presence of microbial communities linked with the efficient iron acquisition functions is supposed to make them enable to enhance iron bioavailability in the rhizosphere of kodo plants. 3.7. Metabolism of Aromatic Compounds Microbial capabilities for utilization of aromatic compound through degradation of xenobiotic chemicals is essential for detoxification of natural habitats [ 81 , 82 ]. We identified sequence reads linked with different pathways involved in the anaerobic degradation of aromatic and xenobiotic compounds, metabolism of aromatic intermediates, and peripheral pathways for catabolism of aromatic molecules ( Figure 5 ). Identified gene sequences were linked with anaerobic toluene and ethylbenzene degradation; 4-hydroxyphenylacetic acid catabolic pathway; catechol and protocatechuate branch of beta-ketoadipate pathway; central meta-cleavage of aromatic compounds; homogentisate and N-heterocyclic degradation pathways; pathways for degradation of benzoate, gentisare, biphenyl, chloroaromatic, chlorobenzoate, naphthalene, and antracene; n-phenylalkanoic acid, phenylpropanoid compound, p-hydroxybenzoate, quinate, salicylate ester, and toluene ( Figure 5 ). Traces of anaerobic benzoate metabolism, a key intermediary in the microbial metabolism of aromatic compounds [ 37 , 83 ] were detected in the dataset. We identified genes catalyzing aromatic amine catabolism, a constituent of herbicide degradation and causal factor behind bladder cancer [ 84 ]. We also detected genes related to enzymes for catabolism of salicylate and gentisate, recognized intermediates in the naphthalene catabolism [ 85 , 86 ] in the rhizosphere microbiome. Carbazole is among the most abundant nitrogeneous compounds from petroleum [ 87 , 88 ]. Likewise, Phenylacetyl-CoA is the component of various substrates like phenylalanine, lignin-related phenylpropane units, phenylalkanoic acids and environmental contaminants such as styrene and ethylbenzene [ 89 ]. In the kodo metagenome, genes related to the enzymes associated with phenylacetyl-CoA catabolic pathway (core) were also identified. Collectively, the results confirm that the microbial communities in the rhizosphere of kodo plants with xenobiotic degradation capabilities hold immense promise for bioremediation of soils from the aromatic compounds. 3.8. Secondary Metabolism Secondary metabolism is one of the most diverse features of microbial communities [ 90 , 91 ]. A wide range of small molecule metabolites are synthesized by microorganisms as a representation of metabolic complexity [ 92 , 93 ]. Being essential tool for self-defense, they play major role in host–microbe, microbe–microbe, and microbe–environment interactions [ 94 ] and act as clinically-used antibiotics, antimicrobials, anticancer agents, immuno-suppressants, and other drugs [ 93 , 95 ]. Besides other microorganisms, Streptomycetales are functional Actinobacterial communities to produce diverse secondary metabolites, especially polyketide and peptide-type antibiotics [ 96 , 97 , 98 ]. Biological processes and pathways that were prominently identified belonged to the aromatic amino acids and derivatives (cinnamic acid degradation, pyrrolnitrin biosynthesis), bacterial cytostatics, differentiation factors, antibiotics (2-isocapryloyl-3R-hydroxymethyl-gamma-butyrolactone) and bacterial morphogens, clavulanic acid biosynthesis, nonribosomal peptide synthetases (NRPS) in Frankia sp. Ccl3, paerucumarin biosynthesis, phenazine biosynthesis, biologically active compounds in metazoan cell defense and differentiation (quinolinic acid and its derivatives, steroid sulfates), biosynthesis of phenylpropanoids (flavanone, phytoalexin, phytosterol, salicylic acid and tannin biosynthesis, phenylpropionate degradation), lipid-derived mediators (cannabinoid biosynthesis), alkaloids biosynthesis from l-lysine, phytohormones (auxin biosynthesis, auxin degradation), and octadecanoids ( Figure 5 ). This information is helpful in investigating the rhizobiome for specific microorganisms through improved culturable methods for obtaining efficient strains with potential secondary metabolic functions. Immense benefits from the belowground microbial dark matter (hidden communities, unexplored metabolites) can also be obtained in terms of novel genes and metabolic pathway machinery with diverse chemistry [ 99 , 100 ]. Genes related to enzymes involved in the auxin biosynthesis (aromatic-L-amino-acid decarboxylase (EC 4.1.1.28), indole-3-pyruvate decarboxylase (EC 4.1.1.74), nitrilase 1 (EC 3.5.5.1) and 2 (EC 3.5.5.1), phosphoribosylanthranilate isomerase (EC 5.3.1.24), tryptophan synthase alpha chain (EC 4.2.1.20), tryptophan synthase beta chain (EC 4.2.1.20)) were identified. Growth regulators like cytokinins and auxin (indole-3-acetic acid; IAA) are microbial products affecting the cell division and elongation in plants [ 101 , 102 ]. Such findings reflected that kodo rhizobiome is rich in the auxin producing and secreting microbial communities. Cinnamic acid is a known allelochemical phenolic that influences seed germination, plant root growth, and affects metabolic processes [ 103 ]. We identified genes related to enzymes (such as 2,3-dihydroxyphenylpropionate 1,2-dioxygenase, 2-keto-4-pentenoate hydratase, 3-(3-hydroxy-phenyl) propionate hydroxylase, 3-phenylpropionate dioxygenase ferredoxin-NAD(+) reductase component, Hca operon (3-phenylpropionic acid catabolism) transcriptional activator HcaR and Probable 3-phenylpropionic acid transporter) concerned with cinnamic acid biosynthesis. . It is reasonable to speculate that the rhizobiome of this crop has functionalities to downstream the influence of cinnamic acid, and thereby, promotes plant growth and development. 3.9. Stress Response Among the gene sequences identified for stress response, most were related to oxidative stress followed by osmotic and heat stress with an overrepresentation of glycine betaine, glucans, glutathione, and superoxide dismutase ( Figure 5 ). Possible reason for this might be the fact that the crop usually grows in harsh drought stress and nutrient depleted conditions [ 49 ] and so, their root associated microbiota are metabolically tuned to such conditions. Apart from the gene sequences related to the enzymes of oxidative, osmotic and heat stress, those involved in acid stress, cold shock, desiccation stress, detoxification, and periplasmic stress were also identified. For oxidative stress, enzymes of various pathways like CoA disulfide thiol-disulfide redox system, glutaredoxins, glutathione: biosynthesis and gamma-glutamyl cycle, glutathione (non-redox reactions and redox cycle both), glutathione analogs: mycothiol, glutathionylspermidine and trypanothione, NADPH:quinone oxidoreductase 2, oxidative stress (general), protection from reactive oxygen species, redox-dependent regulation of nucleus processes, regulation of oxidative stress response were detected ( Figure 5 ). We observed that diverse stress resistance, tolerance and/or avoidance mechanisms are engaged by the microbial communities in the kodo rhizosphere for their survival and performance in the environment. Glutathione plays a significant defensive role against oxidative stress [ 104 , 105 ] and provides protection against toxic xenobiotics including environmental pollutants [ 106 , 107 , 108 ]. We identified genes related to the enzymes of the pathways involved in betaine biosynthesis from glycine, choline, and betaine uptake (also traced multiple copies of betaine biosynthesis sequences), ectoine biosynthesis and regulation, osmoprotectant ABC transporter, osmoregulation, and synthesis of osmoregulated periplasmic glucans. Glycine betaine (GB) is a major organic osmolyte in organisms against different environmental stresses like drought, salinity, high temperature, UV radiation, and heavy metals [ 109 ]. Conclusively, the availability of genes related to stress response processes indicates how the inhabiting microbial communities adopt and respond in the rhizosphere microclimate at both the community and organism level and exhibit metabolic capabilities to support growth and development of kodo plants. 3.10. Virulence, Disease, and Defense Significant number of gene sequences linked with virulence, disease, and defense were also identified in the rhizosphere ( Figure 5 ). Such genes include Adhesion (related to Staphylococcus, Campylobacter , Enterobacteria , and Streptococcus ), Bacteriocins (bacitracin stress response, marinocine, and tolerance to colicin E2), invasion and intracellular resistance, resistance to antibiotics and toxic compounds (multidrug efflux systems and resistance to arsenic, cadmium, mercury, chromium, zinc, vancomycin, cobalt-zinc-cadmium), toxins and superantigens (diphtheria toxin, streptolysin biosynthesis, and transport). It has been observed that the bacterial communities in the rhizosphere defend themselves through bacteriocins or ribosomally synthesized antibacterial peptides [ 110 ]. Adherence is a crucial step of bacterial pathogenesis or infection and colonization with the host [ 111 ]. Bacterial adhesins are surface recognition molecules that allow bacteria to target specific surfaces like root tissues [ 110 , 111 ]. The presence of such genes in the rhizosphere pointed out specialized functions of strengthening rhizosphere colonization by inhabiting bacterial communities. Gene sequences related to resistance against metal contamination in the rhizosphere possibly play significant role in bioremediation [ 62 , 109 ]. Metagenomic analysis of different environments including drinking water [ 112 ], sediment [ 113 ], and soil [ 114 ] has led to identify diversity and abundance of antibiotic resistance genes [ 115 , 116 ]. Our analysis, in concurrence with the previous studies, also showed that the microbial communities from kodo rhizobiome have capabilities to bioremediate against metal contamination and defend plants against disease causing organisms. Studies suggest that plant associated microbial communities differ widely in the soils and particular plant eventually chooses specific core microbiome [ 117 , 118 , 119 ] which is supposed to provide key contribution to plant growth and health [ 120 , 121 , 122 , 123 ]. Metagenomic analysis of kodo rhizosphere also revealed high taxonomic diversity with actinobacterial dominance (42.22%) along with Proteobacteria (23.72%) and the Bacteroides (4%). The observations are supported by earlier study [ 124 ] that on the basis of amplicon metagenome sequencing reflected similar revelations. High throughput sequence analysis of 16S rRNA gene for the assessment of bacterial community composition in three different Andean tuber crops Oca ( Oxalis tuberosa ), Ullucu ( Ullucus tuberosus ), and Mashua ( Tropaeolum tuberosum ) identified Bacteroidetes and Proteobacteria phyla as the most abundant communities [ 125 ]. Extensive overlap between core rhizosphere microbiome in different plant species, e.g., citrus [ 119 ], Arabidopsis [ 126 , 127 ], millet [ 120 ], sugarcane [ 117 ], and cooloola [ 128 ] has been observed to suggest that various factors driving community assembly may become common among plant species. Similarly, analysis of more than 20 wheat rhizosphere metatranscriptomes have led to identify metabolic pathways related to the degradation of aromatic and xenobiotics compounds [ 129 ]. Gene sequences linked with these pathways have also been dominantly observed in the kodo rhizosphere. All together these studies reveal that microbial communities with diverse taxonomic structure and metabolic functions inhabit the crop rhizosphere to contribute in interactive way to support plants in their surrounding environment. Cumulative microbial multifunctionalities in the kodo rhizosphere as is observed in the present study or evidenced from parallel studies on the microbial community structure and function of other crops, ultimately leads to a productive and healthy microenvironment around the plant roots that eventually influences crop survival and productivity."
} | 10,534 |
23780923 | null | s2 | 8,985 | {
"abstract": "Particle get-together: Surface functionalization with a branched copolymer surfactant is used to create responsive inorganic particles that can self-assemble in complex structures. The assembly process is triggered by a pH switch that reversibly activates multiple hydrogen bonds between ceramic particles (see picture; yellow) and soft templates (n-decane; green)."
} | 91 |
36554245 | PMC9777906 | pmc | 8,987 | {
"abstract": "Social insects such as honey bees exhibit complex behavioral patterns, and their distributed behavioral coordination enables decision-making at the colony level. It has, therefore, been proposed that a high-level description of their collective behavior might share commonalities with the dynamics of neural processes in brains. Here, we investigated this proposal by focusing on the possibility that brains are poised at the edge of a critical phase transition and that such a state is enabling increased computational power and adaptability. We applied mathematical tools developed in computational neuroscience to a dataset of bee movement trajectories that were recorded within the hive during the course of many days. We found that certain characteristics of the activity of the bee hive system are consistent with the Ising model when it operates at a critical temperature, and that the system’s behavioral dynamics share features with the human brain in the resting state.",
"conclusion": "5. Conclusions and Future Work Our findings indicate that the honey bee colony inside the hive is a critical system. However, further work is required to ascertain the generalized conjecture that colonies of eusocial insects are critical in support of collective cognition. It is crucial to analyze other datasets to confirm that hallmarks of the kind we observed are ubiquitous across bee species and to analyze other eusocial insects, such as ants and termites. Other computational models of the critical state, such as the Ising model on a complete graph or the XY model with continuous spin dynamics [ 17 ] could also be compared with empirical data. Moreover, criticality manifests itself on different levels. We focused on temporal and spatial correlations; however, other aspects, for example the behavior of the system during coarse-graining, should also be considered. Another interesting direction for future research is to explore how the critical state is related to the hives’ normal daytime activity, such as foraging and swarming, as well as how it is modulated by environmental factors, for example by the day–night cycle. If our hypothesis is on the right track, we should find that increased evidence of criticality in the hives’ resting state is associated with improved collective decision making, such as more efficient foraging behavior. Comparing high-level descriptions of different systems could shed light on general dynamical patterns of cognitive systems that are imperceptible when the focus is too narrow. Analysis of system-level properties such as criticality is a particularly promising approach in this regard. However, much ink has been spilled by some of the best scientific minds in debating the validity of the critical brain hypothesis and the debate is still not settled [ 53 ]. Evidence from other fields, such as provided here, could tip the scales in this debate toward a more widespread acceptance.",
"introduction": "1. Introduction Social insects are capable of creating and supporting sophisticated modes of spatial organization; furthermore, they possess the ability for decision-making at the colony level. What is the basis of this collective cognitive capacity? Several lines of research seek to elucidate what traits are shared by entities capable of such adaptive behavior, regardless of whether their mode of operation is individual or collective [ 1 ]. For the case of individual animals, a prominent conjecture conceived through the cross-pollination of statistical physics and experimental neuroscience is known as the “Critical brain hypothesis”. It holds that the remarkable adaptive abilities of neural systems require them to be poised in the vicinity of the critical state, because in this way, the system has access to the widest repertoire of dynamic patterns. This claim is supported by a notable amount of experimental data, recorded both in vitro and in vivo. At the same time, there is evidence that some collective entities such as swarms of midges and flocks of birds exhibit hallmarks of the critical state at the collective level [ 2 , 3 , 4 ]. However, a comprehensive assessment of criticality was not carried out for any of the major types of eusocial insects, such as ants, bees, and termites. Recent advances in scientific image acquisition and analysis techniques now allow for recording trajectories of individual insects [ 5 ]. In our work we analyzed a dataset of honey bee trajectories, focusing on the hallmarks of the critical state. 1.1. Smarts in Numbers—Collective Intelligence Eusocial insects’ abilities in foraging [ 6 ], enacting complex spatial arrangements of their bodies [ 7 , 8 ] and creating elaborate nesting structures are well known. Furthermore, they can handle making decisions on a more abstract level. For example, a honey bee colony produces a daughter colony when the original site becomes overcrowded [ 9 ]. The choice of nest site depends on a number of parameters and an erroneous decision could lead to the inevitable demise of the colony. Thus, when swarming, bees aggregate themselves into a cluster, usually in a form of penchant hanging from a tree brunch. Then, the collective considers information brought by scout bees about the relative quality of the nearby locations. The swarm evaluates the merits of the proposed locations and makes the choice which is then followed through unanimously, in the overwhelming majority of cases. Everyday functioning of the colony also requires the handling of information to optimize foraging and allocate tasks for individual bees. Ants display similarly complex behavior on the colony level. They are using cooperation to extend their sensing range [ 10 ] and engage in complex physical tasks, such as transporting heavy objects or building elaborate structures. Furthermore different colonies demonstrate distinct differences in behavioral patterns across several behavioral traits, thus having a degree of “collective personality”, which affects their evolutionary fitness [ 11 ]. At an abstract level of description, the mechanisms of collective decision-making share common features with the mechanisms of cognition within the brain [ 1 ]. Famous entomologist Thomas D. Seeley [ 9 ] noted in his book remarkable similarities between the way in which a honeybee swarm performs the task of making a decision for a new nest site and the activity of a primate brain during a perceptual discrimination task. In both cases, the correct decision is acquired through the non-linear aggregation of activity of individual constituents of the system. Other studies showed [ 12 ] that bee colonies adhere to the same psychophysical laws that humans do when making decisions while facing varied and conflicting sources of information. A fundamental organizing principle shared by the brain and eusocial insects is that all forms of behavior and cognitive ability arise from the local interactions between the system’s elements, be it insects or neurons, and does not need to be explicitly organized with a blueprint or central pacemaker of some sort. 1.2. Critical Brain Theory In the neuroscience field, it has been conjectured that healthy brains are poised in the vicinity of second-order phase transition [ 13 , 14 , 15 , 16 ]. Unlike the more familiar case of first-order transition, exemplified by the freezing of water, the second-order transition does not have a sharp boundary separating the two phases. In the vicinity of the critical point, both states of matter could coexist and the system displays a set of remarkable characteristics: most notably, long-range correlations link distant locations, and events of all scales could occur in the system [ 17 ]. Recordings of Local Field potentials (LFPs) from cortical slices [ 18 ], as well as an analysis of neural data of different modalities, including EEG, MEG, and fMRI [ 19 , 20 ], showed that both the isolated neural tissue and the intact functioning brains exhibit statistical properties characteristic of the system in the critical state. Most importantly, the size of fluctuations in the system scales abides by the power-law scaling, making events of all sizes possible, long-range correlations exist in both temporal and spatial domains, and activity patterns exhibit complexity and variability, significantly exceeding what would be expected by random chance. Furthermore, research in the field showed that such a state might be not epiphenomenal (i.e., consequent of but not causal to), but necessary to maintain the brain’s functionality [ 15 ]. This view, which became known as the “critical brain theory”, conjectures that the critical state of the system underlies its key functionality, including its ability to produce a wide range of emergent configurations of activity. Emergent behavior is paramount for an adaptive system, as it underlies its ability to produce a multitude of responses without altering the underlying structure. It has been established that in the vicinity of the critical point, the system has the widest repertoire of dynamic patterns emerging from local interactions only [ 21 ]. A body of evidence, accumulated through computational models and experiments with cortical slices, shows that critical state neural networks are best suited for complex computation. Information transmission, integration [ 22 ], and representation [ 23 ] are optimal, and dynamic range is maximized [ 24 ], allowing for the networks to respond to a wide range of stimuli. These findings are corroborated by medical research showing that deviations from criticality are correlated with suboptimal mental states in humans [ 25 ]. 1.3. Evidence for Criticality in Collective Behavior Evidence of criticality and its implications discussed above in Section 1.3 applies mostly to mammalian brains. As we argue in Section 1.1 , insect communities, despite having little structural resemblance to the brain, share the same burden of navigating the world and making choices crucial to survival. The universality of physical laws implies that different systems could be described with the same set of basic laws. At the same time, principles of convergent evolution make it possible that similar phenomena could come to be in unrelated species if they are advantageous to survival. Given the benefits that the critical state confers to the adaptive ability of the systems, it is fitting to conjecture that swarms and colonies of collective insects would evolve to be positioned in its vicinity [ 4 , 26 ]. Investigations of brains’ critical phenomena focus on analyzing patterns of electric signals (EEG, LFP, MEG) or alternatively using proxy metrics for brain activity (fMRI). Animal collectives use many modes of interaction to exchange information and synchronize actions within the group, including vocal cues, movements, and phenomenal signals. Previous research we reviewed assumes, unanimously, that the spatial and temporal scale at which critical phenomena would presumably be exhibited by such systems makes the movement patterns, correlations, and derivatives thereof the best venue for analysis. Recent research showed that critical phenomena are observable in flocking birds [ 2 ] and swarming of midges [ 3 , 27 ]. Long-range velocity correlations underlie the astonishing ability of these creatures to maneuver collectively with the synchronicity of one. Cursory evidence exists to suggest that ants make use of enhanced coordination between individuals conferred by criticality to maximize the load-carrying capacity of a group [ 28 ] and optimize forage route allocation [ 29 ].",
"discussion": "4. Discussion 4.1. Key Finding and Their Implications In our work, we analyzed a dataset of bee trajectories in a way that allowed us to compare empirical data to a well-studied model. Such an approach has been previously used (e.g., [ 19 ]) to show that key dynamical characteristics of the human brain at its resting state exhibit a notable resemblance to the Ising model when the latter is in the vicinity of the critical state. Long-range temporal autocorrelations are also considered a hallmark of criticality in the Ising model and the neural time-series [ 43 ]. With some minor differences, which are to be expected given the different nature of the data, our analysis of bee correlation networks yielded remarkably similar results, namely similarity to the Ising model at T = T c r i t and lack thereof at low and high temperatures. First, our observations are confirmed by the rigorous statistical analysis of the degree distributions. Second, the analysis of the correlation networks showed that certain characteristics, most notably clustering and path length, are comparable between the network of bee correlations and critical state of the model, but are drastically different otherwise. Third, analysis of the mean parameters K m e a n and M showed that recordings of the average activity of both the bee hive and the Ising model at critical states are marked with considerable autocorrelations within the time-series. These similarities in the dynamics of the systems become even more noteworthy when we consider that in structural terms, both the Ising model and the human brain are drastically different from the bee hive. In the context of our analyses, differences in spatial structure are particularly important. The two-dimensional Ising model possesses only nearest-neighbor interactions, while the human brain is characterized by intricate connection patterns on the macro and micro levels. Although correlation networks are obtained solely from dynamics, one would expect them to be strongly influenced by the underlying spatial structure. The bee hive is quite different because the nodes of its correlation matrix represent agents largely unhindered by constraints in movement and interaction. Despite these dissimilarities, functional constraints on behavior are shared by the systems in question to a degree that precludes the appearance of dynamical similarities by mere chance. We believe that they signal a shared systemic property—the critical state, whose influence on the systems’ dynamics goes beyond specific structural constraints. One potential concern with our comparative analysis is the choice of running the Ising model on a 2D grid, thereby imposing a local interaction constraint on the system. Alternatively, we could have implemented the model on a complete graph, in which all lattice sites are connected. Intuitively, that might seem a better approximation of the bee hive, with highly mobile agents. Empirical research and modeling studies of flocks and schools have demonstrated that in such systems, an ubiquitous strategy of the individual agents is to align their behavior with that of the nearby neighbors [ 44 , 45 , 46 ]. Information, however, could propagate through the whole system seemingly unencumbered by the prevalence of local connections. Such behavior is a clear mark of critical state. We do not have definitive information that bees follow such an alignment pattern inside the hive, yet the remarkable ability of the 2D Ising model with only local interaction to emulate a high-level description of bee hive dynamics, implies that a similar mechanism could be in play. 4.2. Critical Brains and Critical Swarms Our results provide evidence in support of what we could call a “critical colony” hypothesis. As we had summarized earlier in Section 1.2 , being in a critical state provides benefits to a system’s cognitive ability, to an extent that it can be argued that such a state is not simply advantageous, but even necessary. At the same time, there are convincing arguments in Section 1.1 for the claim that social insects are endowed with a sort of collective cognitive capacity, which, despite their entirely different mode of organization, shares key similarities with the capacities of vertebrate brains. Thus, we suggest that the benefits that the critical state brings would be desirable characteristic for both of these systems. Previous research showed that hallmarks of the critical state are observable in swarming midges [ 3 ] and flocking birds [ 2 ]. Moreover, previous research on the same bee dataset found that the time-series of the K m e a n of the bee hive exhibits bursts of activity, significantly exceeding the average level, which is interspersed with quiescent periods [ 30 ]. The distribution of waiting times between these bursts abides by the power-law distribution. The authors did not discuss criticality as such, but it is noteworthy that this kind of distribution is also found to be the case for “avalanches” in the Back–Wisenfield sandpile model, a famous model of self-organized criticality [ 47 ], and for the patterns of the neural activity recorded in the cortical slices of mice [ 18 ] in vitro. One of the benefits of the critical state in neural networks is that it enables an easier spread and integration of information. Our findings show that the correlation graphs of bee activity exhibit distinct small-world structures and contain hubs—nodes with exceptionally high degrees. A similar organization emerges in the Ising model when T = T c r i t . Such network properties are also known to enhance the integration of information and facilitate the spreading of signals. In the human brain, there is a similar structural organization of cortical wiring [ 48 , 49 ]. The bee hive and the critical Ising model lack such structural constraints, yet their functional connectivity is remarkably similar. Uncovering such network structures in the functional correlations of the bees suggests that this type of organization is not only ubiquitous in the brain but is fundamental to the functionality of any cognitive system. It is worth highlighting important differences between our work and the corpus of research that concerns hallmarks of criticality in the swarm dynamics, as well as with the studies employing tools of network science to study eusocial insects [ 5 , 50 ]. The most notable dissimilarity with the latter is that most studies focused on social networks, constructed by observing species-specific means of communication, such as trophallaxis in bees and attenuation in ants. Such contacts, important as they are, only constitute a fraction of individuals’ total activity, and they arguably account only for a portion of the total informational exchange that takes place inside the colony. Significant correlations between the kinetic energy time-series of individuals and highly specific degree distributions of the correlation graph, in our view, reflect features of the social system underlying collective cognition in the hive, aided by its critical state. Hallmarks of critical behavior in collective entities, when studied empirically, were investigated in freely-moving agents: flocking birds or swarming midges. Thus, it is possible to argue that observed features, such as long-range velocity correlations, were begotten by the spatial order the organisms maintained and are transient in nature. The movement data we analyzed were acquired when bees were locked inside the hive and provided with sustenance. They were under no pressure to maintain a specific movement order, as they would have been during swarming, or to move at all, in fact. Given these conditions, it is plausible that the hallmarks of the critical state revealed by our analysis would be observed only if such a state is inherent to the system, much like it is to the human brain at its resting state. Indeed, brain resting-state networks have been proposed to reflect a process of “constant inner state of exploration” that optimizes the system for a given impending input, thus influencing perception and cognitive processing [ 51 , 52 ]. It is exciting to consider the possibility that the colonies of eusocial insects exhibit a similar process."
} | 4,960 |
32885979 | null | s2 | 8,988 | {
"abstract": "Using electrical signals to guide materials' deposition has a long-standing history in metal coating, microchip fabrication, and the integration of organics with devices. In electrodeposition, however, the conductive materials can be deposited only onto the electrode surfaces. Here, an innovative process is presented to electrofabricate freestanding biopolymer membranes at the interface of electrolytes without any supporting electrodes at the fabrication site. Chitosan, a derivative from the naturally abundant biopolymer chitin, has been broadly explored in electrodeposition for integrating biological entities onto microfabricated devices. It is widely believed that the pH gradients generated at the cathode deprotonate the positively charged chitosan chains into a film on the cathode surface. The interfacial electrofabrication with pH indicators, however, demonstrated that the membrane growth was driven by the instantaneous flow of hydroxyl ions from the ambient alginate solution, rather than the slow propagation of pH gradients from the cathode surface. This interfacial electrofabrication produces freestanding membrane structures and can be expanded to other materials, which presents a new direction in using electrical signals for manufacturing."
} | 316 |
34399033 | PMC8597079 | pmc | 8,990 | {
"abstract": "Abstract Lignin is an abundant natural feedstock that offers great potential as a renewable substitute for fossil‐based resources. Its polyaromatic structure and unique properties have attracted significant research efforts. The advantages of an enzymatic over chemical or thermal approach to construct or deconstruct lignins are that it operates in mild conditions, requires less energy, and usually uses non‐toxic chemicals. Laccase is a widely investigated oxidative enzyme that can catalyze the polymerization and depolymerization of lignin. Its dual nature causes a challenge in controlling the overall direction of lignin‐laccase catalysis. In this Review, the factors that affect laccase‐catalyzed lignin polymerization were summarized, evaluated, and compared to identify key features that favor lignin polymerization. In addition, a critical assessment of the conditions that enable production of novel lignin hybrids via laccase‐catalyzed grafting was presented. To assess the industrial relevance of laccase‐assisted lignin valorization, patented applications were surveyed and industrial challenges and opportunities were analyzed. Finally, our perspective in realizing the full potential of laccase in building lignin‐based materials for advanced applications was deduced from analysis of the limitations governing laccase‐assisted lignin polymerization and grafting.",
"introduction": "1 Introduction The production of fossil‐based materials has long been associated with processes that negatively affect the environment, especially accelerating climate change through carbon dioxide emissions. In addition to their environmental impact, the depletion of non‐renewable fossil resources prompted a global call for greener and sustainable substitutes. This gave rise to the increasing research interest in valorizing bio‐based materials as alternatives for fossil resources in the past decades. Among these bio‐based materials, lignin attracts significant attention because of its abundance in plant biomass, polyaromatic structure, and unique properties. Lignin is an enormous bio‐based feedstock. As one of the major constituents of the plant cell walls, lignin is the second most abundant biopolymer on earth, next to cellulose and hemicelluloses. It is a renewable material biosynthesized in plants with an estimated annual production of 5–36×10 8 tons globally. \n [1] \n Industrially, lignin is generated as a side‐stream product traditionally from pulp and paper industries, and recently also from cellulosic bioethanol production. At present, pulp and paper industries worldwide generate about 60 million tons of lignin each year. \n [2] \n By 2030, an additional 225 million tons of lignin annually is estimated to come from processing 750 million tons of biomass for cellulosic bioethanol production in the US alone. \n [3] \n \n Lignin is a complex, highly heterogeneous aromatic biopolymer. It has a three‐dimensional, amorphous structure, constructed from the oxidative coupling of plant phenolic monomers (monolignols). Because of the randomness of linkage generation among monomers, the resulting lignin macromolecules are highly variable and exhibit different physicochemical features. \n [4] \n Lignin has various functional groups such as methoxy, phenolic hydroxy, alcoholic hydroxy, and carbonyl groups, which are in various proportions and have a profound impact on its properties. \n [5] \n \n The complex and variable structure of lignin determine its various unique functions and characteristics. In plants, lignin provides structural support, water‐conductive properties, and defense against pathogens. \n [6] \n In soil, lignin is a precursor for the formation of humus, which is the recalcitrant organic matter that affects soil fertility. \n [7] \n Biodegradation of lignin by microbes such as fungi and bacteria generates modified organic compounds that accumulate in soil organic matter and aid in the formation of humus and humic substances. \n [8] \n Thus, lignin acts as a carbon storage pool both in the biosphere (in plants) as well as in the soil (as organic matter). In line with these unique functions of lignin in nature, industrial lignins isolated from biomass through various pulping methods also exhibit exceptional properties. Lignin is known to exhibit UV‐shielding, antimicrobial, antioxidant, hydrophobic, amphiphilic, emulsifying, and excellent binding properties. \n [9] \n \n Despite the promising potential lignin could play in a bio‐based economy, its utilization is still limited to low‐value applications. Lignin is highly available, but a large proportion of it remains untapped and is only burned for energy recovery at the pulping facility in plant biomass. \n [10] \n Lignin is the largest reservoir of renewable aromatic biopolymers, but its conversion to high‐value aromatic chemicals is still far from industrial scale. One of the biggest drawbacks toward unlocking the full potential of lignin is its heterogeneity in structure, composition, and properties, which all vary depending on the source and mode of isolation. Exhaustive efforts to valorize lignin led to various approaches that take advantage of lignin's unique features while overcoming its heterogeneity. Traditionally, effort has been put on depolymerization of lignin, that is, degradation and fragmentation of natural or technical lignins to smaller‐molecular‐weight soluble compounds and subunits. \n [11] \n This has been the aim in delignification processes in wood pulping and papermaking. Another route of lignin valorization is by utilizing the exceptional characteristics of lignin as a polymeric material itself or coupled with other molecules. In this approach, lignin is either further polymerized or grafted with other molecules to produce lignin‐based materials with properties tailored for specific applications. \n [12] \n Various methods based on chemical, \n [13] \n thermal, \n [14] \n and enzymatic techniques \n [15] \n were explored with the aim of constructing novel lignin‐based polymeric materials. Among these methods, enzymatic lignin valorization received great attention because it has environmentally more acceptable processing conditions. Enzyme‐catalyzed processes operate under mild conditions, require less energy input, and are performed most often in the absence of toxic solvents. \n [16] \n Enzymatic valorization of lignin adapts the concept of how enzymes in nature catalyze the biosynthesis and biodegradation of lignin. Plant, fungal, and microbial enzymes involved in these natural processes were harnessed and investigated for their capabilities to catalyze lignin polymerization or degradation under controlled laboratory conditions, with the aim of finding novel applications for lignin. \n [17] \n \n Laccase is one of the oxidative enzymes that offers vast possibilities for lignin valorization via polymerization or grafting reactions. Laccases are phenol‐oxidizing metalloenzymes widely distributed in nature. \n [18] \n They act on diverse substrates, which can be further expanded by using laccase‐mediator systems, require only oxygen as co‐substrate, and release water as the first product.[ \n 5 \n , \n 16a \n , \n 16b \n ] These characteristics and their ability to act on phenolic and polymeric aromatic compounds make laccases enzymes of high interest for lignin valorization. As biocatalysts, laccases can either polymerize or depolymerize lignin and phenols, depending on the substrate, mediator, and radical reaction conditions.[ \n 16b \n , \n 19 \n ] In this Review, we present a comprehensive summary of the applications of laccases in building lignin‐based materials via polymerization or grafting with other molecules. First, we present a general overview of lignin structure and the properties and sources of different types of lignins. Next, a brief summary about laccases and their mode of action towards lignin‐based materials is introduced. We then evaluate and analyze various studies that utilized laccase for lignin polymerization in order to identify key features that enable successful construction of lignin‐based materials via laccase‐assisted polymerization. Numerous reports have proven the potential of laccase‐mediated polymerization of various types of lignin, but this is the first time that an overall evaluation of the factors that direct the reaction towards polymerization is formulated in a Review. Advanced insights into these factors help future researchers in identifying crucial elements that must be considered when building lignin‐based materials via laccase catalysis. Apart from polymerization, we highlighted the application of laccase in constructing lignin‐based materials via grafting of other molecules to lignin. Previous Reviews on this aspect have been more general, covering various types of enzymes \n [15a] \n or different types of substrates, including small molecules and polymers other than lignin.[ \n 15c \n , \n 16a \n , \n 16b \n ] Here, we focused only on the building of new materials with lignin as a starting material and laccase as the enzyme. Our aim is to highlight the potential of laccases in building novel materials from lignin via polymerization or grafting. In order to assess the potential of laccases in lignin valorization in an industrial setting, we looked for patented processes that utilized laccase in producing new lignin‐based materials. Finally, we present our perspectives on how to further expand the application of laccases for lignin valorization and how to overcome a few obstacles in the development of applicable processes."
} | 2,387 |
39868335 | PMC11760724 | pmc | 8,991 | {
"abstract": "Metatranscriptome (MetaT) sequencing is a critical tool for profiling the dynamic metabolic functions of microbiomes. In addition to taxonomic information, MetaT also provides real-time gene expression data of both host and microbial populations, thus permitting authentic quantification of the functional (enzymatic) output of the microbiome and its host. The main challenge to effective and accurate MetaT analysis is the removal of highly abundant rRNA transcripts from these complex mixtures of microbes, which can number in the thousands of individual species. Regardless of methodology for rRNA depletion, the design of rRNA removal probes based solely upon taxonomic content of the microbiome typically requires very large numbers of individual probes, making this approach complex to commercially manufacture, costly, and frequently technically infeasible. In previous work [ 1 ], we designed a set of depletion probes for human stool samples using a design strategy based solely on sequence abundance, completely agnostic of the microbiomal species present. Here, we show that the human-based probes are less effective when used with mouse cecal samples. However, adapting additional rRNA depletion probes specifically to cecal content provides both greater efficiency and consistency for MetaT analysis of mouse samples. Importance Sequencing total RNA from microbiome samples is seriously impaired by the overwhelming proportion of rRNA to mRNA content. As much as 99% of sequencing reads can be assigned to the rRNA content, thus removal of these abundant transcripts is critical to MetaT analysis. The use of Ribo Zero Plus rRNA depletion probes designed for human gut microbiomes proved to be less effective and more inconsistent across mouse cecal donor samples, a common experimental system for microbiome studies. In the present work, we have extended and refined a taxonomically-neutral probe design method for mouse cecal content. The additional probes were carefully chosen to limit the number needed for effective depletion to reduce both the cost and risk of introducing bias to MetaT analysis. Our results demonstrate this method as efficient and consistent for rRNA removal in mouse cecal samples, thus providing a significant increase in the number of mRNA-rich sequencing reads for MetaT analysis.",
"introduction": "Introduction The diversity and metabolic state of the estimated ~ 1000 species contributing to the intestinal microbiota is immensely important to the health and well-being of the host [ 2 ]. Diet, overall health, and even disease state of the host can, conversely, affect the activity and enzymatic expression patterns of the intestinal microbiome. Our understanding of the microbiome has evolved over the past decades such that it is now understood that the interplay between the microbial population and its host is a dynamic and vital interaction [ 3 ]. To further understand this interaction, it is crucial that we look at not just the composition of the microbes present, but also the metabolic contribution from this population to assess the health and well-being of the host. In the last decades, the use of Next Generation Sequencing (NGS) to interrogate microbiomes, especially from the gut contents of host organisms, has become more cost-effective and technologically attainable [ 4 , 5 ]. Genetic profiling of the microbial populations present in gut microbiomes is traditionally performed by methods such as 16S rDNA sequencing [ 6 - 8 ]. More recently, as NGS has become far less expensive, whole genome bacterial shotgun sequencing has become more commonplace and provides a greater depth of knowledge of the bacterial diversity and inferred function(s) in these complex communities [ 9 - 11 ]. However, metagenome (MetaG) sequencing is mostly limited to taxonomic identification of genus and/or species composition of the samples. The functional metabolic state of the microbes can, at best, be deduced based on assumptions of the relative contributions from the taxonomic groups present. Elucidating the profile of mRNAs being expressed by these populations (their transcriptomes) is more informative. Using transcriptome profiling of microbiomes (i.e. metatranscriptomics) can provide a wealth of valuable information about not just the taxonomic composition, but also the metabolic activity of the microbial population [ 12 ]. The dynamics of gene expression changes between microbiome and host can be simultaneously monitored to establish the health or disease states [ 13 ]. Metatranscriptome (MetaT) sequencing offers a much more detailed view of the overall activity of the microbes by providing real time functional gene expression information, such as what gene families and enzymatic activities are taking place at the time of sample collection and extraction [ 14 , 15 ]. Furthermore, it can be quite informative to track these dynamic changes over time, especially in response to dietary interventions, drug treatments, and disease progression of the host [ 2 , 16 ]. Whereas tracking changes to the taxonomic composition of the gut by MetaG sequencing may be relatively stable upon intervention, MetaT offers the potential for a more detailed and dynamic profiling of the most transcriptionally active participants in the sample [ 17 ]. A major challenge for MetaT analysis is the presence of highly abundant rRNA transcripts. Bacterial small subunit (SSU or 16S) and large subunit (LSU or 23S) rRNA transcripts dominate total RNA samples extracted from gut microbiomes. Indeed, sequencing total RNA from stool samples without rRNA removal can typically result in >95% of the reads matching LSU and SSU rRNA transcripts. Methods to remove the vast diversity of microbiome rRNA can be contrasted with the relatively easy methods available for removing host eukaryotic rRNA from samples. Since polyA tails are added post-transcriptionally to coding mRNAs as part of eukaryotic RNA processing, the mRNAs themselves can be preferentially enriched using oligo-dT capture beads. Additionally, removal of the host rRNA is more feasible since it only requires using sequences from a single species. Several commercially available rRNA removal kits and methods can be utilized to remove rRNA from commonly studied species, such as human, mouse, and rat and provides the means to sequence both mRNA and non-coding transcripts in these sample types. Routinely used methods for removing rRNA from total RNA include enzymatic (i.e. RNase H) depletion, CRISPR-based approaches, or physical removal using hybridization with antisense biotinylated probes and streptavidin magnetic beads [ 18 - 21 ]. However, these methods designed for samples from a single eukaryotic host are not effective for complex microbiome sample types since the microbial rRNA is from a multitude of source organisms whose sequences are evolutionarily divergent [ 1 ]. Removal of these abundant transcripts through targeted probe design, whether using physical or enzymatic means, is a much more complex procedure to permit the deep sequencing of microbial mRNA. In a recent study, a ‘rational’ probe design strategy was established where raw sequencing data was utilized to collect and filter abundant sequences from human gut microbiome samples [ 1 ]. The probe set that was designed demonstrated effective and efficient enzymatic depletion of rRNA from both human adult and infant stool samples with minimal bias introduced. Robust depletion of rRNA within multiple human microbiome sample types, including stool, tongue, and vagina resulted in >60% of sequencing reads available for MetaT analysis. This method is commercially available as the Ribo-Zero Plus Microbiome (RZPM) kit. In this work, we sought to first test the ability of RZPM to deplete rRNA from a set of mouse microbiome samples and, if needed, make use of a similar rational probe design strategy to create supplemental probe pools optimized for mouse gut (specifically, cecal) contents. Since there is currently no commercially available solution for rRNA depletion of mouse microbiome sample types, an important goal is to provide a list of additional probes that can be obtained at minimal cost and combined with RZPM for more effective performance. Additionally, this effort is intended to provide improvements in both consistency and efficiency of depletion for mouse-specific MetaT analysis. We demonstrate that addition of the supplemental probes can provide ~ 75% of the mRNA-rich reads available for MetaT analysis. These extra probes add a minimal cost per sample to the existing RZPM kit yet provide an additional ~ 15% of sequencing reads for functional data analysis.",
"discussion": "Discussion In this work, we describe a novel strategy to adapt and optimize a probe pool initially created for the enzymatic depletion of abundant rRNA sequences in human gut microbiome samples to enable effective and consistent use in mouse cecal samples. Efficient depletion of rRNA sequences in these sample types greatly increases the informational content for use in MetaT analysis. The main goal in these types of studies is to determine the gene expression profile and functional/metabolic characteristics of the microorganisms residing in the host. Knowledge about host-microbe interplay relies on understanding both microbiome contribution as well as the host response and how it can vary with specific gene expression contributions from the microbial community. At our current level of understanding, it is not clear to what extent host response is dependent on specific microorganisms being present. Thus, being able to compare the microbiome population composition to the metatranscriptomic profile during controlled stimulation experiments is critical. The approach to probe design used in this work is agnostic towards the taxonomic content of the samples and instead relies on collecting abundant microbial rRNA sequences from several mouse cecal donors, setting coverage thresholds, and varying probe spacing options to efficiently create additional probes optimized for mouse cecal microbial rRNA content. We initially tested 56 individual cecal donors using the RZPM probe sets (DP1 & DPM) designed against human stool and determined that for many donors, the rRNA depletion resulted in <30% of the sequencing reads matching microbial rRNA. However, several donors demonstrated higher rRNA content; in some cases, up to ~ 50% of reads. We chose 7 donors with rRNA content >30% for use as a training set for additional probe design. Abundant rRNA sequences were collected from these individual samples and merged to create abundant rRNA ‘regions’ and then ranked by median coverage depth from highest to lowest. To investigate probe design efficiency, we combined two options. First, we filtered sequences based upon specific coverage thresholds and second, designed anti-sense probes with various spacing across the rRNA regions selected by coverage. This matrix of options produced probe design pools with various numbers of individual oligos that trend as generally expected; designs against higher numbers of abundant regions and spaced closer together generate more probes than using fewer regions and spacing the probes further apart. We then chose two design pools that represent compromises between these two extremes (the green and blue cells in Table 1 ) and tested their performance on both the same cecal samples used for training as well as samples that were not. Both design options demonstrate improved rRNA depletion performance, but the more ‘packed’ version (using the top 20 most abundant regions and probes spaced 25 nt apart; named the 2025 probe set) results in a statistically significant increase in the percentage on non-rRNA reads generated for MetaT analysis. In addition, the ranges of rRNA content from different donors is generally more compact and consistent when compared to the use of the human gut-centric probes by themselves. The microbiome is present virtually throughout the human body [ 25 ]. However, most areas of the human biome in healthy individuals contain only trace amounts of microbes, with the bulk present within the digestive and respiratory tracts, which provide an enriched conditions for their growth due to contact with the external environment [ 26 ]. This knowledge has resulted in a great deal of investigation into gut microbiomes and the role they play in the health of their hosts, as well as the effect of the host’s diet and health on microbial composition and gene expression. Several studies have suggested an interplay between the microbiome metabolic activity and the response of the host to various interventions. The diet of the host is perhaps an obvious example where consumption of certain nutrients clearly results in changes to the gut flora and activity [ 3 , 27 ]. Therefore, it is important to consider the ability to monitor both host and microbe response to aspects such as dietary stress, disease states, or even medicinal treatment. With this in mind, we performed rRNA depletion and RNA-Seq analysis of three distinct mouse microbiome types: cecal, terminal ileum, and liver. The proportional amount of microbial vs host transcriptome varies considerably between these sample types. The liver and terminal ileum samples contain predominantly host RNA, while the cecal content is mostly microbial. The existing RZPM kit is designed to remove the common rRNA transcripts from human, mouse, and rat samples via the use of the DP1 probe pool. Furthermore, previous work established the use of DPM for microbial rRNA removal from human stool, vaginal, and oral microbiomes. This provides an integrated tool to allow the simultaneous gene expression profiling of both host and human microbiome. A major goal of this current work is to provide tools that will maximize the amount of useful MetaT information available through the use of an optimized set of supplemental probe pools for mouse cecal content. In addition to providing a manageable set of depletion probes, we demonstrate that the use of these supplemental probes does not introduce unwanted bias to either the host- or the meta-transcriptome, in terms of microbial species or metabolic pathway gene expression. Our results suggest that the combination of the 2025 probe set with the RZPM probes (DP1 and DPM) provides an effective tool to enable MetaT analysis of mouse cecal microbiomes. The ability to remove abundant unwanted sequences from total RNA is critical for any whole transcriptome RNA-Seq analysis [ 12 ]. Sequencing total RNA without rRNA removal generally results in the vast majority of sequencing reads aligning to rRNA. Microbiome samples are especially susceptible; typically >95% of all reads are identified as microbial rRNA ( Figure 1 ). In some studies, this rRNA content has been used to track the taxonomic profile of microbiomes and rank species abundance based upon the proportion of reads assigned to each species. Much like metagenome analysis, the proportion of each species can then be used as a proxy to infer metabolic or functional activity of the population [ 28 , 29 ]. However, microbiomes are extremely complex systems, containing hundreds to thousands of different species and the proportional existence of a particular taxon or species related to its metabolic contribution to particular enzymatic pathways is inferential at best. Abundant species may be relatively quiescent or vice versa, and small species populations may be extremely significant to the metabolic state of the population. Furthermore, microbiomes are typically highly dynamic environments/ecosystems that will quickly adapt to changes in diet, disease state, and the various medicines used to treat them. It is for these reasons that having the means to effectively profile microbial gene expression changes via MetaT analysis is critical to our understanding of microbiomes as well as their influence and interactions with their hosts."
} | 3,992 |
25308276 | null | s2 | 8,992 | {
"abstract": "YisP is involved in biofilm formation in Bacillus subtilis and has been predicted to produce C30 isoprenoids. We determined the structure of YisP and observed that it adopts the same fold as squalene and dehydrosqualene synthases. However, the first aspartate-rich motif found in essentially all isoprenoid synthases is aspartate poor in YisP and cannot catalyze head-to-head condensation reactions. We find that YisP acts as a phosphatase, catalyzing formation of farnesol from farnesyl diphosphate, and that it is the first phosphatase to adopt the fold seen in the head-to-head prenyl synthases. Farnesol restores biofilm formation in a Δyisp mutant and modifies lipid membrane structure similarly to the virulence factor staphyloxanthin. This work clarifies the role of YisP in biofilm formation and suggests an intriguing possibility that many of the YisP-like homologs found in other bacteria may also have interesting products and functions."
} | 237 |
38904674 | PMC11192851 | pmc | 8,993 | {
"abstract": "Abstract Direct ammonia oxidation (Dirammox) might be of great significance to advance the innovation of biological nitrogen removal process in wastewater treatment systems. However, it remains unknown whether Dirammox bacteria can be selectively enriched in activated sludge. In this study, a lab-scale bioreactor was established and operated for 2 months to treat synthetic wastewater with hydroxylamine as a selection pressure. Three Dirammox strains ( Alcaligenes aquatilis SDU_AA1, Alcaligenes aquatilis SDU_AA2, and Alcaligenes sp. SDU_A2) were isolated from the activated sludge, and their capability to perform Dirammox process was confirmed. Although these three Dirammox bacteria were undetectable in the seed sludge (0%), their relative abundances rapidly increased after a month of operation, reaching 12.65%, 0.69%, and 0.69% for SDU_A2, SDU_AA1, and SDU_AA2, respectively. Among them, the most dominant Dirammox (SDU_A2) exhibited higher nitrogen removal rate (32.35%) than the other two strains (13.57% of SDU_AA1 and 14.52% of SDU_AA2). Comparative genomic analysis demonstrated that the most dominant Dirammox bacterium (SDU_A2) possesses fewer complete metabolic modules compared to the other two less abundant Alcaligenes strains. Our findings expanded the understanding of the application of Dirammox bacteria as key functional microorganisms in a novel biological nitrogen and carbon removal process if they could be well stabilized. Key points \n • Dirammox-dominated microbial community was enriched in activated sludge bioreactor. \n \n • The addition of hydroxylamine played a role in Dirammox enrichment. \n \n • Three Dirammox bacterial strains, including one novel species, were isolated. \n Graphical abstract \n Supplementary Information The online version contains supplementary material available at 10.1007/s00253-024-13214-2.",
"introduction": "Introduction Nitrogen removal is one of the critical purposes for the design of wastewater treatment systems. The conversion between dinitrogen gas and bioavailable nitrogen (“reactive”) on our planet is predominantly governed by microorganisms (Kuypers et al. 2018 ; Stein and Klotz 2016 ). Advancements in understanding the physiological and ecological characteristics of nitrogen-cycling microorganisms have contributed to the emergence of novel biological treatment processes. Sequential nitrification and denitrification, which form the basis of conventional nitrogen removal systems, have been widely adopted in wastewater treatment plants (WWTPs) (Rahimi et al. 2020 ; Thakur and Medhi 2019 ). The discovery and characterization of anaerobic ammonium oxidation (anammox) (Jetten et al. 1998 ; Kuenen 2008 ; Mulder et al. 1995 ) provide an alternative approach for the complete conversion of ammonia to dinitrogen gas through the cooperation between aerobic and anaerobic ammonium oxidizing bacteria. Due to their reduced oxygen requirements compared to conventional nitrogen removal systems, an increasing number of partial nitritation-anammox systems have been implemented in full-scale WWTPs treating ammonium-rich and municipal wastewaters (Lackner et al. 2014 ; Liu et al. 2017 ). Additionally, recently discovered nitrogen-cycling microorganisms, such as ammonia-oxidizing archaea (AOA) (Konneke et al. 2005 ) and complete ammonia oxidizer (comammox) (Daims et al. 2015 ; van Kessel et al. 2015 ), hold potentials for application in biological nitrogen removal WWTPs (Lawson and Lucker 2018 ; Wang et al. 2021 ). It should be noted that the key players involved in the biological nitrogen removal process, namely nitrifiers and anammox, are autotrophic microorganisms that can be easily inhibited by relatively high concentration of organic carbon in the wastewater. Therefore, the removal of organic carbon should be prioritized, particularly in the case of anammox systems. In addition to autotrophic nitrogen-cycling microorganisms, there has been growing interest in microorganisms capable of simultaneous heterotrophic nitrification and aerobic denitrification (HNAD) under aerobic conditions, as they offer potential for alternative nitrogen removal methods (Chen et al. 2020 ; Joo et al. 2005a ). HNAD nitrogen removal is suggested to proceed through the canonical nitrification (NH 4 + → NH 2 OH → NO 2 − → NO 3 − ) and denitrification process (NO 3 − /NO 2 − → N 2 ). The direct ammonia oxidation (Dirammox) to N 2 via hydroxylamine, which was found in Alcaligenes ammonioxydans and was distinct from the HNAD process, has further expanded the microbial nitrogen-cycling network (Wu et al. 2021 ). As heterotrophic microorganisms, Dirammox bacteria (1) exhibit a rapid growth rate, enabling quick startup of biological nitrogen removal system, and (2) they can also simultaneously remove carbon and nitrogen pollutants from wastewater. Dirammox pathway has been proved to be mediated by enzymes encoded by the gene cluster dnfT1RT2ABCD , as demonstrated by physiological and biochemical experiments (Wu et al. 2021 , 2022 ). Genetic analysis further revealed that this functional gene cluster was phylogenetically conserved in genus Alcaligenes (Hou et al. 2022 ). Several bacterial strains belonging to the genus Alcaligenes had been isolated from environmental samples, and their nitrogen performance had been characterized using synthetic (Chen et al. 2021 ; Joo et al. 2005b ; Zhang et al. 2022 ) or real wastewater (e.g., piggery wastewater) (Joo et al. 2006 ). However, prior to the identification of Dirammox, these isolates may have been wrongly regarded as bacteria involved in the HNAD process. Distribution analysis revealed that approximately 31% Alcaligenes strains were derived from WWTPs or wastewater (Hou et al. 2022 ). The novel nitrogen metabolic pathway and heterotrophic lifestyle of Dirammox bacteria enable them promising candidates for the development of new wastewater treatment systems (Pan and Liu 2023 ). However, it remains unknown how Dirammox strains be selectively enriched in activated sludge (AS), thereby becoming the dominant microorganisms contributing to nitrogen removal. In this study, the objective was to get a Dirammox-dominated AS community for biological nitrogen removal. Additionally, we aimed to isolate and characterize new Dirammox strains from the AS. To achieve this, a lab-scale sequencing batch reactor was set up and inoculated with AS obtained from a conventional secondary WWTP. The reactor was operated to treat synthetic wastewater, with the transient selection pressure of hydroxylamine (an intermediate of Dirammox) being utilized to enrich Dirammox strains. To inhibit the activities of anaerobic denitrifiers, the dissolved oxygen (DO) concentration and well suspend biomass in the reactor was controlled and maintained oxic. Changes in microbial community structures were examined using high-throughput 16S rRNA gene sequencing (V3–V4 region). Isolation of bacteria and assessment of nitrogen-removal rates were conducted to identify the potential Dirammox strains. Furthermore, the validation of microorganisms possessing the Dirammox pathway was performed by integrating whole genome sequencing, genomic analysis, and experimental results. Our findings illustrated that Dirammox bacteria could be rapidly selected as the predominant members in AS and may play a crucial role in the nitrogen removal from wastewater. Three Dirammox strains, including one representing a novel species of Alcaligenes , were isolated from the AS. The relative abundance, ammonia removal performance, and genomic comparison of these Dirammox strains were investigated. This study highlights the potential for achieving rapid enrichment of Dirammox bacteria in activated sludge systems, providing a foundation for the future engineering applications of Dirammox bacteria in biological nitrogen removal processes.",
"discussion": "Discussion Hydroxylamine has been confirmed as intermediate compound in the Dirammox pathway, transiently accumulating during ammonia conversion (Wu et al. 2021 ; Xu et al. 2022 ). Besides its involvement in the Dirammox process, hydroxylamine is also a highly reactive intermediate compound produced by AOA (Konneke et al. 2005 ; Stahl and de la Torre 2012 ), AOB (Caranto and Lancaster 2017 ) and comammox (Daims et al. 2015 ; van Kessel et al. 2015 ). Previous studies have demonstrated that the addition of hydroxylamine can enhance the growth of AOB by accelerating the ammonium uptake rate (Chandran and Smets 2008 ; Harper et al. 2009 ). However, the addition of hydroxylamine has been reported to inhibit NOB (Cao et al. 2017 ; Kindaichi et al. 2004 ). The addition of hydroxylamine can lead to a decrease in the oxidation–reduction potential (ORP) and then create a reductive environment that has a more pronounced inhibitory effect on NOB than AOB (Sui et al. 2020 ). Furthermore, the addition of hydroxylamine has been observed to increase the concentration of NO in the liquid phase (Zhao et al. 2021 ), which could strongly inhibit the growth of Nitrospira (Courtens et al. 2015 ). Consistent with these findings, the dynamics of microbial community in our study revealed the inhibition of NOB and promotion of AOB after treated wastewater with the addition of hydroxylamine at the beginning of each reaction cycle. Despite the increase of AOB following hydroxylamine addition, their relative abundance was below 2.5% in most of the AS samples under the high levels of organic carbon (1.9 g/L COD). Moreover, the high DO levels in the studied reactor could efficiently inhibit the activities of anaerobic denitrification. These results suggested the nitrogen removal of the reactor might be attributed to the presence of novel nitrogen-cycling microorganisms. The microbial community profiling showed the rapid enrichment of Alcaligenes as the dominant population in the lab-scale AS system treating HNM with the addition of hydroxylamine. Considering the widespread distribution of Dirammox pathway among Alcaligenes species (Hou et al. 2022 ), Dirammox bacteria may contribute to the nitrogen removal in the studied reactor. Representative Alcaligenes isolates were obtained for ammonia conversion experiments. The experimental results demonstrated that all three Alcaligenes strains exhibited nitrogen removal activities under aerobic condition. Moreover, the most abundant one displayed the highest nitrogen removal rate. In summary, our study provided evidence that the addition of hydroxylamine in each reaction cycle, coupled with the maintenance of relatively high DO levels, and effectively enriched Dirammox strains in AS systems. While HNM is commonly used to enrich heterotrophic ammonia oxidizers, our study did not address whether the addition of hydroxylamine to HNM could accelerate the enrichment process of Dirammox, as no control experiment (without hydroxylamine) was conducted in the present study. Additionally, it is important to note that hydroxylamine in real environment is toxic and unstable. Therefore, hydroxylamine may serve as a selective agent for the startup of a Dirammox-dominated activated sludge system. Genetic analysis of these three novel Dirammox strains in this study confirmed the universal distribution and phylogenetic conservation of the dnfT1RT2ABCD gene cluster in Alcaligenes (Hou et al. 2022 ; Wu et al. 2021 ; Xu et al. 2022 ). Furthermore, we observed a highly similar gene arrangement surrounding the gene cluster among the five studied Dirammox strains, which belong to four different species ( A. faecalis , A. sp . , A. ammonioxydans , and A. aquatilis ). Based on the genetic annotation of the conserved genes, it is suggested that the metabolism of organic nitrogen such as urea and amide (e.g., glutamine) may be import for Dirammox process. However, we speculate that this conserved flanking regions of dnf gene cluster may not have a direct correlation with the Dirammox activities since SDU_A2, which showed divergent gene content near the dnf gene cluster, also exhibited relatively high nitrogen removal rate. Regarding metabolic potentials, SDU_A2, as the predominant Dirammox strain and a putative new species of Alcaligenes , possessed fewer complete metabolic modules compared to the other studied Dirammox strains. The missing metabolic modules in SDU_A2 were related to amino acid biosynthesis and vitamin metabolism, which may explain its longer lag period under pure cluster experiments. As discussed in previous studies, bacteria with reduced genomes may have selective advantages in stable environments (Brewer et al. 2016 ; D'Souza et al. 2014 ; Johnson et al. 2020 ), suggesting that SDU_A2 may acquire essential metabolites from other associated microorganisms in the AS systems and achieve higher fitness compared to the other Dirammox strains (SDU_AA1 and SDU_AA2). Although Dirammox strains can be selectively enriched as predominant populations in the lab-scale reactor, the observed fluctuation in the abundance Alcaligenes suggested a lack of stability in the community state. Therefore, further investigations are required to optimize operational parameters for the maintenance of community stability and elucidate the underlying mechanisms that enable Dirammox bacteria gain fitness advantages over other microbial members. In conclusion, the selective enrichment of Dirammox strains in AS is a crucial aspect for its engineered application. Having observed the successful enrichment of Dirammox bacteria by the modified HNM solution with addition of hydroxylamine, this study offers a foundation to further evaluate the feasibility of employing Dirammox for simultaneous nitrogen and carbon removal from wastewater. In the studied reactor, an isolate representing novel Dirammox species of the genus Alcaligenes was identified as the most abundant Dirammox strain. Comparative genomic analysis indicated that Dirammox strain with streamlined genome might gain fitness advantage in the complex AS system. The molecular mechanism underlying the distinct activities of Dirammox strains remain to be elucidated."
} | 3,531 |
34699539 | PMC8547634 | pmc | 8,994 | {
"abstract": "While numerous studies have revealed that arbuscular mycorrhizal fungi (AMF) enhance plant performance, the influence of these symbionts on temperate-forest herbaceous species in relation to soil physical and chemical properties has been left largely unexplored. Therefore, two perennial herbs, Geum urbanum (Rosaceae) and Senecio ovatus (Asteraceae), were examined in a laboratory pot experiment to determine whether AMF influenced their growth, photosynthetic performance index, and N and P contents in biomass. The treatments, involving three widespread AMF species, were prepared in the soils of two habitats colonised by both plants, namely beech and riparian forests, as follows: (1) control—soils without AMF, (2) Claroideoglomus claroideum , (3) Funneliformis geosporus , and (4) Funneliformis mosseae . Neither shoot mass nor photosynthetic performance index of G . urbanum and S . ovatus was enhanced by AMF. Senecio ovatus root mass was increased compared to control only by F . geosporus . Inconsistent effects were observed in N and P contents in shoots and roots of both species. The direction and magnitude of these responses were dependent on the fungal species and soil type. Although the plant species belong to families whose representatives are usually regularly colonised by and highly responsive to AMF, our study indicates that AMF had only a slight impact on the performance of G . urbanum and S . ovatus at the early stages of their development. The plants being slightly dependent on AMF are thus adapted to colonise temperate-forest soils with a low level of availability of AMF propagules.",
"introduction": "Introduction Arbuscular mycorrhiza (AM) is one of the ubiquitous symbioses that frequently result in the enhancement of plant performance through nutritional and non-nutritional mechanisms [ 1 ]. However, the impact of arbuscular mycorrhizal fungi (AMF) on their partners is varied and may also be neutral or negative. It has been shown that AM enhances nutrient absorption and growth [ 2 ], competitiveness in communities [ 3 , 4 ], and resistance to unfavourable environmental conditions [ 5 – 8 ] of certain species of plants. In other studies, AM had no effect, or a negative effect, on plant nutrition, growth, and diversity, because the cost of maintaining fungal partners exceeded the benefits resulting from this symbiosis [ 8 – 11 ]. In any case, in these relationships, environmental factors, physical and chemical properties of soil, and, most importantly, fungus and plant species identities were of significance [ 8 , 12 ]. Previous studies on interactions between mycorrhizal fungi and plants in temperate forests focused overwhelmingly on ectomycorrhizas; however, the presence of endomycorrhizas, including AM, has been observed among forest overstorey and understorey plant species [ 13 ]. Studies focused on the impact of AMF on the herbaceous layer of forest ecosystems have shown that AMF are physically and functionally selective in terms of partners [ 14 , 15 ], as well as being influenced by soil properties and plant diversity [ 16 ] and by habitat filtering processes [ 17 ]. Moreover, Moora et al. [ 18 ], using multispecies soil inocula, found that the influence of AMF on the growth, nutrient status, and AMF colonisation of understorey species is site-specific. Similarly, based on field observations of degrees of AMF root colonisation, it was suggested that AMF may play a role in supplying P to understorey species in sites characterised by the scant presence of this element [ 19 ]. Inconsistent effects of AMF soil inocula from young and old forest ecosystems on the growth of understorey plant species were found [ 20 , 21 ]. On one hand, the were no differences between the effects of both AMF soil inocula on shoot and/or root mass [ 20 ]; on the other hand, they varied, with positive effects of AMF from old forests being linked with intensity of use and the impact thereof on AMF community composition [ 21 ]. However, heretofore no studies have focused on the impact of particular AMF species on the performance of herbaceous plants present in forests located in temperate climate zones in relation to soil physical and chemical properties. Therefore, two perennial herbs, Geum urbanum L. and Senecio ovatus (P. Gaertn., Mey. & Scherb.) Willd., were chosen in order to determine whether AMF influenced their performance. In laboratory conditions, we tested their response to inoculation with three widespread AMF species present in forest ecosystems around the world in soils of beech and riparian forests, which are colonised by both plant species. The specific questions addressed in the present study are as follows: (1) Are the plants dependent on AMF for their performance? (2) To what extent do different AMF species affect plant mass, photosynthetic performance index, and N and P contents in biomass? (3) What is the relationship between degree of mycorrhizal colonisation and plant variables? (4) Are these interactions dependent on soils which differ in physical and chemical properties? Given functional diversity in AM symbioses, which is also affected by soil physical and chemical properties [ 8 , 14 ], we expected that the effects of inoculation would differ between plant species, AMF species, and types of soil.",
"discussion": "Discussion We have shown, for the first time, that the herbaceous plants Geum urbanum and Senecio ovatus growing in beech and riparian soils were slightly dependent on AMF for their performance, and that both herbs were able to grow well without the presence of AM. The direction and magnitude of the responses of both plant species to AMF were related to fungal species and soil types. The level of AMF colonisation of G . urbanum was low; in the case of F . geosporus it was near zero. Although higher F values were noted in S . ovatus inoculated with C . claroideum and F . mosseae , the M and A parameters fluctuated around low values; similarly as in the case of G . urbanum , F . geosporus colonisation rates were negligible. The relatively low level of intensity of AMF colonisation of both species is in accordance with rates found among forest herbaceous plants in the field, though higher levels were found in some species [ 19 ]. Carrenho et al. [ 39 ] found that various AMF species colonised their hosts with different degrees of intensity. The level of colonisation was also impacted by the type of soil involved [ 39 – 42 ]. This may be due to the incompatibility of a particular species or strain of AMF with plant partners in a given soil type [ 14 , 18 ]. Compared with control, AMF did not enhance shoot mass or photosynthetic performance index, and very few AMF effects on root mass of both plant species were noted. Moreover, no clear trends were observed regarding enhancement of N and P acquisition due to AMF. Earlier studies on the effects of inoculation with AMF on several species from Rosaceae indicated that their growth responses could be negative, neutral, or positive. On one hand, a study by Sudová and Vosátka [ 10 ] on the inoculation of Fragaria moschata and Potentilla reptans by three AMF species, including F . mosseae , showed negative growth response. However, AMF were effective in supplying P. Nevertheless, higher P content in shoots of both species were not associated with stimulation of their growth, indicating that N rather than P content is the governing factor in these specific interactions [ 10 ]. Similarly, Zobel and Moora [ 9 ] noted the absence of any growth response of Fragaria vesca to AMF. On the other hand, an experiment carried out by Mark and Cassells [ 43 ] on the inoculation of F . vesca with C . claroideum revealed a positive growth response. Studies on the effects of AMF on numerous species from Asteraceae showed, in most cases, positive plant response. The following results have been noted: enhanced growth of Centaurea jacea following inoculation with AMF soil inocula [ 9 ]; increased biomass and enhanced photosynthetic performance index of Senecio umbrosus following inoculation with, among others, C . claroideum and F . geosporus [ 44 ]; and enhanced biomass, but not PI ABS , in Inula ensifolia , Rudbeckia laciniata , and Solidago gigantea following inoculation with several AMF species [ 25 , 45 ]. Mycorrhizal dependency of G . urbanum and S . ovatus concerning growth and N and P acquisition was near zero in both soils, but varied between AMF species in terms of elements. This indicates that neither species is dependent on AMF in this respect. This observation contradicts studies of other species from Asteraceae and Rosaceae, where the level of mycorrhizal dependency for growth was found to be high. Osteomeles anthyllidifolia (Rosaceae), inoculated with six AMF species simultaneously, achieved values of mycorrhizal dependency between 46% and 76%. Nevertheless, these values were related to P content in soils, being higher in soils with lower P content [ 46 ]. In the case of representatives of Asteraceae, mycorrhizal dependency of R . laciniata was 88% and 63% and for S . gigantea 90% and 82% for two soil types involved, respectively [ 25 ]. Similarly, Bidens sandvicencis was rated by Gemma et al. [ 47 ] as a highly AMF-dependent species, as it achieved values of mycorrhizal dependency up to 88% after being inoculated with Rhizophagus aggregatus . These effects were also linked with P content in soil. These studies did not focus on distinctions between the impacts of particular AMF species; however, van der Heijden et al. [ 37 ] showed that mycorrhiza-dependent plant species respond differently to different AMF species. The effects of AMF on plant species can be multidirectional and may vary in different environmental conditions. Literature data confirm that numerous interacting factors, both abiotic and biotic, have an influence on soil microbial properties and related response of plants. For example, in natural forest ecosystems, the co-existence of trees and herbaceous species, which differ in the formation of AM, ectomycorrhiza or are non-mycorrhizal, affect the abundance of AMF propagules in soils, and thus influence the intensity of AMF colonisation degree of plants in particular sites [ 19 , 48 , 49 ]. Moreover, it was observed that in the restoration of degraded areas, higher AMF species richness enhanced inoculum effectiveness. The positive response from plants increased from multiple species to whole soil inoculum [ 50 ]. However, ecologists also signalise that since AMF show functional diversity and their effects are within mutualism and parasitism spectrum [ 51 – 53 ], the key point is to select single effective AMF species than focus on species richness [ 54 ]. No without significance in plant-AMF relationships are also other factors, like soil physical and chemical properties [ 46 , 47 , 55 ] as well as presence of biotic and abiotic stresses. It was reported that AMF can have positive effects on plants in the presence of stressors, such as salinity and heavy metal toxicity [ 56 – 59 ], by both nutritional and non-nutritional mechanisms [ 57 , 58 , 60 , 61 ]. The formation of AM may impact on resistance of plants for pathogens and herbivores by stimulations of bacteria in soils as well as by modifications of secondary metabolite synthesis in plants [ 62 ]. Therefore, other parameters, not measured in the present study, should be examined in future in order to identify complete spectrum of G . urbanum and S . ovatus response to AMF in forest ecosystems. In conclusion, our investigation included three AMF species and soils of two forest habitats, thus enabling us to draw strong inferences on the effect of AMF on G . urbanum and S . ovatus . We report, for the first time, that neither species is dependent on AMF for its growth and photosynthetic performance index. Moreover, we found only slight effects of AMF on N and P acquisition for both plant species, whose direction and magnitude were dependent on fungal species and soil identities. Thus, G . urbanum and S . ovatus are adapted to grow in temperate-forest soils, which can be characterised by a low level of availability of AMF propagules in comparison to other ecosystems [ 19 , 49 , 63 ]. This is further supported by the fact that G . urbanum is also found in habitats with disturbed soil [ 64 ] which are usually characterised by low levels of AMF abundance [ 65 , 66 ]."
} | 3,128 |
25609566 | PMC4302308 | pmc | 8,995 | {
"abstract": "Overwhelming evidence supports the endosymbiosis theory that mitochondria originated once from the Alphaproteobacteria. However, its exact position in the tree of life remains highly debated. This is because systematic errors, including biased taxonomic sampling, high evolutionary rates and sequence composition bias have long plagued the mitochondrial phylogenetics. In this study, we address this issue by 1) increasing the taxonomic representation of alphaproteobacterial genomes by sequencing 18 phylogenetically novel species. They include 5 Rickettsiales and 4 Rhodospirillales , two orders that have shown close affiliations with mitochondria previously, 2) using a set of 29 slowly evolving mitochondria-derived nuclear genes that are less biased than mitochondria-encoded genes as the alternative “well behaved” markers for phylogenetic analysis, 3) applying site heterogeneous mixture models that account for the sequence composition bias. With the integrated phylogenomic approach, we are able to for the first time place mitochondria unequivocally within the Rickettsiales order, as a sister clade to the Rickettsiaceae and Anaplasmataceae families, all subtended by the Holosporaceae family. Our results suggest that mitochondria most likely originated from a Rickettsiales endosymbiont already residing in the host, but not from the distantly related free-living Pelagibacter and Rhodospirillales .",
"discussion": "Discussion Placing mitochondria precisely in the tree of life has been problematic. Sparse taxonomic sampling, sequence composition biases, high evolutionary rates have all plagued the molecular phylogenetic inference of the origin of mitochondria. Here we address this issue with an integrated phylogenomic approach by using a broad taxonomic sampling, better-behaved marker genes and sophisticated models of sequence evolution. Using NeighborNet and spectral analyses, we first demonstrated that there were significant systematic errors in the current genomic dataset. Of particular concern was the potential LBA problem. We alleviated this problem by filling the gaps in the tree with 18 genomes of novel phylogenetic lineages that had not been sequenced before. In particular, we sequenced five Rickettsiales and four Rhodospirillales , two orders that had shown close affiliations with mitochondria previously. We showed that with the broad taxonomic sampling we were able to reduce the systematic errors, evident by the less prominent incompatible splits observed in the spectral analysis after adding the novel lineages. One big hurdle in mitochondrial phylogenetic analysis is the extreme composition biases and high evolutionary rates of the mitochondria-encoded genes. To address this issue, we resorted to well-behaved nuclear genes. We showed that mitochondria-derived nuclear genes have significantly less composition biases and lower rates of evolution than mitochondria-encoded genes. As expected, the tree topologies were sensitive to both the marker datasets and methods used to infer the phylogeny. Because the tree made from the nuclear dataset with the CAT site heterogeneous mixture model was congruent with the tree based on the 200 phylum-level marker genes and was most consistent with the gene order patterns, we chose to make the final tree using this setting. Placing mitochondria firmly within Alphaproteobacteria depends on a robust alphaproteobacterial phylogeny. Overall our final tree using the nuclear dataset is similar to the previously published alphaproteobacterial species trees based on either mitochondrial or phylum-level marker genes 18 19 20 21 22 24 in that they all recover the major alphaproteobacterial groups. However, our genome tree does present novel and interesting branching patterns of alphaproteobacterial species that are particularly relevant to the placement of mitochondria. We discuss these new patterns first. The Holosporaceae family consists of mostly obligate endosymbionts from acanthamoeba. Traditionally it has been assigned to the Rickettsiales order based on the SSU rRNA phylogeny 62 . With only one draft genome ( Odyssella thessalonicensis ) sequenced recently, this family was either absent or very poorly represented in all the previous published genome trees 16 17 18 19 20 21 22 24 47 59 63 . In a recent study with O. thessalonicensis as the sole representative, Holosporaceae was placed outside of the Rickettsiales order and close to the Rhodospirillales 20 . With a much broader taxonomic representation of this family, we placed Holosporaceae as a deep lineage within Rickettsiales , which is consistent with the traditional taxonomy ( Figure 6 ). We think the topology of Georgiades' study is most likely an artifact of sequence composition bias in the data because when we used mitochondria-encoded genes or did not apply the CAT mixture model to account for compositional heterogeneity, we observed topologies similar to that of Georgiades' study as well ( Figure S1–3, S5 ). In addition, our topology is consistent with the gene order patterns and is congruent with the SSU rRNA tree and the genome tree based on 200 phylum-level marker genes. While traditionally SAR11 has been placed within the Rickettsiales clade 19 64 , and as a sister clade to mitochondria 20 22 , recent studies have conclusively shown that this placement is a tree artifact caused by composition bias, as mitochondria, Rickettsiales and SAR11 all have AT rich genomes 21 23 24 . Indeed, when we used models that did not account for composition bias, we observed the traditional topology ( Figure S1, S3, S5 ). However, when we applied models that accounted for compositional heterogeneity, only HIMB59 was mostly placed within the Rickettsiales , while all the other SAR11 members clustered with the free-living bacteria ( Figure S2, S4, S6 ). The paraphyletic nature of the SAR11 group has been well documented previously 21 59 , but there is still uncertainty about the exact position of HIMB59 59 . In the Viklund study, HIMB59 has been positioned either within the Rickettsiales or the Rhodospirillales order depending on the marker datasets used. In our analyses, HIMB59 is almost always positioned within the Rickettsiales regardless of the markers (mitochondrial, nuclear or phylum-level markers) or the methods used (RAxML or PhyloBayes). The only exception is in the PhyloBayes tree of the mitochondrial dataset, where HIMB59 and other SAR11 species together group with free-living bacteria ( Figures S1–6 ). The placement of HIMB59 within Rickettsiales is unlikely caused by the composition bias because the other SAR11 members with more biased AT rich genomes have been separated from the Rickettsiales . We note however that the branch leading to HIMB59 is not completely resolved from other Rickettsiales ( Figure 6 ), indicating that the position of HIMB59 is unstable. Therefore, we consider the position of HIMB59 tentative and sampling of additional taxa close to HIMB59 should help resolve this issue. Recent phylogenomic studies have supported two alternative topologies regarding the position of mitochondria: 1) grouping with the free-living Rhodospirillales order 17 , 2) grouping with the Rickettsiales order 16 18 19 20 21 22 . Resolving this conflict has clear bearing on our understanding of the driving force behind the initial endosymbiosis event. For example, the “hydrogen hypothesis” proposes the metabolic syntrophy between a H 2 -producing alphaproteobacterial symbiont and a H 2 -dependant archaeon as the driving force behind the endosymbiosis 6 . The “oxygen scavenger” hypothesis, on the other hand, proposes that the removal of the toxic oxygen by the Alphaproteobacterium from the anaerobic host has driven the initial symbiosis 65 . A key piece of support for the “hydrogen hypothesis” necessitates that the alphaproteobacterial ancestor of mitochondria possessed a H 2 -producing machinery. Members of the Rhodospirillales order are capable of producing H 2 by fermentation while Rickettsiales species are not. Grouping mitochondria with Rhodospirillales certainly lends stronger support to the “hydrogen hypothesis”. With a much broader taxon sampling of both Rickettsiales and Rhodospirillales , our phylogenomic analyses have almost always placed mitochondria with Rickettsiales and never with Rhodospirillales , regardless of the marker datasets and phylogenetic methods used ( Figures 6 , S7–13 ). Using the same dataset in Esser et al. study but a more sophisticated trimming method to remove fast-evolving sites, Fizpatrick et al. have shown that mitochondria are grouped with Rickettsiales and not with Rhodospirillales 18 . Taking our and Fizpatrick et al. 's results together, we suspect the topology observed by Esser et al. might be a phylogenetic tree reconstruction artifact caused by either inadequate taxonomic sampling or sequence alignment trimming. Our genome tree shows that the Rickettsiaceae / Anaplasmataceae families are the closest relatives of mitochondria (posterior probability 1.0, Figure 6 ). This suggests that the ancestor of mitochondria was most likely a Rickettsiales endosymbiont that had been already living inside the host cells. We note, however, that the endosymbiont did not have to be an obligate intracellular bacterium at the time of the initial endosymbiosis event. As a result, it could have escaped the host later on and given rise to obligate intracellular Rickettsiales lineages as we see today. For the first time, we are able to place mitochondria firmly within the Rickettsiales order. Previous studies have all placed mitochondria as a sister clade to Rickettsiales but never unequivocally within Rickettsiales (if we discount the sister clade relationship of Pelagibacter and mitochondria). In our genome tree, Holosporaceae forms the deepest branch within the Rickettsiales . Mitochondria originated sometime after the divergence of Holosporaceae from the rest of the Rickettsiales . The Rickettsiales /mitochondria clade has a very strong posterior probability support value of 0.97. Therefore, we conclude that mitochondria evolved as a derived lineage from within the Rickettsiales order. The multiple novel Holosporaceae genomes will be extremely valuable in providing insights into the genetic complement of mitochondrial ancestor. Because they are the immediate outgroup of the mitochondria/ Rickettsiaceae / Anaplasmataceae clade, they have great potentials to improve the accuracy of the mitochondrial ancestral reconstruction. For example, based on the genome sequence of Candidatus Midichloria mitochondrii , a novel phylogenetic lineage within Rickettsiales, it has been recently predicted that mitochondrial ancestor possessed flagella and could undergo oxidative phosphorylation under both aerobic and microoxic conditions 66 . In conclusion, using an integrated phylogenomic approach, we placed mitochondria firmly within the tree of life and moved a step closer toward pinpointing the origin of mitochondria. Our results suggest that mitochondria most likely originated from the Rickettsiales lineage , but not from the distantly related free-living Pelagibacter and Rhodospirillales ."
} | 2,818 |
35468283 | PMC9631990 | pmc | 8,996 | {
"abstract": "Treated wastewater\nis a major pathway by which antibiotic resistance\ngenes (ARG) enter aquatic ecosystems. However, knowledge gaps remain\nconcerning the dissemination of specific ARG and their association\nwith bacterial hosts. Here, we employed shotgun metagenomics to track\nARG and taxonomic markers in river biofilms along a gradient of fecal\npollution depicted by crAssphage signatures. We found strong evidence\nfor an impact of wastewater effluents on both community composition\nand resistomes. In the light of such simultaneity, we employed a model\ncomparison technique to identify ARG–host relationships from\nnonassembled metagenomic DNA. Hereby, a major cause of spurious associations\notherwise encountered in correlation-based ARG–host analyses\nwas suppressed. For several families of ARG, namely those conferring\nresistance to beta-lactams, particular bacterial orders were identified\nas candidate hosts. The found associations of bla FOX and cph A with Aeromonadales or bla PER with Chromatiales support the outcome of independent evolutionary\nanalyses and thus confirm the potential of the methodology. For other\nARG families including bla IMP or tet , clusters of bacterial orders were identified which potentially\nharbor a major proportion of host species. For yet other ARG, like,\nfor example, ant or erm , no particular\nhost candidates were identifiable, indicating their spread across\nvarious taxonomic groups.",
"introduction": "Introduction Antibiotic\nresistance in pathogenic bacteria poses a global problem\nof increasing concern. 1 Successful management\nof the crisis of antibiotic resistance requires a holistic approach\nthat recognizes the particular role of terrestrial and aquatic ecosystems. 2 , 3 Environmental systems are, on the one hand, an original source of\nantibiotic resistance genes (ARG). 4 , 5 On the other\nhand, they provide reservoirs and pathways for the spread of acquired\nARG that emerge and proliferate in conjunction with antibiotic therapies\nin human healthcare and livestock farming. 6 − 8 In particular,\nthe role of treated wastewater emissions on the\noccurrence of ARG in surface waters was examined in different geographical\nsettings and with a focus on varying resistance determinants. 9 − 11 Moreover, a number of successful attempts were made to disentangle\nthe impacts of wastewater disposal and other anthropogenic activities\non freshwater resistomes. 12 − 14 The vast majority of those case\nstudies relied on qPCR technology to quantify selected ARG and, possibly,\ngenetic elements involved in their proliferation like, for example,\nintegrons. In recent years, shotgun metagenomics (SMG) is increasingly\nemployed to capture ARG in environmental systems. 15 − 17 In contrast\nto alternative methodologies, SMG yields information on the gene pool\nof entire bacterial communities without prior selection of targets.\nThus, SMG potentially detects a broad spectrum of resistance genes,\nincluding those not being typically considered in surveillance. 18 Moreover, metagenomic sequencing allows for\nthe simultaneous extraction of information on resistome and community\ncomposition from one and the same set of DNA sequences. Finally, relative\nabundances obtained by SMG are believed to be unbiased since neither\ncultivation nor PCR are involved which could result in unequal target\namplification. At the same time, the lack of amplification is considered\nthe main drawback of SMG as it necessarily poses restrictions on sensitivity. One of the biggest challenges of current antibiotic resistance\nresearch remains pinpointing the bacterial hosts of ARG in complex\nenvironmental communities. This issue is nowadays tackled by two complementary\napproaches. On the one hand, molecular methods are being developed\nto actually codetect ARG and phylogenetic markers in single cells\nvia sophisticated PCR protocols, 19 , 20 single-cell\nsequencing 21 or the sequencing of metagenomic\nDNA that underwent cross-linking prior to extraction. 22 , 23 On the other hand, there are attempts to link resistance and phylogenetic\ninformation exclusively in the computational domain. This includes\nthe assembly of large contigs from fragmented metagenomic DNA 24 , 25 and the study of empirical associations between the abundances of\nARG and phylogenetic markers. 16 , 26 , 27 With the assembly based approaches, reconstructed DNA fragments\n(contigs) are scanned for physical co-occurrences of ARG and phylogenetic\nmarkers on one and the same fragment such that, ideally, ARG–host\nrelations can be deduced from individual samples. By contrast, the\nstatistical approach necessarily compares multiple samples of different\ncommunity composition to identify associations between the abundance\nof ARG and taxonomic markers. For the latter approach, ARG and taxonomic\nmarkers do not need to reside on identical DNA fragments. Considering\nthat nonassembled fragments obtained from short-read sequencing typically\ncomprise about 150–300 bp only, such co-occurrences actually\nrepresent very rare exceptions. Experience with the different\napproaches to host identification\nwas recently compiled in a review paper. 28 Of the 21 case studies considered therein, the majority addressed\nmicrobiomes of wastewater or waste originating from livestock farming.\nCultivation-independent studies on ARG–host associations in\nfreshwater systems, however, are still scarce, 16 , 29 − 31 with information being largely confined to eastern\nAsia. The aim of the present study is to shed light on ARG–host\nassociations in freshwater biofilms of a European river receiving\ntreated wastewater from multiple plant effluents. Here, we chose\nthe statistical approach which compares ARG abundances\nin nonassembled metagenomic DNA across samples of variable community\ncomposition. In comparison to metagenome assembly, this approach is\ncomputationally cheap, and it consistently covers both chromosomal\nand plasmid-borne ARG. However, empirical ARG–host associations\nare prone to spurious correlations 28 arising\nfrom hidden effects which simultaneously control resistome and community.\nThe exposure of sampling sites to differing loads of treated wastewater\nis a typical example of such an effect. Consequently, we advanced\nthe statistical inference of ARG–hosts relations from nonassembled\nmetagenomic DNA by implementing a simple but novel model comparison\ntechnique. The latter accounts for simultaneous effects of wastewater\ndisposal on resistomes and bacterial community composition and thus\nsuppresses a major cause of spurious ARG–host relationships.\nThe actual exposure of sampling sites to treated wastewater was assessed\nthrough the quantification of crAssphage sequences as proposed recently. 32 To our knowledge, this study is the first of\nits kind addressing ARG–host relations in a river of central\nEurope. The outcomes are discussed in light of existing knowledge\non the distribution of ARG across taxonomically defined bacterial\ngroups.",
"discussion": "Results and Discussion General Properties of Samples The\naverage number of\nreads per sediment sample was 2.5 × 10 7 with only\nmoderate variation (range: 1.1 × 10 7 –4.5 ×\n10 7 ). At the same time, the samples did not vary substantially\nin terms of diversity based on the number of unique bacterial orders\ndetected. In a rarefaction plot, all samples fell into the region\nwhere the curve levels off suggesting that diversity was adequately\nrepresented by the amount of sequenced material ( Figure 2 ). No indication was found\nfor a correlation between bacterial diversity and the amount of crAssphage\nsignatures contained in samples (Spearman’s ρ = 0.07, p = 0.4). Figure 2 Number of bacterial orders detected in river biofilm in\nrelation\nto sample size (number of reads). The structure of the fitted theoretical\nrarefaction model was adopted from Hess et al. 2019. 39 Exposure of Sampling Sites\nto Treated Wastewater Wastewater\neffluents potentially affect both the resistome and the composition\nof bacterial communities in receiving waters. In statistical analyses\ntargeted at the identification of ARG host, those simultaneous effects\nmust be taken into account to avoid spurious correlations. However,\nthe pollution status of a particular sampling site with regard to\ntreated wastewater is difficult to quantify. This is due to uncertainty\nin estimated effluent rates, dilution effects, as well as possible\nin-stream retention all of which are subject to temporal variability.\nRecently, it has been suggested to employ the signature of crAssphage,\na bacteriophage associated with the human gut flora 38 as a tracer for fecal pollution. 32 To verify the applicability of this approach, sampling sites were\nfirst grouped into ordinal classes according to the suspected exposure\nto wastewater: “None”’ for sites upstream of\nany WWTP, “High” for sites immediately downstream of\nWWTP where effluent and river have just mixed, and “Moderate”\nfor sites in greater distance to upstream plants (≥2 km) where\nimpacts of wastewater have potentially been attenuated by in-stream\nretention and dilution already. Then, all samples were scanned for\ncrAssphage signatures and relative abundances were compared across\nthe ordinal exposure classes ( Figure 3 ). In fact, the number of crAssphage sequences per\nread differed significantly between sample classes with a continuous\nincrease from unspoiled to highly exposed sites. In accordance with\nexpectation, crAssphage abundance was highest in pure effluent water. Figure 3 Relative\nabundance of crAssphage signatures in pure WWTP effluent\n(very left) and river biofilms with different exposure to treated\nwastewater. Differences between adjacent groups are significant with\nall p < 0.02 (one-sided Wilcoxon rank sum test). While the majority of samples collected upstream\nof any WWTP was\nfree of crAssphage signatures, elevated signals were found at some\nsampling points (outliers in the rightmost box of Figure 3 ). The respective samples do\nnot stand out from the rest, neither in sequencing depth (number of\nreads) nor in terms of bacterial diversity. Thus, very likely, these\noutliers indicate cases of illegal wastewater disposal. However, they\ncould also reflect a lack of specificity since crAssphage signatures\nhave recently been detected in feces of nonhuman origin. 43 In conclusion, the number of crAssphage\nsignatures per read appears\nto be a reasonable indicator for the exposure of sampling sites to\ntreated wastewater. Since crAssphage information is continuous and\nquantitative, it was used as a proxy for wastewater exposure in all\ndownstream statistics. Impact of Wastewater on Bacterial Community\nComposition Understanding the possible impact of wastewater\ndisposal on the composition\nof in-river bacterial communities is necessary to properly interpret\nresistome information. In total, 71 bacterial orders were detected\nbased on the chosen filter criteria. For about 20% of those, a positive\nassociation between their relative abundance and the exposure of the\nsampling sites to treated wastewater was established ( Table 2 ). As expected, negative associations\nwere observed as well, reflecting a linkage of certain bacterial groups\nwith primary environmental habitats. Table 2 Bacterial\nOrders Whose Relative Abundance\nin Riverbed Biofilms Was Positively Associated with crAssphage Contamination\nAs an Indicator for Fecal Pollution phylum order Spearman’s\nρ adj. p -value Bacteroidetes Flavobacteriales 0.51 7.4 × 10 –05 *** Chlamydiae Chlamydiales 0.51 6.6 × 10 –05 *** Chloroflexi Chloroflexales 0.28 0.039 * Cyanobacteria Subsection\nI 0.46 0.00033 *** Subsection II 0.43 9 × 10 –04 *** Subsection III 0.35 0.0078 ** Subsection V 0.35 0.0068 ** Firmicutes Lactobacillales 0.53 6.1 × 10 –05 *** Fusobacteria Fusobacteriales 0.49 0.00014 *** Proteobacteria Bdellovibrionales 0.47 0.00024 *** Legionellales 0.45 0.00053 *** Pseudomonadales 0.37 0.0053 ** Rickettsiales 0.66 3 × 10 –08 *** Tenericutes Mycoplasmatales 0.38 0.0038 ** The bacterial groups listed in Table 2 form a heterogeneous set. The phyla Bacteroidetes,\nFirmicutes, Fusobacteria, and Proteobacteria, for example, are known\nto make up most of the human gut microbiome 44 , 45 and a positive association is thus in agreement with expectation.\nBacteroidetes and Proteobacteria have also been shown to majorly contribute\nto the composition of activated sludge microbiomes. 46 By contrast, the correlation of crAssphage contamination\nwith the\nabundance of Cyanobacteria is likely attributed to eutrophication\ncaused by incomplete removal of nutrients in sewage treatment. 47 These two examples illustrate how wastewater\ndisposal can potentially shape river microbiomes via mechanisms of\nselection and invasion. The latter term, however, must be used with\ncare since, depending on bacterial adaptive capabilities, we have\nto expect all forms of invasion ranging from only transient presence\nto the persistent integration into freshwater communities. Although\nthe observed relations between community composition and\ncrAssphage abundance are plausible, the analyses are potentially compromised\nby the high level of aggregation. In particular, positive associations\nmay remain unidentified due to the simultaneous occurrence of positive\nand negative association between crAssphage and taxonomic units at\nlower phylogenetic levels. For example, if “A” and “B”\nrepresent two bacterial families, a positive link between crAssphage\nand “A” may be “canceled out” by a negative\nlink with “B” when the analysis is performed at order\nlevel. Association of Wastewater Exposure with Antibiotic Resistance\nGenes Relative ARG abundance was positively correlated with\nthe exposure of sampling sites to treated wastewater for most of the\ngenes ( Figure 4 , Supporting Information Table S1 ). This was especially\ntrue for genes conferring resistance to aminoglycosides, macrolides,\nsulfonamide, or tetracyclines. By contrast, there was no consistent\npattern for genes providing resistance to beta-lactams or trimethoprim. Figure 4 Association\nof the relative abundance of ARG with the relative\nabundance of crAssphage signatures. All cases where |ρ|≥\n0.3 meet the significance criterion of p < 0.001\nafter correction for multiple testing. In the case of gene families encoding for beta-lactamases, 5 out\nof 10 showed a positive association with crAssphage while the remaining\nfive appeared to be unrelated. Between these two groups, no differences\nwere found, neither with regard to the enzyme class nor in terms of\nthe target spectrum of drugs. Specifically, genes coding for class\nA, B, and D beta-lactamases were present in both groups. Likewise,\nresistance to carbapenems, cephalosporins, cephamycins, monobactams,\npenams, or penems was not uniquely linked to either group, and most\nof the gene families—in both groups—are known to be\neffective against multiple beta-lactam antibiotics according to CARD\nrecords. 48 Heterogeneous trends with regard\nto the occurrence of distinct beta-lactam resistance genes were also\nreported for other environments. For example, bla TEM genes were found to be ubiquitous in soil microbiomes, whereas\nthe abundances of bla OXA or bla CTX\ncorrelated with anthropogenic impacts. 49 , 50 Of particular\ninterest is the result for the two variants of dihydrofolate\nreductase genes ( dfr ) conferring trimethoprim resistance.\nWhile the relative abundance of type I resistance ( dfr A) was significantly increased in samples contaminated with crAssphage\nsignatures, the opposite was true for type II ( dfr B). Strikingly, dfr B was detected in the majority\nof riverbed biofilms, whereas it was not detected in any sample of\ntreatment plant effluent which is unlikely to be by chance ( p = 0.023; Fisher’s exact test). On the one\nhand, this could point toward an environmental origin\nof the dfr B genes. On the other hand, genes of the dfr B family have already been detected in genomes of various\nclinically relevant strains 51 with clear\nevidence for mobility. 52 Hence, the detection\nof dfr B in environmental samples could be a result\nof resistance dissemination predominantly from nonpoint sources. In\nGermany, combined trimethoprim and sulfonamide treatment is not restricted\nto human infections but it is also a legal medication in a veterinary\ncontext, for example, for cattle, pigs, and pets. Within the catchment,\nseven larger facilities of commercial livestock farming were identified\nfrom aerial images and on-site inspection which could potentially\nserve as hot-spots of diffuse resistance dissemination. However, a\nstatistical comparison of ARG abundances observed up- and downstream\nof any of those facilities did not indicate significant effects, irrespective\nof the gene family (Wilcoxon test; all adj. p -values\n>0.2). Resistome data from sites located upstream of any\ntreatment plant\neffluent underwent a separate analysis to better understand the outlier\nsamples depicted as dots in Figure 3 . No statistically significant difference in the relative\nabundance of ARG was found when comparing samples with and without\nelevated levels of crAssphage signatures. One straightforward conclusion\ncould be that the crAssphage signal was misleading in the sense that\nit reflected some local contamination with feces of nonhuman origin.\nHowever, another plausible interpretation would be that elevated crAssphase\nlevels indeed originated from illegal disposal of wastewater but the\ncontributing population was very small and so was the likelihood of\nARG dissemination from actually colonized individuals. Association\nof ARG Abundance with Taxonomic Groups In this work, we followed\nthe statistics-based approach toward the\nproblem of ARG–host identification from metagenomic information.\nConsidering the study design along a gradient of pollution ( Figure 1 ), mere correlations\nbetween the abundance of ARG and taxonomic markers are likely to yield\nspurious outcomes. This is due to the fact that both the abundance\nof ARG and bacterial groups are often simultaneously affected by wastewater\neffluents ( Table 2 , Figure 4 ). Consequently,\nwe refrained from examining correlations but followed a model comparison\napproach. Specifically, we fitted linear models to predict the number\nof ARG copies in a sample, y , using two predictors:\nthe presence of crAssphage signatures, x 1 , and the number of 16S rRNA gene copies associated with a particular\ntaxonomic group of bacteria, x 2 ( eqs 2 and 3 ). To infer the possible value of bacterial abundance information,\nthe two-predictor model ( eq 3 ) was compared to the single-predictor version ( eq 2 ) by means of a likelihood ratio\ntest. Models with negative coefficients a 2 were generally discarded since inverse relationship between ARG\nand bacterial abundances are not of interest in the context of host\nidentification. 2 3 The model comparison approach\ndisclosed\na heterogeneous pattern ( Figure 5 ). Figure 5 Performance of two-predictor models ( eq 3 ) in relation to the single-predictor benchmarks\n( eq 2 ). Colors encode p -values of a likelihood ratio (LR) test with the null hypothesis\nbeing that community information does not contribute to predictive\npower; p -values were adjusted column-wise to account\nfor the fact that all bacterial orders were considered as candidate\npredictors. Symbol size depicts the fraction of variance explained\nby eq 3 ; cases with r 2 < 0.5 were suppressed for clarity. Row\norder was determined by cluster analysis. For the majority of ARG, the incorporation of information on bacterial\ncommunity composition allowed for an improved estimation of gene abundances.\nHowever, results differ substantially between particular ARG families.\nIn the case of beta-lactam resistance genes like amp S, bla FOX, bla PER, or cph A, for example, only a single bacterial order contributed significantly\nto model performance. Thus, the respective orders are likely to play\nan actual role as host of the respective ARG. By contrast, genes\nlike bla GES, bla IMP, bla OXA, msr , or tet were found to\nbe linked with numerous bacterial orders leaving more\nroom for speculation. While all these orders could potentially serve\nas hosts, such outcomes are rather likely to reflect collinearity.\nThe latter can arise from associations between bacterial community\nmembers due to, for example, common environmental preferences or even\nmetabolic dependencies. Nevertheless, even those results are not entirely\ninconclusive since Figure 5 still depicts characteristic patterns. For example, the genes bla GES and bla IMP conferring resistance\nto carbapenems were found to be linked with a different set of bacterial\norders than, for example, ARG of the bla OXA or tet group. Finally, Figure 5 also highlights a few ARG families whose\nrelative abundance was\nnot significantly associated with any bacterial order (e.g., aad A, ant , erm ). Such\nan outcome would be expected for ARG that are widely spread across\ntaxonomic groups possibly facilitated through horizontal transfer\nof plasmids with a broad host range. In fact, genes like aad A or erm have been detected in chromosomal and plasmid\nDNA of numerous bacterial hosts according to current CARD 48 records, including Gram-positive and negative\nspecies. Furthermore, the particular role of horizontal transfer for\nthe dissemination of these genes has been highlighted earlier. 53 , 54 Several of the bacterial orders highlighted in Figure 5 harbor potentially pathogenic\nspecies with drug resistance being clinically relevant. This includes,\nfor example, Aeromonadales, Clostridiales, or Enterobacteriales, while\nsome of the other bacterial groups have not been in the focus of drug\nresistance research so far. Unfortunately, a validation of the empirically\nidentified relationships suggested by Figure 5 is not easily accomplished. On the one hand,\ncase studies on ARG–host relationships in surface waters are\nnot only limited in number but also with regard to geographical coverage. 16 , 29 − 31 On the other hand, whole genome-based information\non ARG prevalence found in repositories like CARD 48 is potentially strongly biased toward culturable bacteria\nof clinical relevance. Nevertheless, some of the ARG–host\nrelations proposed here\nare strongly supported by previous studies on the phylogeny of resistance\ngenes. 55 , 56 This is especially so for ARG that were\npositively linked to the order Aeromonadales. For instance, in agreement\nwith Figure 5 , the\nfish pathogen Aeromonas allosaccharophila was recently\nidentified as the original host of bla FOX genes. 57 Similarly, the cph A gene was\npreviously found to be linked with the host Aeromonas hydrophila . 58 The association of bla PER beta-lactamases with\nthe bacterial order Chromatiales implied by Figure 5 represents another case supported by external\nevaluation. Only recently, it was suggested that bla PER genes were originally acquired by the genus Pararheinheimera , a member of Chromatiales, long before the era of antibiotics 59 with the occurrence in human pathogens being\na result of later horizontal transmission. At a higher level,\nthe candidate associations proposed here support\nthe outcome of previous research on ARG–host associations 28 according to which the majority of hosts falls\ninto the groups of Proteobacteria and Firmicutes. These two phyla\ncontribute the majority of bacterial orders depicted in Figure 5 . The cases of bla FOX, bla PER,\nand cph A clearly illustrate that the statistical\ninference of ARG hosts from nonassembled metagenomic data is actually\nfeasible. However, challenges remain with regard to several aspects.\nFirst of all, it seems necessary to apply the approach to even larger\ndata sets exhibiting considerable variation in the composition of\nbacterial communities. On the one hand, this would allow for an improved\ndetection of false positives by, for example, cross-validation methods.\nOn the other hand, it may help to further disentangle some of the\nclusters depicted in Figure 5 where a particular set of ARG was associated with multiple\nbacterial groups and host relations thus remain inconclusive. Second, it seems necessary to further increase resolution, especially\nof the taxonomic data as pointed out recently. 28 This is due to considerable diversity at higher taxonomic\nlevels like orders or phyla which may obscure ARG–host relations\nmanifested at genera or species level. In this respect, progress could\nbe made through sequencing technologies yielding longer reads. 60 Third, the statistics-based approach to\nthe identification of ARG\ncan certainly profit from independent validation data produced with\ncomplementary techniques like, for example, metagenome assembly 61 or Hi-C sequencing. 23 A sole validation against information on ARG prevalence observed\nin isolates (many of which having a clinical background) can hardly\nsuffice. Even worse, it could result in the false rejection of identified\nARG–host relationships in environmental systems for the reason\nfor apparent implausibility. To possibly validate the ARG–host\nassociations reported\nhere, we applied the memory-efficient MEGAHIT software 62 to assemble six of the metagenomes. About 1 / 5 of the ARG and 1 / 10 of\nthe 16S rRNA-based taxonomic markers detected on the original reads\nwere recovered from contigs. However, among the 8 × 10 6 generated contigs there were only three instances with simultaneous\ninformation on resistance and host. All three cases were related to\nthe macrolide resistance gene msr E with Comamonadaceae\n(order Burkholderiales; 2×) and Microoscillaceae (order Cytophagales;\n1×) being reported as the candidate hosts. This amount of information\nis clearly insufficient for serious validation. In our case, the major\nlimitation appeared to be the insufficient length of the assembled\ncontigs. While a few long sequences of up to about 900 kbp were obtained,\nmedian contig lengths ranged between 590 and 800 bp only and the codetection\nof ARG and specific 16S rRNA information was thus unlikely. Moreover,\none needs to keep in mind that assembly based strategies are not suited\nto the identification of ARG host when the resistance is plasmid-borne.\nIn fact, the full consideration of plasmid-borne ARG is one of the\nmajor advantages of the statistical approach to host identification. A successful identification of ARG–host relations by the\nstatistical approach requires a number of conditions to be met. First\nof all, multiple metagenomic samples must be analyzed each contributing\nmillions of reads. A high number of reads per sample is the key to\nthe detection and quantification of less abundant bacterial groups\nand ARG. Likewise, statistical significance of empirical ARG–host\nrelationships is more likely to be established the more individual\nsamples are available. However, a high number of deeply sequenced\nsamples alone does not guarantee success. Rather, it is crucial that\nindividual samples differ with regard to community composition. Without\nvariance in community composition, the statistics-based inference\nof ARG–host relations would clearly be infeasible. Finally,\nit needs to be stressed that any ARG–host relations\nproposed by statistical analyses should be treated with the usual\ncaution. First, false positives cannot be avoided entirely and a small\nproportion of the identified associations may thus reflect coincidence.\nThis is especially so when the number of multiple tests becomes large,\nfor example, in response to a fine-grained decomposition of the bacterial\ncommunity. To guard against false positives, obtained p -values should undergo rigorous adjustment as in the preparation\nof Figure 5 . Second\nbut more important, candidate bacterial groups must not be regarded\nas the “exclusive hosts”. While they potentially play\nan outstanding role, many ARG families have invaded multiple branches\nof the phylogenetic tree by horizontal transfer and certainly persist\nin multiple bacterial orders or phyla. 63 , 64 To better\nillustrate the possible contribution of taxonomic information\nto the prediction of ARG prevalence, the matrix from Figure 5 was filtered to those bacterial\norders that allowed for the best fit of eq 3 . Furthermore, the fraction of explained variance\nwas decomposed so as to highlight the contribution of community information\nin relation to crAssphage information ( Figure 6 ). For more than 3 / 4 of the gene families, crAssphage data combined with information\non a single bacterial order explained over 50% of the observed variance\nin ARG abundance. For genes conferring resistance to beta-lactam antibiotics,\nup to about 80% of the variance were explained. Figure 6 Performance of linear\nmodels predicting the relative abundance\nof ARG families from crAssphage abundance ( eq 2 ; solid bars) or crAssphage abundance combined\nwith information on bacterial community composition ( eq 3 ; total bar length). For each ARG\nfamily, the indicated bacterial order is the one that allowed for\nthe best fit of eq 3 and\nshaded parts represent the corresponding improvement of the model.\nIf no order name is given, community information had no added value\nwhatsoever. Synthesis We found\nstrong evidence for an impact of\nwastewater effluents on both the taxonomic composition of river bacterial\nbiofilms and their enrichment with ARG. With regard to the latter,\nthe strongest effects were observed for gene families conferring a\nreduced susceptibility to aminoglycosides, macrolides, tetracyclines,\nand selected beta-lactam antibiotics including carbapenems. However,\nthe abundance of several other ARG families coding for beta-lactamases\n(e.g., bla TEM, ampS ) or type II\ntrimethoprim resistance ( dfr B) was apparently unrelated\nto wastewater disposal. Hence, the respective genes are either naturally\npresent in river microbiomes independent of human impacts or they\nare linked with anthropogenic nonpoint emissions. The statistics-based\napproach to the identification of ARG hosts yielded promising results.\nIn several cases, the relative abundance of a particular ARG proved\nto be significantly associated with the occurrence of just one or\ntwo specific bacterial orders. For several ARG families mediating\nbeta-lactam resistance ( bla FOX, bla PER, cph A) the proposed host relationships strongly\nsupport recent external evidence rooted in evolutionary analyses.\nHowever, even cases where a particular ARG is found to be associated\nwith multiple bacterial groups (or no group at all) are not without\nrelevance. In fact, those cases may reflect an efficient horizontal\ntransfer of antibiotic resistance through highly mobile genetic elements\nand call for further examination. Overall, community composition proved\nto be a valuable input to statistical resistome models. Specifically,\nfor 20 out of 23 resistance gene families, information on the abundance\nof particular bacterial orders significantly improved the performance\nof linear models predicting ARG abundance."
} | 7,752 |
21045005 | PMC3022399 | pmc | 8,997 | {
"abstract": "Most plants form root symbioses with arbuscular mycorrhizal (AM) fungi, which provide them with phosphate and other nutrients. High soil phosphate levels are known to affect AM symbiosis negatively, but the underlying mechanisms are not understood. This report describes experimental conditions which triggered a novel mycorrhizal phenotype under high phosphate supply: the interaction between pea and two different AM fungi was almost completely abolished at a very early stage, prior to the formation of hyphopodia. As demonstrated by split-root experiments, down-regulation of AM symbiosis occurred at least partly in response to plant-derived signals. Early signalling events were examined with a focus on strigolactones, compounds which stimulate pre-symbiotic fungal growth and metabolism. Strigolactones were also recently identified as novel plant hormones contributing to the control of shoot branching. Root exudates of plants grown under high phosphate lost their ability to stimulate AM fungi and lacked strigolactones. In addition, a systemic down-regulation of strigolactone release by high phosphate supply was demonstrated using split-root systems. Nevertheless, supplementation with exogenous strigolactones failed to restore root colonization under high phosphate. This observation does not exclude a contribution of strigolactones to the regulation of AM symbiosis by phosphate, but indicates that they are not the only factor involved. Together, the results suggest the existence of additional early signals that may control the differentiation of hyphopodia.",
"conclusion": "Conclusion Collectively, the various reports on the down-regulation of AM symbiosis by P suggest that several successive layers of control operate in roots grown under HP. The experimental conditions used by different authors shed light on one or the other of these control mechanisms. Those described in this report allow the manipulatation of mycorrhizal symbiosis by targeting some of the first events in the interaction, and the testing of a number of hypotheses related to these events. It is demonstrated for the first time that the regulation of AM symbiosis by P is accompanied by a systemic regulation of strigolactone production, an important observation with regards to the hormonal function of these compounds. The decreased strigolactone content under HP, however, does not solely account for the strong mycorrhizal phenotype. The results therefore suggest the existence of additional early signalling events, some of which probably affect the differentiation of hyphopodia. A better understanding of this regulation should reveal important mechanisms required for the symbiosis under favourable conditions, and help circumvent the limitations for this symbiosis associated with the extensive use of P fertilizers in agriculture.",
"introduction": "Introduction Roots of the vast majority of plant species develop symbiotic associations with arbuscular mycorrhizal (AM) soil fungi. Fungal hyphae develop in the root cortex where they form intracellular highly branched structures called arbuscules, and simultaneously in the soil where they form a dense mycelial network. Within the root the plant supplies the fungus with hexoses, at a cost of up to 20% of the carbon fixed by photosynthesis ( Smith and Read, 2008 ). In return, it obtains water and minerals taken up from soil by the mycelial network. The main benefit of the symbiosis for the plant is an enhanced acquisition of phosphorus (P), a frequent limiting factor in plant growth due to its poor solubility and mobility in soils. Despite the importance of AM symbiosis, cellular and molecular events underlying this interaction are only beginning to be unravelled ( Parniske, 2008 ). Direct genetic screens to identify mycorrhizal (myc − ) mutants are extremely cumbersome. As a result, most myc − mutants in fact belong to a subset of mutants initially isolated as deficient in nitrogen-fixing symbiosis, this latter interaction being easier to examine. A consequence of this bias is the relative scarcity of mutants affected in events unique to the AM symbiosis, including pre-colonization signalling and arbuscule development and function ( Marsh and Schultze, 2001 ). Nonetheless, several specific myc − mutants have been identified in the past few years. They can be affected in different stages of the interaction as summarized in Pumplin et al. (2009) : pre-symbiotic fungal growth, formation of hyphopodia (root attachment and penetration structures, formerly referred to as appressoria), epidermal penetration, and arbuscule development (see also Zhang et al. , 2010 ). Various physiological situations are known to affect the development of AM symbiosis. For instance, plants control the extent to which AM fungi can colonize their roots according to their own nutritional requirements. The best known example of such regulations is the control of AM symbiosis according to P availability. Roots can acquire P as inorganic orthophosphate (Pi) through different pathways ( Bucher, 2007 ). In certain conditions the mycorrhizal uptake pathway, which involves specific Pi transporters ( Rausch et al. , 2001 ; Harrison et al. , 2002 ; Paszkowski et al. , 2002 ), can be the major route for P uptake ( Smith et al. , 2003 ). When P is abundant, a direct, probably less costly uptake pathway is preferred ( Nagy et al. , 2008 ), and a reduced root colonization by AM fungi is observed. This down-regulation of the symbiosis by P has been known for a long time ( Graham et al. , 1981 ; Thomson et al. , 1986 ; Elias and Safir, 1987 ; Rausch et al. , 2001 ; and many others). It seems to be a general phenomenon, although its magnitude can vary ( Javot et al. 2007 ; Smith and Read, 2008 ). It has far-reaching consequences in natural ecosystems where it modulates the effect of AM fungi on plant species diversity ( Collins and Foster, 2009 ), as well as in agriculture where strong P fertilization may in the long term decrease the presence and richness of soil AM communities ( Johnson, 1993 ). Little is known about mechanisms underlying the regulation of AM symbiosis by P. A recent study ( Branscheid et al. , 2010 ) has documented this down-regulation in Medicago truncatula , and investigated the identity of the internal signal that triggers suppression of the interaction under high P. Nonetheless, the downstream mechanisms that prevent or limit root colonization by AM fungi remain largely unknown. Early studies led to conflicting results and interpretations, partly due to the variety of species combinations and experimental systems. Some of these early studies interpreted the impact of high P on the fungus in terms of trophic effects: high P would decrease the root secretion of metabolites used by the fungus, such as amino acids or carbohydrates (e.g. Graham et al. , 1981 ; Thomson et al. , 1986 ). An alternative proposition was that qualitative rather than quantitative differences between root exudates of P-replete and P-deficient plants could account for their differential effects on the fungus ( Elias and Safir, 1987 ). This led to the suggestion that P-deprived roots exuded important flavonoid signals that triggered pre-symbiotic fungal growth and activity ( Nair et al. , 1991 ). Advances made in the last 10 years have indeed emphasized the importance of signalling events in mycorrhizal interactions, and the recent identification of some signals may shed new light on the regulation of AM symbiosis by P. Plants and AM fungi are known to exchange molecular signals prior to physical contact, at the so-called pre-symbiotic stage. Various lines of evidence indicate that AM fungi produce diffusible compounds able to modulate root gene expression ( Kosuta et al. , 2003 ; Weidmann et al. , 2004 ), intracellular signalling ( Navazio et al. , 2007 ; Kosuta et al. , 2008 ), development ( Olah et al. , 2005 ), and metabolism ( Gutjahr et al. , 2009 ). Reciprocally, plant roots secrete compounds that stimulate the fungus ( Gianinazzi-Pearson et al. , 1989 ; Siqueira et al. , 1991 ; Tsai and Phillips, 1991 ; Giovannetti et al. , 1996 ; Buée et al. , 2000 ). A group of secondary metabolites called strigolactones were identified as major contributors to this effect ( Akiyama et al. , 2005 ; Besserer et al. , 2006 ). Strigolactones trigger morphological and developmental responses in the fungus such as hyphal branching and spore germination, and enhance fungal mitochondrial activity and respiration ( Besserer et al. , 2006 , 2008 ). Strigolactone-mediated signalling is necessary for a normal level of root colonization, as demonstrated using strigolactone-deficient mutants ( Gomez-Roldan et al. , 2008 ). Most interestingly, these root-exuded compounds also play an important role in planta , acting as hormones that contribute to the regulation of shoot branching ( Gomez-Roldan et al. , 2008 ; Umehara et al. , 2008 ). Prior to the discovery of their roles in AM symbiosis and plant development, strigolactones were known as germination stimulants for the seeds of the parasitic plants Striga and Orobanche ( Bouwmeester et al. , 2007 ). Damage caused to crops by these weeds is lower under strong nutrient fertilization, which led to the investigation of whether P availability influenced strigolactone release into the soil. Indeed, several studies demonstrated a strong negative effect of high P supply on strigolactone production and exudation in various species ( Yoneyama et al. , 2007 a , b ; Lopez-Raez et al. , 2008 ). A reasonable hypothesis is that high P availability would decrease the extent of AM symbiosis by reducing strigolactone production in roots ( Bouwmeester et al. , 2007 ; Yoneyama et al. , 2007 b ). In this report, P fertilization conditions which lead to an almost complete arrest of the first stages of the interaction between pea ( Pisum sativum L.) and two species of AM fungi are described. This strong effect is at least partly linked to regulatory events occurring in the plant partner, as shown by split-root experiments. Furthermore, it is demonstrated that like root colonization, strigolactone production is controlled in a systemic manner by P supply. Hence, strigolactones may contribute to the regulation of AM symbiosis by P, but supplementation experiments indicate that they are not the only factor involved.",
"discussion": "Discussion HP supply can strongly inhibit AM symbiosis The regulation of AM symbiosis by P supply has been observed repeatedly and is considered a general phenomenon. In contrast to most previous studies, however, the experimental conditions described in the present report lead to a clear-cut mycorrhizal phenotype under HP supply, since hardly any symbiotic structures are observed ( Fig. 1 ). Similar effects of HP were observed with 150 and 600 Glomus spores per plant ( Fig. 5 and Fig. 1 , respectively), indicating that a higher inoculum density was not able to circumvent the regulatory mechanisms. The discrepancy between the strong mycorrhizal phenotype reported here and the more moderate effects of P reported previously may relate to the plant species used, and/or to the experimental conditions: in this study, P was supplied daily in the nutrient solution, and plants were inoculated with spores rather than fragments of infected roots containing different kinds of propagules. Inoculation with spores, often regarded as less virulent, probably helps to reveal moderate phenotypes that could be masked with stronger sources of inoculum. For example, the pmi1 mutant of tomato exhibits a severe phenotype when inoculated with spores, but is colonized normally when inoculated with mycorrhizal nurse plants ( David-Schwartz et al. , 2001 ). The effect of HP supply on AM symbiosis is partly mediated by the plant Among the conditions tested, plant growth was maximal under HP conditions ( Supplementary Table S1 at JXB online), which correspond to a moderate P supply (750 μM): in studies on P starvation responses, the P-replete condition usually falls in the 1–3 mM range [e.g. Bonser et al. (1996) on pea; Valdes-Lopez et al. (2008) on bean; Pant et al. (2008) on Arabidopsis ]. The HP nutrient solution does not exhibit toxicity towards the fungal partner, as evaluated by spore germination tests. It also does not seem to modify the ability of the fungus to respond to strigolactones ( Supplementary Fig. S1 ). In addition, in split-root experiments the inhibition of root colonization can be observed in a compartment where the fungus is only exposed to LP ( Fig. 3 ). This regulation of AM symbiosis through systemic signalling is consistent with previous reports (e.g. Thomson et al. , 1991 ; Rausch et al. , 2001 ). It shows that the very strong inhibition of root colonization triggered by HP in the present report involves plant-driven processes and is not only due to a direct effect of local P concentration on the fungus. Yet, the existence of such direct effects cannot be excluded. HP supply arrests AM symbiosis in its first stages Microscopic examination of root samples revealed that HP fertilization reduced the number of hyphopodia formed on the root epidermis. This represents a novel HP-related mycorrhizal phenotype. A straightforward interpretation is that HP prevents hyphopodium formation per se . Alternatively, one could imagine that defects in later symbiotic stages could also lead to a reduced number of hyphopodia; for example, an impaired progression of the fungus within roots could delay or reduce the number of secondary infection events, which would in turn result in a smaller number of attached external hyphae. Several arguments lead us to conclude that the block in AM symbiosis triggered by HP occurs prior to primary hyphopodium formation, rather than later in the symbiotic process. First, the steps of clearing and staining the roots prior to microscopic observation were performed with particular care to prevent possible stripping and loss of hyphopodia (particularly those that did not lead to root colonization). Second, similar observations were made at 4 and 6 wpi ( Table 1 ). The first time point (4 wpi) corresponds to the very beginning of the infection process, when the first arbuscules become visible (<5% root length colonized). Hyphopodia observed at this time point therefore most probably derived from primary hyphae of germinated spores, rather than from secondary infections. At this time point, a very strong effect of HP fertilization was already noted. Third, mutants affected in later stages of the interaction typically exhibit a normal (sometimes even higher) number of hyphopodia ( Bradbury et al. , 1991 ; Bonfante et al. , 2000 ). Therefore, the present observations strongly suggest that HP conditions prevent either pre-symbiotic fungal development or attachment to roots. In contrast to the formation of appressoria by pathogenic fungi, the differentiation of these attachment and penetration structures by AM fungi is still poorly understood. Plants grown under HP are reminiscent of tomato pmi1 and pmi2 ( David-Schwartz et al. , 2001 , 2003 ), and maize nope1 and taci1 mutants ( Paszkowski et al. , 2006 ), in which a reduced frequency of hyphopodia was observed. Unfortunately the genes affected by these mutations have not been identified yet. Nonetheless these mutants, together with the HP conditions described in the present report, should be useful to decipher the mechanisms involved in hyphopodium differentiation. Different kinds of mechanisms could regulate the formation of hyphopodia under HP. One of them is the production by plant roots of stimulatory or inhibitory diffusible compounds. Candidate compounds include flavonoids, some of which have been reported to stimulate AM root colonization by enhancing the number of fungal entry points ( Scervino et al. , 2007 ). Polyamines have also been proposed to favour the formation of hyphopodia ( El Ghachtouli et al. , 1995 ). P availability also affects the production of compounds known to affect fungal development more generally (reviewed in Vierheilig, 2004 ), but in most instances their contribution to the regulation of AM symbiosis by P has not been tested functionally. An exception is the report by Akiyama et al. (2002) that a C-glycosylflavonoid accumulated in melon roots upon P starvation, and that supplementation with this compound restored normal mycorrhizal rates under HP. The reduced accumulation of this compound may therefore account for the decreased root colonization under HP. In contrast to the present report, however, the effects of HP were not observed in the first visible stages of the interaction. Two time points were examined by Akiyama et al. (2002) : 25 d and 45 d post-inoculation (dpi). At 25 dpi, the root colonization levels were similar under LP and HP. HP triggered down-regulation of AM symbiosis only at 45 dpi. In agreement with this, an AM-stimulating effect of the C-glycosylflavonoid on HP-grown plants was only observed at 45 dpi. In contrast, in the present conditions the negative impact of HP on root colonization could be observed as soon as the control roots became colonized (28 dpi, Table 1 ). Therefore, the mechanisms underlying suppression of AM symbiosis by HP may be different in the two systems. In addition, different plant species produce distinct arrays of flavonoids, making it difficult to extrapolate results from one species to another. Still, flavonoids remain interesting candidates as mediators of the P effect. In the present experimental system, branching bioassays supported the hypothesis of an effect of P on pre-symbiotic fungal development, since root exudate extracts of HP-grown plants failed to stimulate hyphal branching ( Fig. 2 ). These extracts did not inhibit the effect of GR24 on the fungus, and therefore appeared to lack branching stimulants that are present in exudates of LP-grown plants. It must be noted, however, that in these experiments ethyl acetate extracts of root exudates were used in order to allow an adequate concentration of the samples. Therefore, it cannot be excluded that in addition to the lack of stimulants in the organic fraction, fungal inhibitors could be found in the aqueous fraction of HP root exudates. Another possible type of regulatory process is the display of signals on the root epidermal surface. For example, AM fungal hyphae can recognize specific patterns displayed by epidermal cells and differentiate hyphopodia on cell wall fragments of the epidermis, but not of other root tissues ( Nagahashi and Douds, 1997 ). In addition, hyphopodia are formed on grooves between adjacent epidermal cells rather than on the outer cell wall. Interestingly, cell walls in these grooves appear thinner, looser, and richer in non-esterified pectin as compared with the tangential walls of epidermal cells ( Bonfante et al. , 2000 ). Whether such changes in cell wall composition contribute to the effect of HP on the formation of hyphopodia deserves further investigation. P supply affects strigolactone production in a systemic manner Strigolactones, identified as important contributors to the effect of host roots on pre-symbiotic fungal growth and metabolism ( Akiyama et al. , 2005 ; Besserer et al. , 2006 , 2008 ), were obvious candidates to mediate the effect of P supply because their synthesis is known to correlate inversely with P supply ( Yoneyama et al. , 2007 a , b ; Lopez-Raez et al. , 2008 ). In agreement with this, strigolactones were undetectable in root exudates of plants grown under HP. Furthermore, HP supply was able to down-regulate strigolactone production in a systemic manner, as evidenced by the analysis of split-root plants ( Fig. 4 ). This novel finding is particularly interesting in the context of the hormonal function of strigolactones. Indeed, a recent study has proposed that strigolactones mediate the tillering response to P starvation in rice ( Umehara et al. , 2010 ). In addition to the effect of strigolactones on lateral bud outgrowth, a role in the control of root architecture has recently been suggested ( Koltai et al. , 2009 ). This raises the possibility that P supply on one side of a plant affects development of a distant part of the root system through a modulation of strigolactone synthesis. It is already known that modifications of root architecture in response to P availability are integrated at the whole-plant level ( Williamson et al. , 2001 ), and it would be worth investigating the contribution of strigolactones to this phenomenon. The analysis of Pi contents in root and shoot tissues of split-root plants ( Fig. 3C, D ) revealed that root colonization levels and strigolactone production were linked to shoot Pi rather than to external P availability or local Pi concentrations in roots. This is consistent with the fact that HP exerts a dominant effect over LP in LP/HP split-root plant with regards to mycorrhizal and strigolactone exudation responses, and also with regards to Pi content (in LP/HP plants shoot Pi contents are similar to those of HP/HP plants). However, the signal underlying this systemic signalling remains unknown. Branscheid et al. (2010) proposed that the microRNA miR399 could act as a P starvation-induced signal to stimulate AM symbiosis under low P. MiR399 is known to accumulate in shoots under P deprivation, and to be transported to roots where it targets PHO2 , a negative regulator of several P starvation responses ( Lin et al. , 2008 ; Pant et al. , 2008 ). Interestingly, miR399 expression responded to AM root colonization, but overexpression of miR399 was not sufficient to improve AM root colonization under HP ( Branscheid et al. , 2010 ), suggesting that additional internal signals are required. Other microRNAs expressed in response to AM colonization and/or P supply ( Gu et al. 2010 ) may be alternative candidates as systemic signals. Strigolactones are not solely responsible for P-triggered down-regulation of AM symbiosis The putative role of strigolactones as mediators of the P effect on AM symbiosis was supported by the good correlation between mycorrhizal colonization and strigolactone exudation in split-root plants ( Figs 3 , 4 ). Supplementation with exogenous GR24, however, failed to restore AM symbiosis in HP-grown plants ( Fig. 5 ). These novel results rule out the proposed hypothesis that HP-grown plants are poorly colonized by AM fungi simply because they do not produce strigolactones ( Yoneyama et al. , 2007 b ; Lopez-Raez et al. , 2008 ). Although a role for strigolactones in the process is still possible and indeed likely, additional mechanisms remain to be discovered. This is consistent with the proposition that hyphal branching is a complex response involving several classes of compounds ( Nagahashi and Douds, 2007 ). The present observations do not imply, however, that the absence of additional stimulatory compounds in HP root exudates is the only explanation for the lack of root colonization under HP. An additional possibility is that the hormonal function of strigolactones (rather than their role as rhizospheric signals) is involved in the regulation of AM symbiosis, for example by influencing root development or the ability of root cells to accommodate AM fungi. This question was not addressed in the present study, and the concentration of GR24 necessary to restore the putative hormonal function(s) of strigolactones in roots is not known. Nevertheless, the hypothesis of a strigolactone requirement at the plant hormonal level is not supported by previous observations that strigolactone-deficient mutants could still be slightly colonized by AM fungi ( Gomez-Roldan et al. , 2008 ). As determined by hyphal branching bioassays, HP conditions do not seem to prevent the stimulation of the fungus by strigolactones. The combination of HP root exudates with GR24 results in an activity similar to that of LP root exudates ( Fig. 2 ). This suggests that hyphal branching and associated metabolic processes are restored in the supplementation experiment (HP+GR24) described in Fig. 5 . The observation that this is not sufficient to allow root colonization by the fungus or the formation of hyphopodia points towards an effect of HP on steps other than hyphal branching, possibly including the differentiation of hyphopodia."
} | 6,110 |
31313468 | null | s2 | 8,998 | {
"abstract": "Empirical knowledge of diversity-stability relationships is mostly based on the analysis of temporal variability. Variability, however, often depends on external factors that act as disturbances, which makes comparisons across systems difficult to interpret. Here, we show how variability can reveal inherent stability properties of ecological communities. This requires that we abandon one-dimensional representations, in which a single variability measurement is taken as a proxy for how stable a system is, and instead consider the whole set of variability values generated by all possible stochastic perturbations. Despite this complexity, in species-rich systems, a generic pattern emerges from community assembly, relating variability to the abundance of perturbed species. Strikingly, the contrasting contributions of different species abundance classes to variability, driven by different types of perturbations, can lead to opposite diversity-stability patterns. We conclude that a multidimensional perspective on variability helps reveal the dynamical richness of ecological systems and the underlying meaning of their stability patterns."
} | 287 |
19321003 | PMC2679711 | pmc | 9,000 | {
"abstract": "Background Metabolomics has emerged as a powerful tool in the quantitative identification of physiological and disease-induced biological states. Extracellular metabolome or metabolic profiling data, in particular, can provide an insightful view of intracellular physiological states in a noninvasive manner. Results We used an updated genome-scale metabolic network model of Saccharomyces cerevisiae, i MM904, to investigate how changes in the extracellular metabolome can be used to study systemic changes in intracellular metabolic states. The i MM904 metabolic network was reconstructed based on an existing genome-scale network, i ND750, and includes 904 genes and 1,412 reactions. The network model was first validated by comparing 2,888 in silico single-gene deletion strain growth phenotype predictions to published experimental data. Extracellular metabolome data measured in response to environmental and genetic perturbations of ammonium assimilation pathways was then integrated with the i MM904 network in the form of relative overflow secretion constraints and a flux sampling approach was used to characterize candidate flux distributions allowed by these constraints. Predicted intracellular flux changes were consistent with published measurements on intracellular metabolite levels and fluxes. Patterns of predicted intracellular flux changes could also be used to correctly identify the regions of the metabolic network that were perturbed. Conclusion Our results indicate that integrating quantitative extracellular metabolomic profiles in a constraint-based framework enables inferring changes in intracellular metabolic flux states. Similar methods could potentially be applied towards analyzing biofluid metabolome variations related to human physiological and disease states.",
"conclusion": "Conclusion The method presented in this study presents an approach to connecting intracellular flux states to metabolites that are excreted under various physiological conditions. We showed that well-curated genome-scale metabolic networks can be used to integrate and analyze quantitative EM data by systematically identifying altered intracellular pathways related to measured changes in the extracellular metabolome. We were able to identify statistically significant metabolic regions that were altered as a result of genetic ( gdh1/GD2 mutant) and environmental (excess ammonium and limited potassium) perturbations, and the predicted intracellular metabolic changes were consistent with previously published experimental data including measurements of intracellular metabolite levels and metabolic fluxes. Our reanalysis of previously published EM data on ammonium assimilation-related genetic and environmental perturbations also resulted in testable hypotheses about the role of threonine and folate pathways in mediating broad responses to changes in ammonium utilization. These studies also demonstrated that the sampling-based method can be readily applied when only partial secreted metabolite profiles (e.g. only amino acids) are available. With the emergence of metabolite biofluid biomarkers as a diagnostic tool in human disease [ 55 , 56 ] and the availability of genome-scale human metabolic networks [ 1 ], extensions of the present method would allow identifying potential pathway changes linked to these biomarkers. Employing such a method for studying yeast metabolism was possible as the metabolomic data was measured under controllable environmental conditions where the inputs and outputs of the system were defined. Measured metabolite biomarkers in a clinical setting, however, is far from a controlled environment with significant variations in genetic, nutritional, and environmental factors between different patients. While there are certainly limitations for clinical applications, the method introduced here is a progressive step towards applying genome-scale metabolic networks towards analyzing biofluid metabolome data as it 1) avoids the need to only study optimal metabolic states based on a predetermined objective function, 2) allows dealing with noisy experimental data through the sampling approach, and 3) enables analysis even with limited identification of metabolites in the data. The ability to establish potential connections between extracellular markers and intracellular pathways would be valuable in delineating the genetic and environmental factors associated with a particular disease.",
"discussion": "Results and discussion I. Reconstruction and validation of i MM904 network i MM904 network content A previously reconstructed S. cerevisiae network, i ND750, was used as the basis for the construction of the expanded i MM904 network. Prior to its presentation here, the i MM904 network content was the basis for a consensus jamboree network that was recently published but has not yet been adapted for FBA calculations [ 46 ]. The majority of i ND750 content was carried over and further expanded on to construct i MM904, which accounts for 904 genes, 1,228 individual metabolites, and 1,412 reactions of which 395 are transport reactions. Both the number of gene-associated reactions and the number of metabolites increased in i MM904 compared with the i ND750 network. Additional genes and reactions included in the network primarily expanded the lipid, transport, and carbohydrate subsystems. The lipid subsystem includes new genes and reactions involving the degradation of sphingolipids and glycerolipids. Sterol metabolism was also expanded to include the formation and degradation of steryl esters, the storage form of sterols. The majority of the new transport reactions were added to connect network gaps between intracellular compartments to enable the completion of known physiological functions. We also added a number of new secretion pathways based on experimentally observed secreted metabolites [ 31 ]. A number of gene-protein-reaction (GPR) relationships were modified to include additional gene products that are required to catalyze a reaction. For example, the protein compounds thioredoxin and ferricytochrome C were explicitly represented as compounds in i ND750 reactions, but the genes encoding these proteins were not associated with their corresponding GPRs. Other examples include glycogenin and NADPH cytochrome p450 reductases (CPRs), which are required in the assembly of glycogen and to sustain catalytic activity in cytochromes p450, respectively. These additional proteins were included in i MM904 as part of protein complexes to provide a more complete representation of the genes and their corresponding products necessary for a catalytic activity to occur. Major modifications to existing reactions were in cofactor biosynthesis, namely in quinone, beta-alanine, and riboflavin biosynthetic pathways. Reactions from previous S. cerevisiae networks associated with quinone, beta-alanine, and riboflavin biosynthetic pathways were essentially inferred from known reaction mechanisms based on reactions in previous network reconstructions of E. coli [ 2 , 47 ]. These pathways were manually reviewed based on current literature and subsequently replaced by reactions and metabolites specific to yeast. Additional changes in other subsystems were also made, such as changes to the compartmental location of a gene and its corresponding reaction(s), changes in reaction reversibility and cofactor specificity, and the elucidation of particular transport mechanisms. A comprehensive listing of i MM904 network contents as well as a detailed list of changes between i ND750 and i MM904 is included [see Additional file 1 ]. Predicting deletion growth phenotypes The updated genome-scale i MM904 metabolic network was validated by comparing in silico single-gene deletion predictions to in vivo results from a previous study used to analyze another S. cerevisiae metabolic model, i LL672 [ 3 ]. This network was constructed based on the i FF708 network [ 22 ], which was also the starting point for reconstructing the i ND750 network [ 2 ]. The experimental data used to validate the i LL672 model consisted of 3,360 single-gene knockout strain phenotypes evaluated under minimal media growth conditions with glucose, galactose, glycerol, and ethanol as sole carbon sources. Growth phenotypes for the i MM904 network were predicted using FBA [ 32 - 34 ], MoMA [ 35 ], and linear MoMA methods as described in Methods and subsequently compared to the experimental data (Table 1 ). Each deleted gene growth prediction comparison was classified as true lethal, true viable, false lethal, or false viable. The growth rate threshold for considering a prediction viable was chosen for each condition and method separately to optimize the tradeoff between true viable and false viable predictions (maximum Matthews correlation coefficient, see Methods). Since i MM904 has 212 more genes than i LL672 with experimental data, we also present results for the subset of i MM904 predictions with genes included in i LL672 (reduced i MM904 set). When the same gene sets are compared, i MM904 improves gene lethality predictions under glucose, galactose, and glycerol conditions over i LL672 somewhat, but is less accurate at predicting growth phenotypes under the ethanol condition. It should be noted that the i LL672 predictions were obtained directly from [ 3 ] and thus the growth rate threshold was not optimized similarly to i MM904 predictions. Overall, when viability cutoff is chosen as indicated above for each method separately, the three prediction methods (FBA, MOMA, and linear MOMA) perform similarly. While the full gene complement in i MM904 greatly increased the number of true viable predictions, the full model also made significantly more false viable predictions compared with reduced i MM904 and i LL672 predictions. However, it is important to note that 143 reactions involved in dead-end biosynthetic pathways were actually removed from i FF708 to build the i LL672 reconstruction [ 3 ]. These dead-ends are considered \"knowledge gaps\" in pathways that have not been fully characterized and, as a result, lead to false viable predictions when determining gene essentiality if the pathway is in fact required for growth under a certain condition [ 2 , 26 ]. As more of these pathways are elucidated and included in the model to fill in existing network gaps, we can expect false viable prediction rates to consequently decrease. Thus, while a larger network has a temporarily reduced capacity to accurately predict gene deletion phenotypes, it captures a more complete picture of currently known metabolic functions and provides a framework for network expansion as new pathways are elucidated [ 48 ]. II. Inferring intracellular perturbation states from metabolic profiles Aerobic and anaerobic gdh1/GDH2 mutant behavior The gdh1/GDH2 mutant strain was previously developed [ 49 , 50 ] in order to lower NADPH consumption in ammonia assimilation, which would in turn favor the NADPH-dependent fermentation of xylose. In this strain, the NADPH-dependent glutamate dehydrogenase, Gdh1 , was deleted and the NADH-dependent form of the enzyme, Gdh2 , was overexpressed. The net effect is to allow efficient assimilation of ammonia into glutamate using NADH instead of NADPH as a cofactor. While growth characteristics remained unaffected, relative quantities of secreted metabolites differed between the wild-type and mutant strain under aerobic and anaerobic conditions. We analyzed EM data for the gdh1/GDH2 and wild-type strains reported in [ 31 ] under aerobic and anaerobic conditions separately using both FBA optimization and sampling-based approaches as described in Methods. 43 measured extracellular and intracellular metabolites from the original dataset [ 31 ], primarily of central carbon and amino acid metabolism, were explicitly represented in the i MM904 network [see Additional file 4 ]. Extracellular metabolite levels were used to formulate secretion constraints and differential intracellular metabolites were used to compare and validate the intracellular flux predictions. Perturbed reactions from the FBA results were determined by calculating relative flux changes, and reaction Z -scores were calculated from the sampling analysis to quantify flux changes between the mutant and wild-type strains, with Z reaction > 1.96 corresponding to a two-tailed p -value < 0.05 and considered to be significantly perturbed [see Additional file 4 ]. To validate the predicted results, reaction flux changes from both FBA and sampling methods were compared to differential intracellular metabolite level data measured from the same study. Intracellular metabolites involved in highly perturbed reactions (i.e. reactants and products) predicted from FBA and sampling analyses were identified and compared to metabolites that were experimentally identified as significantly changed ( p < 0.05) between mutant and wild-type. Statistical measures of recall, accuracy, and precision were calculated and represent the predictive sensitivity, exactness, and reproducibility respectively. From the sampling analysis, a considerably larger number of significantly perturbed reactions are predicted in the anaerobic case (505 reactions, or 70.7% of active reactions) than in aerobic (394 reactions, or 49.8% of active reactions). The top percentile of FBA flux changes equivalent to the percentage of significantly perturbed sampling reactions were compared to the intracellular data. Results from both analyses are summarized in Table 2 . Sampling predictions were considerably higher in recall than FBA predictions for both conditions, with respective ranges of 0.83–1 compared to 0.48–0.96. Accuracy was also higher in sampling predictions; however, precision was slightly better in the FBA predictions as expected due to the smaller number of predicted changes. Overall, the sampling predictions of perturbed intracellular metabolites are strongly consistent with the experimental data and significantly outperforms that of FBA optimization predictions in accurately predicting differential metabolites involved in perturbed intracellular fluxes. Table 2 Statistical comparison of the differential intracellular metabolite data set ( p < 0.05) with metabolites involved in perturbed reactions predicted by FBA optimization and sampling analyses for aerobic and anaerobic gdh1/GDH2 mutant. Aerobic Anaerobic Overall FBA Sampling FBA Sampling FBA Sampling Recall 0.48 0.83 0.96 1.00 0.71 0.91 Accuracy 0.55 0.62 0.64 0.64 0.60 0.63 Precision 0.78 0.69 0.64 0.63 0.68 0.66 Overall statistics indicate combined results of both conditions. Perturbation subnetworks can be drawn to visualize predicted significantly perturbed intracellular reactions and illustrate their connection to the observed secreted metabolites in the aerobic and anaerobic gdh1/GDH2 mutants. Figure 3 shows an example of a simplified aerobic perturbation subnetwork consisting primarily of proximal pathways connected directly to a subset of major secreted metabolites (glutamate, proline, D-lactate, and 2-hydroxybuturate). Figure 4 displays anaerobic reactions with Z-scores of similar magnitude to the perturbed reactions in Figure 3 . The same subset of metabolites is also present in the larger anaerobic perturbation network and indicates that the NADPH/NADH balance perturbation induced by the gdh1/GDH2 manipulation has widespread effects beyond just altering glutamate metabolism anaerobically. Interestingly, it is clear that the majority of the secreted metabolite pathways involve connected perturbed reactions that broadly converge on glutamate. Note that Figures 3 and 4 only show the subnetworks that consisted of two or more connected reactions – for a number of secreted metabolites no contiguous perturbed pathway could be identified by the sampling approach. This indicates that the secreted metabolite pattern alone is not sufficient to determine which specific production and secretion pathways are used by the cell for these metabolites. Figure 3 Perturbation reaction subnetwork of gdh1/GDH2 mutant under aerobic conditions . The network illustrates a simplified subset of highly perturbed reactions connected to aerobically-secreted metabolites predicted from the sampling analysis of the gdh1/GDH2 mutant strain. The major secreted metabolites (glutamate, proline, D-lactate, and 2-hydroxybuturate) were also detected in the anaerobic condition. Metabolite abbreviations are found in Additional file 1 . Figure 4 Perturbation reaction subnetwork of gdh1/GDH2 mutant under anaerobic conditions . Subnetwork illustrates the highly perturbed anaerobic reactions of similar Z reaction magnitude to the reactions in Figure 3. A significantly larger number of reactions indicates mutant metabolic effects are more widespread in the anaerobic environment. The network shows that perturbed pathways converge on glutamate, the main site in which the gdh1/GDH2 modification was introduced, which suggests that the direct genetic perturbation effects are amplified under this environment. Metabolite abbreviations are found in Additional file 1 . To further highlight metabolic regions that have been systemically affected by the gdh1/GDH2 modification, reporter metabolite and subsystem methods [ 30 ] were used to summarize reaction scores around specific metabolites and in specific metabolic subsystems. The top ten significant scores for metabolites/subsystems associated with more than three reactions are summarized in Tables 3 (aerobic) and 4 (anaerobic), with Z > 1.64 corresponding to p < 0.05 for a one-tailed distribution. Full data for all reactions, reporter metabolites, and reporter subsystems is included [see Additional file 4 ]. Table 3 List of the top ten significant reporter metabolite and subsystem scores for the gdh1/GDH2 vs. wild type comparison in aerobic conditions. Reporter metabolite Z-score No of reactions* L-proline [c] 2.71 4 Carbon dioxide [m] 2.51 15 Proton [m] 2.19 51 Glyceraldehyde 3-phosphate [c] 1.93 7 Ubiquinone-6 [m] 1.82 5 Ubiquinol-6 [m] 1.82 5 Ribulose-5-phosphate [c] 1.80 4 Uracil [c] 1.74 4 L-homoserine [c] 1.72 4 Alpha-ketoglutarate [m] 1.71 8 Reporter subsystem Z-score No of reactions Citric Acid Cycle 4.58 7 Pentose Phosphate Pathway 3.29 12 Glycine and Serine Metabolism 2.69 17 Alanine and Aspartate Metabolism 2.65 6 Oxidative Phosphorylation 1.79 8 Thiamine Metabolism 1.54 8 Arginine and Proline Metabolism 1.44 20 Other Amino Acid Metabolism 1.28 5 Glycolysis/Gluconeogenesis 0.58 14 Anaplerotic reactions 0.19 9 *Number of reactions categorized in a subsystem or found to be neighboring each metabolite Table 4 List of top ten significant reporter metabolite and subsystem scores for the gdh1/GDH2 vs. wild type comparison in anaerobic conditions. Reporter metabolite Z-score No of reactions Glutamate [c] 4.52 35 Aspartate [c] 3.21 11 Alpha-ketoglutarate [c] 2.66 17 Glycine [c] 2.65 7 Pyruvate [m] 2.56 7 Ribulose-5-phosphate [c] 2.43 4 Threonine [c] 2.28 6 10-formyltetrahydrofolate [c] 2.27 5 Fumarate [c] 2.27 5 L-proline [c] 2.04 4 Reporter subsystem Z-score No of reactions Valine, Leucine, and Isoleucine Metabolism 3.97 15 Tyrosine, Tryptophan, and Phenylalanine Metabolism 3.39 23 Pentose Phosphate Pathway 3.29 11 Purine and Pyrimidine Biosynthesis 3.08 40 Arginine and Proline Metabolism 2.96 19 Threonine and Lysine Metabolism 2.74 14 NAD Biosynthesis 2.66 7 Alanine and Aspartate Metabolism 2.65 6 Histidine Metabolism 2.24 10 Cysteine Metabolism 1.85 10 Perturbations under aerobic conditions largely consisted of pathways involved in mediating the NADH and NADPH balance. Among the highest scoring aerobic subsystems are TCA cycle and pentose phosphate pathway – key pathways directly involved in the generation of NADH and NADPH. Reporter metabolites involved in these subsystems – glyceraldehyde-3-phosphate, ribulose-5-phosphate, and alpha-ketoglutarate – were also identified. These results are consistent with flux and enzyme activity measurements of the gdh1/GDH2 strain under aerobic conditions [ 32 ], which reported significant reduction in the pentose phosphate pathway flux with concomitant changes in other central metabolic pathways. Levels of several TCA cycle intermediates (e.g. fumarate, succinate, malate) were also elevated in the gdh1/GDH2 mutant according to the differential intracellular metabolite data. Altered energy metabolism, as indicated by reporter metabolites (i.e. ubiquinone-6, ubiquinol-6, mitochondrial proton) and subsystem (oxidative phosphorylation), is certainly feasible as NADH is a primary reducing agent for ATP production. Pentose phosphate pathway and NAD biosynthesis also appears among the most perturbed anaerobic subsystems, further suggesting perturbed cofactor balance as a common, dominant effect under both conditions. Glutamate dehydrogenase is a critical enzyme of amino acid biosynthesis as it acts as the entry point for ammonium assimilation via glutamate. Consequently, metabolic subsystems involved in amino acid biosynthesis were broadly perturbed as a result of the gdh1/GDH2 modification in both aerobic and anaerobic conditions. For example, the proline biosynthesis pathway that uses glutamate as a precursor was significantly perturbed in both conditions, as supported by significantly changed intracellular and extracellular levels. There were differences, however, in that more amino acid related subsystems were significantly affected in the anaerobic case (Table 4 ), further highlighting that altered ammonium assimilation in the mutant has a more widespread effect under anaerobic conditions. This effect is especially pronounced for threonine and nucleotide metabolism, which were predicted to be significantly perturbed only in anaerobic conditions. Intracellular threonine levels were amongst the most significantly reduced relative to other differential intracellular metabolites in the anaerobically grown gdh1/GDH2 strain (see [ 31 ] and Additional file 4 ), and the relationship between threonine and nucleotide biosynthesis is further supported by threonine's recently discovered role as a key precursor in yeast nucleotide biosynthesis [ 51 ]. Other key anaerobic reporter metabolites are glycine and 10-formyltetrahydrofolate, both of which are involved in the cytosolic folate cycle (one-carbon metabolism). Folate is intimately linked to biosynthetic pathways of glycine (with threonine as its precursor) and purines by mediating one-carbon reaction transfers necessary in their metabolism and is a key cofactor in cellular growth [ 52 ]. Thus, the anaerobic perturbations identified in the analysis emphasize the close relationship between threonine, folate, and nucleotide metabolic pathways as well as their potential connection to perturbed ammonium assimilation processes. Interestingly, this association has been previously demonstrated at the transcriptional level as yeast ammonium assimilation (via glutamine synthesis) was found to be co-regulated with genes involved in glycine, folate, and purine synthesis [ 53 ]. In summary, the overall differences in predicted gdh1/GDH2 mutant behavior under aerobic and anaerobic conditions show that changes in flux states directly related to modified ammonium assimilation pathway are amplified anaerobically whereas the indirect effects through NADH/NADPH balance are more significant aerobically. Perturbed metabolic regions under aerobic conditions were predominantly in central metabolic pathways involved in responding to the changed NADH/NADPH demand and did not necessarily emphasize that glutamate dehydrogenase was the site of the genetic modification. The majority of affected anaerobic pathways were involved directly in modified ammonium assimilation as evidenced by 1) significantly perturbed amino acid subsystems, 2) a broad perturbation subnetwork converging on glutamate (Figure 4 ), and 3) glutamate as the most significant reporter metabolite (Table 4 ). Potassium-limited and excess ammonium environments A recent study reported that potassium limitation resulted in significant growth retardation effect in yeast due to excess ammonium uptake when ammonium was provided as the sole nitrogen source [ 33 ]. The proposed mechanism for this effect was that ammonium could to be freely transported through potassium channels when potassium concentrations were low in the media environment, thereby resulting in excess ammonium uptake [ 33 ]. As a result, yeast incurred a significant metabolic cost in assimilating ammonia to glutamate and secreting significant amounts of glutamate and other amino acids in potassium-limited conditions as a means to detoxify the excess ammonium. A similar effect was observed when yeast was grown with no potassium limitation, but with excess ammonia in the environment. While the observed effect of both environments (low potassium or excess ammonia) was similar, quantitatively unique amino acid secretion profiles suggested that internal metabolic states in these conditions are potentially different. In order to elucidate the differences in internal metabolic states, we utilized the i MM904 model and the EM profile analysis method to analyze amino acid secretion profiles for a range of low potassium and high ammonia conditions reported in [ 33 ]. As before, we utilized amino acid secretion patterns as constraints to the i MM904 model, sampled the allowable solution space, computed reaction Z -scores for changes from a reference condition (normal potassium and ammonia), and finally summarized the resulting changes using reporter metabolites. Figure 5 shows a clustering of the most significant reporter metabolites (Z ≥ 1.96 in any of the four conditions studied) obtained from this analysis across the four conditions studied. Interestingly, the potassium-limited environment perturbed only a subset of the significant reporter metabolites identified in the high ammonia environments. Both low potassium environments shared a consistent pattern of highly perturbed amino acids and related precursor biosynthesis metabolites (e.g. pyruvate, PRPP, alpha-ketoglutarate) with high ammonium environments. The amino acid perturbation pattern (indicated by red labels in Figure 5 ) was present in the ammonium-toxic environments, although the pattern was slightly weaker for the lower ammonium concentration. Nevertheless, the results clearly indicate that a similar ammonium detoxifying mechanism that primarily perturbs pathways directly related to amino acid metabolism exists under both types of media conditions. Figure 5 Clustergram of top reporter metabolites (i.e. in yellow) in ammonium-toxic and potassium-limited conditions . Amino acid perturbation patterns (shown in red) were shown to be consistently scored across conditions, indicating that potassium-limited environments K1 (lowest concentration) and K2 (low concentration) elicited a similar ammonium detoxification response as ammonium-toxic environments N1 (high concentration) and N2 (highest concentration). Metabolites associated with folate metabolism (highlighted in green) are also highly perturbed in ammonium-toxic conditions. Metabolite abbreviations are found in Additional file 1 . In addition to perturbed amino acids, a secondary effect notably appears at high ammonia levels in which metabolic regions related to folate metabolism are significantly affected. As highlighted in green in Figure 3 , we predicted significantly perturbed key metabolites involved in the cytosolic folate cycle. These include tetrahydrofolate derivatives and other metabolites connected to the folate pathway, namely glycine and the methionine-derived methylation cofactors S-adenosylmethionine and S-adenosylhomocysteine. Additionally, threonine was identified to be a key perturbed metabolite in excess ammonium conditions. These results further illustrate the close connection between threonine biosynthesis, folate metabolism involving glycine derived from its threonine precursor, and nucleotide biosynthesis [ 51 ] that was discussed in conjunction with the gdh1/GDH2 strain data. Taken together with the anaerobic gdh1/GDH2 data, the results consistently suggest highly perturbed threonine and folate metabolism when amino acid-related pathways are broadly affected. In both ammonium-toxic and potassium-limited environments, impaired cellular growth was observed, which can be attributed to high energetic costs of increased ammonium assimilation to synthesize and excrete amino acids. However, under high ammonium environments, reporter metabolites related to threonine and folate metabolism indicated that their perturbation, and thus purine supply, may be an additional factor in decreasing cellular viability as there is a direct relationship between intracellular folate levels and growth rate [ 54 ]. Based on these results, we concluded that while potassium-limited growth in yeast indeed shares physiological features with growth in ammonium excess, its effects are not as detrimental as actual ammonium excess. The effects on proximal amino acid metabolic pathways are similar in both environments as indicated by the secretion of the majority of amino acids. However, when our method was applied to analyze the physiological basis behind differences in secretion profiles between low potassium and high ammonium conditions, ammonium excess was predicted to likely disrupt physiological ammonium assimilation processes, which in turn potentially impacts folate metabolism and associated cellular growth."
} | 7,413 |
24604640 | PMC3945496 | pmc | 9,005 | {
"abstract": "Clostridium sp. strain Ade.TY is potentially a new biohydrogen-producing species isolated from landfill leachate sludge. Here we present the assembly and annotation of its genome, which may provide further insights into its gene interactions for efficient biohydrogen production."
} | 70 |
36344837 | PMC9675646 | pmc | 9,006 | {
"abstract": "Understanding the extent to which species’ traits mediate patterns of community assembly is key to predict the effect of natural and anthropogenic disturbances on ecosystem functioning. Here, we apply a trait-based community assembly framework to understand how four different habitat configurations (kelp forests, Sargassum spp. beds, hard corals, and turfs) shape the trophic and energetic dynamics of reef fish assemblages in a tropical–temperate transition zone. Specifically, we tested (i) the degree of trait divergence and convergence in each habitat, (ii) which traits explained variation in species’ abundances, and (iii) differences in standing biomass (kg ha −1 ), secondary productivity (kg ha −1 day −1 ) and turnover (% day −1 ). Fish assemblages in coral and kelp habitats displayed greater evidence of trait convergence, while turf and Sargassum spp. habitats displayed a higher degree of trait divergence, a pattern that was mostly driven by traits related to resource use and thermal affinity. This filtering effect had an imprint on the trophic and energetic dynamics of reef fishes, with turf habitats supporting higher fish biomass and productivity. However, these gains were strongly dependent on trophic guild, with herbivores/detritivores disproportionately contributing to among-habitat differences. Despite these perceived overall gains, turnover was decoupled for fishes that act as conduit of energy to higher trophic levels (i.e. microinvertivores), with coral habitats displaying higher rates of fish biomass replenishment than turf despite their lower productivity. This has important implications for biodiversity conservation and fisheries management, questioning the long-term sustainability of ecological processes and fisheries yields in increasingly altered marine habitats. Supplementary Information The online version contains supplementary material available at 10.1007/s00442-022-05278-6.",
"introduction": "Introduction Understanding the role of deterministic and stochastic processes in community assembly is a central goal in ecology, particularly in the Anthropocene, where rapid changes to natural ecosystems challenge current management and conservation paradigms (Pecl et al. 2017 ; Bonebrake et al. 2018 ). Reef ecosystems are at the forefront of this biotic change, with recurrent coral bleaching events causing widespread coral mortality in tropical regions (Hughes et al. 2018 ; Dietzel et al. 2021 ). Likewise, gradual warming and extreme marine heatwaves, coupled with altered biotic interactions, are causing the collapse of kelp forests at the warm-edge of their range (Vergés et al. 2014 , 2016 ; Wernberg et al. 2016 ). These foundational species provide the three-dimensional habitat structure that underpins their influence on biodiversity and associated ecosystem services such as food provision, coastal protection, and nutrient cycling (Jones et al. 1994 ; Romero et al. 2015 ). Across the globe, the replacement of these foundational species by structurally simple, opportunistic, fast-growing turf algae (Filbee-Dexter and Wernberg, 2018 ; Pessarrodona et al. 2021a , b , c ) or alternative canopy-forming foundation species (e.g. Sargassum spp.) (Tanaka et al. 2012 ; Terazono et al. 2012 ) can fundamentally alter the structure of the associated faunal assemblages (e.g. fishes and invertebrates) (e.g. Stuart-Smith et al. 2018 ). However, their consequences for ecosystem functioning remains poorly resolved. The ecosystem functions supported by novel habitat configurations is determined by the extent to which functional traits (i.e. morphological, physiological, or behavioural features) that increase the fitness of species in each habitat are filtered from the regional pool of species (Mcgill et al. 2006 ). Community assembly rules shape the occurrence and relative abundance of species coexisting locally, which is in part mediated by a trade-off between ecological constraints and opportunities provided by local abiotic (e.g. temperature, nutrients, primary productivity, wave exposure) (Bejarano et al. 2017 ; McLean et al. 2021 ; Bosch et al. 2021b ) and biotic (e.g. habitat and resource availability, biotic interactions) conditions (Chase et al. 2009 ; Yeager et al. 2017 ). Proximal human pressures can also shape the number and identity of reef fish traits at local scales (D’agata et al. 2014 ), with extractive human activities (e.g. fishing) selectively impacting areas of the trait space (e.g. removal of large-bodied fishes) (Bosch et al. 2021a ). Alternatively, local species coexistence can also be determined by stochastic processes (e.g. birth, death, immigration and emigration of individuals, i.e. ‘ecological drift’), irrespective of species’ functional identity (i.e. ‘neutral theory’) (Hubbell 2001 ). In reef fishes, this can be exacerbated by their generally large dispersal capacities, that enable them to colonize distant sites and compete for the available living space (Sale 1978 ). Although these community assembly processes are not necessarily mutually exclusive (Vellend et al. 2014 ; Bosch et al. 2021b ), the prevalence of niche-based vs. neutral mechanisms is likely mediated by the arrangement of habitats across spatial scales (Yeager et al. 2011 ), and the degree to which species from the regional pool are habitat specialists or generalists (Stuart-Smith et al. 2021 ). Effective management of transitioning reefs in the Anthropocene requires an understanding on how changes in the functional trait structure of ecological assemblages scales-up to shape ecosystem-level processes that underpin trophic and energetic dynamics (Bellwood et al. 2018 ; Vergés et al. 2019 ). This is paramount in the case of shifting habitat structure, as these changes can alter the composition of basal trophic levels that underpin the nutritional resources available to primary (Russ et al. 2015 ; Pessarrodona et al. 2021a , b , c ) and secondary consumers (Taylor 1998 ; Fraser et al. 2020a , b ; Fraser et al. 2021 ). Furthermore, evidence from coral reefs suggest that changes in ecosystem functions (e.g. productivity and turnover) that underpin the flow of energy and materials might remain undetected using static metrics such as species richness, abundance, and biomass (Morais and Bellwood 2019 ; Morais et al. 2020 ; Tebbett et al. 2021 ). Traditional approaches to estimate fish productivity rely on parameter estimation of trophodynamics (e.g. Christensen and Pauly 1992 ), limiting its use for high diversity systems for which these parameters are unknown for most species. The development of novel frameworks to estimate the productivity of reef fishes from survey and functional trait data have overcome this limitation (Morais and Bellwood 2020 ). However, these have rarely been quantified outside coral reef environments (but see Pessarrodona et al. 2021a , b , c ), hindering generalizations about how habitat reconfigurations might impair the dynamic processes that sustain productive reef ecosystems. Here, we took advantage of a tropical–temperate biogeographic transition zone characterized by the coexistence of a diverse array of habitats of varying structural complexity and thermal affinity. These habitats included reef configurations that have been predicted to arise in temperate reefs under future warming scenarios, as cool-affinity kelp forests ( Ecklonia radiata ) are potentially replaced by three biogenic habitat end-points: reef-building corals ( Acropora spp.), mixed warm and cool Sargassum spp. beds, and turfs (Vergés et al. 2019 ). These habitat reorganizations are expected to shifts the ecosystem functions and services provided by temperate reefs, however, these have rarely been empirically quantified. In this study, we investigated (i) whether fish species coexisting in each habitat converge, or diverge, in their functional traits, (ii) which traits explain variation in species’ abundances across habitats, and (iii) how trait-based habitat filtering scales-up to shape energetic dynamics, measured via three metrics of energy storage and flow: standing biomass (kg ha −1 ), productivity (the amount of fish biomass produced per day, kg ha −1 day −1 ), and turnover (the proportional flow of energy in the system, as being incorporated or released, % day −1 ) (Morais et al. 2020 ). To elucidate how habitat reconfigurations might shift the trophic pathways that underpin fish productivity, we further partitioned these metrics for trophic guilds (herbivores/detritivores, microinvertivores, sessile invertivores, planktivores, and higher carnivores) that underpin trophic interactions and energy transfer in reef fishes (Parravicini et al. 2020 ).",
"discussion": "Discussion Our study used a tropical–temperate biogeographic transition zone characterized by seascape-scale patches of coexisting reef-building corals ( Acropora spp.), kelp forests ( Ecklonia radiata) , Sargassum spp. beds, and turf to test the potential trophic and energetic consequences of predicted biogenic habitat reconfigurations under future warming scenarios (Vergés et al. 2019 ). We showed that reef fish species co-occurring in coral and kelp habitats displayed greater signals of trait convergence, highlighting a directional selection towards functional strategies that maximizes the use of the available niche space provided by these habitats (Winemiller et al. 2015 ). In contrast, species co-occurring in turf and Sargassum spp. habitats displayed greater signals of trait divergence, potentially signalling ecological opportunities minimizing niche overlap and thus enhancing species’ coexistence (Mcgill et al. 2006 ). The local filtering of species’ traits had an imprint on the trophic and energetic dynamics of reef fish assemblages, with remarkably high secondary productivity in turf and mixed habitats compared to Sargassum spp., kelp, and coral habitats. Despite these perceived gains in fish biomass production, turnover (i.e. the rate of biomass flow) was often decoupled for most trophic guilds, particularly for fishes that act as conduits of energy from primary producers to higher trophic levels (i.e. microinvertivores). Higher turnover rates in coral compared to turf habitats, despite their substantially lower productivity, have important implications for conservation and fisheries management, questioning the ability of structurally degraded reef configurations to maintain fish productivity over longer timescales (Robinson et al. 2019 ; Morais et al. 2020 ). The higher proportion of functionally convergent assemblages found in coral and kelp habitats might be related to their higher physical structural complexity. This complexity can offer increased protection against predation to species with particular sizes (e.g. small-bodied) or behaviours (e.g. cryptic) (Graham and Nash 2013 ; Rogers et al. 2018a , b ), while limiting the accessibility to nutritional resources to species with specialised diets (Beger, 2021 ; Stuart-Smith et al. 2021 ). For instance, in our study region, the abundance of highly specialised corallivorous fishes (family Chaetodontidae) displayed a positive association with the cover of reef-building corals, supporting previous observations in coral reefs (Pratchett et al. 2011 ), and highlighting their vulnerability to coral mortality (Graham et al. 2011 ), irrespective of the thermal environment (Stuart-Smith et al. 2018 ). Similarly, many temperate reef fish species in the region are habitat specialists, dwelling within vegetated habitats to minimize predation risk (Tuya et al. 2009 ). Habitat selection by specialist species can thus mediate the range-expansion success of tropical fishes into temperate regions (Beck et al. 2017 ), as exemplified by the close association between warm-affinity species and the cover of hard coral and turf habitats. This highlights the importance of local biotic factors in predicting climate-driven species redistributions, questioning model approaches that solely rely on regional climatic trends (Fernandes et al. 2020 ). A plausible mechanism explaining the differences in thermal affinity found between canopy (kelp and Sargassum spp.) and non-canopy (turf) habitats might be related to the availability of nutritional resources exploited by herbivores. This is particularly true for those functional groups exploiting the resources contained within turfs (e.g. detritus, algae, and cyanobacteria), as these can become more available following the loss of foundation species and expansion of algal turfs (Gilmour et al. 2013 ; Pessarrodona et al. 2021a , b , c ). The higher turnover rates (Bonaldo and Bellwood 2011 ) and lower chemical and physical defences (Littler et al. 1983 ) of the algae within turfs might further enhance the ecological opportunities provided by this habitat, compared to canopy-forming species, such as kelps, that are generally consumed by a few specialised families (e.g. Kyphosidae, Knudsen et al. 2019 ). In contrast, the resources contained within turfs are typically exploited by a diverse suite of tropical herbivorous fishes (e.g. algal farmers, croppers, detritus suckers, scrapers) (Vergés et al. 2014 ), which have evolved morphological and behavioural adaptations to minimize competition for resources across spatial and temporal axes (Siqueira et al. 2019 ). An emerging question in the Anthropocene is how the loss of foundational species and their replacement by structurally simplified habitats (turf here) or alternative foundation species ( Sargassum spp. here) might shifts the trophic and energetic pathways that underpin ecosystem functions and the delivery of food and other services to human societies (Bellwood et al. 2018 ; Vergés et al. 2019 ). Our results indicate that some pathways, particularly those that rely on the availability of basal tropic resources (i.e. herbivores/detritivores), might be enhanced, at least, over short timescales. This effect was particularly strong in the case of scraping parrotfishes (Scaridae), which disproportionately accounted for the abundance, biomass, and productivity of herbivores/detritivores in turf habitats (Fig. S6). These fishes are highly specialized in digesting and assimilating protein-rich autotrophic microorganisms (Clements et al. 2017 ), that can rapidly grow on dead coral or bare reef following disturbances (Diaz-Pulido and McCook 2002 ). In our study region, turfs supported remarkably high productivity of herbivores/detritivores (0.71 ± 0.24 kg ha −1 day −1 ). Of this, ~ 98% (0.70 kg ha −1 day −1 ) was supported by scraping parrotfishes, attaining even higher productivity to that reported for some tropical reefs that have been severely disrupted by environmental disturbances and the rise of turfs (~ 0.40 kg ha-1 day-1, Morais et al. 2020 ). Together with recent evidence from coral reef ecosystems globally (Taylor et al. 2019 ), these results point towards a bottom-up control of herbivores exploiting turf-driven pathways, challenging their classic view as agents of reef resilience through top-down control on benthic algae (Russ et al. 2015 ). Parrotfishes, thus, appear as climate winners over the short-term, albeit local scale factors such as sedimentation could offset the nutritional benefits provided by increased turf availability (Tebbett et al. 2021 ; Pessarrodona et al. 2021a , b , c ). Microinvertivorous fishes, another trophic guild that act as an important conduit of energy to higher trophic levels (Taylor 1998 ), displayed relatively comparable biomass and productivity in turf, mixed, Sargassum spp., and kelp habitats, while these metrics were almost negligible in coral habitats. The structural complexity of fucoids (e.g. Sargassum spp.) and laminariales (e.g. the kelp Ecklonia radiata ), provide microhabitat refugees to small motile invertebrates living as epifauna (e.g. amphipods, isopods) (Edgar 1983 ). Although, in theory, the flattening of reef structural complexity should decrease the amount of microhabitat refugees provided to small motile invertebrates (Pessarrodona et al. 2021a , b , c ), turfs growing on dead coral have been shown to maintain even higher epifaunal productivity than healthy live coral (e.g. Taylor 1998 ; Fraser et al. 2021 ). This high epifaunal productivity in turf habitats can be underpinned by bottom-up (e.g. higher availability of detrital and algal sources) and top-down (i.e. scale-dependence changes in the availability of microhabitat refugees) mechanisms (Fraser et al. 2021 ). The latter is reflected in the epifaunal composition of each habitat, with turfs being majorly composed of small-sized taxa with high turnover rates (mainly harpacticoid copepods) (Fraser et al. 2020b ). In contrast, colonization of corals by smaller sized epifauna can be deterred by chemical and physical defence strategies (Sammarco et al. 1983 ), as well as potential heterotrophy of coral polyps (Goreau et al. 1971 ), with larger, slower paced, taxa (mainly decapods) inhabiting this habitat (Fraser et al. 2020b ). Despite the overall gains in fish biomass and productivity in turf and mixed habitats, turnover (i.e. the rate of biomass flow) generally displayed contrasting patterns. Part of these among-habitat differences might stem from the different thermal affinity of the composite assemblage, as tropical species typically have faster growth rates, early maturation, and shorter lifespans than temperate ones (Beukhof et al. 2019 ). However, for some trophic guilds, turf and coral habitats displayed markedly contrasting patterns, despite both containing a higher proportion of tropical species. For instance, microinvertivores displayed remarkably higher turnover rates in coral habitats, despite their biomass and productivity being substantially larger in turf. The higher productivity, at the expense of lower turnover, indicates potential biomass storage effects in turf habitats for these trophic guilds, whereby a potential short-term increase in the accessibility to preys due to degraded reef structural complexity can drive energetic shifts towards biomass accumulation (Morais et al. 2020 ). In contrast, the complex branching structure of Acropora spp. corals can provide increased protection against predation for early life history stages (Rogers et al. 2018a , b ), enhancing their survival and replenishing stock biomass as adult fishes perish (Rogers et al. 2018a , b ). This was reflected in our study by the generally smaller size of fishes found in coral habitats for the family Labridae, whose constituent species are major contributors to the microinvertivorous trophic pathways (Fig. S5). Our study presents a number of caveats that warrant caution when transferring these results to other reef systems. First, it must be noted that habitats at the study area were sometimes interspersed within scales of 100 s to 1000 m (i.e. at the site-scale). Thus, it is plausible that transects with dominance of one habitat type, still recorded a proportion of species inhabiting nearby habitats due to the generally large home range sizes and mobility of adult demersal fishes (Nash et al. 2015 ). This limitation also entails pseudo-replication among some habitat level comparisons, potentially biasing parameter estimates and inferences of statistical significance (Davies and Gray 2015 ), particularly for those trophic guilds that displayed marginally significant or non-significant results. Finally, as any sampling method, stereo-DOVs are subjected to varying detectability of fish species among habitats (Holmes et al. 2013 ). For instance, small-bodied species with low mobility and cryptic behaviour could have been undersampled in vegetated habitats (kelp and Sargassum spp.) (French et al. 2021 ), as well as in coral habitats due to the complex morphology of the staghorn Acropora spp. corals, compared to turf habitats. This methodological bias could have potentially influenced the taxonomic and functional characterization of fish assemblages (Esmaeili et al. 2021 ), and hence the degree to which we were able to detect patterns of functional divergence and convergence in each habitat. We must note then, that the patterns reported here apply at least to mobile conspicuous species, which are generally observed moving both within and above fronds of vegetated habitats (kelp and Sargassum spp.), as well as the complex branching structure of Acropora spp. corals. Future studies should use a combination of methods to capture both conspicuous and cryptic species to discern the generality of the assembly rules reported here, particularly considering the fine-scale partitioning of available micro-niches by cryptobenthic fish species (Brandl et al. 2018 ). Our study provides valuable insights on the deterministic processes involved in the assembly of fish communities across varying habitat configurations in a temperate-tropical transition zone, and signal potential predictable shifts in the delivery of key ecosystem functions (standing stock biomass, productivity, and turnover) that mediate reef health and the provision of food to human societies. Future studies should seek to decouple the direct and indirect links and effects between changes in environment, habitat, and aspects of biodiversity that scale-up to shape these three important ecosystem functions in rapidly changing tropical-temperate biogeographic transition zones. This is particularly important in the Anthropocene era, where increased frequency and intensity of climate disturbance events are likely to homogenise seascapes over regional and global scales (Dietzel et al. 2021 ; Pessarrodona et al. 2021a , b , c ), disrupting the delivery of key ecosystem functions (Duffy et al. 2016 ; Maureaud et al. 2019 ). Thus, incorporating trends in local habitats changes with regional changes in ocean climate (e.g. temperature and productivity) appears critical to improve climate predictions on biodiversity-ecosystem functioning relationships (Fernandes et al. 2020 ). Given the broad applicability of functional traits, this will help to identify a range of winners and losers beyond biogeographic boundaries, and adapt management and conservation efforts that maximize the delivery of services to human societies whilst minimizing biodiversity loss."
} | 5,602 |
38205316 | PMC10776987 | pmc | 9,007 | {
"abstract": "Polymer nanofiber in nanofibrous membrane produced by electrospinning process can be employed in various fields such as medical engineering, environmental engineering, biotechnology, energy, tissue scaffolds, and protective clothing. In these applications, the mechanical properties of the nanofibrous membrane should be studied to get long-life durability. In the current study, nanofibers are obtained from electrospinning of polyacrylonitrile (PAN) solution in Dimethylformamide (DFM) solvent. Nanofibers are produced with disc, cylinder, wire drum, parallel bars and polygon collectors and their mechanical properties are examined and compared. For this study, a tensile testing machine with special jaws was applied. According to the Scanning Electron Microscope (SEM) images, the average diameter of the produced nanofibers ranges from 300 to 340 nm. In addition, nanofiber layers have a thickness of 0.03 mm. They were cut in the 10 × 25 mm 2 size; then, the tensile test was performed. Results show that produced nanofiber layers by rotating cylinder collector have the highest ultimate strength while the disk collector results in the highest Young's modulus in produced samples.",
"conclusion": "4 Conclusion In this research, nano-fibers were obtained by electrospinning of 13 % PAN solution in DMF solvent, manufactured in the form of a nanofiber layer with the disc (plate), cylinder, wire drum, parallel bars, and polygon collectors, were evaluated and compared in terms of their mechanical properties. According to the results of the tensile test, the cylinder rotary collector has higher ultimate stress than other collectors. However, in terms of Young's modulus, it makes a fixed disc collector of nano-fibers with the highest Young's modulus. According to the electron microscope images, the wire drum collector can create the best parallel arrangement.",
"introduction": "1 Introduction In the last few decades, electrospinning has been considered an efficient method for the production of nanofibers, and the simplicity and ease of the electrospinning method have led to many creativities and innovations in its initial process. Previous researches have shown that electrospinning can produce various organic, ceramic, and fiber composite materials with controllable diameters. In addition, electrospinning has been developed for the direct production of nanofibers with a hollow core-shell structure. Scientists have found in their research that it is necessary to study the relationship between the secondary structure of electrospun nanofibers and process parameters. Research into the production of electrospun nanofiber secondary structures has introduced new methods for designing advanced electrodes, catalyst sources, and sensor devices. Especially hollow nanofibers with a circular cross-section are ideal channels for the passage of nanofluids. In general, research in electrospinning has led to the application of nanofibers in a wide range of fields [ [1] , [2] , [3] , [4] , [5] ]. Electrospinning is fast developing from a single-fluid process [ 6 , 7 ] to coaxial [ 8 ], tri-axial [ 9 ], side-by-side [ 10 ], and other complicated processes [ 11 ]. Correspondingly, uniaxial [ 12 ], core-shell [ 13 ], Janus [ 14 ], tri-layer core-shell nanostructures [ 15 ] have been reported for a wide variety of functional applications. However, one of the most important properties of mechanical performance is often ignored in literature, which is vital for functional applications regardless of the complexity [ 16 ]. Doshi and Reneker [ 17 ] invented the preparation of polyethylene oxide fibers electrically. In this process, after dropping the polymer solution drop and until the electric field overcomes the surface tension, a charged jet exits the solution to the collector, and fibers are formed in the range of nanometer diameter. Inai et al. [ 18 ] used a table-mounted folding plate to collect separate nanofibers. Conductive plates were installed near a paper support tape to collect the fibers regularly. In this case, the separate nanofibers were collected on a paper strip in the desired arrangement. Except for the nanofibers located in the strip center, the excess nano-fibers were separated from it. Then, the sample prepared in the tensile strength test at the nanoscale was measured. Ohgo et al. [ 19 ], Zong et al. [ 20 ], Huang et al. [ 21 , 22 ]and Huang et al. [ 23 ], Li et al. [ 24 ], and Pedicini and Farris [ 25 ] researched mechanical properties of the nanofibers with random arrangement collected by an aluminum plate. Also, Bhattarai et al. [ 26 ], Lee et al. [ 27 , 28 ], Wnek et al. [ 29 ], Khil et al. [ 30 ], Nagapudi et al. [ 31 ], and Ding et al. [ 32 ] investigated mechanical properties of regularly arranged nanofiber laminates produced by rotary collectors. Katti et al. [ 33 ] investigated the effect of parameters such as needle diameter, polymer solution concentration and voltage per unit length on the morphology and diameter of electrospun nanofibers. In their study, antibiotics were loaded into a polylactic glycolic polymer solution (PLGA) to design a drug delivery system and wound healing. In general, they showed that glycolic polylactic nanofibers could be brought to the desired diameter through changes in proportional processing parameters, and antibiotics such as cefazolin can be added to the nanofibers. Therefore, glycolic polylactic nanofibers have shown their potential as antibiotic delivery systems in wound healing. Hong et al. [ 34 ] produced antimicrobial Polyvinyl Alcohol (PVA) nanofibers containing silver nitrate nanoparticles with the chemical formula of AgNO 3 . According to their observations, if a silver nitrate polymer solution is used in polyvinyl alcohol with a weight percent of 10 to 0.1, the electrospinning process can be successful. During their research on the surface of nanofiber structures, Yoo et al. [ 35 ] found that electrospun nanofibers with a huge area-to-volume ratio are very suitable because of their potential applications for medical devices, tissue engineering scaffolds, and drug delivery carriers. Kizildag et al. [ 36 ] investigated conductive polyaniline nano-fibers (PANi) in polyvinyl alcohol (PVA/PANi) produced by electrospinning with rotary collectors and found that conductive nanofibers can be used for a wide range of applications such as electromagnetic interference protection, antistatic applications, gas sensors, tissue engineering scaffolding, biomedical applications, nanoelectronic devices, etc. Also, they produced conductive nanofibers (PVA/PANi) via electrospinning successfully. Wang et al. reported fabrication of electrospun composite fibers based on Poly vinylidene fluoride (PVDF) and multi-walled carbon nanotubes (MWCNTs) [ 37 ]. They found an increase in mechanical and electrical properties of fibers after incorporating MWCNTs into the PVDF fibers. Sun et al. [ 38 ] investigated the applications of electrospun nanofibers in energy. These nano-fibers can be widely used in energy storage systems due to very high surface-to-volume ratio and porosity of electrospun nanofibers. They focused mainly on using nano-fibers in energy storage devices, for example, lithium batteries, fuel cells, dye-sensitized solar cells, and supercapacitors. In another study, Itoh et al. [ 39 ] investigated the morphology, and mechanical properties of PVA nano-fibers spun by free-surface electrospinning. Their research showed that due to the electrical nature of electrospinning, the electrical and ionic conductivity of the polymer solution plays an essential role in this process and the morphology of the fibers. Utilizing three different collectors, Polycaprolactone electrospun fibers have been produced by De Prá et al. [ 40 ]. Based on the results, rotational speed and electrostatic forces are dominant phenomena in stretching fibers collected with rotating drum and static collector, respectively. According to the authors’ knowledge, there is no comparison between the mechanical properties and geometry of nanofibers obtained by electrospinning of 13 % PAN solution in DMF solvent produced by various fixed and rotary collectors. So, this issue is investigated in the present study. First, five types of disk, cylinder, wire drum, parallel bars, and polygon collectors were designed and made, two of which are rotary, and three are fixed models. Then, after the electrospinning process, the mechanical properties of the produced fibers by five collectors are compared.",
"discussion": "3 Results and discussion In this section, the results of the layer tensile test are stated. The tensile test results of each collector are shown in Fig. 7 , Fig. 8 , Fig. 9 , Fig. 10 , Fig. 11 . It is worth noting that the information provided is related to the three replications of the tensile test. The red, green, and blue graphs show the first, second, and third iterations of the samples obtained from different collectors in the following diagrams. Fig. 7 Tensile test of the nanofibers layers manufactured by disc collector. Fig. 7 Fig. 8 Tensile test of the nanofibers layers manufactured by cylinder collector. Fig. 8 Fig. 9 Tensile test of the nanofibers layers manufactured by wire drum collector. Fig. 9 Fig. 10 Tensile test of the nanofibers layers manufactured by parallel bars collector. Fig. 10 Fig. 11 Tensile test of the nanofibers layers manufactured by polygon collector. Fig. 11 Based on the above figures, the mechanical properties of the samples obtained from the electrospinning process with different collectors can be summarized in Table 1 . Table 1 Results related to the repetitions of tensile test in nanofiber layers obtained from different collectors. Table 1 Collector Type Test No. F max Elongation at F max Ultimate Stress Strain at maximum stress E-Modulus k N m m M P a % M P a Disc 1 106.398 8.64 3.641 31.984 101.39 2 110.894 5.89 3.897 36.138 122.3 3 121.684 13.05 3.996 38.395 116.85 Average 112.992 9.19 3.845 35.506 113.51 Wire drum 1 162.251 5.32 5.220 33.764 51.87 2 151.492 7.59 5.577 41.161 63.55 3 171.208 9.91 5.813 39.186 65.35 Average 161.65 7.6 5.537 38.037 60.25 cylinder 1 189.864 8.82 6.432 36.654 83.47 2 167.356 8.57 5.652 33.854 62.96 3 185.856 8.36 6.107 30.141 73.59 Average 181.02 8.58 6.064 33.550 73.34 Parallel bars 1 104.235 3.58 3.484 16.348 83.1 2 106.107 3.69 3.479 14.740 70.39 3 99.348 2.89 3.420 14.752 65.57 Average 103.23 3.38 3.461 15.280 73.02 Polygon 1 84.672 5.56 2.800 21.956 62.81 2 79.453 4.89 2.614 21.693 73.59 3 81.738 5.79 2.751 28.197 64.19 Average 81.95 5.41 2.722 23.949 66.86 According to Table 1 , the highest ultimate stress of the produced nanofiber layers is related to the cylinder collector; 6.064 M P a (see average ultimate stress values). In addition, the models made with wire drum, disc, parallel bars, and polygon collectors are in the following ranks in terms of ultimate stress. In terms of Young's modulus, the highest value refers to specimens made with disc collectors; 113.51 M P a . In this regard, manufactured specimens with cylinder, parallel bars, polygon, and wire drum collectors are in the next ranks. An SEM can be used to examine the diameter of a polymer nanofiber [ 17 ]. Scanning electron microscopy images of the disc (plate), wire drum, cylinder, parallel bars, and polygon collectors are shown in Fig. 12 ( Fig. 12 a disk collector, (b) wire drum collector, (c) cylinder collector, (d) parallel bars collector, (e) polygon collector). Fig. 12 SEM of the specimen manufactured by (a) disk collector, (b) wire drum collector, (c) cylinder collector, (d) parallel bars collector, (e) polygon collector. Fig. 12 By examining this figure, it was identified that the average diameter of nanofibers is between 300 and 340 nm. Also, the fibers in the disk collector are collected irregularly. However, in-cylinder, wire drum, and parallel bars collectors, the fibers tend to be parallel-arranged, with the wire drum collector having the most parallel fiber arrangement. In the case of polygon collectors, the fibers tend to be 90° closer to each other. As the pictures illustrate, the conductive metal arrangement of the collectors is directly related to the fibers' arrangement. By changing the arrangements, the fibers' orientation changes because of the stretching of the fibers towards the conductive metal."
} | 3,081 |
37974103 | PMC10652448 | pmc | 9,008 | {
"abstract": "Food security and environmental pollution are major concerns for the expanding world population, where farm animals are the largest source of dietary proteins and are responsible for producing anthropogenic gases, including methane, especially by cows. We sampled the fecal microbiomes of cows from varying environmental regions of Pakistan to determine the better-performing microbiomes for higher yields and lower methane emissions by applying the shotgun metagenomic approach. We selected managed dairy farms in the Chakwal, Salt Range, and Patoki regions of Pakistan, and also incorporated animals from local farmers. Milk yield and milk fat, and protein contents were measured and correlated with microbiome diversity and function. The average milk protein content from the Salt Range farms was 2.68%, with an average peak milk yield of 45 litters/head/day, compared to 3.68% in Patoki farms with an average peak milk yield of 18 litters/head/day. Salt-range dairy cows prefer S-adenosyl-L-methionine (SAMe) to S-adenosyl-L-homocysteine (SAH) conversion reactions and are responsible for low milk protein content. It is linked to Bacteroides fragilles which account for 10% of the total Bacteroides , compared to 3% in the Patoki region. The solid Non-Fat in the salt range was 8.29%, whereas that in patoki was 6.34%. Moreover, Lactobacillus plantarum high abundance in Salt Range provided propionate as alternate sink to [H], and overcoming a Methanobrevibacter ruminantium high methane emissions in the Salt Range. Furthermore, our results identified ruminant fecal microbiomes that can be used as fecal microbiota transplants (FMT) to high-methane emitters and low-performing herds to increase farm output and reduce the environmental damage caused by anthropogenic gases emitted by dairy cows.",
"conclusion": "Conclusions To achieve sustainable production goals, it is pertinent to determine the abundance and function of microbiomes under real environmental conditions. The present study defines microbiota diversity and its functions under divergent environmental conditions and provides insight into how such microbiota can be used to improve the overall output of dairy farms. The appropriate diets for the low performing herds can be suggested with addition of capsulated FMT by the observations of present study for dairy cows from varying environmental conditions can improve the health barriers in achieving maximum potential milk yield without compromising quality. It is of utmost importance that in changing environments and global warming, natural microbiomes are conserved for sustainable production. This study demonstrated how different gut microbiota compositions in varying environments affect milk yield and quality in dairy cows.",
"introduction": "Introduction Global warming is challenging the food security of an expanding population by impacting gut microbiota diversity and its ecological interactions, especially for commensals, predators, and symbionts. Such changes in the microbiome pose an immediate threat and cause host system dysfunction [ 1 ]. The gut microbiota has been implicated in several biological processes across different species, and its role in dairy cow milk production and quality is of interest to the dairy industry and the well-being of the rural economy [ 2 ]. Microbial products help in food fermentation, methane and nitrogen emissions, and fiber breakdown [ 3 ]. Bifidobacterium, Ruminococcus, and Fibrobacter help in cellulose digestion, whereas Succinovibrinonaceae impacts methane emissions [ 4 – 6 ]. Volatile fatty acids are compounds formed by microbial fermentation in the gut of ruminants that provide an energy source to the host [ 7 , 8 ]. For example, Clostridium sticklandii is involved in NH 3 production, whereas Rosebura species produce butyrate [ 9 – 11 ]. To explore the gut microbiota, feces remain the most important source [ 12 ], and present-day molecular biology techniques and next-generation sequencing (NGS) can help identify complex microbial communities. Fecal microbial composition depends mainly on diet, environment, and health status [ 13 , 14 ]. Kim and Wells’s meta-analysis report showed 10 phyla, 17 classes, 28 orders, 59 families, and 110 genera present in the fecal microbiome of cows, of which the most common phyla reported in several studies were Firmicutes. Proteobacteria and Bacteroidetes [ 15 ]. Animal microbiota composition depends on various factors, including the environment, which influences animal feed intake, and host factors, such as immunity and metabolism, resulting in diversified microbiomes [ 16 ]. Different feed components influence various classes of bacterial and archaeal groups, such as methanobacteria, fiber, and fat digesters [ 17 ]. Dairy cows depend on microbes to obtain various products for the digestion of proteins, fibers, vitamins, and minerals from the diet [ 18 ], and the balance of these components is crucial for the overall output with regard to the quality and quantity of milk [ 17 ]. Besides diet, environmental factors such as water quality, temperature, altitude, latitude, and flora influence the host gut microbiota, causing a multitude of phenotypes [ 19 – 21 ]. In the present study, we evaluated the diversity, abundance, and function of gut microbiota from dairy farms in ecologically diverse zones of Pakistan, namely Chakwal, an arid hilly zone recognized for its great fauna diversity, Salt Range with high availability of pink salt, Patoki as lowland, and a polluted area with the inclusion of animals from local farmers fed concentrate diets and grassland. The objective was to determine microbiomes for better productivity and lower methane emissions and to recommend microbiomes with better performance for use as fecal microbiota transplant (FMT) to low-performing animal herds in original environmental conditions. In this regard, we thoroughly studied and compared the metabolic pathways among the groups to evaluate and logically explain the mechanisms behind each phenotype. The results identified potential fecal microbiomes for use as FMT in compromised herds.",
"discussion": "Results and discussion Data preprocessing DNA was isolated from fecal samples of dairy cows from farms in Chakwal, Salt Range, Patoki and from samples of local farmers’ dairy cattle for constructing metagenomic libraries. The raw sequencing reads obtained were 6.88 Gb, 6.15 Gb, 6.70 Gb, and 7.37 Gb for the Chakwal Patoki, local, and saline ranges, respectively. The clean data obtained was 6.86 Gb, 6.14 Gb, 6.68 Gb, and 7.34 Gb, respectively. Q_30 clean data corresponded to a sequencing error rate of less than 0.001 in the Chakwal study. The Patoki, local, and salt ages were 90.40%, 89.60%, 90.43%, and 90.35%, respectively. The NovaSeq 6000 platform was used for sequencing. All scaftigs were counted in the assembled results with the contribution of scaftigs to each sample. Unutilized reads were subjected to mixed assembly, maintaining the same assembly parameters. The data preprocessing statistics are listed in Table 1 .\n Table 1 Statistics of data preprocessing representing samples, the fragment length used for library construction, Raw Data size of each sample, clean data obtained after quality check, Clean Q_20 data percentage with an error rate less than 0.01, Clean Q_30 with an error rate less than 0.001. The GC content and ratio of clean data over raw data Sample Insert size Raw Data (G) Clean Data (G) Clean_ Q20% Clean_Q30 (%) Clean GC (%) Effective Chakwal 350 6.88 6.86 96.53 90.40 42.41 99.723 Patoki 350 6.15 6.14 96.36 89.60 41.33 99.718 Local 350 6.70 6.68 96.53 90.43 43.09 99.787 Salt_Range 350 7.37 7.34 96.50 90.35 43.87 99.612 Metagenome assembly The clean data were assembled using Soapdenovo. The longest N50 was considered the final result. The scaffolds were interrupted at N to obtain the scaffolds. Clean data were aligned to scaftigs using SoapAligner. Subsequently, a mixed-assembly analysis was conducted by combining all the unutilized reads. Scaftigs of less than 500 bp were filtered, and the remaining effective scaftigs were used for further analysis. The scafting statistics are presented in Table 2 . The distribution of scaffolds in the samples is shown in Fig. 1 .\n Table 2 Statistics of scaftigs. The total length of all the scaftigs, number of scaftigs, average scaftigs length, N50 or N90 represent the length at 50% or 90% of the total length of scaftigs and the maximum length of the scaftigs is provided for each sample SampleID Total length (bp) Number of Scaftigs Average length (bp) N50 Length (bp) N90 Length (bp) Max length (bp) Chakwal 374,089,007 300,980 1,242.90 1,404 578 386,952 Patoki 356,611,352 324,047 1,100.49 1,154 561 168,916 Salt_Range 287,013,105 206,419 1,390.44 1,778 593 671,517 Local 256,340,267 190,855 1,343.12 1,648 589 251,252 NOVO_MIX 732,189,530 861,623 849.78 830 542 30,435 Fig. 1 Distribution of scaftigs. Certain lengths of scaftigs are given at Y1-axis named “Frequence; Certain length of Scaftigs; Percentage of scaftigs to total scaftigs is given at Y2-axis named “Percentage (%)”; The X-axis titled “Scaftigs Length (bp)” indicates the length of Scaftigs. A Chakwal Length distribution, B Local length distribution, C Salt Range length distribution, D Patoki Length Distribution, E NOVO-MIX length distribution Gene prediction and abundance analysis The open reading frame (ORF) was predicted using MetaGeneMark utilizing scaftigs greater than or equal to 500 bp. CD-HIT was used to dereplicate the ORF results to generate a gene catalog in which the longest ORF was chosen as the representative gene, that is, the unigene. Furthermore, clean data were mapped to the gene catalog using SoapAlighner to calculate the mapping reads. The gene catalog statistics are given in Table 3 , and the distribution is shown in Fig. 2 a. The common and peculiar genes in each sample are shown in Fig. 2 b.\n Table 3 Statistics of gene catalog. The number of genes are given as ORFs NO. Genes containing only stop codon is represented as integrity: end. Genes having both start and stop codon is represented as integrity: all. Genes without start and stop codons is shown as integrity: none. The total length of gene catalog is given as (Mbp) million. Average length in the Gene catalog is shown as the average length. GC content of the gene catalog is given as GC Percent ORFs NO 2,858,457 Integrity:end 753,041 (26.34%) Integrity:all 1,302,628 (45.57%) Integrity:none 170,302 (5.96%) Integrity:start 632,486 (22.13%) Total Length (Mbp) 1,455.04 Average Length (bp) 509.03 GC percent 44.3 Fig. 2 Gene prediction and abundance analysis. a Gene Distribution catalog. The number of genes plotted against the Y1-axis, genes percentage against Y2-axis, and genes length against the X-axis. b Venn Diagram to show gene numbers in samples. The number of common genes between/among samples is shown by overlap; the other parts represent the number of special genes in samples Relative abundance of bacteria in managed farms of Chakwal, Salt range, Patoki, and dairy cattle of local farmers A shotgun metagenomic approach identified significant differences in bacteria at the phylum level. The phylum Firmicutes constituted 81% of the total bacteria in the Patoki region, followed by 49% in the Salt Range, 33% in Chakwal, and only 6% in the dairy cattle of local farmers. Firmicutes play a significant role in feed conversion, lower methane emissions, and higher milk yields by the production of short chain fatty acid (SCFA) [ 22 ]; however, high abundance is associated with the overproduction of volatile fatty acids (VFA), which results in ruminant metabolic disorders, including subacute ruminal acidosis, leading to a significant reduction in milk yield [ 23 ]. It became evident from our results that significantly higher milk yields were recorded in the Salt Range region, that is 45 L/day, compared to 18 L/day in Patoki. It is pertinent to note that milk yields in the Chakwal region were 28 L/day. The class Bacilli bacteria present in ruminants are known for their involvement in several metabolic pathways, including breakdown of cellulose and hemicellulose, production of VFAs as an energy source, and overall improved health and increased milk yield if present in appropriate abundance; however, its high abundance is associated with the production of harmful metabolites, including lactic acid, which is a major cause of acidosis where the pH of the rumen becomes too acidic and results in reduced milk yield, poor feed intake, and other health issues [ 15 ]. It was observed that the bacterial class Bacilli was highest in the Patoki region and comprised 32% of total bacteria as compared to 26% in the Salt Range, which shows another dysbiosis of the bacterial class that is responsible for lower milk yields in Patoki. To establish an appropriate abundance of bacilli, a well-balanced diet with less easily fermentable carbohydrates is provided to dairy cows to tackle the imbalance of metabolites. The bacterial class Bacteroidia can maintain a healthy microbiome, resist acidosis by preventing the overgrowth of harmful bacteria, and was also found to be at the lowest in the Patoki region (9%). Bacteroidia is also associated with the production of beneficial metabolites, including SCFA, to help accomplish the energy needs of dairy cows and was the highest in dairy cows of local farmers (48%), suggesting a reasonably high yield of 22 litters/day. The relative abundances of the bacterial phyla, classes, and families are provided in Fig. 3 A, B, and C, respectively. Heatmaps of the top 35 relative genera and species are shown in Fig. 3 D, E, F, and G. Fig. 3 The relative abundance of fecal gut microbiota. A Phylum Level, B Class level, C family level D Heatmap of top 35 phyla E Heatmap of top 35 class members F Heatmap of top 35 families G Heatmap of top 35 genera Lactobacillus plantarum is a species of lactic acid bacteria [ 24 ] commonly found in the gastrointestinal tract of animals, including dairy cows. In recent years, there has been growing interest in using L. plantarum as a probiotic in dairy cow nutrition because of its potential health benefits for both the cow and the milk produced, and its role in protecting against mastitis [ 25 ]. Some reported benefits of L. plantarum supplementation in dairy cows include improved rumen fermentation and digestion, increased milk production, reduced incidence of mastitis and other infections, and improved milk quality [ 25 , 26 ]. L. plantarum is believed to achieve these benefits by promoting the growth of beneficial bacteria in the gut, enhancing immune function in cows, and reducing inflammation [ 27 ]. It was observed that the abundance of L. plantarum was 16% of that of Lactobacillus in Salt Range, compared to 3% in Patoki, 0.5% in Chakwal, and absence in the dairy cows of local farmers. As reported, L. plantarum has a positive impact on milk yield and quality has been observed in dairy cows of the Salt Range, with an average milk yield of 45 L per head per day. It was also observed that Lactobacillus acidophilus abundance was the highest in Salt Range dairy cows, which improved milk quality by reducing somatic cell count and providing resistance against mastitis. It has been reported that L. plantarum plays an important role in increasing beneficial bacteria including L. acidophilus to help improve host health synergistically [ 28 ]. Functional annotation of dairy cows in managed farms of Chakwal, Salt range, Patoki and dairy cattle of local farmers Community physiology can be clarified using the collective functions that are encoded in the genomes of organisms that live together in a community, and can be achieved by employing shotgun metagenomic sequencing. Protein-coding sequences were mapped against KEGG [ 29 ], egg NOG [ 30 ], and CAZy [ 31 ]. Gene numbers and relative abundances were calculated at each level. UniGene annotation results for each database are shown in Fig. 4 A, B and C. It can be seen in Fig. 4 A that UniGene annotation to the KEGG database is the highest in metabolism and specifically in carbohydrate metabolism [57782] followed by amino acid metabolism [44853], environmental processing where membrane transport genes annotated are 31,292, genetic information processing where UniGene corresponds to translation was 30,094 followed by replication and repair, that is, 23,410, and cellular processes where Unigene annotation to cellular community – prokaryotes is 17105. Fig. 4 Functional annotation of fecal gut microbiota in dairy cows. A KEGG database annotations. B eggNOG database annotation. C CAZy database annotation. D KEGG Relative abundance of function. E CAZy Relative abundance. F eggNOG Relative abundance The UniGene annotated to the eggNOG database shown in Fig. 4 B revealed that the highest number of genes were annotated to replication, recombination, and repair, followed by amino acid transport and metabolism, and carbohydrate metabolism and transport. A significant number of genes were annotated for inorganic ion transport and metabolism, posttranslational modification, protein turnover, and chaperones. UniGene annotated to the CAZy database had the highest number of genes annotated to glycoside hydrolases, glycosyltransferases, and carbohydrate-binding modules. The relative abundance of genes for metabolism is highest in dairy cows from local farmers with the lowest in salt range, as shown in Fig. 4 D, while the relative abundance of genes in CAZy shows the highest number of glycoside hydrolases in dairy cows from local farmers and lowest in salt range and its corresponding abundance is also shown in Fig. 4 E, when annotated to eggNOG database where the relative abundance of genes for metabolism was highest in dairy cows from local farmers followed by Patoki and Chakwal shown in Fig. 4 F. Gut microbiota affects metabolic pathways to affect milk yield, milk fat, and milk protein contents mPATH analysis is used to analyze microbiome data, which involves analyzing the gene expression profiles of microbial communities under different environmental conditions or disease states [ 32 ]. In microbiome studies, mPATH analysis can identify differentially regulated microbial pathways associated with specific environmental conditions or disease states [ 5 ]. To perform mPATH analysis of the microbiome data, gene expression profiles of the microbial communities were first generated using techniques such as metagenomics. These gene expression profiles were then used to identify differentially expressed microbial genes under different environmental conditions or disease states. Next, the differentially expressed microbial genes were mapped to microbial pathways using pathway databases such as KEGG. The analysis shows shared and unique pathway information among the compared samples, where nodes represent chemicals and lines represent reactions. Red corresponds to shared reactions, blue corresponds to unique reactions in sample A, and green represents unique reactions in sample B. By comparing samples via mPATH analysis, we observed that fatty acid metabolism and amino acid metabolism pathways were uniquely expressed when Patoki was compared to the Salt Range, as shown in Fig. 5 A. The key difference between the two samples is the reaction that results in the formation of a certain molecule. When acetyl-CoA reacts with ACP (acyl carrier protein (ACP), the product is acetyl-ACP (acyl carrier protein), which is an intermediate in fatty acid biosynthesis. Acetyl-ACP can be used as a substrate for further fatty acid synthesis. Fig. 5 Comparison of Fatty acid metabolism and Amino acid Biosynthesis among different samples. A Fatty acid Metabolism in Patoki vs Salt Range, B Amino acid Biosynthesis comparison between Patoki vs Salt Range, C Fatty Acid Metabolism Chakwal vs Patoki, D Amino acid Biosynthesis comparison Chakwal vs Patoki, E Amino Acid biosynthesis comparison Chakwal vs Salt Range In contrast, when acetyl-CoA directly reacts with CO2 and ATP to form malonyl-CoA, the product is malonyl-CoA, a precursor for fatty acid biosynthesis. Malonyl-CoA is an important intermediate in fatty acid synthesis and is used to extend the length of growing fatty acid chains. Acetyl-ACP is an intermediate in fatty acid biosynthesis, whereas malonyl-CoA is the precursor. Acetyl-CoA reacts with ACP to form acetyl-ACP, which can then be used as a substrate for fatty acid biosynthesis. This pathway is more efficient if the cell needs to rapidly increase fatty acid synthesis, because it is a direct precursor for fatty acid synthesis, can be used immediately in the next step of the reaction, and is the preferred reaction in salt-range dairy cows. It was also observed that salt-range dairy cows use the most efficient pathway to synthesize palmitoyl-CoA, where hexadecanoyl-Acp directly forms palmitoyl-CoA by the enzyme acyl-ACP thioesterase, and is considered more efficient as it bypasses the need for intermediate malonyl-CoA and the enzymatic reactions involved. This pathway is energetically favorable because it bypasses the ATP-dependent carboxylation reaction required to synthesize malonyl-CoA. In contrast, Patoki dairy cows prefer to follow pathways that convert acetyl-CoA to malonyl-CoA by reacting with CO2 and ATP, and later, malonyl-CoA reacts with ACP to form malonyl-Acp. Alternatively, acetyl-CoA directly reacts with CO2 and ATP to form malonyl-CoA, which then reacts with ACP to form malonyl-CoA. This pathway requires higher energy and expenditure of ATPs. The metabolic pathway of fatty acid biosynthesis in patoki also prefers hexadecanoyl-ACP to react with malonyl-CoA to produce palmitoyl-ACP, which is then converted to palmitoyl-CoA by acyl-ACP thioesterase and is less efficient as it requires the intermediate synthesis of malonyl-CoA and additional enzymatic reactions. There was an observed variation in the solid non-fat content of milk where Salt Range dairy cows exhibits 8.29%, and dairy cows of Patoki shows 6.34%, however, there was no significant difference in total milk fat content, which was 3.65% and 3.68% in the Salt Range and Patoki, respectively. When we compared Chakwal region dairy cows to Patoki cows shown in Fig. 5 C, they also showed preference for the same pathway reactions as that of Salt Range dairy cows, where the solid non-fat content of Chakwal was 8.09% and the total fat content was 3.66%. The milk protein content is an important quality parameter that was significantly lower in Salt Range dairy cows (2.68%) than in Patoki cows (3.43%). When Patoki dairy cows were compared to Salt Range dairy cows using mPATH analysis, as shown in Fig. 5 B, we observed that Salt Range dairy cows showed preferred pathway reactions for the conversion of S-adenosyl-l-methionine (SAMe) to S-adenosyl-l-homocysteine (SAH), which is not beneficial because SAMe is a significant methyl donor that plays a critical role in protein synthesis by donating methyl groups to proteins and other molecules. This methylation process is essential for the proper folding and function of many proteins [ 33 ]. On the other hand, SAH is the product of the methylation reaction and acts as a potent inhibitor of methyltransferases, including those involved in protein synthesis. Accumulation of SAH can lead to a decrease in protein methylation and potentially impair protein synthesis without affecting milk yield. Therefore, the conversion ratio of SAMe to SAH should be maintained for the desired milk protein content. This balance is influenced by various factors, including the environment, diet, genetics, and efforts to maintain a proper ratio by supplementing diets with methyl donors, vitamins B9 and B12 to maintain a healthy methionine cycle [ 34 ], which is an active area of research in the field of nutrition and metabolism. When the Chakwal and Patoki amino acid biosynthesis pathways were compared, shown in Fig. 5 D, they did not show the preferred reactions for the conversion of S-adenosyl-L-methionine (SAMe) to S-adenosyl-L-homocysteine (SAH), whereas a comparison of Chakwal to Salt Range showed that Salt Range has the preferred reactions of S-adenosyl-L-methionine (SAMe) to S-adenosyl-L-homocysteine (SAH),as shown in Fig. 5 E. We further examined the abundance of such microbiota that can cause this conversion at a greater rate and found that Bacteroides fragilis which has enzymes called SAM hydrolases that catalyze the breakdown of SAMe to SAH, accounted for 10% of total Bacteroides in Salt Range dairy cows, 5% in Chakwal, and 3% in Patoki."
} | 6,172 |
20405029 | PMC2853565 | pmc | 9,010 | {
"abstract": "Background Hydrogen production by fermenting bacteria such as Escherichia coli offers a potential source of hydrogen biofuel. Because H 2 production involves consumption of 2H + , hydrogenase expression is likely to involve pH response and regulation. Hydrogenase consumption of protons in E. coli has been implicated in acid resistance, the ability to survive exposure to acid levels (pH 2–2.5) that are three pH units lower than the pH limit of growth (pH 5–6). Enhanced survival in acid enables a larger infective inoculum to pass through the stomach and colonize the intestine. Most acid resistance mechanisms have been defined using aerobic cultures, but the use of anaerobic cultures will reveal novel acid resistance mechanisms. Methods and Principal Findings We analyzed the pH regulation of bacterial hydrogenases in live cultures of E. coli K-12 W3110. During anaerobic growth in the range of pH 5 to 6.5, E. coli expresses three hydrogenase isoenzymes that reversibly oxidize H 2 to 2H + . Anoxic conditions were used to determine which of the hydrogenase complexes contribute to acid resistance, measured as the survival of cultures grown at pH 5.5 without aeration and exposed for 2 hours at pH 2 or at pH 2.5. Survival of all strains in extreme acid was significantly lower in low oxygen than for aerated cultures. Deletion of hyc (Hyd-3) decreased anoxic acid survival 3-fold at pH 2.5, and 20-fold at pH 2, but had no effect on acid survival with aeration. Deletion of hyb (Hyd-2) did not significantly affect acid survival. The pH-dependence of H 2 production and consumption was tested using a H 2 -specific Clark-type electrode. Hyd-3-dependent H 2 production was increased 70-fold from pH 6.5 to 5.5, whereas Hyd-2-dependent H 2 consumption was maximal at alkaline pH. H 2 production, was unaffected by a shift in external or internal pH. H 2 production was associated with hycE expression levels as a function of external pH. Conclusions Anaerobic growing cultures of E. coli generate H 2 via Hyd-3 at low external pH, and consume H 2 via Hyd-2 at high external pH. Hyd-3 proton conversion to H 2 is required for acid resistance in anaerobic cultures of E. coli .",
"introduction": "Introduction Bacterial hydrogen production by hydrogenase is studied as a promising source of clean alternative energy [1] , [2] . In the intestinal tract, H 2 produced from bacteria fermentation enables methane production by methanogens [3] and contributes to the growth of pathogens such as Salmonella enterica and Helicobacter pylori \n [4] , [5] . Hydrogenase in Escherichia coli has been suggested to decrease cytoplasmic acid stress and contribute to its acid resistance systems [6] – [9] . Because E. coli need to survive the harshly acidic environment of the stomach to colonize the intestine, acid resistance systems enhance the infective ability of pathogenic E. coli \n [10] – [12] . Several mechanisms have been characterized that enhance survival at pH 2.5 and below [13] , such as the amino acid-dependent glutamate and arginine decarboxylases [14] – [16] . Genes encoding these enzymes and transporters are up-regulated during growth in moderate acid [7] , [17] , [18] . Most of the above studies of E. coli acid resistance address aerated cultures. In natural environments such as the gastrointestinal tract, however, enteric bacteria experience low oxygen. Oxygen limitation and acid stress occur in the microaerobic environment of the stomach [19] , which harbors many obligate and facultative anaerobic organisms such as Clostridium and Veillonella species [20] , [21] . In Salmonella typhimurium, anoxic conditions are required for expression of the acid-resistance component arginine decarboxylase [22] . Hayes et al. (2006) showed that all four hydrogenase isoenzymes are upregulated by acid under oxygen-limited conditions [7] . The four isoforms of hydrogenase catalyze the reversible oxidation of molecular hydrogen to 2H + . However, each hydrogenase functions primarily in one direction. Hydrogenase-1 (Hyd-1, encoded by hya ) and hydrogenase-2 (Hyd-2, encoded by hyb ) are energy-conserving respiratory pathways consuming H 2 with Hyd-2 acting as the primary consumption hydrogenase [23] – [25] . Hydrogenase-3 (Hyd-3) is the primary production hydrogenase [26] ; along with formate dehydrogenase (FDH-H), Hyd-3 makes up the formate hydrogen lyase (FHL) complex, which breaks down formate to carbon dioxide and H 2 \n [6] , [27] – [29] . The function of hydrogenase-4 (Hyd-4) is unclear; it may be a component of a second formate hydrogen lyase system (FHL-2) [26] , [30] , [31] . Mutants deleted for hypF mutant lacks all hydrogenase activity [8] , [32] . A hypF mutant shows decreased acid resistance in partly aerated cultures [7] . Because the function of hydrogenases is intricately connected to metabolic pathways, the pH-dependence of H 2 consumption must be measured in vivo . Previous studies of H 2 production of hydrogenase mutants have been based on harvested cell concentrates, often with addition of 100 mM formate to increase FHL activity, although such high formate concentration is incompatible with growth [9] , [25] , [33] . Our electrode-based methods were applied to live, growing cultures. Since H 2 production was hypothesized as a cellular mechanism for acid resistance, we observed the pH-dependent activity of hydrogenases under the conditions where acid resistance is induced (anaerobic growth at low external pH). We also characterized how pH regulates H 2 production and consumption via each hydrogenase complex, determining the significance of each at low and high pH.",
"discussion": "Discussion \n E. coli use several mechanisms to resist the harshly acidic conditions of the stomach. A previous report revealed the contribution of hydrogenase to acid resistance in partly aerated cultures [7] . Here we clarify that finding to show that specifically Hyd-3, which is a part of the FHL complex, consumes protons to contribute to acid resistance of anaerobic cultures. We first defined the pH regulation of both H 2 consumption and production in various hydrogenase mutants in order to determine which was more important under acidic conditions. Hydrogen production and consumption were measured in vivo, in growing cultures. At acidic pH, H 2 production was dependent only on Hyd-3, and was increased by the deletion of Hyd-2, whereas H 2 consumption was only dependent on Hyd-2. Both H 2 production and consumption rates are commonly measured under conditions such as cells cultured at pH 6.8 and assayed in the presence of 100 mM sodium formate [25] . Under physiological conditions, intracellular formate concentration reaches only as high as 20 mM [35] . Our results are consistent with the previous finding that Hyd-3 is the main production hydrogenase. We further show that hydrogen production is induced at low pH in the absence of exogenous formate. The in vitro pH-dependent activity of the consumption hydrogenase, Hyd-2, is maximal at high pH [23] . In the current report, we saturated an anaerobic culture with H 2 to directly measure Hyd-2-dependent H 2 consumption. This revealed that Hyd-2-dependent consumption increased under alkaline conditions, reaching a maximum at pH 8. Additionally, at pH 5.5 the wild-type strain showed net H 2 production despite being in a H 2 saturated environment. Because alkaline conditions appear to enhance H 2 consumption, it was not expected to contribute to extreme acid survival. A previous study using E. coli MC4100 finds less than 2-fold increase in H 2 production from pH 7.5 to pH 5.5 [26] , whereas we found a 70-fold increase from pH 6.5 to pH 5.5. It is possible that this discrepancy can be attributed to the previous use of 0.2% glucose in the growth media used by Ref. [26] , since hyc expression is repressed by glucose [36] . In order to maximize H 2 production yield, it is of importance to understand whether conditions used to induce H 2 production, such as decreasing pH, increase hyc expression or enhance the enzymatic activity. Our results show that a shift from pH 6.5 to 5.5, a shift from pH 5.5 to 6.5, or the addition of 5 mM benzoate did not affect H 2 production, whereas expression of the large subunit of Hyd-3 increased as pH decreased from pH 7 to pH 5.5 ( Fig. 3 ). Thus, the observed increase in H 2 production is likely due to an increase in hyc expression [7] , rather than a direct effect of external or internal pH on Hyd-3 activity. Extreme-acid survival assays using aerobic cultures showed no hydrogenase-dependent acid resistance ( Fig. 6 ). However, anaerobic cultures required Hyd-3 for survival at or below pH 2.5. The requirement for Hyd-3 increased as the pH decreased, showing a greater effect at pH 2 when compared to pH 2.5. Acid resistance systems are generally defined using aerobic cultures [7] , [12] , [15] , [37] and Hyd-3 is the first reported mechanism that is necessary for anaerobic but not aerobic cultures. The low-oxygen requirement for the acid resistance phenotype makes sense because Hyd-3 is only expressed anaerobically, controlled by the transcriptional activator FhlA [36] , [38] ; and under aerobic conditions Hyd-3 is inactive [28] . Nevertheless, other acid resistance systems are known to be co-induced by acid and anaerobiosis yet still show an acid resistance phenotype with aerobic cultures. For instance, arginine decarboxylase, adiA , is expressed when exposed to acid and low oxygen [7] , [39] . The adiA system confers aerobic acid resistance [15] , although Salmonella typhimurium requires anaerobic growth before extreme-acid exposure [22] . It is likely that greater attention to anoxic conditions will reveal new acid resistance components in E. coli ."
} | 2,460 |
26478859 | PMC4606470 | pmc | 9,013 | {
"abstract": "D-glucaric acid can be used as a building block for biopolymers as well as in the formulation of detergents and corrosion inhibitors. A biosynthetic route for production in Escherichia coli has been developed ( Moon et al., 2009 ), but previous work with the glucaric acid pathway has indicated that competition with endogenous metabolism may limit carbon flux into the pathway. Our group has recently developed an E. coli strain where phosphofructokinase (Pfk) activity can be dynamically controlled and demonstrated its use for improving yields and titers of the glucaric acid precursor myo -inositol on glucose minimal medium. In this work, we have explored the further applicability of this strain for glucaric acid production in a supplemented medium more relevant for scale-up studies, both under batch conditions and with glucose feeding via in situ enzymatic starch hydrolysis. It was found that glucaric acid titers could be improved by up to 42% with appropriately timed knockdown of Pfk activity during glucose feeding. The glucose feeding protocol could also be used for reduction of acetate production in the wild type and modified E. coli strains.",
"conclusion": "5 Conclusions Glucaric acid titers and yields could be improved under multiple culture conditions through timed knockdown of Pfk activity, with maximum improvements of up to 42% observed. In the absence of aTc, the switchable strain IB1486 shows titers comparable to or above those observed with wild-type MG1655, indicating the genetic modifications in IB1486 do not result in degradation of baseline performance and could potentially be applied to high-performing strains for increases in titer. Optimization of strain background and pathway enzyme expression levels may lead to both higher baseline titers and to greater gains from dynamic control of Pfk activity.",
"introduction": "1 Introduction D-glucaric acid was identified by the United State Department of Energy as a top value-added chemical for production from biomass ( Werpy and Petersen, 2004 ). It has a number of potential applications including use in biopolymers ( Kiely and Chen, 1994 ) and as a detergent builder and corrosion inhibitor ( Smith et al., 2012 ). Glucaric acid can be produced through nitric acid oxidation of glucose ( Mehltretter and Rist, 1953 ) but a biological route to glucaric acid production could potentially provide several advantages, including mild processing conditions and high selectivity for the product of interest. Production of D-glucaric acid in Escherichia coli was previously demonstrated by our group via expression of heterologous enzymes from three different organisms ( Moon et al., 2009 ). Titers of 1.13 g/L glucaric acid were achieved in strain BL21(DE3) in LB medium supplemented with 10 g/L glucose. Following demonstration of the initial pathway, some increases in glucaric acid titers were achieved through improved strategies for expression of the myo -inositol oxygenase (MIOX) enzyme, one of the limiting factors in glucaric acid production in LB supplemented with glucose or myo -inositol ( Moon et al., 2010 , Shiue and Prather, 2014 ). However, competition for glucose-6-phosphate (G6P) between native E. coli enzymes (phosphoglucosisomerase and glucose-6-phosphate dehydrogenase) and the first enzyme in the glucaric acid pathway, myo -inositol-1-phosphate synthase (INO1), is also a concern. High level expression of INO1 is required for detectable myo- inositol and glucaric acid production, indicating it competes poorly with endogenous metabolism for substrate ( Moon et al., 2009 ). Additionally, the second pathway enzyme, MIOX, appears to be stabilized by its substrate, myo -inositol, so more rapid accumulation of myo- inositol may help reduce limitations in MIOX activity as well ( Moon et al., 2010 ). With this in mind, our group has explored strategies for development of strains capable of accumulating G6P and directing greater fluxes of this metabolite into production of glucaric acid and myo- inositol. By eliminating the pathways for glucose catabolism in the production strain, and feeding alternative carbon sources, higher yields of glucaric acid from glucose could be achieved ( Shiue et al., 2015 ). However, the rate of glucose uptake in this K-12 host strain was quite slow, especially in minimal medium, and its use was limited to mixed sugar substrates. While gene knockouts provide a static solution for redirecting fluxes in the cell ( Kogure et al., 2007 , Shiue et al., 2015 ), under many conditions, it may be advantageous to develop cells where dynamic changes in enzyme levels can be used to switch between substrate consumption for biomass formation and substrate conversion into product. Dynamic control of key enzymes can be used to facilitate more rapid initial accumulation of biomass, overcoming potential reductions in growth rate, and can eliminate the need for supplementation of the medium or addition of secondary carbon sources required with some gene knockouts ( Anesiadis et al., 2008 , Gadkar et al., 2005 ). At the desired time, activity of the target enzyme(s) can be reduced through decreasing transcription ( Scalcinati et al., 2012 , Solomon et al., 2012 , Soma et al., 2014 ) or translation ( Williams et al., 2015 ) of the enzyme, or initiating rapid degradation ( Brockman and Prather, 2015 , Torella et al., 2013 ). Coupling such controls with sensors capable of reporting on intracellular metabolite levels allows for the development of more complex systems capable of continuously adjusting enzyme levels to balance metabolite pools or maintain cellular state ( Dahl et al., 2013 , Farmer and Liao, 2000 , Xu et al., 2014 , Zhang et al., 2012 ). It was recently shown that by inducing degradation of phosphofructokinase I (Pfk-I) activity in the cell, the pools of G6P could be increased during growth on glucose minimal medium, along with the yields and titers of the glucaric acid precursor myo -inositol ( Brockman and Prather, 2015 ). In this work, we explore the expanded utility of this system for production of glucaric acid from glucose in a semi-defined medium under batch conditions and a fed-batch condition simulated by glucose release from in situ enzymatic starch hydrolysis. To explore the interplay of production conditions with metabolic intervention through Pfk-I degradation, initial screening runs were carried out in 48-well plates in a BioLector benchtop bioreactor. Follow-up experiments were then carried out at altered conditions or altered scale (shake flask) to understand the robustness of the results. Improvements in glucaric acid titer of up to 42% were achieved through appropriately timed induction of Pfk activity knockdown during the fermentation.",
"discussion": "4 Discussion Results with IB1486-GA indicate that dynamic control of Pfk activity can be utilized to improve titers of glucaric acid, a product requiring several enzymatic conversions starting from G6P. The system was applicable for use with a semi-defined medium under both batch and simulated fed-batch conditions. While gains in titer were consistent across multiple conditions, the maximum gains were smaller than those observed previously for myo -inositol production in glucose minimal medium ( Brockman and Prather, 2015 ). Previous work with myo -inositol production in glucose minimal medium showed that switching at low cell density was optimal for the largest gains in titer. In T12 medium, these earlier switching times resulted in more rapid escape and little time for conversion of glucose to glucaric acid, perhaps due to the greater expression burden of the complete glucaric acid pathway and the higher availability of nutrients in T12 that “escapers” could use to rapidly grow and overtake the population. The later switching times result in higher usage of glucose for biomass formation, so the amount of glucose processed after switching to production mode is relatively low. While genetic stability can be achieved out to at least 72 h for aTc addition at 24 h, future work may be needed to address genetic stability in longer fermentations and expand the usefulness of switching between growth and production modes. Activity of the downstream enzymes in the glucaric acid pathway is another potential limitation, but in this particular medium, it does not appear that the activity of MIOX, a bottleneck under some other conditions, was limiting overall pathway yield, as minimal buildup of myo -inositol was observed in the cultures. However, balancing of expression between the three pathway enzymes could be an issue, since high level INO1 expression is required for any myo -inositol to be produced for further conversion ( Moon et al., 2009 ). Reductions in INO1 expression upon expression of other enzymes in the glucaric acid pathway would be expected to limit maximum fluxes into the pathway, also limiting the glucose that could be effectively redirected in a given time period. Importantly, IB1486-GA showed titers that were comparable with a wild-type control strain under fed-batch conditions and superior under batch conditions, indicating the genetic modifications required for control of Pfk activity were not detrimental to baseline glucaric acid production and could potentially be transferred into high-performing strains as well. Although the baseline Pfk activity was low in T12 medium, it was still sufficient for rapid growth without excessive overflow metabolism. More consistent success with chromosomal modifications in the K strains led to the initial construction of the Pfk-I control system in that background, but additional improvements in glucaric acid titer, both with and without Pfk knockdown, can likely be achieved by transferring the genetic modifications of IB1486 to an E. coli B strain. In previous work, wild-type BL21 has outperformed MG1655 containing the same pathway genes ( Moon et al., 2009 , Raman et al., 2014 , Shiue et al., 2015 )."
} | 2,486 |
27426418 | PMC4960307 | pmc | 9,015 | {
"abstract": "The ability to reconfigure elementary building blocks from one structure to another is key to many biological systems. Bringing the intrinsic adaptability of biological systems to traditional synthetic materials is currently one of the biggest scientific challenges in material engineering. Here we introduce a new design concept for the experimental realization of self-assembling systems with built-in shape-shifting elements. We demonstrate that dewetting forces between an oil phase and solid colloidal substrates can be exploited to engineer shape-shifting particles whose geometry can be changed on demand by a chemical or optical signal. We find this approach to be quite general and applicable to a broad spectrum of materials, including polymers, semiconductors and magnetic materials. This synthetic methodology can be further adopted as a new experimental platform for designing and rapidly prototyping functional colloids, such as reconfigurable micro swimmers, colloidal surfactants and switchable building blocks for self-assembly.",
"discussion": "Discussion We have demonstrated that chemically triggered wetting–dewetting phenomena can be utilized to engineer shape-shifting colloids with addressable geometries and compositions. This synthetic concept allowed us to design unusually complex colloidal shapes and reproducibly synthesize them in bulk amounts. Because the method is general and applicable to broad spectrum of materials, it can serve as a fast prototyping platform for the preparation of the next generation of non-spherical light-activated swimmers, active Janus surfactants and shape-shifting particles. The reconfigurability, in particular, can open new avenues for fabricating bulk microstructured materials from self-assembled colloidal crystals and enable us to find new rules for geometry-driven assembly processes. An interesting challenge for the future is to engineer smarter hydrophobe layers that could be set on or off on demand. This would allow for the reversibility of the shape shifting and enable, for example, the assembly of switchable devices."
} | 519 |
25631933 | PMC4309967 | pmc | 9,017 | {
"abstract": "The mechanistic understanding of the dynamic processes linking nutrient acquisition and biomass production of competing individuals can be instructive in optimizing intercropping systems. Here, we examine the effect of inoculation with Funneliformis mosseae on competitive dynamics between wheat and faba bean. Wheat is less responsive to mycorrhizal inoculation. Both inoculated and uninoculated wheat attained the maximum instantaneous N and P capture approximately five days before it attained the maximum instantaneous biomass production, indicating that wheat detected the competitor and responded physiologically to resource limitation prior to the biomass response. By contrast, the instantaneous N and P capture by uninoculated faba bean remained low throughout the growth period, and plant growth was not significantly affected by competing wheat. However, inoculation substantially enhanced biomass production and N and P acquisition of faba bean. The exudation of citrate and malate acids and acid phosphatase activity were greater in mycorrhizal than in uninoculated faba bean, and rhizosphere pH tended to decrease. We conclude that under N and P limiting conditions, temporal separation of N and P acquisition by competing plant species and enhancement of complementary resource use in the presence of AMF might be attributable to the competitive co-existence of faba bean and wheat.",
"conclusion": "Conclusions This study demonstrates that temporal cumulative and instantaneous biomass production of wheat and faba bean were closely correlated with dynamic N and P capture by the competing individuals. Wheat is a strong competitor and showed competitive advantages in both N and P acquisition. Faba bean was inferior to wheat in this respect throughout the growth period, possibly due to the early competitive disadvantages of N and P acquisition. Inoculation with AMF mediated wheat-faba bean competition and acted asymmetrically in favor of faba bean. The greater N and P acquisition by mycorrhizal faba bean indicates that AMF enforce complementary resource use between faba bean and wheat, possibly by increasing nitrogen fixation and enhancing P mobilization processes in the rhizosphere. The temporal separation of N and P uptake is also attributable to competitive co-existence of wheat and faba bean. Our results highlight the importance of studying competition processes rather than the single outcome of the final harvest. The mechanistic understanding of the dynamic patterns linking the nutrient acquisition and physiological processes of competing plants can be instructive for optimizing intercropping systems in terms of maximizing both nutrient capture and biomass yields. Recent accumulating evidence indicates that the diversity and richness of AMF are increased in intercropping vs monocropping systems, thus a favorable intercropping system should take account of the indigenous communities of AMF to boost productivity in a sustainable way.",
"discussion": "Discussion Using the approach of Trinder et al 25 we were able to characterize how AMF regulated the competition process of wheat-faba bean in N and P limiting soils, based on the dynamic trajectories of biomass and N and P uptake by the plants. The main finding of the present study is that AMF mediated wheat-faba bean competition and acted asymmetrically in favor of faba bean. Wheat was a strong competitor and had the competitive advantage in both N and P acquisition whereas faba bean was a weak competitor which showed nutrient use complementarity to wheat. The experiment provides interesting results regarding the links between temporal cumulative and instantaneous biomass production and N and P capture to determine how these processes co-varied in competing individuals. In the present study P was the major growth-limiting nutrient, followed by N. Adding 100 mg/kg N did not meet the requirement of the plants throughout the growth period (218.3 mg/kg soil available N vs about 250 mg/pot N taken up by the plants). In addition, the rapid decline in soil Nmin concentration during the 40–60 d period and values near zero from 60 d on, and the depletion of available P from 60 days on indicate that competition was initially due to N, followed by both N and P at later growth stages when the plants entered the reproductive phase ( Fig. 4 ). Competition for N and P was further indicated by the early senescence of non-mycorrhizal faba bean and wheat plants, irrespective of sole growth or growth in mixture ( Fig. 3 ). When in competition, wheat attained the maximum instantaneous N and P capture approximately five days before the point at which it attained maximum instantaneous biomass production. The results indicate that the plants might have detected the competitor and responded physiologically to resource limitation prior to the response of the biomass. Consequently, the numbers of tillers and effective spikes of wheat decreased significantly when competing with faba bean ( Table 3 ). Our results highlight the notion proposed by Trinder et al 26 and others 33 that sequential measurements of the processes linking biomass production and resource capture by the competitors are important in understanding the dynamics and mechanisms of competitive interactions. Competitive capture of other resources (other nutrients and water) was partially excluded in the pot experiments as nutrients (other than N and P) and water were in sufficient supply. Under field conditions temporal competition and complementarity for light and N have been shown to affect the outcome of yield in a durum wheat-winter pea intercropping system 36 . However, the influence of shading cannot be evaluated using the available data although shading was carefully avoided by leaving a considerable space between adjacent experimental pots. The present experiment indicates that wheat is a strong competitor for N and P ( Fig. 1c, e ). Cereals often have a stronger competitive ability to take up N than legumes 37 . When in competition, the maximum instantaneous N and P capture values of uninoculated wheat were 3.59 and 10.95 times higher than those of faba bean ( Table 2 ). In addition, the maximum instantaneous N and P capture of wheat in mixture occurred 3–5 days earlier than those in isolation and the difference continued to the final harvest, particularly at later harvests (~ day 50 at booting stage), indicating a strong neighbor effect on N and P acquisition and the superior competition of wheat proceeding throughout the growth period when wheat shifted from vegetative to reproductive growth. Inoculation increased the magnitude of the difference in instantaneous P uptake by wheat between sole plants and plants in mixture, but did not change the time taken to attain the maximum instantaneous P capture ( Table 2 ). When in competition the instantaneous N and P capture of both non-mycorrhizal and mycorrhizal faba bean remained relatively constant throughout the growth period ( Fig. 2d, f ).The productivity of the cereal relies heavily on N input 38 . The higher competitive ability might be due to the greater root length of wheat and faster root growth compared to faba bean. In addition, the inherited fast growth rate 36 and consequently high demand for N and P by wheat might provide a strong sink to enforce nutrient acquisition. AM fungi are known to affect plant growth and nutrition and thus alter competitive relationships 13 39 40 . In the presence of AMF the biomass of faba bean increased markedly from day 54 until the final harvest, especially when grown separately. The biomass of wheat remained constant regardless of whether it was grown separately or in mixture ( Fig. 1a ). This study confirms previous studies indicating that wheat is less AMF-dependent 41 , although AMF mediated P uptake might be still active with no increase in P content and biomass 42 43 . By contrast, a strong positive response by faba bean to AMF inoculation was observed ( Fig. S1 ), as indicated by the substantial promotion of plant growth ( Fig. 1b ) and increase in flowers and pods ( Fig. S2 ) of faba bean in the presence of F. mosseae when grown separately. Our results indicate that when in competition AMF asymmetrically favored faba bean ( Fig. 1b ). These results are partly in agreement with previous studies showing that AMF favored legumes when competing with grass species 15 40 . However, these studies and other AMF-related plant competition experiments 44 45 suggest that species that perform better in association with AMF are able to increase their own nutrient uptake and lead to a growth depression in the neighboring competing plant species. In the present study, in the presence of AMF the increased growth of faba bean did not inhibit wheat growth, and the competitive advantages of wheat persisted throughout the growing period. It is unlikely that inoculation with F. mosseae asymmetrically supplied soil nutrients to faba bean, as both instantaneous P and cumulative P capture by wheat were also greatly enhanced ( Fig. 2c, e ). Thus, root competition alone cannot explain the pattern of plant growth, and mycorrhiza-mediated resource competition is important. The most likely explanation for competitive enhancement of mycorrhizal faba bean is that complementarity resource use between faba bean and wheat is enforced by AMF. This is reflected in the dynamic patterns of both N and P acquisition. In the absence of AMF, Nmin and available P were mostly taken up by wheat while soil N and P were less available for faba bean ( Fig. 4 ). In the presence of AMF, although wheat was still able to take up Nmin and P, AMF might have increased N 2 fixation and mobilized P sources otherwise not available to wheat, and thus increased N and P uptake by faba bean. AMF are known to affect N 2 fixation in legumes by increasing the numbers of nodules, nitrogenase activity, the leghaemoglobin content of nodules, and shoot biomass 46 . The increase in N-content may be a consequence of a P-mediated stimulation of N 2 -fixation by mycorrhiza 47 . In the present study the calculated N derived from N 2 fixation at harvest was greatly increased in the mycorrhizal faba bean ( Fig. S3 ). However there was no significant difference in nodule numbers between inoculated and uninoculated faba bean ( Fig. S4 ). With respect to P, accumulating evidence shows that faba bean is effective in P acquisition and thus is less dependent on P fertilization or P sources 7 48 . Compared to wheat, the large seeds of faba bean contain high P concentrations ( Tab. S4 ) and thus can provide sufficient P for faba bean growth at early growth stages. Faba bean shows strong rhizosphere activities including the exudation of carboxylates 48 and acid phosphatase activity, and soil acidification 7 which help the plants to mobilize P under P limiting conditions. In the present study, as summarized in Fig. 5 , AMF might increase P acquisition of faba bean by enhanced exploration of soil P not available to plant roots by the external mycelium, or increase the exudation of citrate and malate and decrease the rhizosphere pH ( Table 4 ). Faba bean has been shown to take up P from organic-P 49 and AMF might increase P uptake from organic P via enhanced ALP activity of the host plants 50 . It is also likely that mycorrhiza-mediated rhizosphere changes might facilitate P uptake by competing wheat and this needs further investigation. Interspecific P facilitation is highlighted to contribute to overyielding in intercropped maize and faba bean in both pot 48 49 and field 32 experiments. In addition, mycorrhizal faba bean requires extra P for nitrogen fixation, and N 2 fixation might further affect P mobilization in the rhizosphere of faba bean. Faba bean and wheat are interconnected by mycorrhizal networks. Previous studies have shown that N fixed by legumes can be transferred to neighboring cereal crops 51 . Trivial N transfer has also been reported 52 . In addition, interspecific P facilitation from larger plants can relieve P deficiency in smaller plants 12 23 . However, recent studies show that competition for P favors the larger and older plants ( Cucumis sativus ) over smaller and younger seedlings ( Solanum lycopersicon ) 19 , and P limitation between interspecific ( Linumusitatis simum vs Sorghum bicolor ) 53 and intraspecific plants ( Andropogon gerardii ) led to size inequality 54 . We did not directly demonstrate N and P transfer between faba bean and wheat. However, on the basis of the results of the present experiments, direct transfer of N and P via CMNs may be minor as wheat and faba bean are in strong competition for limiting soil N and P throughout the growth period. Mechanisms underlying CMNs in plant competitive outcomes are highly complex 19 . Facilitation and/or competition may depend on the identity and diversity of AM fungal species 53 , the age and size of the plants 12 , and the supply levels of important nutrients. A number of studies on legume-cereal interactions have demonstrated that temporal niche separation may be attributable to competition dynamics 55 . In the present study the temporal dynamics of growth and nutrient uptake by wheat and faba bean showed some complementarity. In the absence of AMF, pre-emption of soil nutrients by wheat led to relatively low and constant instantaneous N and P acquisition by faba bean. Consequently, low P and high cost for N 2 fixation inhibited the growth of faba bean throughout the growth period. Our results support the notion that a small difference in early competition exerts a large effect on overall competition during the whole crop development phase 56 . In the presence of AMF the significant correlations between biomass production of faba bean and N and P uptake throughout the growth period indicate that N and P are synergistically enhanced by AMF and consequently lead to increased competitive ability of faba bean ( Fig. 1b, d, f ). The time taken to attain maximum instantaneous P uptake by mycorrhizal faba bean was very similar to that taken by competing wheat and 16 days prior to maximum N uptake by faba bean. Maximum N uptake by faba bean occurred six days later than by competing wheat ( Table 2 ). These results indicate that faba bean depends on AMF to supply the extra P required for nitrogen fixation, and temporal separation of N and P acquisition by wheat and faba bean is important for the competitive co-existence of faba bean and wheat ( Fig. 5 ). Future experiments should incorporate sequential measurement of N 2 fixation activity and P requirement of the root nodules on the legume."
} | 3,657 |
29463739 | PMC5877936 | pmc | 9,020 | {
"abstract": "Significance Bioproduction of chemicals offers a sustainable alternative to petrochemical synthesis routes by using genetically engineered microorganisms to convert waste and simple substrates into higher-value products. However, efficient high-yield production commonly introduces a metabolic burden that selects for subpopulations of nonproducing cells in large fermentations. To postpone such detrimental evolution, we have synthetically addicted production cells to production by carefully linking signals of product presence to expression of nonconditionally essential genes. We addict Escherichia coli cells to their engineered biosynthesis of mevalonic acid by fine-tuned control of essential genes using a product-responsive transcription factor. Over the course of a long-term fermentation equivalent to industrial 200-m 3 bioreactors such addicted cells remained productive, unlike the control, in which evolution fully terminated production.",
"discussion": "Discussion Synthetic product addiction is a concept for linking costly, high-yield metabolite production to cellular growth by a product-responsive biosensor regulating nonconditionally essential genes. We have engineered and shown that such a design can prevent formation of detrimental genetic heterogeneity and be implemented without use of classical selection phenotypes (nutrient prototrophies or antibiotic resistance). Previous biosensor-based designs for product monitoring have harnessed classical conditional selection genes in library-wide selections ( 18 , 19 ) and for enrichment of phenotypic overproducing subpopulations ( 5 ); however, medium amendments such as antibiotics are not feasible for most fermentation products due to cost and regulatory restrictions ( 33 ). Instead, using the endogenous selective pressure of carefully tuned essential genes, we have shown that an addiction design can significantly stabilize mevalonic acid production to industrially relevant cultivation scales, despite a considerable production load of a high-yielding pathway. Although difficult to detect at a population level and on a laboratory scale, evolution is a constraining factor in the performance of bio-production strains ( 8 , 12 ). Biosensor-based product addiction is agnostic to the mechanisms of production declines: By assessing the product, the concept works at the level of the intended phenotypic outcome and thus redirects evolutionary forces for the benefit of an engineered strain design. Addressing such production declines mechanistically is normally a research-intensive step in bioprocess development that faces two fundamental biological factors, namely the spontaneous escape rate from the engineered pathway (e.g., by mobile element transposition, recombination, and replication errors) and the selective production load (e.g., by metabolic toxicities and burdens of biosynthesis). A genome-reduced E. coli strain, MDS42, free of mobile elements may, e.g., provide significant life-time extension to dispensable heterologous pathways ( 34 ), although not necessarily better starting-point production ( 8 ). Classic selection schemes with biosensors (PopQC) can enrich phenotypically better subpopulations ( 5 ), although this requires medium amendments while the necessary tuning and potential to ensure favorable evolutionary stability of such systems are unknown. Pathway toxicities may be addressed using adaptive laboratory evolution strategies or dynamic pathway activation ( 1 , 35 ). Combined, these approaches require significant strain redesign and insight into the specific error modes, which makes systems for continuously maintaining correct fermentation populations appealing. Dynamic, nonconditional addiction to production is therefore an attractive alternative strategy to avoid unpredictable, detrimental error modes from limiting bioprocesses at scale. Synthetic population maintenance should fundamentally require milder growth penalties than library-wide genetic screens, which prompted our use of endogenous cell processes as growth regulators, which are nonconditional in contrast to classical selection genes (design criterion 1). We successfully used the folP-glmM operon; however, other nonconditionally essential processes such as polymerases, gyrases, or toxin/antitoxin systems might also be useful. In designs for biocontainment of genetically engineered organisms, cells have been addicted to supplemented molecules, thereby preventing unintended environmental release ( 36 – 39 ). Such systems have utilized conditional expression of essential genes in circuits that rendered cells strictly viable only under certain conditions such as enzyme redesign for synthetic dependency on a nonconventional amino acid ( 37 ). Using endogenous cell processes, we have demonstrated that synthetic biology can be used to confine a cell to an engineered, costly production genotype. To not unduly compromise bioprocess economics, we evaluated the biosynthetic consequence of our essential process perturbation to ensure that the initial isogenic population did not lose production performance by pleiotropic effects (design criterion 2). An important consideration for synthetic selection designs are the evolutionary forces that promote mutation of critical control nodes. This risk has previously pointed to a need for redundantly layered or toggled selections to prevent escapes due to a single mutation ( 18 , 19 , 36 ). In product addiction, we aimed for such redundancy by the coupling of two systems (production and its addiction), which must mutate individually before escape, while only the production system confers significant reduction in fitness (design criterion 3). Growth restrictions would also delay biomass formation and hence lower the overall process productivity, which effectively increases the required bioreactor capacity ( 9 ). A weakness of our system is the concurrent regulation of two essential genes in an operon, which means that a single mutation in the sensor promoter could cause escape despite two actuating genes. However, we did not observe this in the present study, likely due to our tuning of the system to minimize fitness cost. Product addiction is best suited as a sentinel of product pathways that are active during phases of cellular growth and therefore costly to maintain. This relation is also important since addiction depends on sufficient sensor saturation. Pathways strictly active in stationary growth phase may inherently experience lower genetic instability and be incompatible with a product addiction scheme. Implementation of product addiction systems requires a product-responsive biosensor with a sensitivity that dynamically matches the operational intracellular concentrations in the ideally biosynthetic cells. Sensitivity becomes especially important as extracellular product theoretically might diffuse to cross-feed nonproducing cheater cells and consequently bypass the addiction system. We therefore also searched for nonproductive subpopulations by time-lapse deep sequencing and phenotypic characterization of the fermentation lineages ( Figs. 3 and 4 ) yet did not observe evolving escapes in the addicted lineages. Industrial practice of passing cultures to seed trains of increasing volumes before final scale likely dilutes the product at early stages ( 9 ). However, to bridge the sensitivity gap, sensor tuning may also become important to selectively match the high intracellular concentrations of commercialized cell factory strains, e.g., by directed sensor evolution ( 40 ) or signal-processing buffers ( 41 ). Furthermore, sensor mutagenesis by rational and random approaches have lately shown success in changing transcription factor specificity for recognition of new biological ligands ( 42 , 43 ). This will be important to enable more matching pairs of sensors with high-yielding, loaded metabolic pathways and bring molecular biosensors to work in large-scale fermentations. Not only sensing for the pathway end product, recent molecular or whole-cell biosensors may indeed prove their worth in bioprocessing by, e.g., monitoring of lactate, glycolytic flux or pH levels, and accordingly expand the applicability of product addiction strategies ( 44 , 45 ). In conclusion, we have demonstrated the concept of a synthetic product addiction system, which prevents genetic heterogeneities of nonproducing subpopulations from forming in long-term fermentation with a high-yielding mevalonic acid pathway. We anticipate that utilization of such product addiction systems could significantly aid the robust industrial scale-up of bio-production pathways to maintain a wide range of chemicals and cellular states."
} | 2,177 |
29659511 | PMC5924552 | pmc | 9,023 | {
"abstract": "The pathogen Agrobacterium induces gall formation on a wide range of dicotyledonous plants. In this bacteria, most pathogenicity determinants are borne on the tumour inducing (Ti) plasmid. The conjugative transfer of this plasmid between agrobacteria is regulated by quorum sensing (QS). However, processes involved in the disturbance of QS also occur in this bacteria under the molecular form of a protein, TraM, inhibiting the sensing of the QS signals, and two lactonases BlcC (AttM) and AiiB that degrade the acylhomoserine lactone (AHL) QS signal. In the model Agrobacterium \n fabrum strain C58, several data, once integrated, strongly suggest that the QS regulation may not be reacting only to cell concentration. Rather, these QS elements in association with the quorum quenching (QQ) activities may constitute an integrated and complex “go/no go system” that finely controls the biologically costly transfer of the Ti plasmid in response to multiple environmental cues. This decision mechanism permits the bacteria to sense whether it is in a gall or not, in a living or decaying tumor, in stressed plant tissues, etc. In this scheme, the role of the lactonases selected and maintained in the course of Ti plasmid and agrobacterial evolution appears to be pivotal.",
"introduction": "1. Introduction Members of the Agrobacterium genus are α-proteobacteria that belong to the family Rhizobiaceae. They are plant pathogens, and may induce a disease known as crown gall on a wide range of dicotyledonous plants. The gall formation results from a genetic transformation process that relies upon the transfer of a piece of DNA, the transferred DNA (T-DNA), from the bacteria to the plant cell. In the bacteria, the T-DNA is located on the Ti (tumor-inducing) plasmid that carries most of the virulence determinants. The T-DNA transfer occurs via the activation of virulence ( vir ) genes. These genes encode a type IV secretion system (T4SS) and they are transcribed under moderately acidic conditions, mostly in response to the presence of phenolics such as acetosyringone or sinapinic acid, produced by wounded plant tissues as part of the defense reaction mechanisms (for reviews on the disease induction and genetic transformation formation process, see [ 1 , 2 , 3 , 4 , 5 , 6 , 7 ]). Once in the plant cell, the T-DNA is transferred to the nucleus, and it integrates into the nuclear genome. The T-DNA genes are then expressed. They encode two major functions: (i) the production of two plant hormones, i.e., auxin and cytokinins, the concomitant production of which induces the cell proliferation and the formation of the tumor [ 8 , 9 , 10 ]; and, (ii) the synthesis of low molecular weight molecules called opines, that are characteristic of Agrobacterium -induced overgrowths (for reviews: [ 4 , 5 , 6 , 7 , 8 , 9 , 10 , 11 ]). Opines play critical roles in Agrobacterium ecology. First, they are used by the inciting agrobacteria as specific growth substrates, the genetic determinants involved in the degradation of opines being borne on the tumour inducing (Ti) plasmid (e.g., [ 12 , 13 ]). Second, some opines are inducers of the conjugative transfer of the Ti plasmid which also depends on a second T4SS encoded by the Ti plasmid. Opines in tumors therefore contribute both to the multiplication of the pathogen and the dissemination of the pathogenic traits amongst the agrobacterial population, which in nature mostly consists in Ti-plasmid free cells (for reviews: [ 11 , 14 , 15 ])."
} | 873 |
26657763 | PMC5029188 | pmc | 9,024 | {
"abstract": "Nitrite-oxidizing bacteria (NOB) of the genus Nitrospina have exclusively been found in marine environments. In the brine–seawater interface layer of Atlantis II Deep (Red Sea), Nitrospina -like bacteria constitute up to one-third of the bacterial 16S ribosomal RNA (rRNA) gene sequences. This is much higher compared with that reported in other marine habitats (~10% of all bacteria), and was unexpected because no NOB culture has been observed to grow above 4.0% salinity, presumably due to the low net energy gained from their metabolism that is insufficient for both growth and osmoregulation. Using phylogenetics, single-cell genomics and metagenomic fragment recruitment approaches, we document here that these Nitrospina -like bacteria, designated as Candidatus Nitromaritima RS, are not only highly diverged from the type species Nitrospina gracilis (pairwise genome identity of 69%) but are also ubiquitous in the deeper, highly saline interface layers (up to 11.2% salinity) with temperatures of up to 52 °C. Comparative pan-genome analyses revealed that less than half of the predicted proteome of Ca. Nitromaritima RS is shared with N. gracilis . Interestingly, the capacity for nitrite oxidation is also conserved in both genomes. Although both lack acidic proteomes synonymous with extreme halophiles, the pangenome of Ca. Nitromaritima RS specifically encodes enzymes with osmoregulatory and thermoprotective roles (i.e., ectoine/hydroxyectoine biosynthesis) and of thermodynamic importance (i.e., nitrate and nitrite reductases). Ca. Nitromaritima RS also possesses many hallmark traits of microaerophiles and high-affinity NOB. The abundance of the uncultured Ca. Nitromaritima lineage in marine oxyclines suggests their unrecognized ecological significance in deoxygenated areas of the global ocean.",
"conclusion": "Conclusions Although NOB have an important role in oceanic nitrification and have great phylogenetic diversity and distribution, our understanding of their functions and ecology in the global ocean has generally lagged behind that of their ammonia-oxidizing counterparts, mostly due to the paucity of cultivated marine representatives. This is unfortunately true for members of the proposed phylum Nitrospinae , despite of their prevalence in large swaths of the suboxic ocean. Using single-cell genomics, we show here that the abundant Nitrospina -like bacteria in the BSI of Atlantis II Deep encompass a novel lineage within this phylum (referred to here as Ca. Nitromaritima RS), which is divergent from all cultivated Nitrospina species. Most importantly, we show that these single-cell genomes possess the genetic repertoire for nitrite oxidation, which implies that the uncultured lineages of the phylum Nitrospinae are probably all capable of nitrite oxidation. Using metagenomic fragment recruitment, we also show that Ca. Nitromaritima-like but not Nitrospina -like genotypes are abundant in the anoxic and hypersaline, deeper convective layers of Atlantis II Deep. Genomic data indicate that Ca. Nitromaritima RS possess machineries for taking up a mixture of osmolytes as well as for the biosynthesis ectoine/hydroxyectoine, and are thus capable of combating salt stress. The predicted potential to use nitrate as an alternative electron acceptor coupled putatively to the oxidation formate or hydrogen might be crucial in adapting to the microoxic, polyextreme brine environment.",
"introduction": "Introduction The genus Nitrospina encompasses chemolithoautotrophic nitrite-oxidizing bacteria (NOB), which catalyse the oxidation of nitrite to nitrate, to meet the energy demands for their general metabolism and the fixation of carbon ( Lücker and Daims, 2014 and references therein). Ribosomal RNA (rRNA) gene sequences related to members of this genus have exclusively been detected in marine environments, where they are abundant below the euphotic zone and in mesopelagic waters (~10% of all bacteria), and exhibit a preference for marine sediments and oxygen minimum zones ( Fuchs et al. , 2005 ; Mincer et al. , 2007 ; Santoro et al. , 2010 ; Zaikova et al. , 2010 ; Füssel et al. , 2012 ; Beman et al. , 2013 ; Nunoura et al. , 2015 ). Recent phylogenomic-based analyses of the draft genome of Nitrospina gracilis 3/211 ( Lücker et al. , 2013 ) placed this type species, which was isolated from the Atlantic Ocean (200 miles off the mouth of the Amazon River ( Watson and Waterbury, 1971 ), into a novel bacterial phylum ( Nitrospinae ). Besides N. gracilis , the only other so far cultivated species of this genus is N. watsonii , which was isolated from the suboxic zone of the Black Sea ( Spieck et al. , 2014 ). However, both are phylogenetically closely related and represent only a minor fraction of the vast Nitrospinae 16S rRNA gene sequence diversity in marine environments ( Lücker and Daims, 2014 ). A recent 16S rRNA gene-based high-throughput survey of bacterioplankton in the brine–seawater interface (BSI) of several brine pools in the Red Sea revealed that Nitrospina -like bacteria constituted up to one-third of the bacterial community in the BSI of Atlantis II Deep ( Ngugi et al. , 2015 ). In this oxic–anoxic transition layer, nitrite was undetectable (<0.1 μ M ), and extremely low concentrations of dissolved oxygen (DO 2 ; ~2.2 μ M ; Ngugi et al. , 2015 ) and inorganic phosphate (<1 μ M ; Bougouffa et al. , 2013 ) were encountered. Also, temperature (32 °C), salinity (5.6%) and heavy metal concentrations were higher compared with that in the normal deep-seawater ( Ngugi and Stingl, 2012 ; Ngugi et al. , 2015 ). In comparison, putative NOB have been found to constitute only 2–4% of the overall bacterioplankton community in the overlying oxygenated water column (200–1500 m) that is characterized by isothermal (22 °C) and isohaline (~4.1%) conditions ( Qian et al. , 2011 ; Bougouffa et al. , 2013 ). We therefore speculated that the oxic–anoxic interface layers of deep hypersaline anoxic basins ( Antunes et al. , 2011 ) could be potential ‘hotspots' for Nitrospinae . How such NOB thrive in the polyextreme BSI remains unclear as no NOB culture has been observed to grow at above 40 g NaCl l –1 ( Oren, 2011 ), presumably due to the low net energy gained from their metabolism (Δ G 0 ′=–74 kJ mol –1 NO 2 – ), which is insufficient for both growth and osmoregulation ( Oren, 1999 ). Considering the significant divergence of 16S rRNA gene sequences of diverse Nitrospinae representatives ( Lücker and Daims, 2014 ), and the stark physicochemical differences between the BSI of Atlantis II Deep (high salinity and temperature, deeper depth) and the natural habitats of both Nitrospina species described to date (less salinity, shallow water depth; ( Watson and Waterbury, 1971 ; Spieck et al. , 2014 ), we were prompted to investigate the phylogenetic diversity of Nitrospina -like NOB in the BSI of Atlantis II Deep in detail. We also explored the potential genetic basis for their abundance and probable success in the polyextreme BSI environment using single-cell genomics ( Lasken, 2012 ; Stepanauskas, 2012 ).",
"discussion": "Results and discussion Phylogenetic placement of our single-cell genomes A recent survey of bacterioplankton communities in the BSI of Atlantis II Deep (~2.0 km below the central Red Sea) demonstrated that Nitrospina -like bacteria are relatively abundant in this brine pool ( Ngugi et al. , 2015 ). Based on phylogenetic analyses of rRNA gene sequences from two SAGs, which were obtained from the BSI of the same brine pool, we now show that these abundant Nitrospina -like bacteria are highly diverged from N. gracilis ( Watson and Waterbury, 1971 ). Although the rRNA gene sequences of our SAGs are 99.9% identical, their 16S and 23S rRNA genes have identities of only 92% and 85%, respectively, to that of N. gracilis ( Figures 1a and b ). Phylogenetic analyses also indicate that the rRNA gene sequences of both N. gracilis and our SAGs form distinct lineages within the newly proposed candidate Phylum Nitrospinae ( Lücker et al. , 2013 ; Figure 1 ). The distant affiliation of RS-SAGs to cultivated Nitrospina species at the rRNA gene level implies that they represent a novel uncultured lineage within this phylum. Phylogenetic analyses based on 16S rRNA genes also indicate that the sequence groups of this novel lineage consist of two phylogenetically discrete groups (Clades 1 and 2) that have an average between-clade sequence dissimilarity of 8.4% ( Supplementary Table S2 ). The intraclade average distances range from 3.5% (Clade 1) to 7.3% (Clade 2) at the 16S rRNA gene level, which suggests that the sequences within these clades most likely encompass two separate genera based on the 95% sequence-identity threshold for this taxonomic rank ( Hugenholtz et al. , 1998 ). A robust phylogenetic analysis carried out using the ITS region between the 16S and 23S rRNA genes ( Figure 1c ) indicated further that there are at least five subclusters within Clade 1 (mean pairwise ITS distance of 24.7%), which are distinct from lineages represented by the uncultured Clade 2 and the type species N. gracilis . Clade 1 encompasses sequences from our single cells and also a representative of the most predominant Nitrospina -like sequence cluster in the BSI of Atlantis II Deep and Discovery Deep (accession no.: KM018337; Guan et al. , 2015 ); representatives of this cluster have an abundance of 80–89% relative to all Nitrospina -like sequences in a recent 454 data set of the same locations ( Ngugi et al. , 2015 ; Supplementary Figure S1 ). It also contains two large-insert DNA fragments (accession nos. EU795196 and KF170415) from the Saanich Inlet (125–500 m depth; ( Wright et al. , 2013 ). Interestingly, two publicly available single-cell genomes from the mesopelagic waters of the North Pacific (Station ALOHA, 770 m; SCGC AAA288-L16; Swan et al. , 2011 ) and the North Atlantic (Station Archimedes 4, 511 m; SCGC AB-629-B18) that are 99.5% identical at the 16S rRNA gene level, also affiliate with Clade 1. Our SAGs show identities of only 95% (16S), 93% (23S), and 76% (ITS) to these SAGs from the Atlantic and Pacific Oceans, suggesting that they might consititute a different species. Similarly, Clade 2 is comprised of two fosmid clones from the Montery Bay (Station M1; EB080L20_F04; Mincer et al. , 2007 ) and HOT (station ALOHA; HF0200_07G10; Rich et al. , 2011 ), plus three low-abundance, Nitrospina -like sequences (<1% of all bacterial clones; Guan et al. , 2015 ) from the BSI of three brines in the Red Sea (Erba, Nereus and Kebrit). Because Clade 1 forms a separate cluster from Clade 2 and that of N. gracilis , and considering the average interclade 16S sequence identity of ~91% ( Supplementary Table S2 ) as well as the prominence of Clade 1 sequences in marine environments, we accordingly propose a new provisional genus for Clade 1, ‘ Candidatus Nitromaritima' (latin, maritima ; belonging to the sea). Genome features of Nitrospinae SAGs To get a broader insight into the genomic traits of the two Ca. Nitromaritima SAGs from Atlantis II Deep, we compared their genomic features with those of N. gracilis 3/211 ( Lücker et al. , 2013 ) and the Ca. Nitromaritima SAGs from the oxygenated mesopelagic zone of the North Atlantic and North Pacific oceans ( Table 1 ). The draft genome assemblies of SAGs from the Red Sea (RS-SAGs) consist of 88 (SCGC AAA799-C22) and 97 (SCGC AAA799-A02) contigs with a total size of 1.40–1.68 Mbp. Although GC biases cannot be ruled out completely from the MDA and sequencing procedures ( Yilmaz et al. , 2010 ), the GC content of RS-SAGs (~50%) is higher compared with that in Ca. Nitromaritima SAGs from the Atlantic (SCGC AB-629-B06 and SCGC AB-629-B18) and the Pacific (SCGC AAA288-L16) of ~40% both are also lower compared with that of N. gracilis (56% GC). Based on a proposed set of 104 single-copy genes found universally in sequenced bacterial genomes ( Parks et al. , 2015 ; Supplementary Table S3 ), we estimated that our SAGs are 20–40% complete, whereas the Ca. Nitromaritima SAGs from the Atlantic and Pacific Oceans (0.71–2.04 Mbp in size) have an estimated completeness of 30–75%. Thus, the complete Ca. Nitromaritima genome would be around 2.71 Mbp ( Supplementary Table S3 ), which is slightly smaller than the 3.2-Mbp genome of N. gracilis ( Lücker et al. , 2013 ). Analogous to N. gracilis , >70% of the protein-coding genes in RS-SAGs were predicted functional, with 64% of their pan-proteomes having homologues in the phyla δ -Proteobacteria , Firmicutes , γ- Proteobacteria and Nitrospirae ( Supplementary Figure S2 ). Results of blast-based multiple alignments of genome pairs indicate that the assembled RS-SAGs overlap by 43–52%, with a corresponding ANI of 99% ( Supplementary Table S5 ). These two share 46–55% of their predicted proteins and the AAI of orthologues is high at ~97% ( Figure 2 ). Thus, as expected, over 94% of the 723-shared orthologues were predicted to be syntenic in RS-SAGs, and therefore potentially functionally conserved. However, when the RS-SAGs were compared with the mesopelagic NP- and NA-SAGs, and to N. gracilis , the overlapping genomic fraction was only 11–20%, whereas the ANI values ranged from ~67% to 69%. Only 30–38% of the predicted proteins of N. gracilis and the Nitrospina -like SAGs from the Atlantic and Pacific oceans are predicted to have orthologues in RS-SAGs, and at relatively low identity levels (58.6–69.6% AAI; Figure 2 ). Despite this, 49% of the orthologues shared by RS-SAGs and N. gracilis are predicted to be syntenic, which suggests that many functions are still conserved between these divergent Nitrospinae lineages. Considering the currently accepted genome-based operational boundaries for species circumscription at the nucleotide (>95% ANI) and proteome (66–72% AAI) levels ( Konstantinidis and Tiedje, 2007 , and references therein), this additionally supports a novel genus-level placement of the Nitrospina -like RS-SAGs within the proposed phylum Nitrospinae ( Lücker et al. , 2013 ). Capturing the genotypic diversity of marine Nitrospinae bacteria Given the above phylogenomic scenario, we next evaluated the suitability of cultivated Nitrospinae members (i.e., N. gracilis ) for capturing the diversity of environmental marine clades through comparative fragment recruitments ( Rusch et al. , 2007 ). Based on the coverage and average identity of recruited metagenomics reads against the genome of N. gracilis ( Lücker et al. , 2013 ) and SAGs ( Figure 3 ), our analyses show that close relatives of Ca. Nitromaritima but not N. gracilis , are abundant in the BSI of Atlantis II Deep and the ETSP-OMZ. Here, both Ca. Nitromaritima SAGs from the Red Sea (SCGC AAA799-C22) and the Pacific Ocean (SCGC AAA288-L16) recruited significantly more reads than N. gracilis ( Figure 3a ). The level of recruitment by N. gracilis was surprisingly low (<0.1% of sequence data) even in marine environments, which are known to harbour an abundant (up to 9% of the bacterioplankton) and active ‘ Nitrospina ' community ( Beman and Carolan, 2012 ; Allers et al. , 2013 ; Beman et al. , 2013 ). These results not only corroborate the ubiquity of Nitrospina -like bacteria in OMZs ( Füssel et al. , 2012 ; Beman et al. , 2013 ) but also place representatives of the Ca. Nitromaritima clade as the numerically dominant ‘ Nitrospina '-like NOB in the BSI (Red Sea) and in the OMZ (ETSP) habitats. An extremely low degree of recruitment (<0.1% coverage) was observed also from genomes of other marine-associated NOB ( Figure 3a ), including the unpublished genomes of Nitrococcus mobilis ( Watson and Waterbury, 1971 ) and Nitrospira marina ( Watson et al. , 1986 ), which were obtained from the IMG database ( Markowitz et al. , 2014 ). This implies that the genotypes related to these cultured marine NOB are numerically insignificant in the photic and mesopelagic zones of the Red Sea and the ETSP-OMZ, which is consistent with the niche separation observed between Nitrospina and Nitrococcus species ( Füssel, 2014 ), and between Nitrospina and Nitrospira species ( Nunoura et al. , 2015 ). It also reflects their different metabolic strategies, for example, Nitrospina sustains growth at low oxygen and nitrite concentrations ( Lücker et al. , 2013 ; Nowka et al. , 2015 ), whereas Nitrococcus adopts an organoheterotrophic lifestyle similar to Nitrobacter ( Spieck and Bock, 2005 ; Füssel, 2014 ). Although high salinity is generally recognized to constrain the success of NOB, with >40 g NaCl l –1 (or 4.0% salinity) reported as being inhibitory ( Oren, 2011 ), our results suggest that Ca. Nitromaritima species possibly have a broader salinity (and temperature) range in contrast to this previous assumption. This is evidenced from the increasingly higher recruitment coverage (from ~0.1% to 0.6%) and constantly higher ANI (94±4%) of recruited reads from the overlying 1500-m deep-sea layer towards the first three convective layers of Atlantis II Deep ( Figure 3b ). In these environments, salinity varies from 4.1% to 15.4% and temperature ranges from 22 to 65 °C ( Ngugi et al. , 2015 ). Moreover, Ca. Nitromaritima sequences are also relatively more abundant in the BSI of the adjacent Discovery Deep (~0.3% coverage, 95±4% identity; 13.8% salinity) than in the sulphide-rich BSI and brine of Kebrit Deep (<0.1% coverage; 18.2% salinity). In both of these cases, however, ‘ Nitrospina '-like 16S rRNA genes constitute only about 2% of the bacterial community. Hence, the differential recruitment success observed between the two Ca. Nitromaritima SAGs from the Red Sea and the North Pacific —both being highest in their geographical locations where they were isolated from ( Figure 3a ) —is possibly due to habitat-specific physicochemical differences, which in turn reiterates the phylogenotypic divergence of this group ( Lücker and Daims, 2014 ; this study). The pan-genome of Ca. Nitromaritima RS As our main objective was to elucidate potential metabolic attributes differentiating RS-SAGs from their closest cultivated sibling ( N. gracilis ), we next conducted comparative (pan)-genome analyses through the phylogenomic platform EDGAR ( Blom et al. , 2009 ). For clarity, the pan-genome of RS-SAGs, which we simply refer to as Ca. Nitromaritima RS, as they represent cells of the same species (99% ANI and 97% AAI) that are derived from the same sample and location, is defined here as the total non-redundant gene inventory of their ‘core' and ‘variable' genome sets. The pan-genome of Ca. Nitromaritima RS encompasses 2291 genes with a core set of 723 genes, whereas that estimated for the North Atlantic SAGs (or Ca. Nitromaritima NA) comprises of 2492 genes and a core geneset of 482. Hence, the pan-genome size of Ca. Nitromaritima RS is also in the same range as the individual genomes of Ca. Nitromaritima sp. NP (2182 genes) and N. gracilis (2965 genes), which should allow for meaningful comparitive (pan)-genomics. The COG categories J (translation, ribosomal structure and biogenesis) and T (signal transduction mechanisms) are, respectively, under- and over-represented in Ca. Nitromaritima RS, as compared with the Ca. Nitromaritima SAGs from the Atlantic and Pacific oceans ( Figure 4a ). Notably, the number of signal-transducing histidine kinases (30 vs 4–8) and response regulators (56 vs 9) are higher in Ca. Nitromaritima RS and N. gracilis relative to the other Ca. Nitromaritima SAGs ( Figure 4b ). Although these two-component systems may not solely be required for adapting to the polyextreme environments of Atlantis II Deep as they are abundant also in N. gracilis , their unequal distribution among closely related Ca. Nitromaritima species, however, implies that Ca. Nitromaritima RS uses an extensive, albeit unknown array of interactions that are varied from its mesopelagic counterparts. To fully characterize the genomic content and metabolic (dis)similarities between Ca. Nitromaritima RS and N. gracilis , we performed further comparisons between these two data sets. Using the N. gacilis genome as a reference, we found that it shared 1087 genes with Ca. Nitromaritima RS, and that 1204 and 1878 genes were unique to Ca. Nitromaritima RS and N. gracilis , respectively ( Figure 4c ). Although the core genome is relatively large and accounts for 36.7–47.4% of their protein-coding genes, we also observed that this proportion drops to ~23% when the Atlantic and Pacific Ocean SAGs are included ( Supplementary Figure S3 ), implying an even greater diversity among the marine Nitrospinae lineages. Besides housekeeping, defence and transport functions, the core genome of N. gracilis and Ca. Nitromaritima RS is predicted to encode the genetic repertoire for nitrite oxidation as detailed below. Additionally, with the exception of some key enzymes of the tricarboxylic acid cycle (TCA; Hügler and Sievert, 2011 ), namely pyruvate:ferredoxin oxidoreductase (PFOR), 2-oxoglutarate:ferredoxin oxidoreductase (OGFOR), succinyl-CoA synthase, succinate dehydrogenase and phosphoenolpyruvate carboxykinase, all other enzymes are missing in Ca. Nitromaritima RS, presumably due to the low coverage of the RS-SAGs. The SAGs from the Atlantic and Pacific oceans possess (in addition to PFOR and OGFOR) the ATP-dependent citrate lyase that is key for the reductive tricarboxylic acid pathway, and which is present also in N. gracilis ( Lücker et al. , 2013 ). Enzymes for anaplerotic TCA reactions are also present in the core genome of N. gracilis and Ca. Nitromaritima RS ( Supplementary Table S6 ), including those for replenishing pyruvate (via alanine dehydrogenase), oxaloacetate (via oxaloacetate decarboxylase or aspartate oxidase) and fumarate (via adenylosuccinate synthetase and adenylosuccinate lyase). Although the functionality of reductive TCA enzymes requires experimental confirmation, it is probable that this pathway represents the universal CO 2 fixation mode for members of this phylum. Interestingly, the predicted PFOR of both Nitrospina and Ca. Nitromaritima RS—and not the Atlantic or Pacific SAGs—colocalizes with a rubrerythrin-like protein upstream of the PFOR operon ( Supplementary Figure S4 ). This indicates that the putative rubrerythrin could be important for protection against oxidative damage ( Sztukowska et al. , 2002 ) as all Nitrospinae genomes lack classical reactive oxygen defence mechanisms (e.g., catalase and superoxide dismutase; Lücker et al. , 2013 ; this study); alternatively, the peroxidases in their genomes might also serve this purpose. Interestingly, unlike the almost complete genome of N. gracilis (and the other three Nitrospina -like SAGs), Ca. Nitromaritima RS is predicted to encode for a pyruvate-water dikinase that could convert phosphoenol pyruvate to pyruvate with concomitant phosphorylation of ADP to ATP. However, N. gracilis , Ca. Nitromaritima RS and NA also encode for a pyruvate dehydrogenase, which could decarboxylate pyruvate to acetyl-CoA, thereby regenerating NAD(P) + . Coupling this fact with the potential dual capacity to regenerate pyruvate (and succinate) and oxaloacetate via the complete methylcitrate cycle and the predicted sodium-translocating oxaloacetate decarboxylase present in all Nitrospinae genomes investigated here, and the possession of a predicted NAD + -dependent malic enzyme (EC. 1.1.1.38) in Ca. Nitromaritima RS (see Figure 6 below), implies that these organisms use similar and also alternative routes for replenishing these central metabolic intermediates. Surprisingly, although motility and flagella have never been observed in cultured Nitrospina species ( Watson and Waterbury, 1971 ; Spieck et al. , 2014 ), the Ca. Nitromaritima– Nitrospina core genome is predicted to encode genes for flagellar assembly and bacterial chemotaxis. This suggests that motility is an unseen but common trait among members of this novel phylum. Additionally, their core genome also harbours a vitamin B 12 -uptake system and a few genes of the last steps of the vitamin B 12 biosynthesis pathway—that is, adenosylation to the nucleotide loop assembly ( Moore et al. , 2013 ), as well as several cobalamin-requiring enzymes (e.g., methionine synthase, methylmalonyl-CoA and ribonucleotide reductase). Because N. gracilis has an almost complete genome and also appears to lack the initial genes for the cobalamin biosynthesis pathway, we speculate that Nitrospinae are vitamin B 12 scavengers, which potentially rely on their cobalamin-producing partners (e.g., ammonia-oxidizing archaea; Doxey et al. , 2014 ), for this essential nutrient. It may also partly explain why N. watsonii grows poorly in a minimal synthetic medium without seawater ( Spieck et al. , 2014 ), which reportedly contains vitamin B 12 of up to 30 p M ( Sañudo-Wilhelmy et al. , 2012 ). Genome-based evidences for nitrite oxidation capacity As mentioned earlier, Ca. Nitromaritima RS and NA are predicted to possess the capacity for nitrite oxidation. The key signature enzyme for chemolithotrophic nitrite oxidation is the membrane-anchored molybdeterin-binding NXR ( Meincke et al. , 1992 ), which occurs in two phylogenetically distinct forms: a cytoplasmic-oriented type ( Spieck and Bock, 2005 ) and a periplasmatic type ( Lücker et al. , 2010 ; 2013 ). Both RS-SAGs carry a single periplasmatic-type NXR operon ( Figure 5a ), which harbours the substrate-binding α-subunit (NxrA) with a predicted signal peptide on the N terminus, an Fe-S cluster-containing β-subunit (NxrB), a γ-subunit (NxrC) and a putative TorD-like chaperone subunit (NxrD) inserted between NxrB and NxrC ( Meincke et al. , 1992 ). NxrD probably orchestrates cofactor acquisition and subunit assembly. The nxrABDC operon structure of Ca. Nitromaritima species is therefore dissimilar to N. gracilis , where the nxrD gene is isolated from the two nxrABC operons ( Lücker et al. , 2013 ). However, like in N. gracilis ( Lücker et al. , 2013 ), the NxrC subunit of the two Ca. Nitromarita SAGs is also predicted to possess a signal peptide that overlaps with a transmembrane-spanning region. Altogether, these evidences imply that the NXR complex of Ca. Nitromaritima is oriented similarly as that of N. gracilis ( Lücker et al. , 2013 ; Spieck et al. , 2014 ), in that the NxrC subunit is anchored to the cytoplasmic membrane, whereas the catalytic subunit (NxrA) faces the periplasm. The NxrABDC from Ca. Nitromaritima species is closely related to the N. gracilis enzymes by 91% (NxrA), 97% (NxrB), 75% (NxrD) and 64–69% (NxrC) amino-acid sequence identities, suggesting that they are functionally equivalent. Interestingly, downstream of the NXR gene cluster are two genes coding for a putative nitrate/nitrite sensor-like histidine kinase (NarX) and its cognate response regulator, which is not the case in N. gracilis . Phylogenetically, the nxrA and nxrB encoding genes of RS-SAGs cluster with those of NOB ( Figure 5b and Supplementary Figure S5 ), which harbour periplasmic-oriented NXRs (e.g., Nitrospira and Nitrospina ; Lücker et al. , 2010 , 2013 ) and have high nitrite affinities ( K m =~10–29 μ M ; ( Schramm et al. , 1999 ; Maixner et al. , 2006 ; Nowka et al. , 2015 ). This suggests that the local NOB in the BSI probably operate at low nitrite concentrations. High-affinity NOB (HNOB) are known to be repressed by high nitrite concentrations (>20 m M ) and achieve growth at lower concentrations (10- to 100-fold; Spieck and Lipski, 2011 ) compared with LNOB harbouring the cytoplasmic-oriented NXR (e.g., Nitrobacter and Nitrococcus ). The latter require 2–30 m M nitrite ( Spieck and Bock, 2005 ) and have a high K m for NO 2 – of ~0.41 to 1 m M ( Hunik et al. , 1993 ; Sorokin et al. , 2012 ; Nowka et al. , 2015 ). Based on the relative abundance of the high-affinity nxrA gene (i.e., HnxrA) homologues comprising those of HNOB ( Nitrospina - and Nitrospira -like) and anaerobic ammonia-oxidizing (anammox) bacteria, as well as low-affinity nxrA -like genes from LNOB in metagenomic data sets ( Figures 5c and d ), we can deduce that the organisms harbouring HnxrA are generally abundant at suboxic zones (<20 μ M DO 2 ) and are less prominent in the photic (oxygenated) marine zones. At the specific level of nxrA gene counts from LNOB and HNOB only—that is, excluding nxrA gene homologues of anammox bacteria that have a different physiology from NOB, we found that the LNOB were up to 10 times more frequent than HNOB, especially in the brine habitats and the water column of the ETSP ( Supplementary Figure S6 ). These differences, however, might not be directly correlated to their population structure because of biases in genome copies of nxrA genes between these NOB, which is highest among LNOB (e.g., 2–4 in Nitrobacter and Nitrolancentus species; Starkenburg et al. , 2006 , 2008 ; Sorokin et al. , 2012 ) and lowest in HNOB (e.g., 2 copies in Nitrospira and Nitrospina species; Lücker et al. , 2010 , 2013 ). Based on the taxonomy of the best blastx hits (e-value <10 –20 and >90% coverage), we observed that relative to all HnxrAs in the BSI and ETSP-OMZ, most sequences were closely related with Nitrospina / Ca. Nitromaritima-like bacteria (18–60%), decreasing in the order of relative abundance to anammox-like bacteria (10–50%), and Nitrospira (6–50% Figure 5d ), which underscores the role of Nitrospinae in deoxygenated marine environments ( Levipan et al. , 2014 ). Despite the potential copy number differences, the abundance of nxrA gene type of HNOB covaried positively with that of LNOB (Spearman's rank correlation r =0.53, P <0.001; Supplementary Table S7 ), suggesting that the same environmental factors probably influence their ecology. Our data also show that the frequency of both nxrA gene types is strongly and positively correlated with that of narG ( r =0.53–0.97, P <0.001), and that HNOB positively correlate with amoA gene frequencies ( r =0.40, P <0.05). These results corroborate molecular data that indicate considerable correlations of Nitrospina -like 16S rRNA gene abundances with thaumarchaeal amoA and 16S rRNA gene frequencies ( Mincer et al. , 2007 ; Santoro et al. , 2010 ), and findings from tracer experiments in the ESTP-OMZ ( Beman and Carolan, 2012 ), which showed that the activities of NOB are most likely sustained by nitrate reducers and ammonia oxidizers. Furthermore, taking into account three key environmental variables known to influence the population structure and activities of NOB, namely temperature, salinity and DO 2 ( Focht and Verstraete, 1977 ; Schramm et al. , 1999 ; Alawi et al. , 2009 ; Lebedeva et al. , 2010 ; Oren, 2011 ), we found that the frequency of all the above genes is significantly negatively correlated with DO 2 levels (and temperature; Table 2 ). Surprisingly, the occurence of both nxrA gene types of HNOB and LNOB showed no significant correlation with salinity ( P >0.05), suggesting that it could be less important than DO 2 and temperature for shaping the ecology of marine NOB. Niche adaptation traits of Ca . Nitromaritima RS Oxic–anoxic environments are considered as suitable habitats for chemolithoautotrophs, principally due to the opposing steep gradients of chemical reactants ( Brune et al. , 2000 ). The polyextreme BSI poses additional challenges such as the high salinity, increasing temperatures (at least in Atlantis II Deep) and elevated concentration of heavy metals ( Antunes et al. , 2011 ; Ngugi et al. , 2015 ). Salinity in particular imposes thermodynamic constraints for chemolithoautotrophic NOB ( Oren, 2011 ), as very little energy is gained from their metabolism (Δ G 0 ′=–74 kJ mol –1 NO 2 – ) to support both growth and osmoregulation. Accordingly, the variable and unique ( Supplementary Table S8 ) genome of Ca. Nitromaritima RS should reveal traits for its adaptation to the polyextreme BSI environment of Atlantis II Deep. Among all currently genome-sequenced NOB, only Nitrococcus mobilis Nb-231 and Ca. Nitromaritima RS harbour the potential to synthesize the osmoprotectant ectoine ( Supplementary Figure S7 ), and in the latter case, also hydroxyectoine. The occurrence of a putative ABC-type transporter (EhuACBD) for ectoine in Ca. Nitromaritima RS and its localization next to EctABCD operon ( Supplementary Figure S7 ) implies that Ca. Nitromaritima RS can use extracellular ectoine. In view of the thermoprotective properties of hydroxyectoine ( Tanne et al. , 2014 ) and the estimated lower energy costs for biosynthesis of osmolytes with five to six carbons ( Oren, 1999 ), this genomic trait possibly represents a crucial adaptation for such NOB in the hypersaline and relatively hot Atlantis II brine pool. The fact that the genome also encodes transporters and enzymes involved in the synthesis and interconversion of other small compatible solutes (proline, glutamate and glycerol; Figure 6 and Supplementary Table S9B ) implies that Ca. Nitromaritima RS additionally uses mixtures of osmolytes for osmoregulation. Interestingly, although Ca. Nitromaritima RS and N. gracilis harbour a predicted Trk-type system ( Figure 6 ) that is used by many bacteria, including extreme halophiles for maintaining high internal concentrations of K + ( Corratgé-Faillie et al. , 2010 ), their predicted proteomes do not show the characteristic acid-shifted isoelectric point of typical halophiles ( Supplementary Figure S8 ). This implies that these energy-limited organisms heavily depend on compatible solutes for osmoprotection. Chemolithoautotrophic nitrite oxidizers require oxygen as a terminal acceptor for their metabolism. Because very low DO 2 concentrations are a permanent feature of the BSI environment (~0.3–5 μ M in the BSI; Ngugi et al. , 2015 ), there is also a selective pressure for microorganisms to remain metabolically active under low ambient DO 2 levels. Unsurprisingly, all Ca. Nitromaritima species (and N. gracilis ) lack homologues of the low-affinity aa 3 -type haeme–copper oxidases (complex IV) that are present in Nitrobacter species ( Starkenburg et al. , 2008 ) but encode for an energy-converting electron transport chain that shuttles electrons to terminal oxidase systems capable of using critically low DO 2 levels ( Figures 6 and 7 ). Although they also lack a high-affinity cbb 3 -type haeme–copper oxidases that is present in N. gracilis ( Lücker et al. , 2013 ), presumably due to their low coverage, they appear to encode two putatively different and phylogenetically distinct oxygen-based terminal oxidases ( Supplementary Figure S9 ). The predicted subunit I of these two putative enzymes have a pairwise average identity of only 32% at the amino acid-level. The first enzyme exhibits properties similar to haeme–copper oxidases, namely presence of four haeme and two copper-binding sites ( Supplementary Figure S9B and Pereira et al. , 2001 ), and also shows considerable similarity (40% AAI) to the uncharacterized but functionally transcribed ‘cyt. bd -like oxidase' (NIDE0901) of Ca. Nitrospira defluvii ( Lücker et al. , 2010 ). The α-subunit has a signal peptide and four to five transmembrane domains, which implies localization in the membrane, and is colocalized with other additional subunits with di-haeme residues. The second predicted enzyme (designated here as ‘ bd -like enzymes' Supplementary Figure S9A ) has an unclear function as it is only 26% identical to canonical bd -type oxidases and has neither copper-binding sites nor residues implicated in quinol binding ( Yang et al. , 2007 ). The predicted subunit I possesses between 13 and 15 transmembrane domains, which contrasts with canonical bd -type quinol oxidases ( Bertsova et al. , 1997 ; Yang et al. , 2007 ). Although functional equivalence cannot be ascertained by homology, we speculate that the ‘cyt. bd -like oxidases' might be involved in electron transfer, which necessitates an assessment of their proton-pumping potential and roles in the membrane energetics of Nitrospina and its relatives. Ca. Nitromaritima RS appears also to have another energy production mode. Unlike all other so-far sequenced NOB, it is predicted to encode a putative periplasmic-oriented nitrate reductase (NAP) colocalized together with three putative cytochrome bc -like subunits that potentially function as electron carrier units ( Figure 7 and Supplementary Table S8 ). This implies the possible capacity to use nitrate as an electron acceptor, which should be advantageous because it is energetically more favourable, for example, when coupled to the oxidation of formate (Δ G 0 ′=–369 kJ mol −1 NO 3 – ) or H 2 (Δ G 0 ′=–123 kJ mol −1 NO 3 – ) compared with growth solely dependent on the oxidation of nitrite with O 2 (Δ G 0 ′=–74 kJ mol −1 NO 2 – ). Similar to other NOB, Ca. Nitromaritima RS harbours also a periplasmic copper-containing nitrite reductase (NirK), which typically catalyses the reduction of nitrite to nitric oxide (NO). However, both formate dehydrogenase and/or the catalytic subunit of a hydrogenase (see below), which would enable the generation of a proton-motive force, assuming that both are membrane-bound and cytoplasmatically oriented, are missing in these low-coverage SAGs. The physiological role of the NAP system therefore remains unclear. Experimentally, only Nitrobacter species, Nitrospira moscoviensis and N. mobilis have been shown to reduce nitrate with low-potential electron donors (i.e., H 2 , formate, acetate and pyruvate; Smith and Hoare, 1968 ; Bock et al. , 1987 ; Freitag et al. , 1987 ; Füssel, 2014 ; Koch et al. , 2015 ), producing nitrite and NO, and also ammonium ( Nitrobacter ). These NOB, however, only possess NIR-type nitrite reductases (NirK, NirA and NADH-dependent nitrite reductase, NirBD) but lack nitrate reductases; here, NXR is proposed to function in the reverse direction under anoxic conditions ( Starkenburg et al. , 2008 ; Füssel, 2014 ). Similar to all sequenced NOB, Ca. Nitromatima RS is also equipped with a mechanism for reducing nitrite to ammonia based on the presence of a cytoplasmic NirBD. However, it remains unclear whether NirBD is repressed by the high ammonium concentrations (2–387 μ M ) in the interfaces of Atlantis II Deep ( Ngugi et al. , 2015 ). Intriguingly, N. gracilis appears to use a ferredoxin-dependent nitrite reductase (NirA) instead of NirBD for nitrite assimilation ( Lücker et al., 2013 ), which is similar to some Nitrospira species ( Koch et al., 2015 ). All Nitrospinae species also possess an Amt-type transporter for taking up ammonium, which can alternatively be supplied from the hydrolysis of urea and cyanate as Nitrospinae encode, albeit differentially ( Figure 6 ), a urease (absent in N. gracilis ) and a cyanate hydratase (present in all Nitrospinae genomes). Interestingly, Nitrospina and Nitrospira species appear to have adopted other electron-scavenging pathways also with higher net energy yields such as the Knallgas metabolism (Δ G 0 ′=–237 kJ mol −1 H 2 ; Koch et al. , 2014 ) and anaerobic nitrate/nitrite reduction coupled to H 2 oxidation ( Ehrich et al. , 1995 ). However, none of the Ca. Nitromaritima SAGs encode the putative cytoplasmic type 3b (bidirectional) hydrogenase of N. gracilis ( Lücker et al. , 2013 ), although one of the RS-SAGs (SCGC AAA799-C22) harbours a partial operon encoding homologues of proteins known to be essential for the maturation of hydrogenases, namely an endopeptidase and the so-called hyp genes, HypD and HypE ( Forzi and Sawers, 2007 ). The presence of a predicted Na + -proton antiporter in the Ca . Nitromaritima– Nitrospina core genome ( Supplementary Table S6 ) also implies the potential to generate an electrochemical sodium gradient ( Padan and Schuldiner, 1994 ), which is likely coupled to the proton-motive force generated by nitrite oxidation (or via nitrate reduction), to drive the uptake of extracellular nutrients (including osmolytes such as proline and glycine betaine) using several putative Na + -dependent solute uptake systems encoded in their genomes ( Figure 6 ). Although present also in N. gracilis , the potential capacity to detoxify heavy metals (e.g., mercury, zinc, cobalt, copper and cadmium) and the possession of alternative mechanisms to sequester scarce nutrients, for example, phosphate using a high-affinity phosphate-specific transporter (PstSCABU) or the phosphonates uptake (PhnDEC) and degradation system, are all probably also necessary in the polyextreme habitat of Ca. Nitromaritima RS."
} | 10,260 |
34730273 | PMC9300077 | pmc | 9,025 | {
"abstract": "Abstract Nanomaterials offer exciting properties and functionalities. However, their production and processing frequently involve complex methods, cumbersome equipment, harsh conditions, and hazardous media. The capability of organisms to accomplish this using mild conditions offers a sustainable, biocompatible, and environmentally friendly alternative. Different nanomaterials such as metal nanoparticles, quantum dots, silica nanostructures, and nanocellulose are being synthesized increasingly through living entities. In addition, the bionanofabrication potential enables also the in situ processing of nanomaterials inside biomatrices with unprecedented outcomes. In this Minireview we present a critical state‐of‐the‐art vision of current nanofabrication approaches mediated by living entities (ranging from unicellular to higher organisms), in order to expand this knowledge and scrutinize future prospects. An efficient interfacial interaction at the nanoscale by green means is within reach through this approach.",
"introduction": "1 Introduction Nanomaterials (NMs) are defined as materials whose components or basic building blocks have at least one dimension in the nanoscale (1–100 nm). NMs offer excellent properties, new applications, and unique interactions with biological systems by exploiting nanoscale phenomena. \n [1] \n Despite this potential, nanofabrication approaches still rely on highly complex procedures, often incompatible with green chemistry principles. Therefore, increased efforts should be directed to develop unconventional methods with a higher throughput and lower cost, \n [2] \n going along with a sustainable profile. The use of organisms is a clean and affordable alternative to synthesize NMs, since these methods can be scaled up and also tuned by chemical and genetic modification. \n [3] \n Organisms have developed the synthesis of NMs as a means to adapt to their environment, in order to enhance their life expectancy; thus, they can be considered green factories of useful NMs. The intersection between biology and materials science has provided extraordinary materials that cannot be easily synthesized in the laboratory, but Nature does it at ambient conditions without hazardous chemicals. Some of these are actually NMs with outstanding properties. For instance, magnetotactic bacteria (MTB), already discovered in 1963, \n [4] \n biosynthesize magnetic nanocrystals (MNCs) that allow their orientation and migration under geomagnetic fields (Figure 1 ). \n [5] \n There is also the case of biotemplates, alluding to the use of biomolecules, viruses, or biological extracts as templates for the synthesis or deposition of NMs. This approach is not within the scope of this Minireview, as a living system is not directly involved.[ \n 6 \n , \n 7 \n ]\n Figure 1 Electron micrograph of a magnetotactic bacterium with a visible magnetosome chain. Scale bar=1 μm. Reproduced with permission from ref. [5] . Copyright 2008, American Chemical Society. This Minireview aims at presenting the current state‐of‐the‐art on the use of organisms for the synthesis and processing (i.e. integration into a biomatrix) of NMs. The generation of NMs mediated by living entities is an example of a bottom‐up process, from atoms/ions or molecules to NMs (Scheme 1 ). This strategy encompasses concepts such as chemical synthesis, catalysis, directed precipitation, and mineralization. The main example is the reduction of metallic salts to form zero‐valent metal nanoparticles (ZMNPs), \n [8] \n together with the synthesis of quantum dots, \n [9] \n MNCs, \n [10] \n or bacterial nanocellulose (BNC). \n [11] \n On the other hand, the integration of NMs into a biomatrix represents also a bottom‐up approach in which the components are blended from scratch, in an extremely efficient way, by the action of specific organs or organelles (Scheme 1 ). These nanocomposites possess improved (and even novel) properties due to enhanced interfaces between biomatrices and NMs. Scheme 1 Summary of diverse bionanofabrication approaches. Red background: bionanofabrication through living entities; blue background: in situ biogenic processing of NMs into a biomatrix."
} | 1,042 |
29146781 | null | s2 | 9,026 | {
"abstract": "Semiconductors are central to the modern electronics and optics industries. Conventional semiconductive materials bear inherent limitations, especially in emerging fields such as interfacing with biological systems and bottom-up fabrication. A promising candidate for bioinspired and durable nanoscale semiconductors is the family of self-assembled nanostructures comprising short peptides. The highly ordered and directional intermolecular π-π interactions and hydrogen-bonding network allow the formation of quantum confined structures within the peptide self-assemblies, thus decreasing the band gaps of the superstructures into semiconductor regions. As a result of the diverse architectures and ease of modification of peptide self-assemblies, their semiconductivity can be readily tuned, doped, and functionalized. Therefore, this family of electroactive supramolecular materials may bridge the gap between the inorganic semiconductor world and biological systems."
} | 242 |
34189300 | PMC8215182 | pmc | 9,029 | {
"abstract": "A consortium of microbial community was used for the treatment of acid mine drainage wastewater laden with sulphate and heavy metals. The wastewater was treated in an anaerobic continuously stirred tank bioreactor. The microbial community activity increased the pH from 5.6 to 6.5, and improved sulphate removal up to 85% from an initial sulphate concentration of 8080 mg S O 4 2 − /L in a continuous mode, following enrichment for 21 d. The maximum heavy metal removal percentage was observed for Cd (98%), Al (97%), Mn (95%), Pb (94%), Sr (94%) and Cu (91%). The microbial community showed synergy between strictly anaerobic and facultative Firmicutes sp., which were responsible for the bioreactor performance. The biochemical reaction indicated the microbial community has a wider range of substrates dominated by metallo-aminopeptidases.",
"conclusion": "4 Conclusion The results showed high sulphate reduction with heavy metal precipitation by a consortium of the microbial community in a continuously stirred tank reactor. After an adaptation period, sulphate reduction commenced and redox potential declined. There was an increase in pH while the dissolved concentrations of heavy metals were substantially reduced by the microbial community. The microbial group indicated the presence of both facultative and strictly anaerobic phylum Firmicutes was most useful in heavy metal precipitation and sulphate reduction in the reactor. The enrichment period (21 d) as well as the ability of the microbial community to consume various substrates as energy sources with the release of numerous aminopeptidases that catalyse AMD treatment enhanced the sulphate reduction and metal precipitation. This implies that several compounds could serve as a potential substrate for microorganisms degrading AMD, due to the varying metabolic pathway. These results indicate that this approach can be helpful in the design of efficient in situ AMD treatment.",
"introduction": "1 Introduction Industrialisation culminated in the rise of toxicant-laden wastewater which is a threat to both aquatic and terrestrial environments when disposed-off untreated, especially in most developing nations. Mining is one of such activities on the rise owing to its impact on the economy of those nations. Although, mining activities consume a considerably smaller quantity of water compared to other industrial activities, it is the topmost producer of hazardous wastewater [ 1 ]. The mining industry is a key player in the development of South Africa's economy. Nevertheless, since mining operations cannot be relocated, many neglected mine sites are the main source of most health and environmental challenges [ 2 ]. During mineral extraction, sulphide bearing minerals are exposed to the oxygenated environment causing a cycle of complex geochemical reactions that engenders acid mine drainage (AMD) [ 3 , 4 ]. When discharged untreated and/or partially treated, it drains directly into freshwater bodies and leaches into the water table leading to groundwater contamination [ 1 ]. When such contaminated water is consumed, the vital ions in cells can be replaced by heavy metals which may result in carcinogenic and mutagenic effects, including diarrhea if sulphate concentration is high [ 5 ]. Currently, there are several methods used for treating AMD, including membrane-filtration, floatation, coagulation-floatation, chemical precipitation, reverse osmosis, ion-exchange, filtration and electrochemical, amongst others [ 6 , 7 ]. However, due to cost implications and environmental concerns, these methods are considered unsustainable. Besides, management of high volume of resulting sludge in chemical treatment is challenging [ 8 ]. The high rate of success recorded in anaerobic technology has encouraged researchers to explore its application to the treatment of complex wastewater such as AMD [ 9 , 10 , 11 ]. Treatment using sulphate-reducing bacteria (SRB) is a well-known biotechnological approach in the remediation of AMD. The biotechnological treatment provides less resolubility of sulphide precipitation than hydroxide precipitation within a wide range of pH than the chemical approach [ 12 ]. SRB are a group of microorganisms that utilise sulphate as a terminal electron acceptor. They play a major role in pollutant degradation, organic transformation and sulphur cycle in the environment [ 13 ]. When a suitable carbon source is available, SRB produces bicarbonate ions and sulphide. The bicarbonate elevates the pH while dissolved metals are precipitated by the sulphide. The reactions are summed up in Eqs. (1) , (2) , and (3) [ 14 ]: (1) C H 3 C O O − + S O 4 2 − → H S − + 2 H C O 3 − (2) M e 2 + + H S − → M e S ↓ + H + (3) H C O 3 − + H + → H 2 O + C O 2 Where M e represents the metal ion. Furthermore, microbial communities from AMD play an important role in the effective treatment of wastewater [ 15 , 16 , 17 , 18 ]. Most of these microorganisms used in AMD remediation were found to belong to the phyla; Firmicutes, Actinobacteria, Acidobacteria, Nitrospira, Ciliophora , as well as Proteobacteria which contains both facultative anaerobic and few obligate anaerobic species [ 19 ]. Different culturing techniques have been reported in the study of microbial diversity in water and wastewater [ 20 ]. The culture-independent technique offers the benefit of precise assessment and taxonomy of microorganisms in a given sample [ 21 , 22 ]. Because of the ability of microorganisms to survive and replicate in harsh environment such as extreme pH, they are considered suitable for the treatment of AMD. Similarly, metal pollution is a major concern in AMD management, analysis of microbial diversity of AMD will give a clear perception of the dominant microorganisms that can be deployed in the treatment of metal-laden AMD [ 19 , 20 ]. Due to the high sensitivity of bacteria towards heavy metals, application of SRB is often limited to the wastewater with low heavy metals concentration. Consequently, most reports grow the bacteria separately before using it for the treatment [ 23 , 24 ]. However, the performance of SRB grown on AMD laden with high concentrations of metals such as Al 3+ , Fe 2+ , Mg 2+ & Mn 2+ is barely been reported. Therefore, the goal of this study was to identify the group of microorganisms in the heavy metal-laden AMD samples and to ascertain the effectiveness of the identified microbial group in an AMD remediation system.",
"discussion": "3 Results and discussion 3.1 Microbial community diversity and biochemical reactions The microbial community distribution is shown in Figure 1 . At the phylum level, Firmicutes was predominant (39%), followed by Proteobacteria (15.5%) while Bacilli (40.80%) were the most dominant microbial communities at the class level, in raw AMD sample (S a ). Similarly, Firmicutes (38%) and Proteobacteria (28.6%) were the most dominant at phylum level while Bacilli (35.7%) and Actinobacteria (16.7%) were prevalent at class level in the treated AMD sample (S b ). These findings corroborate the prevalence of Firmicutes in the microbial population of the AMD [ 20 , 31 , 32 ]. This implies that the Firmicutes especially Bacilli are adaptable enough to the extremely acidic pH of AMD, making them suitable biological agent in bioremediation of contaminated environment. Figure 1 Community barplot analysis of raw AMD and treated AMD at phylum (A) and class (B). Figure 1 Table 3 shows the microbial diversity and richness indices. The values of Shannon and Chao indices for S a were higher than that of S b , an indication that the microbial species richness reduced during the remediation process in the reactor. This could be attributed to the anaerobic operating conditions which are not suitable for some microbial community. For both samples, the coverage was above 99% which suggest that the abundance analysis is a good representative of the microbial diversity. Table 3 Microbial community diversity and richness indices of samples. Table 3 Sample ID Cluster Chao Shannon Coverage S a 123 3813 4.809 0.999 S b 42 903 3.737 1.0 Biochemical tests in combination with metagenomic analyses attested the dominance of Bacilli in the microbial population of the bioreactors used for AMD remediation. Albeit, identified species in VITEK® 2 compact system are predominantly facultative organisms such as Bacillus amyloliquefaciens, B. atrophaeus, B. cereus, B. mycoides, and B. thuringiensis, B. smithii, as well as B. subtilis which propagates anaerobically using nitrate as electron acceptor [ 33 , 34 ]. The dominant Bacillus species were deposited with NCBI database. Detailed biochemical identification and their respective confidence level are shown in Table 4 . Table 4 Biochemical identification of microbial species in the AMD system. Table 4 Organism Confidence level Probability Accession Number Bacillus smithii Excellent 98% MT994646 Bacillus cereus Excellent 98% MT994644 Bacillus mycoides Excellent 98% MT994645 Bacillus thuringiensis Excellent 98% MT994648 Bacillus amyloliquefaciens Good 90% MN538986 Bacillus atrophaeus Good 90% MT994643 Bacillus subtilis Good 90% MT994647 Furthermore, the microbial community indicated various substrates being utilised as expected. Prominent in the substrates were glycogen, D-galactose, pyruvate, Inulin, D-glucose, urea, saccharose/sucrose, acetate, citrate, and DL-lactate, amongst others. Table S1 indicated that, contrary to the previous reports that limit the range of substrates as energy sources for organisms remediating acid mine drainage, the number of electron donors and acceptors was determined to vary [ 35 , 36 ]. This supports the affirmation that more than a hundred compounds could serve as a potential substrate for microorganisms degrading AMD, due to the varying metabolic pathway under both aerobic and anaerobic conditions [ 37 , 38 , 39 ]. In addition, the dominance of aminopeptidase in the biochemical reactions was an indication of the consortium's ability to survive under nitrogen-limited conditions. Prominent among the enzymes are β-Xylosidase, Leucine-arylamidase, β-galactosidase, alanine arylamidase, tyrosine arylamidase, and α-Glucosidase, including phosphatase, which acts as biocatalyst for sulphate reduction [ 40 ]. In search of survival in a polluted environment, several heavy metal tolerant organisms have been shown to produce these metallo-aminopeptidases enzymes [ 41 , 42 ]. The microbial community used in this study also showed resistance to several known inhibitors (Bacitracin, Kanamycin, Novobiocin, Oleandomycin, Optochin and Polymixin B) [ 43 , 44 ]. 3.2 Performance of the continuous reactor systems for AMD remediation Several sulfidogenic reactors have been operated in diverse modes such as batch, continuous or semi-continuous with varying levels of performance. Singh et al. [ 45 ] reported 82% sulphate reduction in a static batch anaerobic reactor while 80 % removal efficiency was observed in a batch biofilm reactor [ 46 ]. Meanwhile, a continuous mode reactor with two-stage operations was the most widely reported to have a high remediation potential [ 5 , 23 , 47 , 48 ]. In an up-flow anaerobic granular sludge bed (UASB), a 98% sulphate reduction was reported by Najib et al. [ 5 ] similar to the report of Dev et al. [ 47 ] in an up-flow anaerobic packed bed reactor. The reactor in this study was operated for 42 d at temperature 35 ± 2 °C and start-up pH of 7–7.5. Fresh AMD (8080 mg S O 4 2 − /L) was introduced to the reactor on the 22 nd day. The sulphate profile showed a steady rise in sulphate reduction until the end of continuous operation, together with microbial propagation – Figure 2 . This reveals the effectiveness of the microbial community, taking into account the original concentration of sulphate in the raw AMD. Previous studies have always focused on synthetic wastewater with a lower sulphate concentration of less than 3000 mg S O 4 2 − /L [ 13 , 47 , 49 ]. The relatively large residual sulphate concentration (1195 mg S O 4 2 − /L) can be attributed to the slow rate of reduction in addition to high heavy metals concentration in the raw AMD which impeded the microbial activities. Due to the toxicity of heavy metal at higher concentrations, previous reports have shown that they inhibit microbial activities during sulphate reduction and thus reduce their metabolism [ 23 ]. Furthermore, a high concentration of copper caused almost a 50% reduction in microbial removal efficiency [ 50 ]. After 7 d of continuous stirring and data capturing, the reactor was left in a static batch mode for 14 d, and sulphate concentration was found to have reduced to 60 mg S O 4 2 − /L, representing a 99% removal efficiency which compared well with previous reports on AMD remediation. This study implied that the physicochemical properties of the microbial environment play a major role in heavy metal inhibition in sulphate reduction operating systems and that a single-mode operation is insufficient for the reduction of the sulphate in heavy metal-laden AMD. Figure 2 Microbial growth and percentage sulphate removal in continuous mode. Figure 2 A decline in pH was noticed at the beginning of the continuous operation mode most likely because of highly acidic raw AMD introduced – Figure 3 . Most known sulphate-reducing bacteria grow at optimum pH between 6 and 8 [ 51 ]. At low pH, more energy investment is required for the migration of protons across cell membranes and less energy will be available for microbial growth. However, thermodynamic studies have shown that Gibbs's free energy of sulphate reduction is higher at lower pH resulting in more energy gains [ 52 ]. When this energy gains support proton migration, suitable and sustainable growth is achievable. The BLAST result of the sample sequences showed similarity with Acidithiobacillus ferrooxidans (0.09%) and Acidiphilium sp. (0.05%) which might have accounted for the little growth observed during days 1–2 when bioreactors operated in a continuous mode. Furthermore, there was an increase in redox potential (Eh) due to the higher Eh of the raw AMD – Figure 3 . A steady decrease in the Eh and increase in pH was observed after 2 nd day of continuous operation, suggesting an adjustment of the microbial community to the new conditions. An identical drop in Eh and a rise in pH have been reported for the treatment of AMD [ 5 , 23 , 47 ]. Figure 3 pH and redox potential profile of the microbial community during sulphate reduction. Figure 3 Table 5 shows the initial and residual concentrations of heavy metal in the raw AMD prior and post-treatment with the microbial community, respectively. Heavy metals were removed in the form of metal sulphide precipitates. The microbial community reduces sulphate to sulphide which reacts with the heavy metal ions, resulting in insoluble metal sulphide precipitate. The highest metal removal efficiency was found in Cd 2+ (98%) followed by Al 3+ (97%). Removal percentages of 69, 66, 58 and 55% were observed for Cr 3+ , As 3+ , Zn 2+ , and Mg 2+ , respectively, with all other metals being removed above 70%. This performance could be attributed to the metallo-aminopeptidases activities in the presence of divalent metallic cations in the bioreactor. The existence of Mn 2+ , Cu 2+ , Zn 2+ and Fe 2+ has shown to alter the activities of metallo-aminopeptidases [ 40 , 53 , 54 ]. Previous reports have also shown that Cu 2+ , Al 3+ , Ni 2+ , Pb 2+ and Fe 2+ are precipitated at acidic pH but could be precipitated at pH above 9.5 [ 55 , 56 ]. The influence of heavy metal tolerant facultative B. cereus in the microbial consortium as well as pH < 7 in the reactor facilitated the high metal removal in the AMD remediation. These results were similar to a report of a series of batch reactors and a floating column, whereby greater than 97% removal efficiency of heavy metals (Cd 2+ , Zn 2+ , and Cu 2+ ) were reported by the synergy observed between AMD degrading microbes and B. cereus [ 57 ], including a 99% removal of Al 3+ in AMD using microbial consortium [ 58 ]. Although some reports have shown total abatement of heavy metals with sulphate reduction in the range of 80–90% [ 14 , 59 ], the relatively high metal removal with sulphate reduction (85%) in this study can be enhanced by optimising process parameters to provide a kinetically suitable environment for the proliferation of the microbial community. Table 5 Effect of the microbial community on the heavy metals removal in the AMD. Table 5 Heavy metals Raw AMD (mg/L) After treatment (mg/L) Ave. % Removal Al 3+ 484.7 ± 3.25 14.4 ± 0.85 97,03 As 3+ 0.32 ± 0.02 0.11 ± 0.01 65,63 Cd 2+ 0.5 ± 0.11 0.009 ± 0.003 98,20 Cu 2+ 0.46 ± 0.05 0.04 ± 0.001 91,30 Cr 3+ 0.13 ± 0.01 0.04 ± 0.001 69,23 Fe 2+ 2308 ± 5.51 260.3 ± 2.78 88,72 Mg 2+ 297.6 ± 2.67 132.5 ± 2.11 55,48 Mn 2+ 60.8 ± 1.89 3.15 ± 0.21 94,82 Ni 2+ 8.09 ± 0.56 1.75 ± 0.08 78,37 Pb 2+ 5.47 ± 0.43 0.32 ± 0.01 94,15 Sr 2+ 1.0 ± 0.11 0.058 ± 0.002 94,20 Zn 2+ 7.93 ± 0.34 3.3 ± 0.13 58,39 Bold indicates microbial community almost removed heavy metal completely."
} | 4,291 |
34976308 | PMC8666610 | pmc | 9,030 | {
"abstract": "Graphical abstract",
"introduction": "1 Introduction In terrestrial microenvironments, microbial communities often provide beneficial effects to other organisms, e.g., biocontrol agents grown on the surface of plant roots, thereby preventing the growth of bacterial and fungal pathogens [1] .This beneficial effect is often associated with the production of antimicrobial substances and antibiotics [1] . Antibiotic production was shown to be regulated as well as affected by the biological, chemical and physical features of the environment [2] , [3] , [4] . However, the guiding rule for coordinating antibiotic production with the biotic environment remains unknown. In many natural scenarios, bacteria grow in heterogeneous communities organized into a complex 3D structure, designated as biofilms [5] . The 3D structure of the biofilm was suggested to relieve metabolic stress, by the utilization of channels formed below the ridges and wrinkles within the colony that may facilitate diffusion of fluids, nutrients and oxygen [6] , [7] , [8] , [9] . The formation of a biofilm is a developmental process, in which various genetic programs are activated in a specific order in different subpopulations of cells, for the proper establishment of a functional structure [7] , [9] , [10] , [11] , [12] , [13] , [14] . This apparent coordination can be explained by the temporally distinct exposure of cell subpopulations to specific microenvironments [13] . To form a functional structure, biofilm-forming cells produce polymers that constitute the extracellular matrix (ECM), where they bind to each other and to the surface. The ECM plays an important role in the resistance and resiliance of the entire biofilm community [15] , [16] , [17] . Although the ability to generate an ECM appears to be a common feature of multicellular bacterial communities, there is remarkable diversity in the means by which these matrices are constructed [18] . The most extensively studied components of biofilm ECMs are carbohydrate-rich polymers (i.e., extracellular polysaccharides or exopolysaccharides (EPS)), proteins, nucleic acids [18] , [19] and biogenic minerals [20] , [21] . Bacillus subtilis is a spore-forming facultative anaerobe and is associated with the rhizosphere and soil microbiomes [22] . This bacterium often serves as a model organism for beneficial Gram-positive bacteria, and its undomesticated strains form robust and architecturally complex biofilms [23] . B. subtilis is capable of forming various types of biofilms including on solid surfaces (colony), in the air–water interface (pellicles or floating biofilms) and submerged biofilms in domesticated strains [18] . The ECM of B. subtilis is characterized by the exopolysaccharides encoded by the epsA-O operon and the proteins TasA and BslA [22] , [24] . TasA is a functional amyloid and is encoded by the tapA-sipW-tasA operon [24] , [25] , [26] . The b iofilm s urface l ayer protein A (BslA) is involved in the formation of a water-repellent hydrophobic coat over the biofilm and is critical for pellicle and colony biofilms [27] , [28] . All matrix components were expressed and promoted during pellicle formation. Interestingly, all extracellular matrix components were shown to have additional non-structural roles: The protein TasA was shown to regulate motility, extracellular matrix production and the general stress response [29] , [30] and exopolysaccharides were shown to activate the master regulator Spo0A [31] which regulates biofilm formation, sporulation and the production of the antibiotic Bacillaene [23] , [32] , [33] . Therefore, the role of the extracellular matrix in microbial competition could be multifactorial due to its independent structural and non-structural roles. Here, we used imaging flow cytometry to evaluate the roles of all major extracellular matrix components in microbial competition for floating biofilm (pellicle) formation. The population within B. subtilis biofilms and root associated communities is heterogeneous [14] , [34] , [35] , a heterogenicity which is affected by the production of the extracellular matrix. To overcome this fundamental property of biofilms, we monitored the effects of the extracellular matrix on the single cell level, relying on imaging flow cytometry. This method combines the power and speed of traditional flow cytometers with the resolution of the microscope. It therefore allows for high rate complex morphometric measurements in a phenotypically defined way [36] , [37] . We uncovered that exopolysaccharides, but not the proteinous matrix components, have a dual role in excluding non-self-community members from mixed communities while promoting the self-aggregation and co-aggregation with related species. This role was indirect, and could be attributed to the exopolysaccharides dependent production of bacillaene within floating biofilms.",
"discussion": "3 Discussion Bacteria in nature are most often found in the form of multicellular aggregates commonly referred to as biofilms [44] , [45] . When compared to the planktonic (free-living) state, cells in biofilms are more protected from environmental insults, including sterilizing agents, antibiotics, and the immune system. Biofilms enable bacteria to attach more firmly to their hosts and better access to nutrients [46] , [47] , [48] , [49] , [50] , [51] , [52] . The self-produced extracellular matrix (ECM) surrounds and protects the cells, and makes them adhere to each other or to a surface [19] . This feature makes bacterial biofilms an especially appealing system in which to study multicellular development, with exopolysaccharides, carbohydrate rich polymers being the most studied and wide spread ECM component [18] , [53] . Various genetic analyzes have provided strong evidence that biofilm exopolysaccharides play a fundamental structural role in different bacterial species, impact bacterial virulence, and promote capsule formation [54] , [55] , [56] , [57] , [58] , [59] . The biofilm of B. subtilis contains several exopolysaccharide polymers, produced by the epsA-O operon, and composed of glucose, galactose and N-acetyl-galactosamine [60] , [61] . Colonies of mutants in the epsA-O operon, and specifically the glycosyltransferase gene epsH , lack the exopolysaccharide component of the ECM and are featureless, as opposed to the wrinkled wild type colony [23] . Here we report that in addition to their structural role, manifested by their necessity for B. subtilis to generate pellicles (floating biofilms) with itself [62] and with a related bacterium, B. atrophaeus ( Fig. 1 ), the exopolysaccharides act to induce the production of bacillaene, a polyketide antibiotic [33] , [63] , [64] , [65] which was recently shown to be essential for the elimination of phylogenetically distinct Bacillus s pecies [41] , [66] . Our results indicate that this non-structural role of the exopolysaccharides is manifested by a capacity of B. subtilis to repel the phylogenetically distinct competitor, B. mycoides from the pellicle and its surrounding media. Interestingly, the protein matrix component TasA induced Bacillaene while repressing the production of the surfactant and antibiotic surfactin [67] , [68] , also involved in horizontal gene transfer [69] . This result may explain the heterogeneity in gene expression of antibiotics within the biofilm [41] , and predicts that their local expression may also reflect the local concentration of the extracellular matrix components. So far we could observe two global signals for inducing antibiotic production in B. subtilis : peptidoglycan [41] and plant secretions [37] that induced both surfactin and bacillaene. In contrast, ECM driven regulation of antibiotic production is highly specific: TasA represses surfactin and induces bacillaene, and exopolysaccharides trigger the production of bacillaene but to some extent represses surfactin expression, indicating an overall fine-tuning of antibiotic production. One advantage of differential ECM-driven regulation is a potential capacity to control local expression within the complicated biofilm structure [18] , [70] . When considering a developmental model for biofilm formation, it is tempting to speculate that the bacterial ECM is involved in regulation of genetic programs in designated subpopulation of cells in the biofilm [18] . It has been evident that in multicellular eukaryotes, the production of communication factors depends on cell–ECM interactions [71] . In this work, we describe a similar role for the exopolysaccharides in changing the decision-making processes and the competitiveness of the bacterial biofilm-forming cells. Furthermore, we demonstrate how this ECM-derived cue maintains an essential subset of antibiotic producing cells within the biofilm population."
} | 2,227 |
26614655 | null | s2 | 9,031 | {
"abstract": "Most natural microbial systems have evolved to function in environments with temporal and spatial variations. A major limitation to understanding such complex systems is the lack of mathematical modelling frameworks that connect the genomes of individual species and temporal and spatial variations in the environment to system behaviour. The goal of this review is to introduce the emerging field of spatiotemporal metabolic modelling based on genome-scale reconstructions of microbial metabolism. The extension of flux balance analysis (FBA) to account for both temporal and spatial variations in the environment is termed spatiotemporal FBA (SFBA). Following a brief overview of FBA and its established dynamic extension, the SFBA problem is introduced and recent progress is described. Three case studies are reviewed to illustrate the current state-of-the-art and possible future research directions are outlined. The author posits that SFBA is the next frontier for microbial metabolic modelling and a rapid increase in methods development and system applications is anticipated."
} | 271 |
21150903 | null | s2 | 9,032 | {
"abstract": "Computation underlies the organization of cells into higher-order structures, for example during development or the spatial association of bacteria in a biofilm. Each cell performs a simple computational operation, but when combined with cell-cell communication, intricate patterns emerge. Here we study this process by combining a simple genetic circuit with quorum sensing to produce more complex computations in space. We construct a simple NOR logic gate in Escherichia coli by arranging two tandem promoters that function as inputs to drive the transcription of a repressor. The repressor inactivates a promoter that serves as the output. Individual colonies of E. coli carry the same NOR gate, but the inputs and outputs are wired to different orthogonal quorum-sensing 'sender' and 'receiver' devices. The quorum molecules form the wires between gates. By arranging the colonies in different spatial configurations, all possible two-input gates are produced, including the difficult XOR and EQUALS functions. The response is strong and robust, with 5- to >300-fold changes between the 'on' and 'off' states. This work helps elucidate the design rules by which simple logic can be harnessed to produce diverse and complex calculations by rewiring communication between cells."
} | 320 |
34556155 | PMC8461876 | pmc | 9,033 | {
"abstract": "Background Microorganisms can be metabolically engineered to produce a wide range of commercially important chemicals. Advancements in computational strategies for strain design and synthetic biological techniques to construct the designed strains have facilitated the generation of large libraries of potential candidates for chemical production. Consequently, there is a need for high-throughput laboratory scale techniques to characterize and screen these candidates to select strains for further investigation in large scale fermentation processes. Several small-scale fermentation techniques, in conjunction with laboratory automation have enhanced the throughput of enzyme and strain phenotyping experiments. However, such high throughput experimentation typically entails large operational costs and generate massive amounts of laboratory plastic waste. Results In this work, we develop an eco-friendly automation workflow that effectively calibrates and decontaminates fixed-tip liquid handling systems to reduce tip waste. We also investigate inexpensive methods to establish anaerobic conditions in microplates for high-throughput anaerobic phenotyping. To validate our phenotyping platform, we perform two case studies—an anaerobic enzyme screen, and a microbial phenotypic screen. We used our automation platform to investigate conditions under which several strains of E. coli exhibit the same phenotypes in 0.5 L bioreactors and in our scaled-down fermentation platform. We also propose the use of dimensionality reduction through t-distributed stochastic neighbours embedding (t-SNE) in conjunction with our phenotyping platform to effectively cluster similarly performing strains at the bioreactor scale. Conclusions Fixed-tip liquid handling systems can significantly reduce the amount of plastic waste generated in biological laboratories and our decontamination and calibration protocols could facilitate the widespread adoption of such systems. Further, the use of t-SNE in conjunction with our automation platform could serve as an effective scale-down model for bioreactor fermentations. Finally, by integrating an in-house data-analysis pipeline, we were able to accelerate the ‘test’ phase of the design-build-test-learn cycle of metabolic engineering. Supplementary Information The online version contains supplementary material available at 10.1186/s12934-021-01675-3.",
"conclusion": "Conclusions We have seen that our automated platform is able to rapidly and effectively set up microplate experiments to phenotype enzymes and microbial strains. The automation of such routine metabolic engineering workflows greatly expands the number of different strains/enzymes and media conditions that can be examined, resulting in large experimental datasets that can assist strain design. With machine learning applications in metabolic engineering becoming more prevalent, there is an urgent need to develop tools and protocols for accurate and reproducible phenotyping strains and enzymes at smaller scales. Automated systems are uniquely suited for this task since they eliminate human error and require standardized protocols to function. Furthermore, recent efforts toward developing robot programming languages that allow for the development of cross-platform protocols enable relatively easy implementation of complex laboratory workflows [ 45 – 47 ]. While automation can enhance experimental throughput, conducting experiments at accelerated rates also increases operational costs and the amount of laboratory waste generated due to the number of pipette tips and other labware used. Laboratory plastic waste has become a major concern in the current era of high-throughput experimentation [ 48 – 50 ]. It is quite ironic that the same research labs that work on developing microbes for sustainable production of chemicals end up generating several million tonnes of plastic waste in the process. Through the development of effective and fast decontamination protocols, we eliminated the need for plastic pipette tips while maintaining experimental throughput. Disregarding repeated and failed experiments, we estimate that nearly 4000 pipette tips would be required to complete the two case studies examined in this work if they were done manually or using a disposable tip liquid handling platform. Further, the automated pipette calibration protocol developed here enables the quick setup of a broad range of liquid handling systems for different pipetting programs and would also assist in routine maintenance without the need for additional expensive equipment. One concern with phenotyping microbial strains in microplates is the inability to replicate the mixing regimes, oxygen transfer and other physical characteristics of fermentation observed in larger pH controlled bioreactors. These considerations are better addressed in miniature bioreactors that have been designed to be small scale replicas of bench-top bioreactors. Nevertheless, by leveraging the enhanced throughput of microplate experiments, we were able to analyze the effect of a large number of media conditions on the cellular phenotypes in a relatively short period of time. Consequently, we were able to identify glucose concentrations that restricted fermentation durations and thereby, reasonably reproduce bioreactor phenotypes in microtiter plates under anaerobic conditions. Furthermore, modern dimensionality reduction and data visulalization techniques such as tSNE could be used in conjunction with microplate experiments to assist in choosing strains for scale-up. We believe that since microplates offer higher experimental throughput at very low costs, our platform will serve as an effective and representative screen before moving on to larger scales. Furthermore, integration of our data analysis pipeline—IMPACT [ 56 ] with the strain testing pipeline has enabled the visualization and analysis of large datasets that emerge as a consequence of our platform, and will accelerate future strain design endeavours. While successful at anaerobic phenotyping, we believe that the experimental protocols described in this study are broadly applicable to various liquid handling platforms for a wide range of applications and this work will assist the development of sustainable automated high throughput experimental platforms.",
"discussion": "Results & discussion A decontamination protocol for fixed-tip liquid handlers Fixed-tip liquid handling systems require decontamination after every pipetting step to curb biological cross-contamination. A disinfection step where tips are washed and incubated with ethanol has been proposed in the past to address contamination issues [ 25 ]. However, this protocol required the incubation of pipette tips in ethanol for 5 min between each pipetting step, reducing the throughput of this system. More recently, one study used a layer of ethanol, aspirated immediately before aspirating biological samples to maintain sterility [ 31 ]. While this protocol is faster, it may result in reduced cell viability due to direct contact between the disinfectant and cells. To address these issues, we examined the effectiveness of a simple decontamination protocol that uses a solution of sodium hypochlorite (bleach) to disinfect pipette tips (Fig. 2 a). In order to simulate typical contamination events during cell culture workflows, we programmed the pipette to aspirate 200 μL of viable E. coli cells in their exponential phase of growth, hold for 30 s with the pipette tips dipped inside the culture, and dispense the cells back into the solution. Then, the tips aspirate 400 μL of bleach, hold for a specified interval— ‘t’ seconds with the tips dipped inside, and dispense the disinfectant. We repeat this bleach wash for a specified number of times— ‘n’ and when complete, wash the tips with system liquid—sterilized ultrapure water, to remove any traces of the disinfectant. Finally, to examine the effectiveness of our decontamination procedure, we aspirate 200 μL of sterile LB media from a microplate, hold for 30 s and dispense back into the same wells. Any persisting E. coli cells in the tips would lead to contamination of the media and show cell growth after incubation of the plate. We used a wash with water as a negative decontamination control to ensure that contamination events are captured effectively using this procedure. Fig. 2 Preliminary decontamination protocol. a Steps to decontaminate and investigate effectiveness of the decontamination protocol. ‘n’ represents the number of washes with the disinfectant and ‘t’ represents the duration for which the disinfectant is held within the tips for each wash. b Initial decontamination test using different concentrations of sodium hypochlorite(bleach) with ‘n’ = 4 and ‘t’ = 0 and the default air-gap of the system (10 μL). Each bar represents effectiveness calculated from 24 replicates First, we examined the efficacy of this procedure using varying concentrations of bleach, with ‘n’ = 4 washes and zero hold time ( ‘t’ = 0 s). The sterilization effectiveness was calculated as the percentage of contaminated wells resulting from the corresponding decontamination procedure. As seen in Fig. 2 b, the negative control—water resulted in zero effectiveness. Increasing the concentration of bleach seemed to positively impact the effectiveness of our protocol. However, even at the highest concentration of bleach, we only observed a 50% effectiveness of decontamination. We considered that varying the number of washes— ‘n’ and the hold time for the disinfectant— ‘t’ could improve our system due to longer contact with bleach. Increasing the number of washes and the hold time indeed had a positive impact on the sterilization effectiveness, with the best values being achieved at the highest levels of ‘n’ and ‘t’ (Fig. 2 d—top-left panel). However, this was still unacceptable as the target was to completely eliminate contamination events. Moreover, operating at the highest levels of ‘n’ and ‘t’ increased the run-time of the decontamination protocol to about 1 min and would therefore reduce the throughput of our system. Upon further investigation of the pipetting protocol, we observed that like most fixed-tip liquid handling systems, our pipettes aspirate a very small amount of air (10 μL) before each pipetting step to separate the system liquid from the liquid being pipetted—the process liquid (Fig. 3 a). By increasing this air-gap, we were able to remarkably improve our decontamination protocol, achieving complete sterilization using an air-gap of 250 μL (Fig. 3 b and Additional file 1 : Figure S1). Interestingly, at the highest level of air-gap, we observed zero contamination events even at our lowest levels of ‘n’ and ‘t’ . It appears that when the volume of the air-gap is less than the maximum operating volume of the process liquid, there is a possibility for the sterile system liquid to come in direct contact with parts of the pipette that have not yet been disinfected. The system liquid is therefore compromised and could harbour viable cells, which increases the possibility of contamination during further pipetting steps (Fig. 3 c). An air-gap greater than the highest process volume ensures complete separation of the system and process liquids, leading to proper decontamination (Fig. 3 c). We found that our protocol remained effective over a range of bleach concentrations even at the lowest levels of ‘n’ and ‘t’ (Fig. 3 d). Fig. 3 Optimizing decontamination protocol. a Schematic showing tip layout during a typical pipetting step. b Effect of varying the air-gap on the effectiveness of sterilization using 12% sodium hypochlorite for different values of ‘n’ —number of disinfectant washes and ‘t’ —disinfectant hold time. Each bar represents effectiveness calculated from 8 replicates. Negative controls using water as the disinfectant resulted in zero sterilization effectiveness for all values of ‘n’ and ‘t’ . c Proposed mechanism for enhanced sterility upon increasing the volume of the air-gap to be larger than pipetted volumes. d Sterilization effectiveness for different disinfectants with an air-gap of 250 μL. Each bar represents effectiveness calculated from 72 replicates While bleach serves as an effective disinfectant, there have been recent concerns surrounding the release of chloramines and cyanogen chloride upon its reaction with nitrogenous compounds present in growth media [ 32 ]. These compounds are toxic and have been reported to cause chronic health problems in humans. Hence, we tested the efficacy of 70% ethanol as an alternate disinfectant and found that it is as effective as bleach in preventing contamination events (Fig. 3 d). However, in our study, we autoclaved all spent media and used the disinfectant only to remove residual trace microbial contamination in the pipette tips, ensuring that the disinfectant never came in direct contact with growth media. Hence, for all further experiments, we chose to use two washes with 6% bleach as the disinfection technique. The duration of the entire decontamination procedure is about 10 s and is therefore at par with the throughput achieved using disposable plastic tips, with no plastic waste generated and minimal amounts of disinfectant used. Automated photometric calibration of liquid handling pipettes Following the implementation of our decontamination protocol, we observed that the accuracy of the pipettes had diminished quite significantly, with aberrant volumes being pipetted consistently. In order to examine the pipetting accuracy of the liquid handler before and after changing the air-gap, we used a photometric assay to compare the volumes pipetted by the automated platform to manually pipetted standards, similar to an assay described previously [ 33 ]. In our assay, we used an aqueous solution of potassium dichromate (K \\documentclass[12pt]{minimal}\n\t\t\t\t\\usepackage{amsmath}\n\t\t\t\t\\usepackage{wasysym} \n\t\t\t\t\\usepackage{amsfonts} \n\t\t\t\t\\usepackage{amssymb} \n\t\t\t\t\\usepackage{amsbsy}\n\t\t\t\t\\usepackage{mathrsfs}\n\t\t\t\t\\usepackage{upgreek}\n\t\t\t\t\\setlength{\\oddsidemargin}{-69pt}\n\t\t\t\t\\begin{document}$$_{2}$$\\end{document} 2 Cr \\documentclass[12pt]{minimal}\n\t\t\t\t\\usepackage{amsmath}\n\t\t\t\t\\usepackage{wasysym} \n\t\t\t\t\\usepackage{amsfonts} \n\t\t\t\t\\usepackage{amssymb} \n\t\t\t\t\\usepackage{amsbsy}\n\t\t\t\t\\usepackage{mathrsfs}\n\t\t\t\t\\usepackage{upgreek}\n\t\t\t\t\\setlength{\\oddsidemargin}{-69pt}\n\t\t\t\t\\begin{document}$$_{2}$$\\end{document} 2 O \\documentclass[12pt]{minimal}\n\t\t\t\t\\usepackage{amsmath}\n\t\t\t\t\\usepackage{wasysym} \n\t\t\t\t\\usepackage{amsfonts} \n\t\t\t\t\\usepackage{amssymb} \n\t\t\t\t\\usepackage{amsbsy}\n\t\t\t\t\\usepackage{mathrsfs}\n\t\t\t\t\\usepackage{upgreek}\n\t\t\t\t\\setlength{\\oddsidemargin}{-69pt}\n\t\t\t\t\\begin{document}$$_{7}$$\\end{document} 7 ) within concentration ranges that showed a linear relationship with absorbance at 350 nm, as a photometric standard. We pipetted different levels of the standard within volume ranges required during routine operation (3–200 μL) into a microplate. Then, an on-deck plate reader was used to measure the absorbance and determine the concentration of samples in each well, thereby providing an accurate estimate of the pipetted volumes. We observed that after increasing the air-gap, the pipetting error increased significantly for all pipette tips (Fig. 4 a), with values of up to 40% for some tips, implying that pipetting accuracy would depend on the volume of air-gap used for each pipetting step. The deviations in pipetted volumes were well above the maximum acceptable limits specified by the International Organization for Standardization [ 34 ] and would certainly hinder normal operation of the platform. Fig. 4 Automated photometric pipette calibration. a Change in pipetting error due to an increase in the air gap. b Workflow for automated photometric calibration. The liquid handler is made to pipette a photometric standard at different levels onto a microplate. The absorbance data of the microplate are recorded and fed to a pythonic script which automatically calculates pipetting errors and calibration parameters for the pipette. c Pre and post-calibration pipetting error with the air-gap adjusted to ensure sterility. The maximum allowable error was obtained from ISO8655 standards. Accuracy ranges for manual pipettes were obtained from various manufacturers of multi-channel pipettes Anticipating that there would be a need to vary the pipetting air-gap in the future to accomodate different operating volumes, we wished to develop a procedure that would enable quick and reliable determination of calibration parameters for the pipette tips. While automated gravimetric methods have been explored in the past for calibrating liquid handling pipettes, these would require the presence of a specialized, on-deck high-accuracy balance with minimal air-flow to prevent evaporation [ 35 ], which may not be available on most liquid handling decks. We expected that the volume estimates calculated using the photometric standard could be used to calibrate the pipettes. Upon analysis, we found a strong linear correlation between the pipetted volumes and the expected volumes within three different volume ranges—high (50–200 μL), mid (10–50 μL), and low (3–10 μL). Hence, we programmed the liquid handler to pipette eight different levels of the photometric standard within the three volume ranges in triplicate (Fig. 4 b). To enable automated processing of the data, we developed a python based script that accepts the absorbance data of the photometric standard along with the layout of the microplate used for calibration to determine the pipetting error for each volume pipetted. The script is then made to generate calibration parameters by performing a linear fit between the programmed/expected volume and the actual pipetted volume. Using these parameters it is possible to determine the volume that needs to be programmed into the liquid handler for a required volume to be pipetted. Using these new calibration parameters, we analyzed the pipetting accuracy for each of the custom volume ranges with the increased air-gap. We found that our photometric calibration procedure reduced the deviation for all pipette tips significantly and brought them well below the maximum acceptable limits and within the ranges guaranteed by pipette manufacturers for multi-channel pipettes (Fig. 4 c). However, it should be noted that any other changes in the physical characteristics of the fluid being pipetted or other pipetting factors such as air-gap would necessitate re-calibration. For example, we observed that simply increasing the speed of pipetting by a significant amount could lead to increased pipetting errors (Additional file 1 : Figure S2). Nevertheless, by using only on-deck instruments for calibration and a python script to automatically calculate calibration parameters, we were able to reduce the time required for calibrating each volume range to about 10 min. Hence, this protocol and the python script can be easily adapted to calibrate a wide variety of liquid handlers to restore accuracy when changing the pipetting parameters or the fluids being pipetted. Maintaining sustained anaerobic environments in microplates Having established protocols to eliminate contamination and calibrate pipettes, we aimed to investigate our platform’s ability to accelerate the ‘test’ phase of the DBTL cycle in metabolic engineering. As mentioned before, we were particularly interested in developing protocols for anaerobic phenotyping of enzymes and microbial strains in microplates due to the oxygen limiting nature of most high density fermentation processes. Short enzyme assays under anaerobic conditions can be achieved with relative ease through the addition of the oxygen scavenging enzymes such as glucose oxidase or Oxyrase along with suitable substrates [ 36 ] in each well of the microplate. However, accurate phenotyping of microbial strains under anaerobic conditions using such enzymatic de-oxygenation would be challenging due to the need for glucose or other substrates for the enzymes to function. This would hinder accurate quantification of these metabolites after fermentation, resulting in incomplete carbon balances. Therefore, we decided to to use an anaerobic chamber to remove oxygen from the microplate by subjecting it through cycles of vacuum and flushing with nitrogen gas. While anaerobic chambers are excellent for expelling oxygen from microplates, they require additional sophisticated equipment to control humidity. Without humidity control, the evaporation rates within anaerobic chambers are quite high, resulting in loss of media volume. Upon culturing different E. coli strains within the anaerobic chamber, we found that the rates of evaporation were so high that accurate measurements of cell density could not be made even though the duration of our fermentations were quite short (Additional file 1 : Figure S4). As a possible solution, we examined the sealing efficacy of various adhesive films to sustain the anoxic conditions generated within the anaerobic chamber for fermentations outside. To measure of oxygen penetration into the microplate, we calculated biomass yields (ratio of final to initial biomass, measured as absorbance at 600 nm) of wild type E. coli (MG1655) grown to saturation in a rich defined medium within each well. Since E. coli grows faster under aerobic conditions, we should expect a consequent higher yield in wells that have increased oxygen penetration and low yields where anoxic conditions were sustained. As expected, in our control with a gas permeable film, we found a relatively high median biomass yield, characteristic of high oxygen penetration (Fig. 5 a). The use of a microplate lid with anaerobic adhesive tape did not offer much improvement in the seal, with only a modest decrease in the median biomass yield. The aluminium and polyester seals (typically used in PCRs) offered a significant improvement in the seal, with the polyster film being able to reduce the variability amongst wells as well. However, upon analysis of the biomass yield distribution within the microplates, we found clear patterns of enhanced growth in certain areas, likely resulting from improper sealing and heterogeneous oxygen concentrations(Fig. 5 a and Additional file 1 : Figure S3). Hence, the use of a film would inevitably lead to heterogenity in cellular phenotypes in addition to increased throughput times due to the need for manual sealing of each microplate. Fig. 5 Establishing anaerobicity in 96-well microplates. a Effectiveness of various seals in preventing oxygen penetration into microplates containing E. coli MG1655 in RDM, sealed within an anaerobic chamber. The biomass within each microplate are represented as violin plots. To the right of each violin plot, the distribution of biomass yields are represented as heatmaps showing deviation of the biomass yields from the median biomass yield within that plate. b Time-course showing cell density and instantaneous growth rate of E. coli MG1655 in RDM with and without a layer of oil in the presence of oxygen and with a layer of mineral oil inside an anaerobic chamber Alternatively, a layer of mineral oil (50 μL), pipetted on top of the microbial culture in each well offered a homogeneous gas exchange profile, evidenced by the tight distribution of biomass yield (Fig. 5 a and Additional file 1 : Figure S3). The mineral oil was also successful at completely eliminating loss of media during the fermentation within the anaerobic chamber, restoring the ability to monitor growth accurately (Additional file 1 : Figure S4). In order to ensure that the growth profiles of E. coli are only affected by the resulting oxygen transfer and not directly by the mineral oil, we examined the growth of four different strains of E. coli with and without the layer of mineral oil, inside and outside the anaerobic chamber (Fig. 5 b and Additional file 1 : Figure S4). We were able to clearly distinguish three different regimes in all the growth profiles—(I) an initial regime where dissolved oxygen in the media is used, indicated by the relatively higher growth rates of cells grown outside the anaerobic chamber, (II) an intermediate regime where the cells without the layer of mineral oil outside the anaerobic chamber are able to grow at accelerated rates due to increased oxygen transfer, and (III) a final growth phase where all the cells grow at similar rates due to no oxygen transfer due either to high cell densities or to the layer of mineral oil. It can be inferred from growth regimes (I) and (III) that the mineral oil does not directly impair or assist the growth of the strains but only controls the rate of gas exchange. Hence, it is suitable to maintain anoxic growth within an anaerobic chamber for extended durations with minimal loss of media due to evaporation. Case study 1: applying the liquid handling platform for an anaerobic enzymatic screen As a preliminary validation of our high throughput phenotyping platform, we sought to perform an anaerobic activity screen of the enoate reductase enzyme YqjM from Bacillus subtilis ( Bs -YqjM). This enzyme belongs to the family of old yellow enzymes (EC 1.6.99.1) which are broadly known as enoate reductases. They use non-covalently bound flavin mononucleotide (FMN) to catalyze the reduction of double bonds found in \\documentclass[12pt]{minimal}\n\t\t\t\t\\usepackage{amsmath}\n\t\t\t\t\\usepackage{wasysym} \n\t\t\t\t\\usepackage{amsfonts} \n\t\t\t\t\\usepackage{amssymb} \n\t\t\t\t\\usepackage{amsbsy}\n\t\t\t\t\\usepackage{mathrsfs}\n\t\t\t\t\\usepackage{upgreek}\n\t\t\t\t\\setlength{\\oddsidemargin}{-69pt}\n\t\t\t\t\\begin{document}$$\\alpha$$\\end{document} α , \\documentclass[12pt]{minimal}\n\t\t\t\t\\usepackage{amsmath}\n\t\t\t\t\\usepackage{wasysym} \n\t\t\t\t\\usepackage{amsfonts} \n\t\t\t\t\\usepackage{amssymb} \n\t\t\t\t\\usepackage{amsbsy}\n\t\t\t\t\\usepackage{mathrsfs}\n\t\t\t\t\\usepackage{upgreek}\n\t\t\t\t\\setlength{\\oddsidemargin}{-69pt}\n\t\t\t\t\\begin{document}$$\\beta$$\\end{document} β -unsaturated aldehydes and ketones using NADPH or NADH as electron donors [ 37 ]. The ability of Bs -YqjM and other enoate reductases to reduce -ene groups is important for the catalysis of chemical commodities such as muconic acid to adipic acid (a pre-cursor to nylon). However, the activity of Bs -YqjM enzymatic activity is known to be supressed in the presence of oxygen under aerobic conditions due to a prominent background reaction where electrons from NADPH are transferred to dissolved molecular oxygen in the buffer. In contrast, its activity is markedly increased under anaerobic conditions where electrons are instead donated to its target -ene substrates [ 38 ]. For the 2-cyclohexen-1-one substrate, Bs-YqjM was reported to have a K \\documentclass[12pt]{minimal}\n\t\t\t\t\\usepackage{amsmath}\n\t\t\t\t\\usepackage{wasysym} \n\t\t\t\t\\usepackage{amsfonts} \n\t\t\t\t\\usepackage{amssymb} \n\t\t\t\t\\usepackage{amsbsy}\n\t\t\t\t\\usepackage{mathrsfs}\n\t\t\t\t\\usepackage{upgreek}\n\t\t\t\t\\setlength{\\oddsidemargin}{-69pt}\n\t\t\t\t\\begin{document}$$_{M}$$\\end{document} M value of 0.3–0.6 mM under anaerobic conditions created using a glucose-glucose oxidase system, which consumes the dissolved molecular oxygen in the buffering solution to simulate completely anaerobic conditions. To demonstrate the use of an automated LiHa platform for performing anaerobic assays, we purified BsYqjM and assayed its activity for 2-cyclohexen-1-one by monitoring changes in the absorbance at 340 nm due to NADPH oxidation. After calibration of the tips for smaller volumes in the 3–10 μL range, we observed a K \\documentclass[12pt]{minimal}\n\t\t\t\t\\usepackage{amsmath}\n\t\t\t\t\\usepackage{wasysym} \n\t\t\t\t\\usepackage{amsfonts} \n\t\t\t\t\\usepackage{amssymb} \n\t\t\t\t\\usepackage{amsbsy}\n\t\t\t\t\\usepackage{mathrsfs}\n\t\t\t\t\\usepackage{upgreek}\n\t\t\t\t\\setlength{\\oddsidemargin}{-69pt}\n\t\t\t\t\\begin{document}$$_{M}$$\\end{document} M value of 0.35 ± 0.06 mM using the automated platform (Fig. 6 a). In comparison, we performed the same assay manually and observed a K \\documentclass[12pt]{minimal}\n\t\t\t\t\\usepackage{amsmath}\n\t\t\t\t\\usepackage{wasysym} \n\t\t\t\t\\usepackage{amsfonts} \n\t\t\t\t\\usepackage{amssymb} \n\t\t\t\t\\usepackage{amsbsy}\n\t\t\t\t\\usepackage{mathrsfs}\n\t\t\t\t\\usepackage{upgreek}\n\t\t\t\t\\setlength{\\oddsidemargin}{-69pt}\n\t\t\t\t\\begin{document}$$_{M}$$\\end{document} M value of 0.33 ± 0.4 mM. The similarity of these K \\documentclass[12pt]{minimal}\n\t\t\t\t\\usepackage{amsmath}\n\t\t\t\t\\usepackage{wasysym} \n\t\t\t\t\\usepackage{amsfonts} \n\t\t\t\t\\usepackage{amssymb} \n\t\t\t\t\\usepackage{amsbsy}\n\t\t\t\t\\usepackage{mathrsfs}\n\t\t\t\t\\usepackage{upgreek}\n\t\t\t\t\\setlength{\\oddsidemargin}{-69pt}\n\t\t\t\t\\begin{document}$$_{M}$$\\end{document} M values to each other and to published literature values suggested that the LiHa platform could be used to automate the preparation of screens, such as those to determine the optimal pH for maximum activity. Towards this end, we determined Bs-YqjM’s activity across pH 2.2–8 using the liquid handler (Fig. 6 b). We found that BsYqjM operates optimally at pH 5–6, which aligns with previously reported results that Bs-YqjM prefers slightly acidic conditions [ 38 ]. Fig. 6 Anaerobic enzymatic screen. a Enzymatic activity of YqjM on 2-cyclohexen-1-one determined manually and by the liquid handler. Enzyme activity is represented in units of μmol/min. b Effect of pH of the medium on the activity of YqjM on 2-cyclohexen-1-one Case study 2: scaling down anaerobic microbial phenotypes from pH controlled bioreactors to microplates Having assessed the efficacy of our system in determining enzyme kinetic parameters under anaerobic conditions, we wished to investigate the applicability of a fixed-tip liquid handling system for a high-throughput characterization of microbial phenotypes under anaerobic conditions. While it is possible to rapidly cultivate microbial strains using our platform, the possible deviation of phenotypes at increasingly larger scales is a cause for concern, resulting in ambiguity of the strains to be chosen for further screening. Previous studies examining scaling considerations have primarily investigated the difficulty of improving oxygen transfer rates within the wells of microplates [ 18 , 39 ]. However, since we are interested only in anaerobic environments, oxygen transfer rates may not play a key role in determining phenotypes. Rather, the concentration of substrate, pH, and other media conditions could be the determining factors. Hence, as a second test case to validate our platform, we investigated the ability to scale-down microbial phenotypes observed in pH controlled 500 mL bioreactors to 96 well microplates under anaerobic conditions. To this end, we examined the growth and metabolite profiles of four strains of E. coli —MG1655 and its lactate overproducing deletion mutant, MG1655 \\documentclass[12pt]{minimal}\n\t\t\t\t\\usepackage{amsmath}\n\t\t\t\t\\usepackage{wasysym} \n\t\t\t\t\\usepackage{amsfonts} \n\t\t\t\t\\usepackage{amssymb} \n\t\t\t\t\\usepackage{amsbsy}\n\t\t\t\t\\usepackage{mathrsfs}\n\t\t\t\t\\usepackage{upgreek}\n\t\t\t\t\\setlength{\\oddsidemargin}{-69pt}\n\t\t\t\t\\begin{document}$$\\Delta (adhE, pta)$$\\end{document} Δ ( a d h E , p t a ) at three different stages of adaptive laboratory evolution (denoted \\documentclass[12pt]{minimal}\n\t\t\t\t\\usepackage{amsmath}\n\t\t\t\t\\usepackage{wasysym} \n\t\t\t\t\\usepackage{amsfonts} \n\t\t\t\t\\usepackage{amssymb} \n\t\t\t\t\\usepackage{amsbsy}\n\t\t\t\t\\usepackage{mathrsfs}\n\t\t\t\t\\usepackage{upgreek}\n\t\t\t\t\\setlength{\\oddsidemargin}{-69pt}\n\t\t\t\t\\begin{document}$$\\Delta (adhE, pta)$$\\end{document} Δ ( a d h E , p t a ) -D1, D28 and D59 to represent the duration of adaptive laboratory evolution in days) [ 40 ]. These strains were chosen because of the expected difference in their anaerobic phenotypes. During anaerobic growth, E. coli undergoes mixed acid fermentation due to the non-availability of oxygen as a terminal electron acceptor to produce ATP and regenerate the redox cofactors NAD and NADP. Instead, E. coli produces a mixture of formate, acetate, ethanol, lactate, and small quantities of other organic acids as terminal fermentation products (Fig. 7 a), with acetate, ethanol, and formate being preferred products due to higher energy yields. Due to deletions around key fermentation reactions involved in acetate and ethanol production (pta and adhE respectively), the deletion mutants used in our study are expected to show high lactate yields. Further, because these strains are products of adaptive laboratory evolution, those strains at a later stage of evolution are expected to show increased growth rates. Fig. 7 Comparison of E. coli ’s anaerobic phenotype in bioreactors and microplates. a Schematic showing typical fermentation pathways in E. coli . Typical products of mixed acid fermentation on glucose are shown in the pathway along with key fermentation reactions shown in italics. The metabolites measured in this study are shown in blue. b Microbial phenotypes reduced to two components through t-distributed stochastic neighbors embedding (t-SNE) performed on the metabolite (acetate, formate, lactate, pyruvate, and succinate) yields and growth rates of E. coli strains grown in rich defined media in a bioreactor and microplates with different initial concentrations of substrate (glucose). Cluster boundaries were drawn manually for illustrative purposes. c A comparison of WildType E. coli ’s growth rate and metabolite yields on glucose obtained from a bench-top 0.5 L bioreactor and 96-well microplates with different initial concentrations of substrate (glucose) To compare the metabolic state of the different strains grown in a bioreactor and microplates, we calculated the growth rates and yields of five different products of fermentation on glucose towards the end of the exponential phase of growth(Additional file 1 : Figure S8). The deletion mutants grown in microplates showed good agreement with the bioreactor phenotype as is, possibly due to the elimination of the most prominent fermentation modes—acetate and ethanol production. However, the wild type strain showed pronounced phenotypic differences in the microplate, producing significantly lower levels of formate. It appeared that more carbon flux was directed towards lactate production than formate production in the microplates, resulting in less energy efficient fermentation and therefore, reduced growth rates. In order to eliminate the possibility of residual dissolved oxygen in the media causing aberrant phenotypes and lower formate yields, we examined the effect of adding the reducing agents—1 mM cysteine, 1 mM dithiothreitol (DTT), and 8 mM sodium sulfide to scavenge any residual oxygen and maintain reducing conditions within the media (Fig. 7 b and Additional file 1 : Figure S8). Higher concentrations of sodium sulfide were chosen because previous experiments at the 1mM level showed no visible differences in the phenotype. To better visualize and compare the overall phenotypic differences resulting from the different strains and media conditions, we performed a dimensionality reduction of the seven analytes (growth rate and yields of acetate, formate, lactate, pyruvate, succinate and biomass on glucose) through principal component analysis (PCA) (Additional file 1 : Figures S6 and S7). Upon analysis of the scores of each experimental trial on the first two principal components, the bioreactor trial for the wild-type strain resulted in phenotypes which could not be replicated in microplates since the bioreactor trials seemed to be isolated from the clusters formed by the microplate trials. Further, PCA indicated that residual oxygen may not an issue since the addition of reducing agents did little to alter the phenotypes. Examining the individual analytes (Additional file 1 : Figure S8), we found that the addition of cysteine at 1 mM did not alter the metabolite and growth profiles significantly for any of the strains. The addition of DTT showed a decrease in the yield of nearly all products including biomass for all strains, indicating that it could be inhibitory to the cells. Interestingly, the addition of sodium sulfide seemed to push the metabolic state slightly towards that observed in the bioreactor, with increased growth rates and acetate yields but lower lactate yields. However, since we did not observe similar phenotypes using the other reducing agents, we hypothesized that this difference could be due to the basic nature of sodium sulfide, which would result in longer fermentation times and therefore a different metabolic profile. We confirmed this by growing E. coli at a higher starting pH, resulting in longer fermentation duration, and similar trends in the metabolite yields and growth rates as observed in the addition of sodium sulfide. Hence, we concluded that our platform resulted in complete anaerobicity of the media and it was not dissolved oxygen that was affecting the metabolic state of the cells. It appeared that the pH and consequently, the fermentation duration played a more important role in determining the phenotype of the wild-type strain, as expected. The implementation of pH control in microplates requires specialized microplates with base delivery systems or mini-bioreactors, which would greatly increase operational costs [ 41 , 42 ]. We proposed that varying initial glucose concentrations would offer a crude yet inexpensive means to alter the duration of fermentation, thereby limiting pH change, and consequently, impact the phenotypes of all strains. Therefore, we grew the E. coli strains with different starting concentrations of glucose to examine this effect and determine glucose concentrations that allowed the phenotype of the wild-type strain observed in the bioreactor trial to be replicated in microplates (Fig. 7 c and Additional file 1 : Figure S10). At high initial glucose concentrations, all strains showed increased lactate yields and reduced biomass, formate and acetate yields on glucose. Specifically, for the wild type strain, this indicates that a significant portion of the carbon flux is directed towards lactate production with reduced flux through pfl , pta , and adh , resulting in less efficient fermentation and reduced growth rates. However, at lower substrate concentrations, the overall fermentation duration and consequently, the pH change during the fermentation decreased. This resulted in less overflow of carbon flux towards lactate and increased yields of biomass, acetate and formate, with almost no lactate and maximal formate, acetate and growth rates at the lowest concentrations analyzed. Performing the same dimensionality reduction through PCA as described previously, we found that varying initial glucose concentrations significantly alters the overall phenotypes exhibited by the cells, as shown by the spread of the scores of each experimental trial in the principal component space (Additional file 1 : Figure S9). Interestingly, several microplate trials with overall phenotypes very close to their bioreactor counterparts for each strain were observed. Particularly, the wild-type strain seemed to be closest to the microplate trial starting with 6 g/L of glucose. The other strains seemed less impacted by high initial glucose concentrations and showed good agreement with the bioreactor phenotype even at high glucose concentrations. While these results indicate that phenotypes observed in bioreactors can be reasonably replicated in microplates by varying initial substrate concentrations, the exact value for each strain may not be the same, as seen here. Further, the optimal glucose concentration for each strain cannot be determined a priori, which may lead to ambiguity in determining better performing strains to be chosen for scale up. Hence, we wished to investigate dimensionality reduction techniques, using which strains showing similarities at the bioreactor scale could be clustered together while segregating those that showed significant differences. Our dataset from the experiments varying initial glucose concentrations was ideal for this purpose since we observed an array of different phenotypes at the microplate scale for the same strain. Further, the mutant strains— \\documentclass[12pt]{minimal}\n\t\t\t\t\\usepackage{amsmath}\n\t\t\t\t\\usepackage{wasysym} \n\t\t\t\t\\usepackage{amsfonts} \n\t\t\t\t\\usepackage{amssymb} \n\t\t\t\t\\usepackage{amsbsy}\n\t\t\t\t\\usepackage{mathrsfs}\n\t\t\t\t\\usepackage{upgreek}\n\t\t\t\t\\setlength{\\oddsidemargin}{-69pt}\n\t\t\t\t\\begin{document}$$\\Delta$$\\end{document} Δ (adh, pta)-D1 and \\documentclass[12pt]{minimal}\n\t\t\t\t\\usepackage{amsmath}\n\t\t\t\t\\usepackage{wasysym} \n\t\t\t\t\\usepackage{amsfonts} \n\t\t\t\t\\usepackage{amssymb} \n\t\t\t\t\\usepackage{amsbsy}\n\t\t\t\t\\usepackage{mathrsfs}\n\t\t\t\t\\usepackage{upgreek}\n\t\t\t\t\\setlength{\\oddsidemargin}{-69pt}\n\t\t\t\t\\begin{document}$$\\Delta$$\\end{document} Δ (adh, pta)-D28 showed very similar phenotypes at the bioreactor scale. As seen previously (Additional file 1 : Figure S9), principal component analysis was only partially successful in this effort—while most trials with the D1 and D28 strain exp appeared in the same cluster, trials with the D59 strain also occurred very close to them. Moreover, the wild-type strains could not form a single cluster, possibly due to the large variability in the metabolite yields and non-linear correlations between the different metabolites used. Hence, PCA alone cannot be used to determine strains that would show similar performance at larger scales. A relatively new dimensionality reduction algorithm—t-distributed stochastic neighbors embedding, which recreates the probability distribution of the similarity of entities from a higher dimensional space and projects it onto two dimensions, has been found to be successful at clustering similar entities when a large number of dimensions are involved [ 43 ]. Particularly, it has found use in analyzing single cell transcriptomic data [ 44 ]. Even though our dataset is comprised of only 6 dimensions i.e. the yields of five metabolites and the growth rates, we proposed that tSNE could potentially be successful at clustering similarly performing strains in a two-dimensional space, particularly due to its use of non-linear dimensionality reduction. Remarkably, t-SNE performed on our phenotypic data showed near perfect clustering of strains showing similar performance at the bioreactor scale (Fig. 7 b). Specifically, all microplate trials from the wild-type strains and the \\documentclass[12pt]{minimal}\n\t\t\t\t\\usepackage{amsmath}\n\t\t\t\t\\usepackage{wasysym} \n\t\t\t\t\\usepackage{amsfonts} \n\t\t\t\t\\usepackage{amssymb} \n\t\t\t\t\\usepackage{amsbsy}\n\t\t\t\t\\usepackage{mathrsfs}\n\t\t\t\t\\usepackage{upgreek}\n\t\t\t\t\\setlength{\\oddsidemargin}{-69pt}\n\t\t\t\t\\begin{document}$$\\Delta$$\\end{document} Δ (adh, pta)-D59 strain were resolved into their individual clusters in spite of the visible differences in the phenotypes of individual trials. The two mutants \\documentclass[12pt]{minimal}\n\t\t\t\t\\usepackage{amsmath}\n\t\t\t\t\\usepackage{wasysym} \n\t\t\t\t\\usepackage{amsfonts} \n\t\t\t\t\\usepackage{amssymb} \n\t\t\t\t\\usepackage{amsbsy}\n\t\t\t\t\\usepackage{mathrsfs}\n\t\t\t\t\\usepackage{upgreek}\n\t\t\t\t\\setlength{\\oddsidemargin}{-69pt}\n\t\t\t\t\\begin{document}$$\\Delta$$\\end{document} Δ (adh, pta)-D1 and \\documentclass[12pt]{minimal}\n\t\t\t\t\\usepackage{amsmath}\n\t\t\t\t\\usepackage{wasysym} \n\t\t\t\t\\usepackage{amsfonts} \n\t\t\t\t\\usepackage{amssymb} \n\t\t\t\t\\usepackage{amsbsy}\n\t\t\t\t\\usepackage{mathrsfs}\n\t\t\t\t\\usepackage{upgreek}\n\t\t\t\t\\setlength{\\oddsidemargin}{-69pt}\n\t\t\t\t\\begin{document}$$\\Delta$$\\end{document} Δ (adh, pta)-D28 that showed similar performance at the bioreactor scale were resolved into a single cluster. These results indicate that tSNE could be used effectively to shortlist strains for analysis at larger scales, since it is able to effectively segregate strains showing markedly different phenotypes. Therefore, while initial glucose concentrations affect the phenotypes of microbial strains at the microplate scale significantly, the use of dimensionality reduction techniques such as tSNE could be used to resolve these differences and identify overall phenotypic differences between strains."
} | 11,036 |
30795747 | PMC6387494 | pmc | 9,034 | {
"abstract": "Background Ectomycorrhizal fungi (ECM) play a central role in nutrient cycling in boreal and temperate forests, but their role in the soil food web remains little understood. One of the groups assumed to live as specialised mycorrhizal feeders are Protura, but experimental and field evidence is lacking. We used a combination of three methods to test if Protura are specialized mycorrhizal feeders and compared their trophic niche with other soil invertebrates. Using pulse labelling of young beech and ash seedlings we analysed the incorporation of 13 C and 15 N into Acerentomon gallicum. In addition, individuals of Protura from temperate forests were collected for the analysis of neutral lipid fatty acids and natural variations in stable isotope ratios. Results Pulse labelling showed rapid incorporation of root-derived 13 C, but no incorporation of root-derived 15 N into A. gallicum . The transfer of 13 C from lateral roots to ectomycorrhizal root tips was high, while it was low for 15 N. Neutral lipid fatty acid (NLFA) analysis showed high amounts of bacterial marker (16:1ω7) and plant marker (16:0 and 18:1ω9) fatty acids but not of the fungal membrane lipid 18:2ω6,9 in A. gallicum . Natural variations in stable isotope ratios in Protura from a number of temperate forests were distinct from those of the great majority of other soil invertebrates, but remarkably similar to those of sporocarps of ECM fungi. Conclusions Using three in situ methods, stable isotope labelling, neutral lipid fatty acid analysis and natural variations of stable isotope ratios, we showed that Protura predominantly feed on mycorrhizal hyphae via sucking up hyphal cytoplasm. Predominant feeding on ectomycorrhizal mycelia by Protura is an exception; the limited consumption of ECM by other soil invertebrates may contribute to carbon sequestration in temperate and boreal forests. Electronic supplementary material The online version of this article (10.1186/s12898-019-0227-y) contains supplementary material, which is available to authorized users.",
"conclusion": "Conclusions All three methods used indicate that Protura predominantly feed on ECM by sucking up the cytoplasm of hyphal cells. Specialized feeding on a narrow spectrum of prey contrasts the dominance of generalist feeders in soil animal communities [ 42 , 43 ]. This also applies to the most abundant soil mesofauna taxa, i.e. Collembola and Oribatida [ 44 ]. Limited consumption of ECM hyphae by soil invertebrates might have contributed to the evolutionary success of the plant—mycorrhiza symbiosis and to major ecosystem functions such as plant growth and storage of organic matter in boreal and temperate forest soils.",
"discussion": "Discussion All three methods used in our study supported the assumption that Protura in their natural habitat actively feed on ECM. In the beech rhizosphere A. gallicum incorporated 13 C but not 15 N from labelled plants indicating that the species fed on ECM hyphae since plant C, but little plant N, is transferred into mycorrhizal fungi. In fact, ectomycorrhizal root tips were highly enriched in 13 C and less in 15 N, whereas lateral roots were less enriched in 13 C but more in 15 N, which is in line with the functioning of ECM in capturing soil N and transferring it to plant roots [ 22 ]. Our results suggest that C and N in A. gallicum originated from different sources. While C is derived from freshly assimilated plant C transported from leaves into roots and into ECM, N is derived from soil via inorganic and organic N compounds derived from decomposing soil organic matter assimilated by ECM hyphae and transported to plant roots [ 23 ]. This contrasts other soil invertebrates relying on root-derived resources which use both root C and N for tissue formation [ 24 ]. Due to low sample numbers in ash caution is needed in interpreting the findings, however, as compared to beech, A. gallicum incorporated markedly less root-derived C in the ash rhizosphere, indicating that A. gallicum feeds little on arbuscular mycorrhizal fungi associated with ash. Presumably, Protura switch diet and feed on saprotrophic fungi if ECM are scarce as suggested earlier [ 13 ]. However, as indicated by low abundance of A. gallicum in the ash as compared to the beech rhizosphere, they suffered from food shortage resulting in low density. Little feeding on arbuscular mycorrhizal fungi by A. gallicum likely is related to the smaller hyphal diameter of arbuscular mycorrhizal fungi as compared to ECM [ 22 ], suggesting that small size prevents effective consumption of the hyphal cytoplasm. Compared to saprotrophic fungi, arbuscular mycorrhizal fungi are less preferred by fungal feeding soil invertebrates [ 25 , 26 ], but see [ 27 ]. Potentially, arbuscular mycorrhizal fungi are protected against predation by metabolites provided by the plant [ 28 ]. The results support earlier undirect evidences that in temperate forests Protura rely on root-derived resources [ 10 , 29 ] and are specialized in feeding on mycorrhiza [ 13 , 14 ]. The main predators of Protura are assumed to be Gamasida [ 30 ], which is supported by a strong decrease in abundance with increasing numbers of Gamasida [ 31 ]. Thus, freshly-fixed root-derived C may be incorporated into small-sized soil predators via an ECM—Protura energy channel but this needs further investigation in controlled experiments. NLFA analysis added to the results of the stable isotope labelling data suggesting that Protura ingest food resources by sucking on plant based resources. High incorporation of the plant marker fatty acids 16:0 and 18:1ω9 in A. gallicum also has been reported for other fungal feeding animals such as the Collembola species Protaphorura fimata Gisin, 1952 feeding on the fungus Agrocybe gibberosa (Fries) Fayod, 1889 [ 32 ]. High concentration of the plant marker fatty acids 16:0 und 18:1ω9 in A. gallicum might reflect that via feeding on ECM they incorporate plant fatty acids transported into ECM [ 33 , 34 ]. In contrast to our hypothesis, A. gallicum contained little 18:2ω6,9, a dominant component of the lipid membrane of fungi commonly used as fungal biomarker [ 35 ] and reaching high concentrations in fungivorous microarthropods such as Lepidocyrtus cyaneus Tullberg, 1871 (21.86 ± 1.64%; S. Bluhm, unpubl. data). However, it has been found that the concentration of 18:2ω6,9 is ten times lower in the NLFA as compared to the PLFA fraction in ECM fungi [ 34 ]. This supports earlier observations that, in contrast to Collembola grazing on fungi, A. gallicum sucks up the cytoplasm of mycorrhizal hyphae, thereby not ingesting membranes. Furthermore, it has been shown that ECM have distinct fatty acid profiles varying between species [ 36 ]. The high concentrations of the bacterial-marker fatty acids 16:1ω7 and 18:1ω7 in A. gallicum also may be explained by feeding on ECM, as these biomarkers may also be present in basidiomycetes and arbuscular mycorrhizal fungi [ 37 , 38 ]. The trophic niche of Protura, as reflected by natural abundances of 13 C and 15 N, largely overlapped with that of ECM again supporting the conclusion that Protura feed on ECM. The 15 N natural abundance in A. gallicum in microcosms with unlabelled control plants exceeded the 15 N natural abundance in ECM root tips by 3.5‰, which is in line with the mean trophic level fractionation of 3.4‰ [ 39 ]. Natural variations in stable isotope ratios of Protura differed markedly from those of other soil invertebrates, suggesting that selective feeding on ECM by Protura is unique. Other soil animal taxa such as Onychiuridae (Collembola) also might feed on ECM, but in addition feed on other resources such as root hairs, i.e. are not specialized in feeding on ECM [ 9 , 40 ]. The fact that the density of Protura typically is low as compared to other mesofauna groups, contrasts the high biomass of ECM in temperate forest ecosystems. This striking pattern indicates that ECM are well protected from grazing by soil invertebrates including Protura, presumably via toxic compounds and crystalline ‘spines’ on the surface of hyphae [ 28 , 41 ]. High toxin concentrations and exclusive feeding on ECM by Protura likely contribute to their low abundance."
} | 2,063 |
31697017 | PMC6973155 | pmc | 9,035 | {
"abstract": "Abstract With the goal of imposing shape and structure on supramolecular gels, we combine a low‐molecular‐weight gelator (LMWG) with the polymer gelator (PG) calcium alginate in a hybrid hydrogel. By imposing thermal and temporal control of the orthogonal gelation methods, the system either forms an extended interpenetrating network or core–shell‐structured gel beads—a rare example of a supramolecular gel formulated inside discrete gel spheres. The self‐assembled LMWG retains its unique properties within the beads, such as remediating Pd II and reducing it in situ to yield catalytically active Pd 0 nanoparticles. A single PdNP‐loaded gel bead can catalyse the Suzuki–Miyaura reaction, constituting a simple and easy‐to‐use reaction‐dosing form. These uniquely shaped and structured LMWG‐filled gel beads are a versatile platform technology with great potential in a range of applications.",
"conclusion": "Conclusion In conclusion, we report spatial control over a LMWG assembly by combining a LMWG (DBS‐CONHNH 2 ) and a PG (alginate) to form spherical core–shell gel‐bead structures (or worms). Combining alginate with DBS‐CONHNH 2 enhances thermal stability and rheological performance. The mechanical properties of the hybrid gel can be tuned by the alginate concentration, giving gels with a range of stiffnesses and optimisable strain resistance, suggesting potential applications in, for example, cell culture. The LMWG (DBS‐CONHNH 2 ) retains its unique properties within the hybrid gel, such as the ability to reduce Pd II to Pd 0 NPs in situ, thus creating catalytic gel beads. Gel beads could be simply added into a Suzuki–Miyaura reaction, with just a single bead being able to facilitate the reaction. The ease of dosing these shaped and structured gel beads demonstrates an advantage of this approach—fusing the function of an active LMWG with the shaping potential of a PG. We suggest that this hybrid‐gel approach using calcium alginate to form gel beads should be broadly applicable to a wide range of different LMWGs in order to formulate them into gel spheres, and work in this direction is currently underway in our laboratories. This is therefore a very simple, highly versatile platform technology that could see widespread use in extending the range of LMWG applications. In addition to working on extending the range of gelators incorporated within these beads, we are also investigating further control to yield micro/nano‐sized gel beads, and demonstrating the full potential scope of encapsulated shaped and structured LMWG materials, thus opening up even more wide‐ranging new applications.",
"introduction": "Introduction Supramolecular hydrogels self‐assembled from low‐molecular‐weight gelator (LMWG) building blocks in water have seen rapid recent development. 1 A range of gels has been developed targeting high‐tech applications including regenerative medicine, wound healing, pharmaceutical formulation, optoelectronics, energy storage, and environmental remediation. 2 The physical features of a gel (for example, stiffness or porosity) as well as the chemical programming inherent within the LMWG scaffold can optimise gels for specific applications. However, in many cases, supramolecular gels suffer from rheological weakness, meaning they simply fill the vessel in which they are formed. This can make it challenging to endow self‐assembled gels with desired shapes and/or structures, yet the ability to shape and pattern such gels would open up new horizons for LMWGs. 3 Gels with spatially resolved structures could, for example, direct stem‐cell fate in regenerative medicine, 4 act as vehicles for controlled drug delivery, 5 or act as patterned conducting gels in integrated soft electronic devices that may ultimately interface with living systems. 6 A number of strategies have emerged to shape and structure supramolecular gels, 3 including photopatterning, 7 3D printing, 8 electrochemistry, 9 and surface‐mediated processes. 10 Several reports have used controlled diffusion to achieve spatial resolution. 11 Surprisingly, however, there have been limited reports of a supramolecular gel being formulated as spherical particles. Miravet and co‐workers reported this by dropwise addition of a DMSO solution of the gelator into an anti‐solvent, 12 while Ulijn and co‐workers used microfluidic methods and a water‐in‐oil emulsion to form gel microspheres. 13 Spherical nanofibre shells have also been formed via gelator self‐assembly at the interface of oil‐in‐water emulsion microspheres. 14 \n A key strategy that can enhance the behaviour of LMWGs is to form hybrid gels, 15 combining them with a polymer gelator (PG)—such systems can, for example, combine the responsiveness of a LMWG with the robustness of a PG network, hence enabling more effective shaping and structuring of the LMWG system. 3 Alginic acid is a fascinating PG—biocompatible, biodegradable, and versatile. 16 It is a natural polysaccharide composed of β‐ d ‐mannuronic acid and α‐ l ‐glucuronic acid units linked through β‐1,4 bonds (Figure 1 ). Its sodium salt is water‐soluble and forms hydrogels when mixed with multivalent cations (for example, Ca 2+ ) by generating ionic interchain bridges. Alginate gel beads can be obtained by dropwise addition of an aqueous alginate solution to CaCl 2 . 17 This is a well‐known gel system, explored in schools‐level education and exploited in pharmaceutical as well as food sectors. 18 More complex core–shell alginate beads in which the interior of the bead is filled with a second component can also be made. 19 However, to the best of our knowledge, there are no examples in which a self‐assembled LMWG has been incorporated within a polymer microgel bead.\n Figure 1 Gelator structures—low‐molecular‐weight gelator (LMWG) DBS‐CONHNH 2 and polymer gelator (PG) based on alginic acid. We envisaged a multicomponent gel in which the PG network would effectively act as a spherical mould to constrain LMWG self‐assembly. To achieve this spatial control, we decided to combine the alginate PG with 1,3:2,4‐di‐(4‐acylhydrazide)‐benzylidenesorbitol (DBS‐CONHNH 2 , Figure 1 ), a thermally responsive gel, demonstrated to be biocompatible and with potential applications ranging from environmental remediation and catalysis to drug formulation and tissue engineering. 20 In this paper, we report how combining the PG and LMWG gives a multicomponent system. The two networks can be spatially organised either a) as an extended standard vial‐filling gel with interpenetrating networks, or b) as well‐defined core–shell‐structured gel beads (or worms). Surprisingly, given the many uses of alginate and the versatility of LMWGs, reports of hybrid gels combining an alginate PG with LMWGs are rare, and in all cases, standard gels were made. 21 To the best of our knowledge, this is the first time a PG has imposed spherical shape onto an LMWG, thus yielding core–shell supramolecular gel beads (Figure 2 ).\n Figure 2 Schematic representation of the preparation of DBS‐CONHNH 2 /alginate multicomponent gels. 1) DBS‐CONHNH 2 is suspended in an aqueous solution of sodium alginate. 2) The suspension is heated until complete dissolution of the LMWG. To obtain a hybrid gel with extended interpenetrating networks, the hot solution was left to cool to room temperature, allowing the DBS‐CONHNH 2 network to form. An aqueous solution of CaCl 2 (5 %, 1 mL) was then added on top of the gel (3 a) to diffuse in, cross‐link the alginate, and form the second gel network (4 a). Alternatively, the hot solution was added to an aqueous solution of CaCl 2 dropwise, or as a continuous stream to form gel beads or (3 b) worms/strings (4 b), respectively. Note: The gels were coloured pink using food colouring to be better visualised.",
"discussion": "Results and Discussion The LMWG, DBS‐CONHNH 2 , was synthesized as previously reported. 20a This LMWG forms hydrogels at low concentrations (0.3 % wt/vol) using a heat–cool cycle. Low‐viscosity sodium alginate PG is commercially available and, as described above, can be triggered by CaCl 2 to form gels. Since the two gels have orthogonal assembly methods, we reasoned a specific spatial arrangement of the two networks within the hybrid LMWG/PG gel could be imposed (Figure 2 ). Initially, to demonstrate the orthogonality of the two gelators, the DBS‐CONHNH 2 /alginate interpenetrating network hydrogel was obtained using a stepwise approach (Figure 2 , panel 4 a) combining an aqueous suspension of DBS‐CONHNH 2 (0.3 % wt/vol) with sodium alginate (0.5 % wt/vol). Heating ensured complete dissolution of the LMWG, with gelation being triggered on cooling. Once the DBS‐CONHNH 2 gel had formed, an aqueous solution of CaCl 2 (5 % wt/vol, 1 mL) was added to the top of the gel and allowed to diffuse through it, causing cross‐linking and gelation of the alginate. The gel properties are briefly summarised below. Macroscopically, the thermal stability, evaluated via a simple tube‐inversion method, indicated that alginate increased the gel–sol transition temperature ( T \n gel ) from 86 °C for DBS‐CONHNH 2 gel (0.4 % wt/vol) to >100 °C, that is, the alginate PG network improves thermal stability. In terms of mechanical properties, oscillatory rheology using parallel plate geometry indicated that the DBS‐CONHNH 2 hydrogel (0.4 % wt/vol) has an elastic modulus ( G′ ) of 800 Pa, the alginate gel (0.4 % wt/vol) has a G′ of 490 Pa, whereas two‐component gels at similar loadings displayed higher G′ values (>5000 Pa)—the two networks thus support each other, increasing stiffness (Supporting Information, Table S2, Figures S15–S23). Similar effects are frequently observed for interpenetrated network polymer gels. 22 Furthermore, hybrid gels obtained using low alginate concentrations were more resistant to strain than gels formed by the individual components, with a linear viscoelastic region (LVR) that extends up to ca. 50 % strain in contrast to ca. 6.5 % for an equivalent amount of calcium alginate and 25 % for the gel formed only by DBS‐CONHNH 2 . Higher alginate concentrations made the hybrid gels more brittle. The loading of alginate thus allows optimisation between G′ (stiffness) and resistance to strain (brittleness). Tunable mechanical properties of this type are of great use in cell‐culture applications. 4 \n On the nanoscale, scanning electron microscopy (SEM) and transmission electron microscopy (TEM) indicated that DBS‐CONHNH 2 and calcium alginate both formed extended nanofibres, ca. 20–40 nm and 40–60 nm in diameter, respectively (Figures S8 and S9). The two‐component interpenetrated network gel exhibited long nanofibers with diameters of ca. 20–50 nm, consistent with both LMWG and PG networks being present—the networks could not be differentiated because of their relatively similar fibre diameters. On the molecular scale, IR spectroscopy (Figure S2) indicated that the alginate O−H stretching frequency (3390 cm −1 ) shifted to 3370, 3362, and 3351 cm −1 in the two‐component gel obtained using 1.0 %, 0.5 %, and 0.3 % wt/vol of alginate, respectively, combined with 0.3 % wt/vol of DBS‐CONHNH 2 . As the relative loading of LMWG increases, the alginate O−H band thus progressively shifts to smaller wavenumbers, suggesting non‐covalent interactions between DBS‐CONHNH 2 and alginate in the hybrid gel, which provides evidence for interaction between the networks, in support of rheology. In the presence of alginate, the O−H (3282 cm −1 ) and N−H (3167 cm −1 ) stretching bands of DBS‐CONHNH 2 were broadened, also supportive of interactions with the alginate network. Having determined that these two gel networks could indeed be assembled in a stepwise manner, we then targeted LMWG/PG hybrid gels with spatially constrained organisation—specifically core–shell gel beads (Figure 2 , panel 3 b, and Figure 3 a). We used the same quantities of DBS‐CONHNH 2 and sodium alginate, but after heating, the resulting hot solution was added dropwise to aqueous CaCl 2 (5 % wt/vol). Small gel beads (Figure 3 b) rapidly formed on calcium‐induced cross‐linking of the alginate chains, with simultaneous self‐assembly of DBS‐CONHNH 2 on cooling. The beads were then quickly removed from the mixture. To make the method reproducible and obtain gel beads of similar dimensions, each gel bead was prepared by adding 20 μL of hot alginate/DBS‐CONHNH 2 solution. We combined DBS‐CONHNH 2 (0.3 % wt/vol) with different alginate concentrations and established that 0.5 % wt/vol was the minimum PG concentration required to isolate spheroidal gel beads. They could also be made with higher alginate concentrations (that is, 0.75 and 1.0 % wt/vol), but at lower concentrations (≤0.3 % wt/vol), they were more irregular.\n Figure 3 Images of hybrid DBS‐CONHNH 2 /alginate gel beads. a) Schematic diagram of a bead; b) Photograph of beads (droplet size 20 μL) adjacent to a ruler (scale in cm); c)–e) Optical microscopy of the cross‐section of a bead. c) Droplet size 20 μL, scale bar 500 μm, d) droplet size 1 μL, scale bar 150 μm, e) Bead embedded in resin and coloured using toluidine blue (scale bar 1 mm); f) SEM image of a bead (scale bar 500 μm); g) SEM image of the surface of a bead (scale bar 1 μm); h) SEM image of the interior cross‐section of a bead (scale bar 1 μm). The gel beads had diameters of 3.0–3.6 mm (Figure 3 b). The theoretical diameter ( d ) of a sphere of a known volume ( V ) is obtained using: d = 2 3 V / 4 π 3 \n. Since for each gel bead, a volume of 0.020 mL (=0.02 cm 3 ) was used, spheres of 0.336 cm (3.36 mm) diameter were predicted—the observed bead diameters therefore agree with expectations. The diameter was varied by simply changing the volume of liquid added dropwise to CaCl 2 . Using 5 and 1 μL volumes, we obtained gel beads with diameters of 1.6–2.0 mm and 0.75–1.0 mm, respectively (Figure 3 d). Simple optical microscopy clearly indicated core–shell structures (Figures 3 c and d). Further optical microscopy on the gel beads cut in half, embedded in resin and dyed with toluidine blue, indicated a clear difference between the interior volume and the outer shell in the hybrid gel‐bead cross‐section (Figure 3 e). This was not seen for the beads formed from alginate alone (Figure S7). SEM (Figure 3 f) provided insight into the nanoscale morphologies of the bead surface (Figure 3 g) and cross‐section (Figure 3 h). Samples were prepared by freeze‐drying to minimise drying effects. DBS‐CONHNH 2 /alginate and alginate gel‐bead surfaces appeared wrinkled (Figures 3 g, S12, and S13) and densely packed, consistent with a highly cross‐linked calcium alginate shell. The SEM image of the cross‐section of the hybrid gel beads shows an extended nanofibrillar network in the core of the bead (Figure 3 h), consistent with incorporation of the LMWG in self‐assembled form inside the bead. By varying the mode of addition of the hot solution containing the LMWG/PG mixture to CaCl 2 , the gels could be formed into other shapes, for example, worms (Figure 2 , panel 4 b). Worms were prepared by adding the hot alginate/DBS‐CONHNH 2 solution to the CaCl 2 solution as a thin stream rather than dropwise. Stupp and co‐workers also used calcium chloride solution to induce the formation of gel worms, 23 although in their case, a peptide amphiphile was used as the self‐assembling unit which itself was stiffened as a result of interactions with calcium ions—no PG was present to mediate the process. Our data are consistent with a model in which, as the hot solution is added dropwise into calcium chloride, the periphery is rapidly converted into a calcium alginate cross‐linked shell. As the system cools, the LMWG then assembles within this sphere (or worm) to form a self‐assembled gel interior. In this way, the calcium alginate PG effectively acts as a vessel or mould that contains the self‐assembling LMWG. This prevents the LMWG from uncontrolled assembly into an extended vial‐filling gel, and hence yields discrete shaped and structured LMWG/PG objects. To quantify the amount of DBS‐CONHNH 2 incorporated into each gel bead, a simple 1 H NMR experiment was used. Ten beads were isolated and dried under vacuum. The resulting solid was dissolved in [D 6 ]DMSO, dissolving all the DBS‐CONHNH 2 but not alginate, so the LMWG can be determined by 1 H NMR. Acetonitrile (CH 3 CN) was used as an internal standard, and the concentration of LMWG was hence calculated by comparing the integrals of relevant resonances (DBS‐CONHNH 2 aromatic protons: δ=7.53 and 7.83 ppm, and the acetonitrile CH 3 group: δ=2.09 ppm; Figure S1). In principle, 50 gel beads (20 μL volume each) could be prepared from 1 mL of water containing DBS‐CONHNH 2 (0.3 % wt/vol, 6.32 μmole) and sodium alginate (0.5 % wt/vol). If the DBS‐CONHNH 2 was fully incorporated and evenly distributed into the gel beads, each bead should contain ca. 0.12 μmole of LMWG. The NMR study showed that the amount of LMWG in each gel bead was ca. 0.11 μmole. This experiment was highly reproducible and we therefore reason that >90 % of the LMWG is incorporated within the LMWG/PG gel beads, demonstrating the efficiency of this fabrication method. IR spectroscopy (Figures S2 and S3) indicated that in the hybrid gel beads, the O−H and N−H stretching bands of DBS‐CONHNH 2 were broadened, and the alginate O−H stretching frequency shifts from 3390 cm −1 to 3352 and 3341 cm −1 (with 1.0 and 0.5 % wt/vol of alginate, respectively). These shifts are similar to those described for the interpenetrated gels described above. To demonstrate one possible use of these spatially constrained hybrid gels, we explored catalysis. Gels have great potential in catalysis as a result of their solvated nature and the ability of small‐molecule reagents to diffuse through them—indeed, gels can be considered intermediate between homogeneous and heterogeneous catalytic systems, combining the advantages of both. 24 We recently reported that DBS‐CONHNH 2 hydrogels achieve efficient in‐situ reduction of precious metals to yield gels with embedded metal nanoparticles (NPs). 20c Furthermore, gels with embedded palladium nanoparticles (PdNPs) can catalyse Suzuki–Miyaura cross‐coupling reactions. 25 We were interested to see if the presence of alginate affected Pd uptake or catalysis and demonstrate advantages of the gel bead formulation. Gel samples were left to interact with aqueous PdCl 2 (3 mL, ca. 5 m m ), and at specified times, the supernatant PdCl 2 was analysed by UV/Vis spectroscopy (Figures 4 a and S25–S27) to determine the remaining concentration of Pd II and thus the amount of Pd incorporated within the gel. The calcium alginate gel itself could also incorporate Pd II , in agreement with literature reports. 26 However, based on the colour of the Pd‐loaded calcium alginate gel being yellow, the incorporated Pd is clearly still in the oxidation state +2 (Figure S30). On the contrary, when DBS‐CONHNH 2 was present in the hybrid gel, the gel changed to dark brown/black suggesting not only Pd II incorporation but in‐situ reduction to Pd 0 (Figure S30). When the gel was prepared as hybrid gel beads, Pd uptake was faster compared with the extended interpenetrating network gel in vials, presumably due to the greater relative surface area of the beads—a black colour, consistent with reduction of Pd II to Pd 0 NPs, was again observed. The total amount of Pd within the DBS‐CONHNH 2 /alginate gels was ca. 33 % of that in our previously prepared DBS‐CONHNH 2 /agarose gels. 25 This agrees with the proposal above that there are interactions between DBS‐CONHNH 2 and alginate networks—we suggest these somewhat limit the ability of the acylhydrazide to reduce Pd II to Pd 0 . The formation of PdNPs was confirmed by TEM and SEM (Figures 4 c,d, S28, and S29), with the NPs being attached to the gel fibres (where the acyl hydrazide groups are located) and mostly spherical with diameters <5 nm.\n Figure 4 a) UV/Vis spectra of Pd uptake by Pd hybrid gel beads (3.00 mg DBS‐CONHNH 2 in 0.5 mL H 2 O, 0.5 mL 1 % alginate, 1 mL 5 % CaCl 2 ); b) Amount of Pd embedded within the gel beads; c) TEM image of hybrid gel beads with PdNPs, scale bar 200 nm; d) SEM image of hybrid gel beads with PdNPs, scale bar 0.5 μm. The catalytic activity of DBS‐CONHNH 2 /alginate gels loaded with PdNPs was studied in a standard Suzuki–Miyaura cross‐coupling reaction between 4‐iodotoluene and phenylboronic acid (0.8 mmol scale). 25 When we used the whole amount of extended interpenetrating network DBS‐CONHNH 2 /alginate gel (3 mg of DBS‐CONHNH 2 and 1 mL of 1 % alginate) containing ca. 12 μmol of Pd (1.2 mol %) and performed the reaction in the vial in which the gel was formed, we obtained the desired product 2 a in 98 % yield after stirring at 50 °C for 24 h—however, we note that under these stirring conditions, the gel was broken down. The reaction was then performed without stirring, using just one single hybrid gel bead as a catalyst (ca. 0.4 μmol of Pd, 0.05 mol %). Pleasingly, product 2 a was obtained in 99 % yield after 24 h. This clearly demonstrates that these hybrid gel beads have high catalytic potential, and that even a single bead can effectively catalyse the Suzuki–Miyaura reaction (molar ratio of catalyst:reagent=1:2000). The conversions obtained using these DBS/CONHNH 2 /alginate hybrid LMWG/PG gel beads (99 % after 24 h using 0.05 mol % Pd) were very similar to those obtained and reported previously using simple DBS‐CONHNH 2 /agarose hybrid gels (93 % after 18 h with 0.05 mol % Pd), suggesting encapsulation within the gel bead is not having an adverse effect on catalytic performance. To demonstrate some scope of these catalytic gel beads, we also performed reactions with a range of other substrates to give 2 b – 2 f in good yield (Scheme 1 ). Scheme 1 Suzuki cross‐coupling reaction using a single Pd‐hybrid gel bead. Reaction conditions: 4‐iodoarene (0.80 mmol), phenylboronic acid (0.96 mmol), K 2 CO 3 (1.60 mmol), EtOH (3 mL), H 2 O (1 mL), and Pd hybrid gel bead (prepared using 1 mL of 1 % alginate; containing ≈0.05 mol % of Pd). The reaction was carried out without stirring at 50 °C for 24 h. Compound 2 a was made using a single gel bead recycled five times. Conversions determined by 1 H NMR. Although the PdNP gels showed excellent catalytic activity, they could not be easily removed from the reaction. We attempted to increase their mechanical stability by increasing the amount of alginate (1 mL of 2 % alginate solution) or using high‐viscosity alginate (1 mL of 1 % alginate solution), but the gel bead could not be removed with a spatula after reaction. We therefore simply left the gel bead in the reaction vial, removed the reaction mixture by a Pasteur pipette, washed the gel bead with diethyl ether and water, and charged the reaction vial with fresh starting materials. In this way, it was possible to re‐use a single Pd‐hybrid gel bead five times (Scheme 1 ), with high conversion and yield, pleasingly demonstrating the recyclabillity and re‐use of these gel beads. We tested the Pd‐leaching from these beads (Supporting Information, Section S11) and found some palladium was leached into the solvent during reaction. At the end of the reaction, if the solution was removed from the bead and charged with different Suzuki‐reaction substrates, then the second Suzuki reaction would proceed to >90 %, even in the absence of the bead. Leaching is more pronounced than from our previously reported agarose hybrid hydrogels (34 % Suzuki coupling achieved using the filtrate). 25 We suggest that this results from Pd in the alginate shell being less effectively bound and the larger relative surface area of the small beads used here. Nonetheless, a significant amount of Pd is clearly retained within the beads because, as described above, they can be re‐used in the reaction five times (an overall molar ratio of catalyst:reagent=1:10 000) and the gel beads can definitely be considered as the source of Pd required for the reaction. Overall, it is evident the LMWG retains its fundamental Pd remediation and catalysis properties within these shaped and structured core–shell beads. As such, this fabrication method is a very simple way of imposing shape onto an active and functional self‐assembled gelator. The core–shell hybrid gel beads are a straightforward and efficient dosing form for these catalytic gels—one single bead can be placed into the reaction vessel to facilitate the Suzuki–Miyaura cross coupling and the product is easily extracted. This would therefore be an effective way of supplying catalytic gels in a simple physical form, which is easy for the end‐user to employ in synthesis. This clearly demonstrates the advantage of combining a functional LMWG with a PG that plays the role of imposing defined shape and structure onto the overall system."
} | 6,232 |
36380916 | PMC9632252 | pmc | 9,039 | {
"abstract": "PET (polyethylene terephthalate) has good transparency, corrosion resistance, gas barrier properties and mechanical properties, and is widely used in beverage bottles, fabrics, food packaging, tires, films, engineering plastics and other fields. With the rapid growth in demand and use of PET materials, the pollution of waste PET to the environment has become increasingly prominent. The recycling methods of waste PET mainly include primary recycling, mechanical recycling, chemical recycling, and energy recycling. The chemical recycling method is of great significance for solving environmental problems and reducing the plastic industry's dependence on petrochemical resources, and is an inevitable choice for realizing PET closed-loop recycling. In this paper, the chemical depolymerization methods of waste PET, the types of alcoholysis catalysts with the greatest possibility of industrialization, and the high-value application research of chemical recovery products are reviewed in order to have a good reference significance and promote the recycling and high-value utilization of waste PET.",
"conclusion": "5 Conclusion and outlook PET can be widely used as fiber and plastic in various fields, which brings convenience to people, but also causes serious white pollution problems due to the accumulation of a large number of wastes in the natural environment, and also causes a large amount of waste of petrochemical energy. With the improvement of people's awareness of environmental protection, the recycling of waste polyester has become a very popular topic. In several chemical depolymerization schemes, the hydrolysis process is relatively mature, and the product purity is high, but the acid and alkaline hydrolysis are corrosive to the production equipment, and the waste liquid needs to be treated. Reducing the acid and alkali concentration is the direction of future research. The methanol alcoholysis method has been gradually abandoned due to its harsh reaction conditions, but the method of DMT to prepare high-value products by transesterification is still worth exploring. Ammonolysis requires a more economical and feasible route to change the status quo due to the complex product purification and low added value of the product. Ethylene glycol alcoholysis method has moderate reaction conditions, low energy consumption, and the depolymerization product BHET can be used in high value to prepare polyurethane, unsaturated polyester, coating film-forming substances, plasticizers, etc. , so as to achieve carbon emission reduction and PET green closed-loop recycling. Personally, this method is theoretically the best choice for realizing large-scale industrialization, and has considerable environmental, social and economic benefits. In order to achieve the “double carbon” goal and the sustainable development of materials, the recycling of waste PET can be developed from the following aspects. (1) Advocate garbage classification, and fundamentally carry out garbage pretreatment first. (2) The recycling of polyester should be application-oriented, develop theories and methods based on degradation and preparation of new products, and strive to achieve green environmental protection and reduce energy consumption in the recycling process. (3) Balance the development of physical recycling, chemical recycling, physical–chemical and biological recycling methods, and enrich the existing recycling system. (4) Improve the substitutability of recycled products and the market acceptance of depolymerization products, and gradually realize the industrialization of various technologies. In addition, the government should also give certain support to promote the healthy and efficient development of PET recycling technology.",
"introduction": "1 Introduction Polyethylene terephthalate, referred to as PET, is a saturated polyester obtained by the polycondensation of PTA (purified terephthalate) or DMT (dimethyl terephthalate) and EG (ethylene glycol), 1 It is a semi-crystalline thermoplastic resin, which is a saturated polyester that can be used to prepare chemical fibers and films. The production of traditional textiles has come from PET fibers since the mid-1940s, and it was not until the 1980s that PET was widely used to produce plastic bottles, and in 1987 its production exceeded 3 billion bottles. In recent years, with the development of science and technology, PET also has more types and is further used in a wider range of fields, such as high-strength fibers, films, coatings, auto parts, electronic devices, etc. It is closely related to our life, so the demand has been rising in recent years. Fig. 1 shows the proportion of global PET plastic production to various plastics production in recent years. PET is difficult to degrade under natural conditions, and the white pollution problem caused by it has attracted the attention of various countries. Generally speaking, plastics have a low recycling rate after use, however, PET is one of the materials with a higher recycling rate, and in 2017, nearly 57% of the PET bottles in the world were recycled in Europe. 2 Energy recovery of waste PET by incineration or pyrolysis is not feasible, because it will have adverse effects on the environment and human beings, and high-value secondary raw materials cannot be obtained. Primary recycling has strict requirements on raw materials, while mechanical recycling is less efficient. The side reactions caused by the thermal degradation process will cause the physical properties of the recycled products to decline, change the color, and finally reduce the value of the products. Recycling is not a slogan or a marketing activity, but a need for a circular economy. At the same time, it is also the protection of the ecological environment by energy conservation and emission reduction, which is conducive to the realization of “carbon peaking” and “carbon neutrality”. 3 Therefore, how to recycle waste PET and realize its high-value utilization has become an important problem for the majority of polymer workers. Fig. 1 The share of PET plastics in various plastics production. 4 The recycling process of waste PET is generally divided into four categories, 5 Namely primary recovery (re-extrusion), secondary recovery (mechanical), tertiary recovery (chemical), quaternary recovery (energy recovery). Primary recycling is the recycling of uncontaminated raw materials. It is a simple and low-cost process to recycle waste plastics into the factory. Secondary recycling is a mechanical recycling technology, mainly through a series of processes such as cutting, crushing, and melting. However, after repeated use, the strength of PET will decrease compared with the original, and the brittleness will increase, which will affect the quality of the product. In the end, it can only be downgraded and recycled. 6 Tertiary recycling refers to chemical recycling, in which polymers are degraded into monomers or oligomers. At present, the chemical recycling methods of waste PET polyester mainly include the following: (1) hydrolysis method; (2) methanol alcoholysis method; (3) ethylene glycol alcoholysis method; (4) alcohol-alkali combined depolymerization method; (5) ammonolysis; (6) other depolymerization methods. In the process of PET depolymerization into monomer recovery, it mainly includes hydrolysis to recover TPA (terephthalic acid), 7 methanol alcoholysis to recover DMT, 8,9 ethylene glycol alcoholysis to recover BHET (diethylene glycol terephthalate), 10 and ammonolysis to recover BHETA (bis(2-hydroxyethylene)terephthalamide). 5 Four-stage recovery refers to the recovery of energy, because most waste polyesters are derivatives of petroleum, which can recover heat during combustion. In this paper, the chemical depolymerization method of waste PET, the types of alcoholysis catalysts with the greatest possibility of industrialization, and the high-value application of chemical recovery products are reviewed, in order to provide reference and promotion for the high-value utilization of waste PET resources in green recycling. The general idea is shown in Fig. 2 . Fig. 2 General thinking of waste PET degradation and high value application review."
} | 2,050 |
32925899 | PMC7529429 | pmc | 9,040 | {
"abstract": "In this study we analyze the growth-phase dependent metabolic states of Bdellovibrio bacteriovorus by constructing a fully compartmented, mass and charge-balanced genome-scale metabolic model of this predatory bacterium ( i CH457). Considering the differences between life cycle phases driving the growth of this predator, growth-phase condition-specific models have been generated allowing the systematic study of its metabolic capabilities. Using these computational tools, we have been able to analyze, from a system level, the dynamic metabolism of the predatory bacteria as the life cycle progresses. We provide computational evidences supporting potential axenic growth of B . bacteriovorus ’s in a rich medium based on its encoded metabolic capabilities. Our systems-level analysis confirms the presence of “energy-saving” mechanisms in this predator as well as an abrupt metabolic shift between the attack and intraperiplasmic growth phases. Our results strongly suggest that predatory bacteria’s metabolic networks have low robustness, likely hampering their ability to tackle drastic environmental fluctuations, thus being confined to stable and predictable habitats. Overall, we present here a valuable computational testbed based on predatory bacteria activity for rational design of novel and controlled biocatalysts in biotechnological/clinical applications.",
"introduction": "Introduction Predation is a biological interaction where an individual, the predator, feeds on another, the prey, to survive. Since predation has played a central role in the diversification and organization of life, this system provides an interesting biological model from both an ecological and evolutionary point of view. Predation is an example of coevolution where the predator and prey promote reciprocal evolutionary responses to counteract the adaptation of each other [ 1 ]. This interspecific relationship is widely extended in nature, including the microbial world where the main predators are bacteriophages, protozoa and predatory bacteria [ 2 ]. Focusing on bacteria, this group is composed, among others, by Bdellovibrio and like organisms (BALOs) which are small, highly motile, and aerobic gram-negative predatory bacteria that prey on a wide variety of other gram-negative bacteria. Originally discovered in soil [ 3 ], BALOs are ubiquitous in nature. They can be found in terrestrial and aquatic habitats, bacterial biofilms, plants, roots, animals and human feces [ 4 ] and lung microbiota [ 5 ]. B . bacteriovorus is the best characterized member of the group of BALOs and the genome of different strains, including HD100, Tiberius and 109J have been sequenced providing a reliable source of genetic information [ 6 – 8 ]. B . bacteriovorus exhibits a biphasic growth cycle ( Fig 1 ), including a free-swimming attack phase (AP) and an intraperiplasmic growth phase (GP) inside the prey´s periplasm forming the so-called bdelloplast structure. During AP, free living cells from extracellular environment are in active search for new preys. After attachment, and once the predator-prey interaction is stable and irreversible, the predator enters in the prey`s periplasm, where it grows and replicates DNA during the GP using the cytoplasm of the prey cell as a source of nutrients and biomass building blocks. When the prey is exhausted, B . bacteriovorus grown as a filament, septates into several daughter cells, lyses the ghost-prey’s outer cell membrane and releases into the medium [ 6 , 9 ]. Interestingly, host-independent (HI) mutants of Bdellovibrio strains have been found under laboratory conditions. These HI predators are able to grow axenically (without prey) in a rich-nutrient medium mimicking the dimorphic pattern of elongated growth, division and the development of the host-dependent (HD) cells following a multiple fission strategy [ 10 ]. It is worth noticing that the axenic growth of these mutant strains is given by a mutation in the host interaction (hit) locus, which has been described as being involved in regulatory and/or scaffold elements, such as type IV pilus formation and also related to the attachment and invasion of the prey [ 11 ]. This argues in favor of this mutation having no direct metabolic (enzymatic) impact. In fact, the main metabolism of these HI derivatives should not have suffered changes with respect to the wild type Bdellovibrio strains. 10.1371/journal.pcbi.1007646.g001 Fig 1 Lifecycle of B. bacteriovorus HD100. 1) Prey location: B . bacteriovorus moves towards prey-rich regions. 2) Attachment: the predator anchors to the host cell, which leads to the infection. 3) Invasion: B . bacteriovorus enters the periplasm of the prey cell. 4 and 5) Growth in bdelloplast and development: the prey has a rounded appearance due to cell wall modification and B . bacteriovorus grows in the periplasm and replicates its DNA. B . bacteriovorus uses the prey cytoplasm as a source of nutrients. 6 and 7) Septation and development: the predator septates when resources become limited and it matures into individual attack phase cells. 8) Lysis: mature attack-phase cells lyse the cell wall of the bdelloplast, initiating the search for fresh prey. The complete cycle takes about 4 h. B . bacteriovorus ’ extraordinary repertoire of susceptible preys allows for a wide range of potential applications based on its predatory capability, such as biocontrol agent in medicine, agriculture, aquaculture and water treatment [ 12 – 15 ]. Furthermore, it has been proposed as an excellent source of valuable biotechnological enzymes and as a biological lytic tool for intracellular products, due to its hydrolytic arsenal [ 4 , 16 , 17 ]. Moreover, regarding its unique lifestyle it represents a good model for evolution studies focusing, for example, on the origin of the eukaryotic cell [ 18 , 19 ]. Despite the interest that this predatory bacterium’s potential applications have recently aroused among the scientific community, its complex lifestyle and growth conditions make it hard to implement metabolic and physiological studies. As a direct consequence, to date, its physiology and metabolic capabilities remain an enigma to a large extent [ 20 ]. Moreover, the potential of this predator to be used as a biotechnological chassis depends on the quantity and quality of the available metabolic knowledge. Therefore, expanding the knowledge of this predatory bacterium is essential for the full exploitation of its unique biotechnological applications. This process would require a reliable platform supporting the rational understanding of its characteristics. Following this aim, the advent of genomic age and the subsequent large amount of derived high-throughput data, have largely contributed to deeper understanding of microbial behavior, at system level [ 21 ]. Specifically, genome-scale metabolic models (GEMs) are being used to analyze bacterial metabolism under different environmental conditions [ 22 , 23 ]. GEMs are structured representations of the metabolic capabilities of a target organism based on existing biochemical, genetic and phenotypic knowledge which can be used to predict phenotype from genotype [ 24 ]. The application of Constraint-Based Reconstruction and Analysis (COBRA) approaches [ 25 ] together with specific GEMs have been successfully applied for better understanding of interspecies interactions such as mutualism, competition and parasitism providing important insights into genotype-phenotype relationship [ 26 ]. Despite GEMs being powerful tools to elucidate the metabolic capabilities of single systems, addressing the complex metabolism of bacterial predators having biphasic growth-cycles such as B . bacteriovorus is challenging and has remained elusive so far. We provide here the first step toward the metabolic understanding at system level of B . bacteriovorus by the reconstruction of its metabolism at genome-scale. We further use this cutting edge computational platform as a test bed for the integration and contextualization of transcriptomic and physiological data shedding light on the biphasic lifestyle of this predatory bacterium.",
"discussion": "Discussion Integrative approaches combining traditional and innovative technologies are currently being addressed to establish the metabolic network of hot-spot microorganisms. This issue becomes much more challenging when it refers to predatory microorganisms such as the bacterium B . bacteriovorus , which exhibit a bi-phasic lifestyle. With the aim of elucidating the metabolic network wired to predator physiology and lifestyle, we implemented a computational test-bed that proved very useful in the assessment of our predator’s phenotype-genotype relationships, while providing new insight on how B . bacteriovorus ’ metabolism operates at the systems level. Complex B . bacteriovorus lifestyle has guided a significant genome streamlining process and the acquisition of biosynthetic energy-saving mechanisms Comparison of the essential reactions between B . bacteriovorus and other intracellular lifecycle bacteria and free-living microorganisms has revealed the loss of biosynthetic pathways ( S3 Table , reactions exclusive to free-living microorganisms). This metabolic scenario is only possible because the host/prey metabolic machinery provides the required biomass building blocks during the intracellular stage of the growth cycle. Despite numerous auxotrophies having been reported in specific genes [ 6 ], the metabolic model has allowed the functional contextualization of these biosynthetic deficiencies within the network. For instance, model-based analyses identified additional metabolic gaps which had remained unknown so far, while on the other hand they provided alternative metabolic routes overcoming theoretical auxotrophies. Overall, our analysis has shown a significantly higher number of auxotrophies than previously thought. The loss of essential biosynthetic genes is a typical characteristic of bacteria existing in nutrient-rich environments, such as lactic acid bacteria, endosymbionts or pathogens [ 76 ]. In this sense, although B . bacteriovorus HD100 possesses a relatively large genome, it could also be included in this “genome streamlining” bacterial group because it directly employs whole molecules from the cytoplasm of the prey [ 74 , 77 , 78 ]. With regard to the production of the biomass building blocks, it is noteworthy that most amino acids suffer a total lack of biosynthesis pathways. In contrast, B . bacteriovorus is fully equipped with the biosynthetic routes for nucleotides and fatty acids. Keeping in mind the macromolecular composition of a prokaryotic cell’s cytoplasm as the natural growth niche of B . bacteriovorus (50% proteins, 20% RNA, 10% lipids, 20% remaining components), it is easy to speculate why the oligopeptide transporter systems are widely represented. While the factors driving de novo synthesis or the uptake of biomass building blocks are still unknown, it is likely that these processes are extremely regulated and only activated in the absence of intermediates. A significant flux feeding nucleic acid biosynthesis was predicted ( Fig 6 ). Thus, an important amount of nucleotides came from de novo synthesis pathways. This would occur during in vivo conditions even in the presence of nucleotides in the extracellular medium (prey´s cytoplasm). This high requirement of nucleotides beyond the amount provided by the prey could justify the presence of a complete nucleotide biosynthesis pathway in contrast with the scenario found in the biosynthesis of amino acids and cofactors when multiple autotrophies were found. In addition, the presence of these complete metabolic pathways determines the potential ability of the predator to survive and grow without prey, as predicted by the model. Supplying the model with a rich medium based on amino acids returned a simulation which provided key information about growth and generation of biomass. Importantly, this potentially independent growth might be associated with B . bacteriovorus ’ role as a balancer of bacterial population either in aquatic or soil environments, or in the intestine of healthy individuals, because survival of predator cells is not uniquely dependent on the predation event [ 70 ]. Related to the essential reactions exclusive of the intracellular microorganism ( Salmonella , Shigela , Yersinia and Bdellovibrio ), it can be highlighted the relevance of the lipid synthesis. These molecules participate in crucial biological processes, including signaling and organization of the membrane of the cells. For intracellular pathogens, it has been described that lipids are also crucial for the interplay with the host cell [ 79 ]. The uptake of intracellular pathogens, such as Salmonella typhimurium or Mycobacterium tuberculosis is led by a re-organization of the lipid microdomains to avoid the degradative environment of the lysosomes. Besides, in concordance with the biphasic life cycle of this intraperplasmic predator, lipid composition determines the structural and functional integrity of the extracellular forms of pathogens [ 80 ]. On the whole, our data support the hypothesis and suggest that the metabolic properties of B . bacteriovorus are closer to those of the postulated minimal metabolic network. This low robustness of the metabolic network suggests Bdellovibrio is more niche-specific than previously thought and the environmental conditions governing predation may be relatively uniform. However, in-depth studies of the metabolic capabilities of the predator are needed to complete the metabolic network and obtain more reliable in silico predictions. Nutrient availability and biological objective largely conditioned the metabolic shift from i CHAP to i CHGP The development of i CH457, i CHAP and i CHGP has provided a computational framework for a better understanding of the physiological and metabolic versatility of BALOs and other predatory bacteria. These models have provided a mechanistic explaining of the required metabolic shift between the different phases. Thus, metabolic fluxes estimations during AP and GP in absence of objective using random sampling are fully compatible with the expected biological objective in these phases e.g., ATP production and growth, respectively. For instance, during GP, several metabolic pathways become inactive, allowing carbon flux distribution re-routing toward biosynthetic pathways. The TCA cycle shifts from a completely operational state during AP to an anaplerotic mode by inactivating the decarboxilative branch including citrate synthase, aconitase and isocitrate dehydrogenase. In parallel, glutamate was used as a main carbon and energy source. The metabolic switch in B . bacteriovorus between the different growth phases has revealed an environmental adaptation of this predator to tackle a rich medium, which would provide an explanation for the development of HI strains. Overall, the carbon flux predictions were compatible with the complex lifestyle of Bdellovibrio cells and provided an unprecedented overview of the metabolic shifting required to move from AP to GP, as well as new knowledge about the connections within the predator’s metabolic network. Finally, the results obtained during this study contribute not only to increasing the available metabolic knowledge of B . bacteriovorus , but also to providing a computational platform for the full exploitation of this predatory bacterium as a biotechnology workhorse in the near future."
} | 3,905 |
25626903 | PMC4324309 | pmc | 9,041 | {
"abstract": "ABSTRACT Understanding the structure, functions, activities and dynamics of microbial communities in natural environments is one of the grand challenges of 21st century science. To address this challenge, over the past decade, numerous technologies have been developed for interrogating microbial communities, of which some are amenable to exploratory work (e.g., high-throughput sequencing and phenotypic screening) and others depend on reference genes or genomes (e.g., phylogenetic and functional gene arrays). Here, we provide a critical review and synthesis of the most commonly applied “open-format” and “closed-format” detection technologies. We discuss their characteristics, advantages, and disadvantages within the context of environmental applications and focus on analysis of complex microbial systems, such as those in soils, in which diversity is high and reference genomes are few. In addition, we discuss crucial issues and considerations associated with applying complementary high-throughput molecular technologies to address important ecological questions.",
"conclusion": "CONCLUDING REMARKS AND FUTURE PERSPECTIVES Significant progress has been made in the development and application of high-throughput molecular technologies for microbial community analysis, but many challenges still remain, especially in the context of environmental applications. For instance, metagenomic sequence assembly, especially from complex communities like those in soil, is one of the grand challenges in bioinformatics ( 51 , 155 ) although metagenome-specific assembly algorithms ( 155 ) and methods for “binning” genomes from metagenome data ( 64 , 156 ) have led to numerous successes. Single-cell genomics technologies are also proving to be a powerful complement to metagenome studies ( Fig. 3 ) ( 50 , 151 , 152 ). Another grand challenge for the application of high-throughput molecular tools for microbial community research is the analysis, visualization, and interpretation of massive amounts of both sequencing and array data, especially shotgun metagenome sequencing data ( 16 , 18 , 41 , 100 ). For instance, it is difficult to annotate abundant short read sequences to be tabulated and compared in an intuitive manner. This limits our ability to address ecological questions related to microbial biodiversity (e.g., taxonomic, phylogenetic, genetic, functional diversity), functional trait-based microbial biogeography ( 94 , 134 , 137 ), and ecosystem functioning, stability, and succession ( 157 – 159 ). Many excellent bioinformatics tools have been developed for processing, mining, visualizing, and comparing molecular data ( 41 ), but they are not optimized for dealing with the vast amounts of experimental data from complex communities like those in soil. Network tools to delineate the interactions among different microbial populations based on high-throughput metagenomics datasets are a promising new development, since understanding the interactions among different species is a central but poorly understood issue in microbial ecology ( Fig. 3 ) ( 4 , 99 , 160 ). Each omics technology has its strengths and weaknesses and must be selected based on the biological questions and objectives of the study ( Fig. 3 ). In general, open-format technologies are most suitable for exploratory discovery studies, whereas the closed-format technologies can be advantageous for more narrowly defined, hypothesis-driven, quantitative, and comparative studies ( 117 ). As sequencing technologies improve and costs decrease, high-throughput sequencing may replace microarrays as the method of choice for many applications ( 40 ), but for now, microarray-based closed-format approaches play a valuable role in microbial community analysis, especially for complex microbial communities whose comprehensive sampling remains infeasible ( 16 ). Functional metagenomics will continue to identify functions of previously unknown genes. As more functional gene sequences of interest become available, functional arrays that are both more comprehensive (e.g., the next generation of GeoChip, with up to 1 million probes) and more specific (e.g., PathoChip and StressChip) ( 123 , 124 ) will be developed for addressing different ecological questions and applications. Also, high-throughput molecular technologies should be integrated with other approaches, such as single-cell genomics, metaproteomics ( 161 ), and metametabolomics ( 35 , 162 ), as well as targeted techniques like stable isotope probing ( Fig. 3 ), to address ecological questions and hypotheses within the context of environmental and medical applications. Only in this way will their power for microbial community analysis be realized. The ultimate goal of microbial ecology is to understand who is where, with whom, doing what, why, and when ( 159 ). To answer such questions, reliable, reproducible, quantitative, and statistically valid ( 146 ) experimental information on community-wide spatial and temporal dynamics is needed. Also, to achieve this predictive goal, it is essential to model microbial community dynamics and their behaviors at both structural and functional levels ( Fig. 3 ). With the rapid and continuous advances of molecular high-throughput technologies and high-performance computational tools, it is anticipated that in the not-too-distant future, microbiologists will be able to model and predict the behaviors of microbial communities. A new era of quantitative predictive microbial ecology is coming."
} | 1,376 |
34035260 | PMC8149669 | pmc | 9,043 | {
"abstract": "Arbuscular mycorrhizal (AM) and ectomycorrhizal (EcM) associations are critical for host-tree performance. However, how mycorrhizal associations correlate with the latitudinal tree beta-diversity remains untested. Using a global dataset of 45 forest plots representing 2,804,270 trees across 3840 species, we test how AM and EcM trees contribute to total beta-diversity and its components (turnover and nestedness) of all trees. We find AM rather than EcM trees predominantly contribute to decreasing total beta-diversity and turnover and increasing nestedness with increasing latitude, probably because wide distributions of EcM trees do not generate strong compositional differences among localities. Environmental variables, especially temperature and precipitation, are strongly correlated with beta-diversity patterns for both AM trees and all trees rather than EcM trees. Results support our hypotheses that latitudinal beta-diversity patterns and environmental effects on these patterns are highly dependent on mycorrhizal types. Our findings highlight the importance of AM-dominated forests for conserving global forest biodiversity.",
"introduction": "Introduction Variation in community composition (beta-diversity) provides key insights into mechanisms of community assembly and biodiversity maintenance across local and regional scales 1 – 4 . Total beta-diversity arises from two components: species turnover (i.e., species replacement) and species nestedness (i.e., where sites with fewer species tend to be subsets of sites with more species) 5 , 6 . These two beta-diversity components are closely associated with various ecological, historical, and evolutionary processes. Species turnover usually occurs among communities with high speciation rates, dispersal limitation, ecological drift, or habitat heterogeneity 7 – 9 . In contrast, species nestedness often occurs in communities with nested habitat conditions and selective extinction or selective recolonization across environmental gradients 5 , 10 , 11 . Studies of the latitudinal gradient in beta-diversity have yielded mixed results, with U-shaped, unimodal, positive, negative, or neutral trends being reported in the literature 3 , 12 – 15 . In particular, some studies partitioning beta-diversity have found that species turnover decreases with increasing latitude, while species nestedness increases 16 , 17 . However, the latitudinal patterns of these two beta-diversity components of trees have not been extensively explored, particularly at the global scale. Key gaps remain in our understanding how local biotic interactions contribute to patterns of beta-diversity across large-scale gradients 18 . In particular, the importance of mutualistic biotic interactions in determining latitudinal gradients in beta-diversity of trees remains largely unknown. Mutualistic interactions among plants and mycorrhizal fungi may be one of the most important, but least studied, biotic interactions that contribute to patterns of plant beta-diversity across latitudes. Arbuscular mycorrhizal fungi (AM fungi) and ectomycorrhizal fungi (EcM fungi) form symbioses with more than 80% of terrestrial plants globally 19 , 20 . Although plant-mycorrhizal associations are ubiquitous, the geographic variation in relative abundance, diversity, and distributions of AM and EcM plant species may influence patterns of plant beta-diversity via several ecological and evolutionary mechanisms 21 – 23 . Mycorrhizal associations may influence latitudinal variation in beta-diversity through differences in how AM and EcM plants adapt to habitat conditions (i.e., habitat adaptation) 24 – 27 . Greater adaptation of species to specific habitat conditions may enhance speciation rates and reduce extinction rates 25 , 28 . AM plants and EcM plants differ in their soil nutrient uptake capacities and trade-offs of carbon cost. AM plants are superior competitors for available inorganic nutrients compared to EcM plants. EcM plants, however, have greater capacity to mineralize nutrients from organic matter directly than AM plants 21 , 29 . Furthermore, AM and EcM plants respond differently to climate conditions, with AM plants preferring to wet and warm conditions, while EcM plants are better adapted to dry and cold conditions. Thus, the warm, wet, and aseasonal tropical regions with high decomposition rates are primarily dominated by AM trees despite of some exceptional EcM-tree-dominated forests, whereas the dry, cold, and seasonal temperate regions are primarily dominated by EcM trees 24 , 25 . This latitudinal gradient in habitat adaptation may provide AM trees in tropical regions with higher speciation rates but lower selective extinction rates than in temperate regions 23 – 25 , 30 , 31 . Such higher speciation rates and/or lower extinction rates of trees may in turn increase total beta-diversity and species turnover in the tropics by increasing the number of species in the regional species pool 15 , 32 . Lower selective extinction rates may decrease species loss across environmental gradients (i.e., species nestedness) in the tropics 5 . In contrast, EcM trees in temperate regions may have higher speciation rates, lower extinction rates, and a larger species pool than in tropical regions due to habitat adaptation. This may lead to higher species turnover and lower species nestedness of EcM trees in temperate than in tropical regions 5 , 33 – 36 . Mycorrhizal associations may also influence forest beta-diversity via differences in plant-soil feedbacks (PSFs) between AM and EcM trees 26 , 27 , 34 – 37 . For example, AM trees generally perform better in soils from heterospecifics than from conspecifics (i.e., a negative PSF), whereas EcM trees perform better in soils from conspecifics than from heterospecifics (i.e., a positive PSF) 26 , 38 . Differences in PSFs between AM and EcM tree species may be the result of less protection of roots of AM trees from soil pathogens due to the lack of mantle formation on the host root surface 26 , 39 , 40 , or because EcM trees are better able to mine nutrients from soil organic matter arising from host trees 27 . In communities dominated by AM trees, negative PSFs are predicted to reduce the performance of conspecific individuals of abundant species and promote the persistence of rare species 26 , 41 . In turn, rare species that are habitat specialists may increase species turnover by promoting uniqueness of species composition among localities 33 . Negative PSFs may also increase species turnover by limiting the spatial extent of species ranges, resulting in more species unique to different localities and fewer species found in common among localities 34 , 36 . Thus, the negative PSFs common among AM trees may promote species turnover. In contrast, positive PSFs in more EcM-dominated communities could promote the performance of conspecific individuals of abundant species and inhibit rare species, leading to selective loss of rare species due to competitive exclusion 26 , 35 , which generates patterns of species nestedness. The strength of conspecific negative-density dependence and the prevalence of AM trees have been demonstrated to decrease with increasing latitude 42 , 43 . The weaker negative PSFs and lower predominance of AM plants may lead to a decrease in species turnover with increasing latitude 33 , 34 , 36 . In contrast, species nestedness of EcM plants may increase with latitude due to the greater prevalence of EcM species with positive PSFs 5 , 24 – 26 , 35 . Despite widespread interest in how mycorrhizal associations influence host population dynamics, biodiversity maintenance, and ecosystem functioning at various spatial scales 25 – 27 , the effects of mycorrhizal associations on the latitudinal gradient in tree beta-diversity remain unexplored. In this study, we examine how mycorrhizal associations and environmental factors (climate and topography) may influence the latitudinal gradient in beta-diversity of forest trees. Using data from 45 large, stem-mapped forest plots across the globe (Fig. 1 ), we calculate total beta-diversity, the abundance-weighted species turnover component (hereafter species turnover), and the abundance-weighted species nestedness component (hereafter species nestedness) for AM trees, EcM trees, and all trees (a combination of AM trees, EcM trees, and other trees). We expect that total beta-diversity and species turnover decrease with increasing latitude, whereas species nestedness increases. In particular, we test three hypotheses: (1) Latitudinal gradients in beta-diversity and its components are highly dependent on mycorrhizal types of host trees; (2) Latitudinal gradients in beta-diversity and its components are mainly shaped by environmental rather than spatial variables; and (3) Effects of environmental and spatial variables on beta-diversity and its components are highly dependent on types of mycorrhizal associations. We find that latitudinal beta-diversity patterns and environmental effects on these patterns are highly dependent on mycorrhizal types. AM rather than EcM trees predominantly contribute to decreasing total beta-diversity and turnover and increasing nestedness with increasing latitude. Fig. 1 Global distribution of 45 forest plots. Plots range in size from 2.1 ha (Nanjenshan) to 60 ha (Jianfengling) and in latitude from 21.5 °S (Ilha do Cardoso, Brasil) to 61.3 °N (Scotty Creek, Canada), covering all continents with forests (i.e., Asia, Africa, Europe, South America, North America, and Oceania).",
"discussion": "Discussion AM trees influence the latitudinal gradient in tree beta-diversity Despite widespread interest in patterns of forest beta-diversity across biogeographic gradients, the role of mutualistic biotic interactions in shaping these gradients remains largely unknown. Our findings based on 45 large forest plots covering a wide range of latitudes (25.1° S ~ 61.3° N) and on simulation experiments provided insights into the roles of mutualistic mycorrhizal associations, as well as climate, on patterns of beta-diversity. First, we found that latitudinal patterns of total beta-diversity, species turnover, and species nestedness are strongly associated with mutualistic associations among tree species and mycorrhizal fungi. Specifically, we found that community-wide patterns of total beta-diversity, species turnover, and species nestedness of all trees largely reflect those same patterns for AM trees (Fig. 2 and Supplementary Figs. 1 – 3 ). In contrast, for EcM trees, total beta-diversity and species turnover generally lacked significant latitudinal patterns, although patterns of species nestedness were mixed (Fig. 2 and Supplementary Figs. 1 – 3 ). This suggests that AM trees are the predominant contributors to overall latitudinal gradients in tree beta diversity. Second, for AM trees and all trees, total beta-diversity, species turnover, and species nestedness were generally largely explained by environmental factors, especially temperature and precipitation, suggesting the latitudinal gradients in beta-diversity may be largely driven by deterministic processes. In contrast, for EcM trees, beta-diversity, species turnover, and species nestedness were not strongly associated with environmental variables. Mutualistic associations between mycorrhizal fungi and host plants may contribute to latitudinal gradients in beta-diversity observed in the present study via several mechanisms. First, mycorrhizal associations may affect beta-diversity by mediating the strength of interspecific competition and local distribution ranges of species through plant-soil feedbacks (PSFs), which are generally negative for AM trees and positive for EcM trees 26 , 34 – 36 . Negative PSFs for AM trees may enhance the recruitment of heterospecific trees, especially those rare tree species 26 , 39 , 41 . Replacement of conspecific individuals by heterospecific individuals represents the abundance-weighted species turnover. The maintenance of more rare species especially those with specific habitat preferences, may lead to higher species turnover among localities potentially due to habitat filtering 33 . Moreover, negative PSFs may restrict local distribution ranges of species, generating higher species turnover among localities due to fewer shared species with narrower distributions 34 , 36 . As negative PSFs may decrease with increasing latitude 44 , weaker negative PSFs for AM trees at higher latitudes could decrease species turnover 25 , 33 , 34 , 36 . Our result that species turnover of AM trees and all trees decreased with increasing latitude is in line with our expectation. In contrast, positive PSFs for EcM trees, which may be better protected against soil pathogens by fungal root mantle, may instead promote success of conspecific individuals, and may consequently lead to competitive exclusion of competitively inferior species 26 , 35 . In turn, selective species loss from competitive exclusion increases species nestedness 5 , 26 , 35 . Increasing prevalence of EcM-associations at higher latitudes should increase species nestedness of EcM trees with positive PSFs 5 , 25 , 26 , 35 . Our result that species nestedness of EcM trees generally increased with latitude, supports our expectation. Second, mycorrhizal associations may affect beta-diversity by influencing speciation rates and extinction rates through habitat adaptation 23 – 25 , 30 , 31 . Mycorrhizal associations may promote habitat adaptation of host plants by increasing access to soil nutrients. However, the lack of comparable soil-nutrient data for most of forest plots in this study (data from online soil databases are too coarse at the forest plot scale as soil properties vary substantially across space even in a short distance) prevents us from explicitly testing the soil nutrient effects on the latitudinal beta-diversity gradients of AM and EcM trees. However, this will be a promising direction for the future studies. Global biogeography of AM trees was reported to be primarily driven by high litter decomposition rates whereas EcM trees was primarily driven by low litter decomposition rates 25 . Tropical habitats with higher decomposition rates may promote AM trees whereas temperate habitats with lower decomposition rates may promote EcM trees 25 . Adaptation to tropical regions may increase speciation rates and decrease extinction rates of AM trees, and may consequently lead to larger species pools of AM trees compared to those in temperate regions 24 , 25 , 31 . Larger species pools may increase beta-diversity by strengthening species uniqueness among localities, i.e., species turnover, due to narrow local distribution ranges of AM trees 34 , 36 . In addition, decreased extinction rates in tropical regions may consequently reduce the loss of species that creates species nestedness 5 , 24 , 25 . Our results that total beta-diversity and species turnover of AM trees generally decreased with increasing latitude while species nestedness of AM trees increased are in accordance with our expectation. Similarly, adaptation to temperate habitats may decrease extinction rates and increase speciation rates and species pools of EcM trees at temperate compared to tropical latitudes 30 , 31 . Larger species pools may in turn influence species turnover of EcM trees 15 , 32 . However, we found that species turnover of EcM trees was generally not correlated with latitude (Fig. 2 and Supplementary Figs. 1 – 3 ), which partly violated our expectation that species turnover of trees decreased from tropics towards poles. Two reasons, not mutually exclusive, may explain this unexpected result. First, the species pool of EcM trees was generally not (or extremely weakly) correlated with latitude (Supplementary Fig. 8 ); because positive PSFs may increase local distribution ranges and inhibit heterospecifics, this may counteract the effects of greater speciation rates on the species pool of EcM trees at temperate latitudes. Second, EcM trees with wide local distribution ranges may not significantly influence species turnover among localities 26 , 34 , 36 . We found that AM trees predominantly contributed to the latitudinal gradients in beta-diversity of all trees, supporting our first hypothesis. One potential reason may be the local distribution ranges mediated by PSFs. AM trees with narrow local distribution ranges may disproportionately contribute to the overall composition dissimilarity among localities (beta-diversity), whereas EcM trees with wide local distribution ranges may homogenize the overall species composition 26 , 34 , 36 . The simulation experiments confirmed that the strong contribution of AM trees to the latitudinal gradient is not simply a function of disparate abundance or species richness between AM and EcM trees (Supplementary Figs. 2 and 3 ). These observed and simulated results jointly suggested that processes strongly relevant to mycorrhizal associations, such as PSFs and habitat adaptation, rather than sampling bias (i.e., greater abundance or richness of AM trees) may contribute to the latitudinal gradients in beta-diversity of trees. Although general latitudinal patterns of beta-diversity were detected, we also found three exceptional patterns at the scale of 50 m × 50 m: (1) total beta-diversity of AM trees was not correlated with latitude; (2) total beta-diversity of EcM trees decreased with increasing latitude; and (3) species nestedness of EcM trees was not correlated with latitude. These exceptions may result from the scale-dependent strength of PSFs, a possibility in need of further exploration. Distance between conspecific individuals in different quadrats may increase with quadrat size, and consequently PSFs of conspecific individuals among quadrats may decrease 45 . In turn, weaker positive PSFs may decrease species nestedness 5 , 26 , 35 . This may be more prevalent in temperate regions than in tropical regions because temperate regions have higher prevalence of EcM trees with positive PSFs compared to tropical regions 5 , 25 , 26 , 35 , 45 . Thus, species nestedness may decrease faster in temperate than in tropical regions, which may consequently shape a neutral trend in species nestedness of EcM trees at the scale of 50 m × 50 m. Similarly, weaker PSFs may also shape a decreasing trend of total beta-diversity for EcM trees and a neutral trend of total beta-diversity for AM trees via species turnover and species nestedness because total beta-diversity is the sum of species turnover and species nestedness. Effects of climatic factors on mycorrhizal-mediated tree beta-diversity, species turnover, and species nestedness The result that environmental variables generally explained more variations in total beta-diversity, species turnover, and species nestedness than did spatial variables suggests a predominant role of habitat filtering in shaping the latitudinal patterns of total beta-diversity and its two components, supporting our second hypothesis. Climatic factors have been found to be extremely important for beta-diversity 3 , 32 . Temperature and precipitation, in particular, were significantly associated with total beta-diversity, species turnover, and species nestedness of AM trees and all trees (Figs. 3 , 4 and Supplementary Figs. 5 – 7 ). In contrast, total beta-diversity, species turnover, and species nestedness of EcM trees were not correlated with climatic variables in most cases (Fig. 4 and Supplementary Figs. 5 – 7 ). Climatic variables can exert effects directly and indirectly through biotic interactions on the relatively local-scale diversity patterns 46 . We found that the latitudinal beta-diversity gradients and the effects of climatic factors on beta-diversity were highly dependent on the mycorrhizal types of trees, supporting our third hypothesis. These findings suggest that climate may likely affect latitudinal gradients in beta-diversity, species turnover, and species nestedness of host trees indirectly through its influence on mycorrhizal associations 24 , 25 , 34 , 36 , although climate may also directly affect processes shaping beta-diversity such as speciation, extinction, and dispersal limitation 5 , 7 – 11 . Previous studies have shown that AM fungi are physiologically less tolerant than EcM fungi to low temperatures and decrease colonization below 15 °C, due to the lack of cold-tolerant traits 24 , 47 , 48 . In contrast, EcM fungi with cold-tolerant traits are well adapted to low temperatures 24 , 25 . In addition, temperature and precipitation are positively correlated with litter decomposition rate which has been reported to be the primary driver differentiating mycorrhizal associations between AM and EcM trees 24 , 25 . Thus, the prevalence of AM-associations was positively correlated with higher temperature and greater precipitation toward the equator, whereas the prevalence of EcM-associations was more common at low temperature and precipitation toward the poles (Supplementary Figs. 8 – 10 ) 24 , 25 . In turn, AM-associations may contribute to the decreasing trends in beta-diversity and species turnover and the increasing trends in species nestedness of host trees across latitudes (Fig. 2 ) via negative PSFs and habitat adaptation. In contrast, EcM-associations may contribute to the neutral latitudinal trends in beta-diversity and species turnover, but contribute to an increasing trend in species nestedness of host trees with latitude (Fig. 2 ), possibly through positive PSFs and habitat adaptation 26 , 34 , 36 . In summary, we found that total beta-diversity and species turnover of both AM trees and all trees significantly decreased with increasing latitude, while species nestedness increased. Species nestedness of EcM trees also generally increased with latitude, whereas total beta-diversity and species turnover of EcM trees were generally not correlated with latitude, probably due to the wide local distributions of EcM trees which did not influence the overall compositional differences among localities. The latitudinal patterns of total beta-diversity, species turnover, and species nestedness of all trees were largely contributed by AM rather than EcM trees. Environmental factors were generally much more important than spatial factors in shaping latitudinal patterns of beta-diversity and its components of AM trees and all trees, suggesting that habitat filtering on mycorrhizal associations may be a major ecological process that determines the latitudinal beta-diversity gradient in trees. In particular, temperature and precipitation were the most important environmental factors. Environmental variables likely drive latitudinal gradients in total beta-diversity, species turnover, and species nestedness by affecting mycorrhizal associations of trees. The major contribution of AM trees in forests to the latitudinal gradient in beta-diversity of forest communities underscores the importance of AM trees for global biodiversity conservation. However, the causal relationships between mycorrhizal associations and tree beta-diversity need further exploration in following studies. Future research is also needed to discover the mycorrhizal associations of more tree species and the characterization of individual mycorrhizae species, their specificity for tree hosts and environmental adaptations."
} | 5,850 |
32266749 | PMC7318629 | pmc | 9,046 | {
"abstract": "Abstract Soil legacy effects are commonly highlighted as drivers of plant community dynamics and species co‐existence. However, experimental evidence for soil legacy effects of conditioning plant communities on responding plant communities under natural conditions is lacking. We conditioned 192 grassland plots using six different plant communities with different ratios of grasses and forbs and for different durations. Soil microbial legacies were evident for soil fungi, but not for soil bacteria, while soil abiotic parameters did not significantly change in response to conditioning. The soil legacies affected the composition of the succeeding vegetation. Plant communities with different ratios of grasses and forbs left soil legacies that negatively affected succeeding plants of the same functional type. We conclude that fungal‐mediated soil legacy effects play a significant role in vegetation assembly of natural plant communities.",
"introduction": "Introduction Plants and soil organisms are interdependent and the microbiome in the soil is shaped by the plants that grow in the soil (Phillipot et al. \n 2013 ; Bardgett & Van der Putten 2014 ). This microbial signature can remain as a legacy in the soil after the plant is gone, and in turn affect other plants growing later in the same soil (Kulmatiski et al. \n 2008 ; Van der Putten et al. \n 2013 ; Teste et al. \n 2017 ; Eppinga et al. \n 2018 ). It is often speculated that soil legacy effects created by plants play an important role in regulating plant community dynamics and plant coexistence (Lekberg et al. \n 2018 ; Semchenko et al. \n 2019 ). It was recently shown that inoculation of soils with biotic legacies can change plant community development under natural conditions (Wubs et al. \n 2016 ; Wubs et al. \n 2019 ). However, experimental evidence for soil legacy effects of plant communities with different characteristics on responding plant communities in natural systems is lacking (Reynolds et al. \n 2003 ; Ehrenfeld et al. \n 2005 ; Van der Putten et al. \n 2013 ). Herbaceous grassland plant species such as grasses (monocots) and forbs (dicots) differ fundamentally in root architecture (Craine et al. \n 2001 , 2002 ; Ravenek et al. \n 2016 ), water and nutrient acquisition (Tjoelker et al. \n 2005 ; Ravenek et al. \n 2016 ), and in defense (Latz et al. \n 2015 , 2016 ; Zhang, Van der Putten & Veen 2016 ). These differences between plant functional types can modulate soil communities (Kos et al. \n 2015 ; Latz et al. \n 2015 ; Zhang, Van der Putten & Veen 2016 ), leaving soil legacy effects that affect subsequent plant growth (Wubs & Bezemer 2018 ; Heinen et al. \n 2018 ; Heinen, Biere & Bezemer, 2019 ). Generally, grass and forb species exhibit negative conspecific soil legacy effects (Kulmatiski et al., \n 2008 ), which is often explained by the accumulation of specialised pathogens (Van der Putten et al., \n 2013 ). However, growing in conspecific soil can also lead to positive effects through the accumulation of mutualists in the soil (Morrien et al., \n 2017 ; Hannula et al. \n 2017 ; Teste et al. \n 2017 ). In pot experiments, grasses often have increased performance on soils conditioned by forb species and vice versa (Petermann et al. \n 2008 ; De Kroon et al. \n 2012 ; Wubs & Bezemer 2018 ). As plant species‐specific communities of soil organisms develop around the roots of plants, soil legacies may become stronger over time (Diez et al. \n 2010 ). While it has been shown that individual plants in the field influence their local soil community (De Rooij‐Van der Goes, Peters & Van der Putten 1998 ; Bezemer et al. \n 2006 ; Casper & Castelli 2007 ; Van de Voorde et al. \n 2011 ; Hannula et al. \n 2019a , b ), how different plant communities drive soil legacies in the field and how this affects the establishment of responding mixed plant communities in these soils is not known (Ehrenfeld et al. \n 2005 ; Kardol et al. \n 2007 ; Van der Putten et al. \n 2013 ). We grew six different plant communities in a temperate grassland. Each plant community consisted of a combination of grass and/or non‐leguminous forb species (hereafter: forbs) which were grown in different ratios (0:100; 25:75; 75:25 or 100:0% forb:grass respectively). The (sub)plots were exposed to different durations of conditioning by starting the treatments in two different years. After the conditioning phase of one or two years, all plant communities were removed from the soil, and the same seed mixture of 33 grassland species was sown in each treatment (sub)plot as a responding plant community. In both phases we recorded the abundance of all plant species, soil abiotic characteristics, and soil fungal and bacterial community composition. In the conditioning phase, we expected that plant communities would influence soil abiotic characteristics and soil biotic composition, and we expected that the soil biota would affect the establishment of future plant communities in the responding phase. We hypothesised that manipulation of the composition of the conditioning plant communities will result in different microbial soil legacies, and specifically in the accumulation of specialised soil pathogens and mutualists such as arbuscular mycorrhizal fungi (AMF). Second, we hypothesised that in the response phase, grasses and forbs would be less abundant in soils that had been dominated by their own functional type in the conditioning phase, due to the accumulation of soil pathogens. Third, we hypothesised that these effects would be stronger in soils with a two‐year legacy than in one‐year legacy soils, due to the gradual development of specific soil microbiomes over time. Lastly, we hypothesised that soil legacy effects would be mediated by microbial changes in the soil, rather than by soil abiotic characteristics.",
"discussion": "Discussion Here, we show in a field experiment that compositionally different plant communities create legacies in the soil that, in turn, alter the composition of subsequent plant communities that establish in these soils. Plant communities with different ratios of grasses and forbs created unique soil microbiomes, and these effects were most notable in the soil fungal community. These fungal soil legacies, in turn, affected the responding plant communities. Specifically, both grass and forb abundances in the responding phase were negatively affected by their respective abundance in the previous plant community and this effect was mediated by soil processes. We show that manipulating the composition of the vegetation in grasslands alters the microbiome in the soil, and that this alters the succeeding vegetation. Plant communities dominated by species of a certain functional type create legacies that negatively impact plants from the same functional type. This result is very robust, as the same pattern was observed in all six plant communities that were used to condition the soil in this field experiment. This finding is also in strong agreement with previous work from artificial/pot studies (Kulmatiski et al. \n 2008 ; Petermann et al. \n 2008 ; De Kroon et al. \n 2012 ; Wubs & Bezemer, 2018 ). The functional type of a plant also has a strong effect on the community structure of soil fungi (Kos et al. \n 2015 ; Heinen et al. \n 2018 ; Hannula et al. \n 2019b ). We hypothesised that manipulation of the composition of the conditioning plant communities would result in different microbial soil legacies mainly due to accumulation of specialised soil pathogens and mutualists such as arbuscular mycorrhizal fungi. We detected that, despite their overall low relative abundance at least in our study, fungal plant pathogens in the soil seem to play an important role in modulating the composition of plant communities. Contrary to our hypothesis, we did not detect a consistent contribution of AMF in these soil legacies and in their role in influencing plant communities. Earlier findings show that the composition of the AMF community in the soil highly depend on the composition of the plant species that grow in the soil and not on the functional groups these plants belong to, and that effects on and of AMF may be masked in multi‐species plant communities (Morrien et al. \n 2017 ; Mommer et al. \n 2018 ). Moreover the sampling of soils, not roots, may have played a role, as AMF are less easily detectable in soils than in roots (Saks et al \n . \n 2014 ). In the soils of plant communities that had more grasses, we found an accumulation of fungal pathogens (dominated by grass‐associated fungal pathogens). Interestingly, the relative abundance of forb‐associated pathogens was very low and there was no relationship with the abundance of forbs in the vegetation. Forbs are a broad phylogenetic group (comprised of many plant families). Forb pathogens that specialise on a specific family or group of forb species are unlikely to accept hosts from all forb families, and as a result the relative abundances of such specific forb pathogens may not drive the abundance of this functional group as a whole. Grasses, on the other hand, are phylogenetically more closely related to each other (all Poaceae). Due to this higher relatedness, pathogens specialised in this group are more likely to affect a larger proportion of the functional group as a whole. While some pathogens have a rather broad host range, even specialised pathogens may attack a range of host plants if they are closely related (Barrett & Heil 2012 ). This may explain why accumulation of grass‐associated pathogens negatively affected grass abundance in the field, while no general pattern was detected for forbs. Importantly, our results indicate that negative soil legacy effects on grasses observed in mid‐successional grasslands, can be, at least partially, explained by accumulation of pathogens (Kulmatiski et al. \n 2008 ; Van der Putten et al. \n 2013 ). Our results further reveal that both bacteria and fungi in the soil respond to the conditioning plant communities that grow in the soil. The effects on fungal communities, but not on the bacterial communities or abiotic characteristics of the soil, are longer‐lasting, and have knock‐on effects on the subsequent responding plant communities (Kardol et al. \n 2006 ). We may conclude that soil bacterial communities, although responsive to conditioning treatments, play a less important role in affecting the community dynamics of responding plant communities. As the soil communities were sampled in September 2017, three months after the conditioning vegetation was removed, the original conditioning effects on soil bacteria may have disappeared. This is in strong agreement with recent findings that soil fungal communities are shaped over time by plants, whereas bacterial communities are shaped far less strongly by plants, and instead more by varying environmental conditions over time (Hannula et al. \n 2019b ). Soil legacy effects in natural plant communities are likely not driven by one taxon specifically, but rather by the composition of the soil fungal community as a whole (Semchenko et al. \n 2018 ; Bennett & Klironomos 2018 ; Mommer et al. \n 2018 , but see Harrison & Bardgett, 2010 ). Importantly, we show that conditioning effects of plant communities on soil biota, outweigh the effects on soil abiotic parameters, and are drivers of soil legacy effects on plant growth in the field. One potential confounding factor in the results is that plant roots and seeds originating from the conditioning plant community could have been left behind in the soil after the conditioning community was removed and that these roots may have influenced the composition of the responding communities, either directly via regrowth or via affecting the soil. There were some positive conspecific relationships between conditioning and responding plant species, but these effects were community‐specific. For instance, a positive conspecific relationship was observed for R. acetosella . This species flowers very quickly and produces many seeds. It is therefore plausible that seeds produced during the conditioning phase, and that entered the seedbank, caused an increased local abundance of this species in the responding communities. Furthermore, we observed a positive conspecific relationship for C. vulgare and H. lanatus . Both species regrow from root systems in pot experiments (R. Heinen, pers. obs.) and hence for these species regrowth may be responsible for these observed relationships. However, it is unlikely that these effects have had a strong effect on the responding plant community as a whole, as the strongest relationships – observed between functional types in the conditioning versus the responding plant communities – were negative and thus cannot be explained by regrowth or seed production. We therefore conclude that soil legacy effects must be the dominant driver of these effects. It is important to note that at the plant species level, we detected very few indicators for conspecific plant–soil feedbacks. This is an interesting finding as the field site used in this study has been used to collect soil from for countless plant–soil feedback studies over the past decades. In the majority of these studies, plant species grown in soils from this site have negative conspecific feedback effects (e.g. Wubs & Bezemer, 2016 ; Heinen et al. \n 2018 ). This indicates that individual plant–soil feedbacks as observed in pot studies, may be counter balanced by other plant species that simultaneously grow in (and thus condition) the soil in natural and diverse plant communities. We speculate that conspecific plant–soil feedbacks could play a larger role in less diverse or more disturbed systems such as dune vegetation. However, future work is needed to investigate the role of plant diversity in plant–soil feedbacks in the field. In conclusion, we show that the ratios between plants of different functional types within a plant community mediate plant‐induced microbial soil legacies, and that these legacies determine the composition of later establishing plant communities in the field. Importantly, this means that by managing current plant communities in the field, we can influence the composition of future plant communities and the ecological functions they provide. This opens new avenues for optimising nature management practices, which is vitally important in the face of global change, for instance in making nature more robust to climate change or invasions."
} | 3,640 |
29358742 | null | s2 | 9,048 | {
"abstract": "Peptidic natural products (PNPs) include many antibiotics and other bioactive compounds. While the recent launch of the Global Natural Products Social (GNPS) molecular networking infrastructure is transforming PNP discovery into a high-throughput technology, PNP identification algorithms are needed to realize the potential of the GNPS project. GNPS relies on the assumption that each connected component of a molecular network (representing related metabolites) illuminates the 'dark matter of metabolomics' as long as it contains a known metabolite present in a database. We reveal a surprising diversity of PNPs produced by related bacteria and show that, contrary to the 'comparative metabolomics' assumption, two related bacteria are unlikely to produce identical PNPs (even though they are likely to produce similar PNPs). Since this observation undermines the utility of GNPS, we developed a PNP identification tool, VarQuest, that illuminates the connected components in a molecular network even if they do not contain known PNPs and only contain their variants. VarQuest reveals an order of magnitude more PNP variants than all previous PNP discovery efforts and demonstrates that GNPS already contains spectra from 41% of the currently known PNP families. The enormous diversity of PNPs suggests that biosynthetic gene clusters in various microorganisms constantly evolve to generate a unique spectrum of PNP variants that differ from PNPs in other species."
} | 367 |
32783358 | null | s2 | 9,049 | {
"abstract": "Natural products and secondary metabolites comprise an indispensable resource from living organisms that have transformed areas of medicine, agriculture, and biotechnology. Recent advances in high-throughput DNA sequencing and computational analysis suggest that the vast majority of natural products remain undiscovered. To accelerate the natural product discovery pipeline, cell-free metabolic engineering approaches used to develop robust catalytic networks are being repurposed to access new chemical scaffolds, and new enzymes capable of performing diverse chemistries. Such enzymes could serve as flexible biocatalytic tools to further expand the unique chemical space of natural products and secondary metabolites, and provide a more sustainable route to manufacture these molecules. Herein, we highlight select examples of natural product biosynthesis using cell-free systems and propose how cell-free technologies could facilitate our ability to access and modify these structures to transform synthetic and chemical biology."
} | 258 |
30930856 | PMC6428765 | pmc | 9,050 | {
"abstract": "Hadal ocean sediments, found at sites deeper than 6,000 m water depth, are thought to contain microbial communities distinct from those at shallower depths due to high hydrostatic pressures and higher abundances of organic matter. These communities may also differ from one other as a result of geographical isolation. Here we compare microbial community composition in surficial sediments of two hadal environments—the Mariana and Kermadec trenches—to evaluate microbial biogeography at hadal depths. Sediment microbial consortia were distinct between trenches, with higher relative sequence abundances of taxa previously correlated with organic matter degradation present in the Kermadec Trench. In contrast, the Mariana Trench, and deeper sediments in both trenches, were enriched in taxa predicted to break down recalcitrant material and contained other uncharacterized lineages. At the 97% similarity level, sequence-abundant taxa were not trench-specific and were related to those found in other hadal and abyssal habitats, indicating potential connectivity between geographically isolated sediments. Despite the diversity of microorganisms identified using culture-independent techniques, most isolates obtained under in situ pressures were related to previously identified piezophiles. Members related to these same taxa also became dominant community members when native sediments were incubated under static, long-term, unamended high-pressure conditions. Our results support the hypothesis that there is connectivity between sediment microbial populations inhabiting the Mariana and Kermadec trenches while showing that both whole communities and specific microbial lineages vary between trench of collection and sediment horizon depth. This in situ biodiversity is largely missed when incubating samples within pressure vessels and highlights the need for revised protocols for high-pressure incubations.",
"conclusion": "Conclusions Here, we present the first comparison of microbial communities within hadal sediments of two trenches. Sediment community composition varied by trench of collection, sediment horizon depth, and water column depth, changes predicted to be due in part to variations in organic matter concentrations. Future studies of hadal sediments should couple their analyses of community composition to organic matter concentrations and compositions. While the communities differed between the two trenches, neither appeared to be dominated by endemic microbial communities at the 97% OTU level. Instead, the hadal sediments shared many cosmopolitan taxa similar to those found in other abyssal and hadal sites, suggesting members of these lineages may be ubiquitous at hadal depths. These findings highlight the possibility of microbial dispersal over long distances between hadal zones. Whether these taxa are actually distinct, both between trenches and from those found at abyssal sites, will ultimately require whole genome comparisons and analyses of phenotypic plasticity, and not just partial 16S rRNA gene analyses. Culturing and in situ abundances of known piezophiles showed that these taxa represent a relatively small fraction of environmental samples and were enriched in the Kermadec Trench, perhaps because of affiliation with organic-rich conditions. After long-term batch incubation of sediments at in situ high hydrostatic pressure, these taxa came to dominate the communities at the expense of initially more abundant members. The attempted isolation of piezophiles extends back to the 1940s and yet very few taxa have been isolated, potentially because of the use of pressure vessels. Future work should attempt to more closely mimic in situ conditions using recirculating systems or, perhaps more effectively, attempt to enrich for microorganisms in situ , as current practices involving removing samples from the deep-ocean ultimately select for a few taxa that are not representative of deep-ocean sediment communities at large.",
"introduction": "Introduction Ocean sediments make up one of the largest biomes on earth, harboring an estimated 3 × 10 29 total microbial cells distributed in 3 × 10 8 km 3 of sediment with 8 × 10 7 km 3 of pore water ( Kallmeyer et al., 2012 ; Amend and LaRowe, 2016 ). Deep-sea sediment microbial community composition is influenced by organic matter abundance and content ( D’Hondt et al., 2009 ; Bienhold et al., 2012 , 2016 ; Kallmeyer et al., 2012 ; Jacob et al., 2013 ), sediment horizon depth ( Walsh et al., 2016a , b ), water column depth ( Jacob et al., 2013 ), and geographical location ( Hamdan et al., 2013 ; Bienhold et al., 2016 ). Sediment communities are distinct from those in the water column despite the deposition of sinking taxa from above ( Zinger et al., 2011 ; Hamdan et al., 2013 ). While surficial sediments include high abundances of Gammaproteobacteria , Deltaproteobacteria , Alphaproteobacteria , and Actinobacteria ( Zinger et al., 2011 ; Ruff et al., 2015 ), deeper subsurface layers are dominated by the Chloroflexi and Atribacteria (OP9/JS1; Bienhold et al., 2016 ; Walsh et al., 2016b ). These deeper communities may consist of taxa adapted to deep subsurface conditions ( Inagaki et al., 2015 ) or which are found at shallower sediment horizon depths and survive after burial ( Starnawski et al., 2017 ). Sediment microbial communities at hadal depths remain largely unexplored. These sites are deeper than 6,000 m water depth and are typically affiliated with trenches, steep-walled depressions formed through the subduction of one tectonic plate below another. Sediment oxygen concentrations can drop from 200 μmol l −1 to undetectable levels over the top 10 cm in trenches, indicating high rates of oxygen consumption ( Glud et al., 2013 ; Wenzhöfer et al., 2016 ). Topographical funneling of organic matter may sustain this activity ( Danovaro et al., 2003 ; Glud et al., 2013 ; Wenzhöfer et al., 2016 ) as increases in organic material with water depth have been observed in the Mariana Trench ( Luo et al., 2017 ) and modeled in the Kermadec Trench ( Ichino et al., 2015 ). An alternative source of organic carbon within trenches may be geochemical inputs from below ( Li et al., 1999 ; Fujiwara et al., 2001 ; Tarn et al., 2016 ). Until recently, microbial community analyses of hadal sediments have been limited to 16S rRNA gene sequence studies with small sample sizes ( Kato et al., 1997 ; Li et al., 1999 ; Yanagibayashi et al., 1999 ; Nunoura et al., 2013 ; Yoshida et al., 2013 ; Luo et al., 2015 ) and cultivation attempts. Culture-independent analyses have identified taxa affiliated with the same lineages as those found within other shallower deep-ocean sediments and suggested the importance of nitrogen cycling within these communities ( Nunoura et al., 2013 , 2018 ; Yoshida et al., 2013 ; Luo et al., 2015 ; León-Zayas et al., 2017 ). High-pressure, culture-based analyses have predominantly found copiotrophic members of the Gammaproteobacteria , including Shewanella , Colwellia , Moritella , and Psychromonas ( Kato et al., 1998 ; Nogi et al., 1998 , 2002 , 2004 , 2007 ). Two of the deepest locations in the ocean are the Mariana and Kermadec trenches. The Mariana Trench, located in the Northern Hemisphere near the Mariana Islands, extends to 10,984 m at its greatest depth ( Gardner et al., 2014 ). The Kermadec Trench begins off the northeastern coast of New Zealand and reaches a maximum depth of 10,047 m ( Angel, 1982 ). These trenches reside approximately 6,000 km apart within the Pacific Ocean. Deep-sea sediments can show high levels of microbial endemism and significant decay of community similarity over distance ( Zinger et al., 2014 ; Bienhold et al., 2016 ). Endemism could be especially prevalent in hadal trenches, which are predicted to be rich in endemic taxa due to their extreme depths and geographical isolation ( Beliaev, 1989 ). Furthermore, water mass inputs and annual rates of primary production vary between the two trenches, with primary productivity in the overlying waters of the Kermadec estimated at 87 g C m −2 yr −1 compared to 59 g C m −2 yr −1 in the waters above the Mariana Trench ( Longhurst et al., 1995 ; Jamieson, 2015 ). Therefore, we hypothesize that geographical isolation and differences in organic matter input lead to distinct community compositions between the two trenches. In this study, we investigated the microbial communities within surficial sediment (0–10 cm) samples collected from 6- to 9-km water depths in the Kermadec Trench and 7- to 8-km depths in the Mariana Trench with both culture-independent high-throughput 16S rRNA gene sequencing and culture-dependent characterization.",
"discussion": "Discussion Similar Lineages Are Present in both Mariana and Kermadec Trench Sediments In this study, we evaluated the microbial community composition within trench sediments to test the hypothesis that hadal zones have distinct microbial communities from one another. While sediment communities were observed to be distinct between trench of collection and sampling site, there was significant overlap in the abundant taxa found in the Mariana and Kermadec trenches. Shared OTUs within both trenches represented greater than 90% of all reads. Therefore trench endemic OTUs made up small proportions of the communities when evaluated at 97% similarity. Many abundant taxa were closely related to members identified within other abyssal and hadal samples. These taxa belonged to lineages previously identified as having cosmopolitan members at bathyal and abyssal depths ( Bienhold et al., 2016 ; Mußmann et al., 2017 ), such as sequences related to JTB255, BD2–11, JTB23, and the genus Marinicella . These results indicate that members within these lineages are present even at hadal depths. Similarly, the isolates obtained at high hydrostatic pressures were related to the genera Colwellia , Shewanella , and Moritella , consistent with previous studies. Many of the partial 16S rRNA genes of isolates from the present study were more than 97% similar to those of other piezophilic isolates. New strains were also obtained, including isolates related to the genus Psychrobium within the Gammaproteobacteria , Arcobacter within the Epsilonproteobacteria , and a member of the Flavobacteriaceae. Unfortunately, none of these isolates survived cryopreservation or repeated subculturing. Still, this Psychrobium isolate was related to that previously enriched after long-term pressurization ( Aoki et al., 2014 ). Altogether, our results demonstrate the possible dispersal of OTUs between two widely separated trenches. Deep-ocean currents may lead to the dispersal and deposition of microorganisms in sediments ( Müller et al., 2014 ), such as Antarctic Bottom Water flowing between the Kermadec and Mariana trenches. It is also possible some members do not require dispersal between trenches, but may originate within abyssal sediments, a possibility not yet evaluated. In this scenario, the microbes in question would possess high fitness in both abyssal and trench zones, potentially spreading between the two environments via bottom currents, or perhaps through earthquake-induced mass-wasting deposition down slope ( Oguri et al., 2013 ). If taxa endemic to specific trenches exist in the hadal settings examined, they must exist at the strain rather than the species level, be rare, were lost during sampling, or are present in patchy or sample-specific distributions and were missed by our sampling. Comparisons with microbial communities in more distant trenches, such as the Puerto Rico or Atacama trenches, may show higher sequence abundances of endemic taxa. Inter- and Intra-Trench Variation May Be Due to Organic Matter Differences in organic matter due to primary production in overlying surface waters and its deposition through topographical funneling may be one of the most important factors structuring communities within trenches ( Danovaro et al., 2003 ; Glud et al., 2013 ; Ichino et al., 2015 ; Wenzhöfer et al., 2016 ). The Kermadec Trench may have higher concentrations of organic matter than the Mariana Trench because of differences in primary productivity at the surface ( Longhurst et al., 1995 ; Jamieson, 2015 ). While we do not have organic matter concentrations to report here for each core, preliminary data from the 0–1-cm fraction at 8000 m in each trench suggest that percent total organic carbon is higher in the Kermadec Trench (~0.5%) than the Mariana Trench (~0.4%; Grammatopoulou et al., in prep). Therefore, it is reasonable to hypothesize that organic matter is in part responsible for the differences between the Mariana and Kermadec trench communities. Consistent with this, the Kermadec Trench was enriched, relative to the Mariana Trench, in the Bacteroidetes , Actinobacteria , and Proteobacteria , lineages that have been found to correlate with higher concentrations of organic matter ( Bienhold et al., 2012 ; Learman et al., 2016 ). In contrast, the Mariana Trench had higher proportions of Thaumarchaeota , Chloroflexi , and other uncharacterized lineages. Although Archaea are ubiquitous in marine sediments, organic matter concentrations are thought to negatively correlate with abundances of ammonia-oxidizing Archaea ( Luo et al., 2015 ; Learman et al., 2016 ), potentially due to differences in electron acceptor availability or Archaea outcompeting Bacteria under energy-starved conditions ( Valentine, 2007 ; Hoehler and Jorgensen, 2013 ). The Chloroflexi may also be adapted to degrading recalcitrant organic matter ( Landry et al., 2017 ). Furthermore, the number of piezophilic isolates and related sequences in the high-throughput community data were higher within the Kermadec than the Mariana Trench and were enriched in the upper layers of sediment. Their enrichment in the Kermadec Trench pelagic community and on larger size fractions has been suggested to be a result of adaptations to higher concentrations of organic matter, including particulate forms ( Peoples et al., 2018a ). Intra-trench variability may also be influenced by organic matter due to topographic funneling into the axis of the trench. Within the Kermadec Trench the Chloroflexi and Acidobacteria were enriched at 6- and 7-km depths whereas the Nitrospirae and Actinobacteria are more abundant at 8- and 9-km depths. Enrichments of Nitrospirae within the hadal water column have been attributed to a more eutrophic environment ( Nunoura et al., 2015 ). Altogether, these findings suggest the Kermadec Trench may be enriched in organic matter relative to the Mariana Trench. Ultimately, deep-sea microbial communities are governed by a myriad of variables that may contribute to these inter- and intra-trench differences, such as hydrography ( Hamdan et al., 2013 ), specific location of sample collection, temporal variability and season of sample collection ( Lampitt, 1985 ), sediment lithology ( Probandt et al., 2017 ), or the quality, not just the quantity, of organic matter present. Our findings support the notion that organic matter can contribute to the spatio-temporal variability in deep-sea microbial communities. Centimeter-Scale Sediment Depth Changes Select for Certain Microbial Lineages While trench sediments may become mixed and suspended due to tectonic activity and topographic instability ( Kawagucci et al., 2012 ; Oguri et al., 2013 ; Nunoura et al., 2016 ), the sediment communities studied here were stratified and compositionally distinct from those in the water column above them ( Peoples et al., 2018a ). Because the oxygen penetration depth can be limited to the top 10 cm in trenches ( Glud et al., 2013 ; Wenzhöfer et al., 2016 ), we compared the microbial communities present in the shallower and deeper sediment horizons. Community richness and diversity varied with sediment horizon depth, consistent with previous comparisons of surficial and deep subsurface environments ( Durbin and Teske, 2010 ; Teske et al., 2011 ; Shulse et al., 2016 ; Walsh et al., 2016a , b ). Our findings suggest that specific deep-sea lineages are enriched within deeper marine sediments. Within the Thaumarchaeota, MGI-α showed enrichment in the upper sediment while those belonging to the MGI-η subgroup were more abundant in the deeper sediments. Such ecotype differentiation has been previously noted in abyssal sediments ( Durbin and Teske, 2010 ; Tully and Heidelberg, 2013 ; Lauer et al., 2016 ) and may be due to changes in organic matter abundance or oxygen availability ( Durbin and Teske, 2010 ). Abundances of alternative electron acceptors, such as nitrate, sulfate, or iron, influence community composition ( D’Hondt et al., 2009 ; Durbin and Teske, 2010 , 2012 ; Nunoura et al., 2013 ; Jessen et al., 2017 ) and therefore likely play an important role in hadal sediments ( Nunoura et al., 2013 , 2018 ) as the oxygen penetration depth can be shallow ( Glud et al., 2013 ; Wenzhöfer et al., 2016 ). Relative sequence abundances of the Woesearchaeota increased with increasing sediment horizon depth. This archaeal phylum has members that are specifically enriched in anoxic niches and can have fermentative or symbiotic lifestyles ( Castelle et al., 2015 ; Lazar et al., 2017 ; Liu et al., 2018 ). Differences in genomic potential and niche separation of Woesearchaeota suggest that unexplored diversity exists within this phylum ( Shcherbakova et al., 2016 ; Narrowe et al., 2017 ). OTUs related to the Woesearchaeota within our dataset were remarkably distinct from other previously identified studies, showing highest similarity to sequences from abyssal and hadal sites and low (<95%) similarity to representative sequences from other habitats ( Supplementary Figure 10 ). The Marinimicrobia , which are abundant within the deep-ocean water column ( Nunoura et al., 2015 ; Tarn et al., 2016 ; Peoples et al., 2018a ), also increased with sediment horizon depth. Based on phylogenetic analysis ( Supplementary Figure 6 ) the Marinimicrobia OTUs identified here belong to deep-sea sediment-associated clades that have not been previously identified ( Hawley et al., 2017 ). Current High-Pressure Culturing Methods Are Inappropriate for Most Deep-Sea Taxa Although a large diversity of Bacteria and Archaea were found within the sediments, very few taxa were successfully isolated. Many of those that were belong to the same genera as known piezophiles, consistent with most previous isolation attempts from the deep sea. Interestingly, after unamended, long-term static pressurization of sediment samples, higher relative sequence abundances of taxa related to the cultured piezophiles Psychrobium , Colwellia , Arcobacter , and Shewanella were found. In shallow-ocean communities, Colwellia is one of the first responders to microcosm conditions ( Stewart et al., 2012 ; Mayali et al., 2016 ) and enrichments of Colwelliaceae , Moritellaceae , Psychromonadaceae , and Shewanellaceae have been observed within enrichments of Arctic bathyal-depth sediment samples under high pressure ( Hoffmann et al., 2017 ). Therefore, regardless of location, depth of collection (surface, bathyal, and in this study hadal), nutrient enrichment, or temperature or pressure incubation conditions, taxa belonging to the same heterotrophic and copiotrophic genera within the Gammaproteobacteria are enriched under mesocosm conditions. These taxa may contain metabolic versatility for colonizing various ecological niches during fluctuating environmental conditions ( Stewart et al., 2012 ). In contrast, microbial populations from immediately recovered samples were enriched in taxa belonging to uncharacterized and uncultivated lineages representative of the in situ diversity. Taken together with the enrichment of culturable taxa, these findings highlight the difficulties in obtaining pure cultures of representative and novel deep-ocean lineages. This study is the first to show that long-term incubations in pressure vessels, regardless of nutrient amendment or collection location, clearly select for the same piezophilic taxa. Decompression during sample retrieval, static incubation conditions in pressure vessels leading to lack of oxygen or other important nutrients, or eukaryotic predation ( Tsagaraki et al., 2018 ) may significantly bias our ability to obtain cultures of piezophiles."
} | 5,117 |
22509169 | PMC3325761 | pmc | 9,052 | {
"abstract": "We used medic ( Medicago truncatula ) to investigate effects of inoculation with two arbuscular mycorrhizal (AM) fungi and application of arsenate (AsV) and phosphate (Pi) on mechanisms underlying increased tolerance (in terms of growth) of AM plants to AsV. We tested the hypotheses that (1) inoculation with AM fungi results in down-regulation of MtPht1;1 and MtPht1;2 genes (encoding high-affinity Pi and AsV uptake systems in the direct root epidermal pathway) and up-regulation of the AM-induced MtPht1;4 (responsible for transfer of Pi from the arbuscular interface to cortical cells), and (2) these changes are involved in decreased As uptake relative to P uptake and hence increased As tolerance. We also measured expression of MtMT4 , a Pi starvation-inducible gene, other genes encoding Pi uptake systems ( MtPht 1;5 and MtPht1;6 ) and arsenate reductase ( MtACR) and phytochelatin synthase ( MtPCS ), to gain insights into broader aspects of P transfers in AM plants and possible detoxification mechanisms. Medic responded slightly to AM colonization in terms of growth in the absence of As, but positively in terms of P uptake. Both growth and P responses in AM plants were positive when As was applied, indicating As tolerance relative to non-mycorrhizal (NM) plants. All AM plants showed high expression of MtPT4 and those inoculated with Glomus mosseae showed higher selectivity against As (shown by P/As molar ratios) and much lower expression of MtPht1;1 (and to some extent MtPht1;2 ) than Glomus intraradices -inoculated or NM plants. Results are consistent with increased P/As selectivity in AM plants (particularly those inoculated with G. mosseae ) as a consequence of high P uptake but little or no As uptake via the AM pathway. However, the extent to which selectivity is dependent on down-regulation of direct Pi and AsV uptake through epidermal cells is still not clear. Marked up-regulation of a PCS gene and an ACR gene in AM plants may also be involved and requires further investigation.",
"introduction": "Introduction Arsenic (As) is toxic to both plants and animals, so that entry into and movement through food chains pose significant problems for human health (Heikens et al., 2007 ; Zhao et al., 2010 ). In consequence, considerable attention is being paid to the mechanisms by which As is absorbed and redistributed in plants, as well as to strategies that may reduce uptake and/or provide a basis for remediation of contaminated soils (Heikens et al., 2007 ; Zhao et al., 2009 , 2010 ). Here we focus on arsenate (AsV), which is the main arsenic species occurring in aerobic soils. Arsenate is an analog of orthophosphate (Pi) and both AsV and Pi are absorbed by the same Pi transporters in the root hairs and epidermis (Heikens et al., 2007 ; Zhao et al., 2009 , 2010 ). Most research, particularly that carried out in solution culture, has focused on AsV uptake via this direct pathway and on the way that Pi may compete with it. However, the majority of plants grown in non-sterile soil form arbuscular mycorrhizas (Smith and Read, 2008 ) which provide an additional, arbuscular mycorrhizal (AM) pathway by which nutrients, particularly P, are absorbed and transported to root cortical cells via the AM fungus (Smith et al., 2011 ). The AM pathway is distinct from the direct pathway; it involves different cell types, different Pi transporters, and is likely to be separately regulated (Smith and Smith, 2011 ; Smith et al., 2011 ). Although the AM pathway is potentially capable of transporting As, new knowledge of the interplay between the activities of direct and AM pathways is beginning to reveal the mechanisms underlying the effects that AM symbioses have in ameliorating the toxic effects of AsV on plant growth (Christophersen et al., 2009a ; Smith et al., 2010 ). Arbuscular mycorrhizal symbioses ameliorate As toxicity and AM plants consistently show higher P/As ratios in tissues than non-mycorrhizal (NM) counterparts (see Smith et al., 2010 for references). This indicates that the uptake pathways in AM and NM plants discriminate differently between Pi and AsV. Previously we used barley ( Hordeum vulgare ) as the host for the AM fungus Glomus intraradices because this plant does not respond positively to the symbioses in terms of growth or P uptake; hence interpretation of effects of the symbiosis on Pi and AsV uptake were not confounded by markedly different sizes and P nutrition of the AM and NM plants (Christophersen et al., 2009a ). It is known that the AM pathway plays a major role in uptake of Pi by barley (Zhu et al., 2003 ; Grace et al., 2009 ), and that activity of the direct pathway is concurrently reduced because there is no increase in total P uptake per plant (see Smith et al., 2009 ; Smith et al., 2011 ). In the work of Christophersen et al. ( 2009a ), the reduction of direct pathway activity in AM plants was associated with lower expression of the epidermal Pi transporters ( HvPht1;1 and HvPht1;2 ) involved in Pi and AsV uptake, while the expression of the AM-inducible transporter HvPht1;8 , responsible for Pi uptake by root cortical cells in the AM pathway, was highly up-regulated and unaffected by As application. AM plants had lower specific AsV uptake (uptake per unit weight of root) and higher P/As ratios in shoots than NM plants. Results supported the hypothesis that down-regulation of the direct pathway lowers both AsV and Pi uptake via that route, while activity of the AM pathway in Pi uptake compensates for lower Pi uptake via the direct pathway but transports little or no As. Most work on the effects of AM symbiosis on As toxicity has been done with plant species that grow larger and take up more P when AM, compared with NM counterparts. In such species, the AM pathway delivers large amounts of P to the plant and effects of AM colonization in decreasing P (and potentially As) delivery via the direct pathway are not as clear as they are in non-responsive plants such as barley. If there is no functional down-regulation of the direct pathway in responsive AM plants, then specific uptake of AsV by this route should remain unchanged, but overall discrimination of uptake in favor of Pi (and hence increased P/As ratios) would be provided by high delivery of P and low (or negligible) delivery of As via the AM pathway, as suggested by Christophersen et al. ( 2009a ). Previous work has consistently shown higher specific P uptake in AM-responsive plants in the presence of As, compared with NM counterparts. However, effects on specific As uptake ranged from decreases (Ultra et al., 2007 ) to increases (Liu et al., 2005 ; Xia et al., 2007 ), with several reports of no effects (Ahmed et al., 2006 ; Pope, 2006 ; Pope et al., 2007 ; Xia et al., 2007 ). These differences leave open the question of whether down-regulation of the direct pathway is involved in lowering AsV uptake. In this paper we examined this hypothesis by investigating the effects of AM colonization by two different AM fungi on As toxicity in and Pi and AsV uptake by medic ( Medicago truncatula ), a plant that frequently responds positively to AM colonization in terms of growth and P uptake. We used soil P levels designed to lower these responses. We made concurrent measurements of the expression of plant Pi transporters in the direct pathway ( MtPht1;1 and MtPht1;2 ) and the AM-inducible Pi transporter gene MtPht1;4 (involved in operation of the AM pathway). We also examined the expression of two other genes encoding P transporters in roots ( MtPht1;5 and MtPth1;6 ), whose expression patterns and responses to P supply and AM colonization are less well known (see Grunwald et al., 2009 ). Expression of a P starvation response gene MtMT4 (Burleigh and Harrison, 1998 ) and of two genes potentially involved in As detoxification mechanisms [a phytochelatin synthase (PCS) gene and an arsenate reductase (ACR gene)] were also included to check whether the treatments influenced P starvation at the molecular level and whether the As detoxification mechanisms were influenced by AM colonization (see Table 1 ). Table 1 Summary of information 1 on genes chosen for expression analysis in medic ( Medicago truncatul a ) plants . Gene name (abbreviation) Identity Tissue location Affinity for Pi Effect of increased P Effect of AM status of roots 2 MtMT4 Non-coding RNA, involved in Pi-deprivation signaling pathway Roots NA Decreased Decreased MtPht1;1 ( PT1 ) Pi transporter Root epidermis and cortex Low Slowly decreased Decreased MtPht1;2 ( PT2 ) Pi transporter Root epidermis cortex and vascular tissue Low Slowly decreased Decreased or little affected MtPht1;4 ( PT4 ) Pi transporter AM root cortex Low Not known Large increase MtPht1;5 ( PT5 ) Pi transporter Root epidermis cortex and vascular tissue High Rapidly decreased Maintained or decreased MtPht1;6 ( PT6 ) Pi transporter Roots. Other tissues not reported Not reported Unaffected Decreased MtACR 3 Arsenate reductase No previous information MtPCS 3 Phytochelatin synthase No previous information 1 Information on phosphate transporters and MtMT4 based on Burleigh and Harrison ( 1999 ), Burleigh and Harrison ( 1998 ), Grunwald et al. ( 2009 ), Javot et al. ( 2007 ), Liu et al. ( 2008 ). For arsenate reductase and phytochelatin synthase see text . 2 Differential effects depending on fungal identity have been reported in some cases . 3 Putative genes for which no previous information is available. For sequence identification procedure, see text . Glomus intraradices was chosen as one AM fungal symbiont because it was the fungus used in our previous experiments with barley (Christophersen et al., 2009a , b ) and M. truncatula (Pope et al., 2007 ) and Glomus mosseae because it has been used with several different responsive plant species in many of the previous investigations of effects of AM fungi on As toxicity (e.g., Liu et al., 2005 ; Ahmed et al., 2006 ; Chen et al., 2007 ; Xia et al., 2007 ).",
"discussion": "Discussion Arbuscular mycorrhizal colonization by both fungi was relatively high and small decreases with As application only occurred in plants inoculated with G. intraradices , as shown previously for this plant/fungus combination (Pope et al., 2007 ). In most previous investigations, including those using G. mosseae , effects of As on percent root length colonized have not been widely observed (Smith et al., 2010 ). Here the more marked effect of 5 As on total and arbuscular percent colonization by G. intraradices could have been related to higher concentrations of As in roots colonized by this fungus compared with those colonized by G. mosseae . Reduced expression of the AM-inducible transporter PT4 with increasing arsenic in G. intraradices -inoculated plants grown at low P could have been related to the reduction in colonization and arbuscule development. Both these points require further investigation. Medic did not show large positive responses to AM colonization in terms of growth at LP0As, but there were significant positive responses to inoculation in terms of total plant P uptake and specific P uptake, with effects generally greater in plants inoculated with G. mosseae than with G. intraradices . Both these effects are reflected in higher P concentrations in the AM plants. Large positive responses were not expected because of the chosen P applications. With HP0As, both fungi produced small growth depressions, possibly due to carbon drain to the fungus that was not fully compensated by P uptake by the AM pathway (Smith et al., 2009 ). Increases in P concentrations, P content, and specific P uptake in AM plants compared with NM counterparts, together with high expression of the AM-inducible Pi transporter MtPht1;4 , suggest significant delivery of P via the AM pathway. The NM plants showed significant growth reductions and As toxicity as As application was increased (as shown previously, Chen et al., 2007 ; Pope et al., 2007 ). Toxicity in NM plants was significantly alleviated by additional P supply only at 2.5 As (see also Pope et al., 2007 ), but inoculation increased growth over NM controls at both levels of P with G. intraradices at 2.5 As and with G. mosseae at both 2.5 As and 5 As. These effects were associated with higher P concentrations, contents, and specific P uptake. The molar ratios of P/As were highest for G. mosseae -inoculated plants and lowest for NM plants, with G. intraradices -inoculated plants intermediate or equal to NM plants. Hence G. mosseae -inoculated plants showed the highest selectivity of P uptake over As uptake in both roots and shoots. The effect of AM colonization on increasing P/As selectivity is completely consistent with much previous work (Zhao et al., 2009 ; Smith et al., 2010 ) and provides the starting point for our exploration of possible mechanisms. Our hypothesis was that the high P/As selectivity would be associated with continuing supply of P, but little or no As, via the AM pathway and reduced uptake of both P and As via the epidermal direct pathway. The increased specific P uptake in AM plants and the high expression of PT4 in the AM pathway, regardless of small effects of As application on G. intraradices colonization, is consistent with this hypothesis. Furthermore, reduced expression of PT1 and PT2 in medic colonized by AM fungi (as shown here and previously in the absence of As; Liu et al., 1998 ; Burleigh, 2001 ; Chiou et al., 2001 ), particularly in plants inoculated with G. mosseae , suggests that activity of the direct pathway was lower than in G. intraradices -inoculated plants. This observation provides some explanation for the differential effects of the two fungi. The lower expression of both PT1 and PT2 observed here with G. mosseae does not agree with the findings of Grunwald et al. ( 2009 ) who showed that a different isolate of this AM fungal species had only very small effects on expression of these genes. The discrepancy may be the result of use of different HKG in the two investigations. Nevertheless, much more work is needed to sort out variations in gene expression such as this in the context of functional diversity among different plant–AM fungal combinations. Analysis of expression of the other genes encoding Pi transporters (Table 1 ) does not shed much further light on this issue. In G. mosseae -inoculated plants PT5 showed lower expression than other treatments at 0 As, with a significant increase as As application increased. Expression of PT6 was reduced to the same extent in AM plants with both fungi, compared with NM plants (as shown previously by Grunwald et al., 2009 ), but the role of this gene in Pi (or AsV) uptake or redistribution in plants remains obscure. Specific As uptake by NM plants was not significantly lower at HP than LP, which would have been expected if competition between Pi and AsV was an important factor influencing As uptake. This finding suggests that competition in uptake from soil between AsV and Pi may only make a small contribution to the overall effects of P on As toxicity (see Pope et al., 2007 ; Christophersen et al., 2009b ). Data for specific As uptake did not show the decrease in AM compared with NM plants at either P level that would be expected if lower uptake via the direct pathway and/or increased AsIII efflux are major contributors to lower AsV content and high P/As selectivity. Although specific As uptake was generally lower in G. mosseae -inoculated than in G. intraradices -inoculated plants neither had lower specific uptake than equivalent NM plants. Increases in specific As uptake in G. intraradices -inoculated plants may have been the result of uptake and delivery of As via the AM pathway. However, this is inconsistent with findings for non-responsive barley using the same isolate of G. intraradices (Christophersen et al., 2009a ) and responsive Medicago sativa , using G. mosseae (Chen et al., 2007 ). In both cases plants were grown in compartmented pots and results showed little or no evidence for As transfer via the AM pathway. Furthermore, if this was the explanation, higher transfer of As via G. mosseae would have been expected because these plants apparently had higher AM pathway activity than those inoculated with G. intraradices . The issues relating to differential activity of direct pathway and AM pathway in the context of uptake of Pi and AsV can only be readily resolved by the use of radioactive tracers of both As and Pi in compartmented pots (Smith et al., 2010 ). There remains the possibility that effects of AM inoculation other than those associated with Pi or AsV uptake may be involved in As tolerance in AM plants. Here, we have provided preliminary evidence that AM colonization increases expression of two plant genes [phytochelatin synthase ( MtPCS ) and arsenate reductase ( MtACR )] that encode proteins thought to be involved in arsenate detoxification. Both Medicago genes were expressed in NM plants and showed no major induction in the presence of As. The lack of difference in expression between G. intraradices - and G. mosseae -inoculated plants does not help explain the differential effects of the two fungal symbionts in alleviating As toxicity. In the case of MtPCS the lack of effect of As is in line with previous work showing constitutive production of PCs (see Clemens and Persoh, 2009 ). It has been suggested that PCs are involved in metal homeostasis and that apparent roles in detoxification of As follow from this (see Clemens and Persoh, 2009 ; Zhao et al., 2009 ). Increased MtPCS expression in AM roots, as shown here, could be primarily related to the role of AM fungi in delivering metals such as Zn to the roots (Bürkert and Robson, 1994 ). In the case of MtACR , increased expression might result in increased reduction of AsV to AsIII causing detoxification and possibly increased As transfer to the shoots (see Bleeker et al., 2006 ; Duan et al., 2007 ; Zhao et al., 2009 for references). However, increased shoot As was not detected in our analyses. The possibility that AsIII might be effluxed from either roots or AM fungal hyphae (Smith et al., 2010 ) is not likely because AM colonization did not decrease specific As uptake. Roles of both genes in alleviating As toxicity and more generally in metal binding in AM plants require further research."
} | 4,617 |
38129516 | PMC10739816 | pmc | 9,053 | {
"abstract": "The Escherichia coli chemotaxis network, by which bacteria modulate their random run/tumble swimming pattern to navigate their environment, must cope with unavoidable number fluctuations (“noise”) in its molecular constituents like other signaling networks. The probability of clockwise (CW) flagellar rotation, or CW bias, is a measure of the chemotaxis network’s output, and its temporal fluctuations provide a proxy for network noise. Here we quantify fluctuations in the chemotaxis signaling network from the switching statistics of flagella, observed using time-resolved fluorescence microscopy of individual optically trapped E. coli cells. This approach allows noise to be quantified across the dynamic range of the network. Large CW bias fluctuations are revealed at steady state, which may play a critical role in driving flagellar switching and cell tumbling. When the network is stimulated chemically to higher activity, fluctuations dramatically decrease. A stochastic theoretical model, inspired by work on gene expression noise, points to CheY activation occurring in bursts, driving CW bias fluctuations. This model also shows that an intrinsic kinetic ceiling on network activity places an upper limit on activated CheY and CW bias, which when encountered suppresses network fluctuations. This limit may also prevent cells from tumbling unproductively in steep gradients.",
"introduction": "Introduction A common feature of living organisms is their ability to sense environmental signals and respond to these signals by modifying their behavior. This ability is enabled by signal transduction, which converts environmental inputs into behavioral outputs 1 . Studies have shown that signaling networks must operate in the presence of noise not only in their inputs but also in the circuit components themselves 2 , 3 . Until recently, it was thought that signaling networks had evolved to be robust against undesirable noise 4 – 7 . More recent studies have shifted to understanding the role of noise in regulating and fine-tuning biological function 8 , 9 . For example, noise resulting from transcription/translation has been measured precisely and shown to play a critical role in networks for gene expression and regulation 10 – 12 . In contrast, studying noise resulting from signaling networks at the post-translation level has proven more challenging. One extensively studied signaling system is the chemotaxis network of E. coli , which cells use to navigate their environment 13 – 17 . E. coli cells swim in a random walk consisting of “runs”—during which their flagella rotate counter-clockwise (CCW)—and “tumbles”—during which one or more flagella rotate clockwise (CW) 18 – 21 . Changing environmental conditions are sensed through a two-component signaling system comprising receptors that bind extracellular ligands and a kinase, CheA, that transfers its phosphoryl group onto downstream effectors 22 . The response regulator, CheY, when phosphorylated by the receptor kinase complex to CheY-P, binds to the flagellar motor and increases the probability of CW motor rotation 23 – 25 . The phosphatase CheZ carries out the opposite reaction, maintaining a dynamic equilibrium between CheY and CheY-P (Fig. 1 a) 26 , 27 . Additionally, the methyltransferase CheR and the methylesterase CheB covalently modify receptors, and the resulting modulation of CheA activity affects CheY-P levels over the timescales of chemotactic adaptation 28 – 30 . While the population-averaged relationships between these signaling protein concentrations and cellular motility in E. coli are now well understood 13 – 16 , 24 , the role of fluctuations in modulating cell behavior remains comparatively unexplored. Figure 1 Estimating the temporal motor bias fluctuations from flagellar dynamics of single E. coli cells. ( a ) Schematic of a multi-flagellated E. coli cell showing key reactions of the chemotaxis signaling network. CheY is phosphorylated to CheY-P by the receptor kinase complex (CheA; dark blue); CheY-P is dephosphorylated by the phosphatase CheZ (gray). CheY-P binding to flagellar motors (mustard) causes a switch from CCW to CW rotation, which leads to cell tumbling. ( b ) Temporal fluctuations in [CheY-P] due to chemotaxis network dynamics and their effect on flagellar switching statistics. (i) [CheY-P] temporal fluctuations. (ii) Switch-like response of motor CW bias, c , to [CheY-P]. (iii) Resulting temporal fluctuations in motor bias c ( t ) and its distribution p ( c ), characterized by the mean μ c and standard deviation σ c . (iv) CCW/CW rotation state of three independent flagellar motors corresponding to the instantaneous motor bias c . ( c ) Schematic of two-channel laminar flow chamber for optical trap assay. A single cell with fluorescently labelled flagella (gray stars) is captured from the bottom channel (“Cells”), aligned along the flow between two optical traps (red cones), moved to the upper channel (“Blank”), and its fluorescent flagella (yellow stars) imaged by stroboscopic slim-field microscopy (green). ( d ) Fluorescence data trace from representative trapped cell with N = 3 flagella. Top, still images of fluorescent flagella, with position of the unlabeled cell body approximately indicated by the dashed yellow line. CW and CCW rotating flagella are labelled where clearly visible. Middle, CCW/CW rotation state of each flagellum vs. time (mustard). Bottom, corresponding number n CW of CW flagella vs. time (light blue). ( e ) Probability distribution p N ( n CW ), determined experimentally from d (light blue bars). The mean μ c and standard deviation σ c of the motor bias are estimated from the parameters of the distribution p N ( n CW ) using Eqs. ( 3 ) and ( 4 ). Noise in the chemotaxis network was first inferred by Korobkova et al. 31 from long-term measurements of individual rotating flagellar motors. Inside the cell, the CheY-P concentration, [CheY-P], fluctuates in time due to noise sources upstream in the signaling network (Fig. 1 b,i). These fluctuations in turn affect downstream behavior. The motor CW bias, i.e. the probability of CW rotation of a single flagellar motor, has an ultrasensitive switch-like dependence 25 on the intracellular [CheY-P] (Fig. 1 b,ii), resulting in fluctuations in motor rotational state (Fig. 1 b,iii) and in the cell’s swimming behavior. Noise in the E. coli chemotaxis signaling network is thought to have functional consequences for sensing and navigation in complex natural microenvironments. It has been proposed to allow cells to sample 3-D space more effectively 31 , 32 , enhance chemotactic drift up a gradient 33 – 35 , and synchronize flagellar switching to mitigate differences in swimming behavior among cells with different numbers of flagella 36 , 37 . Here, we use optical trapping coupled with time-resolved fluorescence microscopy 37 , 38 to infer temporal network fluctuations from the statistics of flagellar switching in individual multi-flagellated E. coli cells. Analyzing cells at steady state, we determine the mean and fluctuations in CW bias, which reveal that the network is poised at a low CW bias, favoring CCW flagellar rotation/running, and that transient fluctuations drive CW flagellar rotation/tumbling. Previous studies using flagellar motor behavior 31 , 39 or fluorescence-based reporters 40 , 41 to infer noise in the chemotaxis network have been limited to long timescales (> 10 s) due to temporal averaging. However, studies of flagellar tracking show that short timescale fluctuations are important to explain observations of correlated flagellar switching 36 , 42 . In contrast to most earlier approaches, our method measures fluctuations on shorter timescales (~ 3 s), comparable to individual run and tumble durations. We exploit this feature to track carefully the time evolution of signaling noise in cells responding to a stimulus that increases CheA activity. This, in turn, allows us to measure network fluctuations across the accessible range of motor CW biases. We find that fluctuations are significantly reduced when the motor CW bias is increased away from its steady-state value. A simple stochastic model in which noise in signaling arises from burst-like fluctuations in CheA activity recapitulates all of our experimental results and suggests that the decrease in fluctuations upon stimulation is due to a kinetic ceiling on the CheA activity.",
"discussion": "Discussion In this work we demonstrate a new approach for inferring fluctuations in the chemotaxis network based on the statistics of flagellar switching in multi-flagellated E. coli cells. One advantage of this approach is that its accuracy in quantifying network noise does not depend on temporal averaging, which limited previous measurements to long time scales (> 10 s) 31 , 39 – 41 . Many recent measurements of network noise have been made through FRET imaging systems that require data collection and averaging over long periods of time, and thus sacrifice temporal resolution. Single flagellar tracking using high speed cameras has emerged as an alternative to measure network noise at short timescales 36 , and only very recently has revealed short time fluctuations (< 1s) 57 . Our approach to estimating network noise relies on fluorescence-based observations of multiple flagellar motors making independent simultaneous “measurements” of the intracellular CheY-P level, and tuning their CW bias in response. This feature makes it possible to measure fluctuations in CW bias (and infer the underlying network noise) over time scales of individual runs and tumbles and to track their time evolution. As demonstrated in Fig. 4 , we can accurately determine the CV in CW bias over a ~ 3-s time window (see Materials and Methods; this time resolution can in principle be improved further by pooling over a larger number of cells). In turn, studying cells as they undergo adaptation enables us to quantify network fluctuations across the accessible range of motor CW biases, as summarized in Fig. 5 . In Fig. 5 c the relationship between the CV and mean in CW bias provides a signature for the underlying E. coli chemotaxis signaling network noise, against which we can test various models. We thus sought a quantitative model to reproduce the noise characteristics we observed. The CW bias of every flagellar motor depends on the CheY-P concentration in an ultrasensitive switch-like manner (Fig. 1 b,ii) 25 , customarily modeled by a sigmoidal Hill equation of the form 5 \\documentclass[12pt]{minimal}\n\t\t\t\t\\usepackage{amsmath}\n\t\t\t\t\\usepackage{wasysym} \n\t\t\t\t\\usepackage{amsfonts} \n\t\t\t\t\\usepackage{amssymb} \n\t\t\t\t\\usepackage{amsbsy}\n\t\t\t\t\\usepackage{mathrsfs}\n\t\t\t\t\\usepackage{upgreek}\n\t\t\t\t\\setlength{\\oddsidemargin}{-69pt}\n\t\t\t\t\\begin{document}$$c(y_{P} ) = \\frac{{y_{P}^{H} }}{{y_{P}^{H} + K^{H} }},$$\\end{document} c ( y P ) = y P H y P H + K H , where y P ≡ [CheY-P], K is the CheY-P concentration at 0.5 CW bias, and H is the Hill coefficient. (For cells at steady state, K ≈ 3.1 μM and H is expected to be ~ 20 58 .) Due to this switch-like dependence, c is sensitive to small temporal fluctuations in [CheY-P]. CheY undergoes fast phosphorylation-dephosphorylation reactions (Fig. 1 a), which lead to number fluctuations in CheY-P (Fig. 1 b,i): 6 \\documentclass[12pt]{minimal}\n\t\t\t\t\\usepackage{amsmath}\n\t\t\t\t\\usepackage{wasysym} \n\t\t\t\t\\usepackage{amsfonts} \n\t\t\t\t\\usepackage{amssymb} \n\t\t\t\t\\usepackage{amsbsy}\n\t\t\t\t\\usepackage{mathrsfs}\n\t\t\t\t\\usepackage{upgreek}\n\t\t\t\t\\setlength{\\oddsidemargin}{-69pt}\n\t\t\t\t\\begin{document}$${\\text{CheY}}\\underset{{k_{z} }}{\\overset{{k_{A} a}}{\\rightleftharpoons}}{\\text{CheY - P}}{.}$$\\end{document} CheY ⇌ k A a k z CheY - P . Here, the rate of CheY phosphorylation by the CheA-receptor complex is written as k A a , where a is the probability that CheA is in its active state and k A is the maximum phosphorylation rate 59 , 60 , and k Z is the rate of CheY-P dephosphorylation by the phosphatase CheZ. The intracellular [CheY-P] fluctuates due in part to the stochastic nature of the reactions in Eq. ( 6 ) and in part to fluctuations in the CheA kinase activity a itself 31 , 41 . In SI Discussion , we examine how different sources of noise can reproduce the observed behavior in CW bias fluctuations. Simple models incorporating CheY-P number fluctuations through Eq. ( 6 ) do not recapitulate the experimental trends. The main issue is that these models predict that CW bias fluctuations should to tend to zero as c approaches 1. This behavior occurs because c ( y P ), in Eq. ( 5 ), exhibits a plateau when [CheY-P] > > K , making it insensitive to fluctuations in [CheY-P] when CW bias is close to unity. However, as our data in Fig. 5 c shows, σ c / µ c decreases to zero when CW bias = 0.5. Lele et al. 61 previously carried out experiments ruling out the possibility of a plateau in c vs [CheY-P] at intermediate CW bias levels. This finding suggests that CheY-P fluctuations themselves must be suppressed when c = 0.5. One possibility to account for this observation is that there exists a cap on the amount of CheY available for phosphorylation. For example, if such a cap limited the maximum CheY-P concentration to [CheY-P] ≈ K , then network fluctuations would be suppressed near a CW bias of 0.5 according to Eq. ( 5 ). To test this mechanism, we constructed a mutant ΔcheZ strain (“RB03”; see Materials and Methods) lacking the phosphatase CheZ, in which all the available CheY is expected to be phosphorylated. Replicating our flagellar imaging analysis for this strain resulted in a mean CW bias of 0.99 ± 0.01 (data not shown), higher than that observed following a step-down stimulus, ruling out such a mechanism. (The CV for this strain was 0.02; data not shown.) This result is consistent with estimates of the total concentration of CheY of ~ 10 μM > > K 55 . An alternative possibility is that there exists a kinetic ceiling on the CheA-receptor complex, which limits the amount of CheY that can be phosphorylated at any one time. Since CheY-P undergoes dephosphorylation in the reaction scheme Eq. ( 6 ), the fraction of CheY that is phosphorylated must be less than 1 even when CheA is maximally active. Such a ceiling in the maximum [CheY-P] would lead to a reduction in [CheY-P] fluctuations. To explore the latter mechanism quantitatively, we considered a comprehensive model taking into account fluctuations in CheY-P number and in the activity of the CheA-receptor complex during phosphorylation-dephosphorylation kinetics. To model CheA fluctuations, we allowed CheA to interconvert between active and inactive states, leading to a fluctuating activity a ( t ). Adapting the approach of Paulsson et al. 56 , 62 used to model gene expression noise, we derived an analytical solution for the coefficient of variation in [CheY-P] in the presence of CheA fluctuations (see SI Discussion ). Writing this expression in terms of CW bias gives 7 \\documentclass[12pt]{minimal}\n\t\t\t\t\\usepackage{amsmath}\n\t\t\t\t\\usepackage{wasysym} \n\t\t\t\t\\usepackage{amsfonts} \n\t\t\t\t\\usepackage{amssymb} \n\t\t\t\t\\usepackage{amsbsy}\n\t\t\t\t\\usepackage{mathrsfs}\n\t\t\t\t\\usepackage{upgreek}\n\t\t\t\t\\setlength{\\oddsidemargin}{-69pt}\n\t\t\t\t\\begin{document}$$\\frac{{\\sigma_{c} }}{{\\mu_{c} }} = H(1 - c)\\sqrt {\\frac{{\\tau_{Y} }}{{\\tau_{Y} + \\tau_{c} }}\\frac{1}{{\\mu_{{y_{P} }} V_{C} }}\\left( {1 - \\frac{{\\mu_{{y_{P} }} }}{{y_{tot} }}} \\right)\\left[ {1 + \\left\\langle b \\right\\rangle \\left( {1 - \\frac{{\\mu_{{y_{P} }} }}{{\\alpha y_{tot} }}} \\right)} \\right]} .$$\\end{document} σ c μ c = H ( 1 - c ) τ Y τ Y + τ c 1 μ y P V C 1 - μ y P y tot 1 + b 1 - μ y P α y tot . The appearance of the Hill coefficient H in Eq. ( 7 ) follows from the coupling of CheY-P fluctuations to those in CW bias c in Eq. ( 5 ). Here, τ c is the characteristic timescale for motor switching and \\documentclass[12pt]{minimal}\n\t\t\t\t\\usepackage{amsmath}\n\t\t\t\t\\usepackage{wasysym} \n\t\t\t\t\\usepackage{amsfonts} \n\t\t\t\t\\usepackage{amssymb} \n\t\t\t\t\\usepackage{amsbsy}\n\t\t\t\t\\usepackage{mathrsfs}\n\t\t\t\t\\usepackage{upgreek}\n\t\t\t\t\\setlength{\\oddsidemargin}{-69pt}\n\t\t\t\t\\begin{document}$$\\tau_{Y} = (k_{A} a + k_{Z} )^{ - 1}$$\\end{document} τ Y = ( k A a + k Z ) - 1 is that for CheY phosphorylation-dephosphorylation; the factor that depends on τ c and τ y accounts for temporal averaging that results from the different fluctuation timescales for motor switching and CheY reactions. The other factors inside the square root represent the number fluctuations in CheY-P; y tot ≈ 10 μM is the total CheY concentration inside the cell, and V C is the E. coli cell volume, assumed to be 1.4 fL 63 ( \\documentclass[12pt]{minimal}\n\t\t\t\t\\usepackage{amsmath}\n\t\t\t\t\\usepackage{wasysym} \n\t\t\t\t\\usepackage{amsfonts} \n\t\t\t\t\\usepackage{amssymb} \n\t\t\t\t\\usepackage{amsbsy}\n\t\t\t\t\\usepackage{mathrsfs}\n\t\t\t\t\\usepackage{upgreek}\n\t\t\t\t\\setlength{\\oddsidemargin}{-69pt}\n\t\t\t\t\\begin{document}$$V_{C}^{ - 1} \\approx$$\\end{document} V C - 1 ≈ 1.2 nM). The factor in brackets specifically represents the contribution from CheA activity fluctuations. Here \\documentclass[12pt]{minimal}\n\t\t\t\t\\usepackage{amsmath}\n\t\t\t\t\\usepackage{wasysym} \n\t\t\t\t\\usepackage{amsfonts} \n\t\t\t\t\\usepackage{amssymb} \n\t\t\t\t\\usepackage{amsbsy}\n\t\t\t\t\\usepackage{mathrsfs}\n\t\t\t\t\\usepackage{upgreek}\n\t\t\t\t\\setlength{\\oddsidemargin}{-69pt}\n\t\t\t\t\\begin{document}$$\\left\\langle b \\right\\rangle$$\\end{document} b denotes the number of new CheY-P generated during the time periods when CheA is active. The factor \\documentclass[12pt]{minimal}\n\t\t\t\t\\usepackage{amsmath}\n\t\t\t\t\\usepackage{wasysym} \n\t\t\t\t\\usepackage{amsfonts} \n\t\t\t\t\\usepackage{amssymb} \n\t\t\t\t\\usepackage{amsbsy}\n\t\t\t\t\\usepackage{mathrsfs}\n\t\t\t\t\\usepackage{upgreek}\n\t\t\t\t\\setlength{\\oddsidemargin}{-69pt}\n\t\t\t\t\\begin{document}$$\\alpha \\equiv k_{A} /(k_{A} + k_{Z} )$$\\end{document} α ≡ k A / ( k A + k Z ) is the fraction of CheY phosphorylated when all CheA are active, i.e. when the activity a = 1. This model recapitulates the features of the data well. Figure 5 c shows a fit to Eq. ( 7 ) (dotted line) with parameters \\documentclass[12pt]{minimal}\n\t\t\t\t\\usepackage{amsmath}\n\t\t\t\t\\usepackage{wasysym} \n\t\t\t\t\\usepackage{amsfonts} \n\t\t\t\t\\usepackage{amssymb} \n\t\t\t\t\\usepackage{amsbsy}\n\t\t\t\t\\usepackage{mathrsfs}\n\t\t\t\t\\usepackage{upgreek}\n\t\t\t\t\\setlength{\\oddsidemargin}{-69pt}\n\t\t\t\t\\begin{document}$$\\left\\langle b \\right\\rangle$$\\end{document} b = (6 ± 1) × 10 2 and \\documentclass[12pt]{minimal}\n\t\t\t\t\\usepackage{amsmath}\n\t\t\t\t\\usepackage{wasysym} \n\t\t\t\t\\usepackage{amsfonts} \n\t\t\t\t\\usepackage{amssymb} \n\t\t\t\t\\usepackage{amsbsy}\n\t\t\t\t\\usepackage{mathrsfs}\n\t\t\t\t\\usepackage{upgreek}\n\t\t\t\t\\setlength{\\oddsidemargin}{-69pt}\n\t\t\t\t\\begin{document}$$\\alpha$$\\end{document} α = 0.32 ± 0.02 ( R 2 = 0.65; errors represent 95% confidence interval). Analogous to “burst size” in stochastic gene expression 64 , 65 , \\documentclass[12pt]{minimal}\n\t\t\t\t\\usepackage{amsmath}\n\t\t\t\t\\usepackage{wasysym} \n\t\t\t\t\\usepackage{amsfonts} \n\t\t\t\t\\usepackage{amssymb} \n\t\t\t\t\\usepackage{amsbsy}\n\t\t\t\t\\usepackage{mathrsfs}\n\t\t\t\t\\usepackage{upgreek}\n\t\t\t\t\\setlength{\\oddsidemargin}{-69pt}\n\t\t\t\t\\begin{document}$$\\left\\langle b \\right\\rangle$$\\end{document} b increases number fluctuations in CheY-P, which are intrinsically low due to the high CheY copy number (see SI Discussion ). The parameter \\documentclass[12pt]{minimal}\n\t\t\t\t\\usepackage{amsmath}\n\t\t\t\t\\usepackage{wasysym} \n\t\t\t\t\\usepackage{amsfonts} \n\t\t\t\t\\usepackage{amssymb} \n\t\t\t\t\\usepackage{amsbsy}\n\t\t\t\t\\usepackage{mathrsfs}\n\t\t\t\t\\usepackage{upgreek}\n\t\t\t\t\\setlength{\\oddsidemargin}{-69pt}\n\t\t\t\t\\begin{document}$$\\alpha$$\\end{document} α represents the fact that the contribution of CheA fluctuations to CheY-P noise must go to zero (as in Fig. 5 c) when a = 1, which corresponds to a mean CW bias of ~ 0.5. (We note that the noise suppression previously mentioned by Colin et al. 41 occurs in the opposite limit of a = 0.) The value of \\documentclass[12pt]{minimal}\n\t\t\t\t\\usepackage{amsmath}\n\t\t\t\t\\usepackage{wasysym} \n\t\t\t\t\\usepackage{amsfonts} \n\t\t\t\t\\usepackage{amssymb} \n\t\t\t\t\\usepackage{amsbsy}\n\t\t\t\t\\usepackage{mathrsfs}\n\t\t\t\t\\usepackage{upgreek}\n\t\t\t\t\\setlength{\\oddsidemargin}{-69pt}\n\t\t\t\t\\begin{document}$$\\alpha$$\\end{document} α points to a kinetic ceiling on CheA-receptor complexes of k A = 0.47 k Z , or ~ 14 s −1 assuming a constant CheY-P dephosphorylation rate of k Z = 30 s −1 , within the reported range 54 , 59 , 60 . A maximum rate k A = 14 s −1 is consistent with reported values of the CheA auto-phosphorylation rate, the rate-limiting step for CheY phosphorylation 33 , 54 , 59 , 60 . (We note that in the ΔcheZ strain, the kinetic ceiling on k A would not cap [CheY-P] since k Z = 0). Our observations suggest that network fluctuations are critical drivers for CW flagellar rotation/tumbling in E. coli . Previous studies 36 , 42 , 66 proposed that waves of CheA activity could cause transient increases in [CheY-P]. Our data and model appear to be consistent with this mechanism, with the “burst size” \\documentclass[12pt]{minimal}\n\t\t\t\t\\usepackage{amsmath}\n\t\t\t\t\\usepackage{wasysym} \n\t\t\t\t\\usepackage{amsfonts} \n\t\t\t\t\\usepackage{amssymb} \n\t\t\t\t\\usepackage{amsbsy}\n\t\t\t\t\\usepackage{mathrsfs}\n\t\t\t\t\\usepackage{upgreek}\n\t\t\t\t\\setlength{\\oddsidemargin}{-69pt}\n\t\t\t\t\\begin{document}$$\\left\\langle b \\right\\rangle$$\\end{document} b in Eq. ( 7 ) representing such waves in activity (see Fig. 5 d for a schematic depiction). Our fit parameters suggest that several hundred CheY molecules are phosphorylated during such events, a not-insignificant fraction of the total number, estimated to be ~ 8000 55 . We envision that transient increases in [CheY-P], driven by waves of phosphorylation by the receptor kinase complex 36 , increases the CW bias to generate tumbles. However, the amount of cellular [CheY-P] is subject to the constraints of CheA phosphorylation kinetics. When the cell experiences a network activating stimulus, and the receptor kinase complex is pushed to its maximum activity, the cellular [CheY-P] reaches its upper limit. This is manifested as high CW bias and suppressed fluctuations in CW bias. Previous single-cell measurements of flagellar rotation by bead tracking 31 , 39 and of CheA activity using fluorescent reporters 40 , 41 have reported long-term noise in the chemotaxis network. This has largely been attributed to CheR-CheB methylation-demethylation dynamics 31 , 67 and, recently, to new sources such as receptor clustering and other dynamics 40 , 41 , 66 . A direct comparison between these results and ours is difficult because of the differences in timescales between the measurements (3–40 s vs. 10–1000 s). Notably, burst-like noise similar to what we observe 36 , 42 has been attributed to cooperative receptor state switching 66 . While our approach aligns with other recent work that extends noise measurements to fast timescales of the order of run and tumble durations, photobleaching of the dyes limits the duration of our traces and limits the overlap between the measurement timescales. For this reason, we have deliberately made our model for CheA activity fluctuations in Eq. ( 7 ) agnostic to the source of noise to allow for various possibilities. (We nevertheless note that the general form for CheA activity noise is similar to that used by Colin et al. 41 ; see SI Discussion for more details). The noise characteristics of the chemotaxis network revealed in our measurements may have several functional consequences. First, network fluctuations may act to synchronize flagellar switching 36 , 37 , 42 , 66 , which was shown to make swimming behavior robust to variation in flagella number 37 . E. coli has also been proposed to exploit long-timescale network fluctuations to explore larger volumes of space 31 , 32 and to increase drift speeds, enhancing migration along increasing attractant gradients 33 – 35 . In addition, our observation of a mean CW bias well below the midpoint of the c vs CheY-P curve at steady state is consistent with theory and simulations 45 predicting that cells’ drift velocity along chemical gradients is maximized at low CW bias 47 , an idea supported by recent experiments 46 . Lastly, the kinetic ceiling in receptor kinase activity which restricts network fluctuations when the mean [CheY-P] increases (as depicted in Fig. 5 d) may prevent CheY-P concentrations from saturating and leading to continuous and unproductive CW flagellar rotation/tumbling. Such behavior could result in increased E. coli swimming efficiency down steep decreases in attractant concentration, as likely found in natural environments. These findings point to network fluctuations tuned to maximize chemotactic drift."
} | 6,181 |
30091100 | null | s2 | 9,054 | {
"abstract": "Cyanobacteria are attractive hosts for converting carbon dioxide and sunlight into desirable chemical products. To engineer these organisms and manipulate their metabolic pathways, the biotechnology community has developed genetic tools to control gene expression. Many native cyanobacterial promoters and related sequence elements have been used to regulate genes of interest, and heterologous tools that use non-native small molecules to induce gene expression have been demonstrated. Overall, IPTG-based induction systems seem to be leaky and initially demonstrate small dynamic ranges in cyanobacteria. Consequently, a variety of other induction systems have been optimized to enable tighter control of gene expression. Tools require significant optimization because they function quite differently in cyanobacteria when compared to analogous use in model heterotrophs. We hypothesize that these differences are due to fundamental differences in physiology between organisms. This review is not intended to summarize all known products made in cyanobacteria nor the performance (titer, rate, yield) of individual strains, but instead will focus on the genetic tools and the inherent aspects of cellular physiology that influence gene expression in cyanobacteria."
} | 316 |
26484219 | PMC4583624 | pmc | 9,055 | {
"abstract": "An actinobacterial strain, designated SO9-6, was isolated from a copper iron sulfide mineral. The organism is Gram-positive, facultatively anaerobic, and coccoid. Chemotaxonomic and phylogenetic properties were consistent with its classification in the genus Kocuria . Here, we report the first draft genome sequence of Kocuria marina SO9-6 under accession JROM00000000 ( http://www.ncbi.nlm.nih.gov/nuccore/725823918 ), which provides insights for heavy metal bioremediation and production of compounds of biotechnological interest."
} | 134 |
36909291 | PMC9995654 | pmc | 9,057 | {
"abstract": "Abstract Excitable optoelectronic devices represent one of the key building blocks for implementation of artificial spiking neurons in neuromorphic (brain-inspired) photonic systems. This work introduces and experimentally investigates an opto-electro-optical (O/E/O) artificial neuron built with a resonant tunnelling diode (RTD) coupled to a photodetector as a receiver and a vertical cavity surface emitting laser as a transmitter. We demonstrate a well-defined excitability threshold, above which the neuron produces optical spiking responses with characteristic neural-like refractory period. We utilise its fan-in capability to perform in-device coincidence detection (logical AND) and exclusive logical OR (XOR) tasks. These results provide first experimental validation of deterministic triggering and tasks in an RTD-based spiking optoelectronic neuron with both input and output optical (I/O) terminals. Furthermore, we also investigate in simulation the prospects of the proposed system for nanophotonic implementation in a monolithic design combining a nanoscale RTD element and a nanolaser; therefore demonstrating the potential of integrated RTD-based excitable nodes for low footprint, high-speed optoelectronic spiking neurons in future neuromorphic photonic hardware.",
"conclusion": "6 Conclusions This work demonstrates experimentally a RTD-based optoelectronic circuit operating as an excitable, spiking artificial neuron, benefiting from optical I/O ports, allowing its use in prospective optically interlinked spiking photonic neural networks. The system, referred to as PRL node, combines in its layout a micrometric InGaAs/AlAs RTD element with high PVCR \n ≈ 8.5 \n coupled to a photodetector and a telecom-wavelength VCSEL, providing respectively the optical input and output of the PRL node. We have demonstrated how such system allows for multiple optical pulsating (spiking) input signals (here n = 2) to be summed up on the photodetector of the node in a wavelength-independent manner, allowing for additional robustness in operation and lower demands on coherence and precise wavelength selection in future interconnected systems based upon interlinked PRL nodes. We have also shown the presence of a well-defined excitability threshold in the system, and a spiking refractory period of T \n \n ref \n ≈ 90 ns in the proof-of-concept system realisation of this work. This allows already, without any additional system optimisation stage, a reliable activation of all-or-nothing spiking responses at up to 10 MHz rates. By further optimization of RTD’s electronic circuit and by progressing towards monolithically-integrated structures with highly reduced dimensions, we believe the operation speed can be significantly increased. We validate this claim numerically, showing that the experimentally achieved spiking functionalities can be also obtained with a nanoscale RTD-based O/E/O system at GHz rates. Finally, we have successfully demonstrated spike-based processing tasks with the proposed PRL node, including a coincidence detection (logical AND) as well as an exclusive OR (XOR) task using an additional pre-processing network layer. These results provide the first investigation and proof-of-concept demonstration of an O/E/O RTD-based, deterministically activated spiking photonic neuron. Future research will focus on system optimisation towards faster spiking rates reaching GHz speeds, as well as on the development of improved RTD devices with embedded optical windows to allow direct photodetection in the RTD structure; thus permitting to eliminate the currently used externally-coupled PD module. Additionally, we will focus on experimental validation of signal propagation between master-receiver PRL nodes, ultimately aiming towards photonic spiking neural networks powered by artificial excitable optoelectronic neurons.",
"introduction": "1 Introduction Artificial Intelligence (AI) and Machine Learning (ML) algorithms nowadays power a wide range of advanced computational tasks, ranging from natural language processing and realistic image synthesis [ 1 ] to solutions solving major challenges such as protein folding [ 2 ]. As a general principle, higher computational capability of AI models goes hand in hand with their scale. Hence, further growth in the size of these models is expected as new, more complex tasks are being explored. This can be observed in current models such as GPT-3, whose 175 billion parameters [ 3 ] represent over an order of magnitude increase in the number of parameters when compared to its previous iteration. With the growth of scale and increase in resource and requirements of these AI models, the chips on which those algorithms run come more into the spotlight, fuelling the search for alternative, AI-optimised hardware. In particular, approaches beyond the conventional Von-Neumann architecture of digital processors (with distinct memory and logic units) are receiving increasing interest. These alternative computing schemes offer the promise of relieving the stalling chip performance improvements due to CMOS downscaling bottlenecks and architecture limitations. Neuromorphic (brain-inspired) engineering is a prime example of such unconventional computing approach. Neuromorphic computing systems attempt to harness the vast computational capabilities and power efficiency of the brain by mimicking and abstracting its architecture. These systems rely on high degree of parallelism and concepts such as event-based, asynchronous computation and in-memory computing. Driven both by their utility in the fields of AI and computational neuroscience, neuromorphic computers are being developed by both academic [ 4 , 5 ] and industrial parties [ 6 , 7 ] in a variety of technology platforms. In particular, neuromorphic realisations based on photonics offer some highly desirable benefits. The use of light allows for high bandwidth and low-loss, wavelength-division multiplexed (WDM) communication schemes without unwanted inductive crosstalk and resistive heating in wires, while advances in the field of photonic integrated circuits (PICs) allow for high-density chip integration. The field is currently ongoing rapid expansion, with many different classes of photonic devices being investigated for brain-inspired computing and AI acceleration. These include quantum-dot lasers [ 8 , 9 ], superconducting nanowires [ 10 , 11 ], integrated photonic components including modulators [ 12 – 14 ], semiconductor optical amplifiers [ 15 , 16 ], micro-rings [ 17 – 19 ], phase change material-based PICs [ 20 , 21 ] as well as vertical cavity surface emitting lasers (VCSELs) subject to injection locking [ 22 – 24 ] or with saturable absorber sections [ 25 – 29 ]. Furthermore, VCSELs have been previously demonstrated as a viable technology for spike-based optical computing by utilising their high speed spiking dynamics for tasks such as all-optical convolution [ 30 ], pattern classification [ 31 ] or rate-coded encoding of image data [ 32 ]. Simultaneously, a recent study has demonstrated VCSELs suitability for integration into arrays [ 33 ], which is crucial for realisation of larger-scale on-chip integrated circuits. In this work, we introduce a modular, excitable, optoelectronic spiking neuron based on a resonant tunnelling diode (RTD) electrically coupled to a PD (Thorlabs PDA8GS) serving as a receiver, and to a telecom-wavelength, fiber pigtailed VCSEL serving as a transmitter, together realising an O/E/O system. RTDs are a class of semiconductor devices that typically employ a double barrier quantum well (DBQW) semiconductor heterostructure, allowing for ultrafast quantum tunnelling through the resonant states of the well. This sets RTD-based oscillators among the fastest semiconductor devices operating at room temperature, with currently highest achieved frequency reaching 2 THz [ 34 ]. RTDs exhibit a highly nonlinear, N -shaped I – V with a negative differential conductance (NDC) region, which introduces gain and nonlinear dynamical responses. RTDs have been successfully employed for photodetection with very high sensitivity [ 35 , 36 ], as receiver systems [ 37 ], for small-scale THz imaging [ 38 ] and in circuits for high-speed data transmission [ 39 , 40 ]. RTD-based oscillator circuits can also exhibit excitability, yielding these devices as highly-promising elements for use in novel brain-inspired computing paradigms [ 41 ] and in so-called cellular neural networks [ 42 , 43 ]. Previous works have demonstrated spike-shaped oscillations [ 44 ] and neuron-like, excitable stochastic (noise-driven) spiking in systems of RTDs connected to either a laser diode (RTD-LD) [ 41 ] or a photodetector (RTD-PD) and using electrical noise or modulated optical input [ 45 ]. A signal-regenerating spiking memory cell with an optoelectronic RTD circuit has also been reported [ 46 ] as well as optically induced stochastic resonance effects [ 47 ]. Recently, nanoscale RTD-based LEDs [ 48 ] have been proposed as a viable solution for low-power, high-speed and low footprint optical spiking nodes. A detailed numerical analysis on the temporal characteristics and delays in the propagation of spiking signals in nanoscale RTD-based optoelectronic neurons (using RTD-LD to PD-RTD interlinked systems) can be found in [ 49 ]. Furthermore, a numerical study of a feed-forward spiking neural network based on RTD-LD/PD master-receiver nodes with spatiotemporal spike pattern detection and information processing functionality was recently proposed in [ 50 ]. In Section 2 , we introduce the layout of the studied RTD-based optoelectronic node and the experimental setup. While previous studies focused on stochastic, noise-induced spiking [ 45 ], our layout enables deterministic, user controlled, optically induced spike triggering of the RTD-based photonic neuron, which is key for practical information processing. Furthermore, our photonic neuron combines for the first time an RTD coupled to a telecom-wavelength operating VCSEL, both systems with proven track record and recognised potential for use in optical neuromorphic systems. In Section 3 , we evaluate the excitable responses of the system, including its well-defined spiking threshold and refractory (lethargy) period. In Section 4 , we demonstrate in-device coincidence detection (logical AND) and exclusive logical OR (XOR) tasks, two of the key functionalities for practical operation in networked arrangements. Finally, in Section 5 , we provide future outlook of a nanoscale RTD artificial photonic neuron based on a monolithic design and demonstrate the coincidence detection task in such low footprint, high speed system."
} | 2,673 |
37646003 | PMC10462140 | pmc | 9,058 | {
"abstract": "Human activity is altering the environment in a rapid pace, challenging the adaptive capacities of genetic variation within animal populations. Animals also harbor extensive gut microbiomes, which play diverse roles in host health and fitness and may help expanding host capabilities. The unprecedented scale of human usage of xenobiotics and contamination with environmental toxins describes one challenge against which bacteria with their immense biochemical diversity would be useful, by increasing detoxification capacities. To explore the potential of bacteria-assisted rapid adaptation, we used Caenorhabditis elegans worms harboring a defined microbiome, and neomycin as a model toxin, harmful for the worm host and neutralized to different extents by some microbiome members. Worms raised in the presence of neomycin showed delayed development and decreased survival but were protected when colonized by neomycin-resistant members of the microbiome. Two distinct mechanisms facilitated this protection: gut enrichment driven by altered bacterial competition for the strain best capable of modifying neomycin; and host avoidance behavior, which depended on the conserved JNK homolog KGB-1, enabling preference and acquisition of neomycin-protective bacteria. We further tested the consequences of adaptation, considering that enrichment for protective strains may represent dysbiosis. We found that neomycin-adapted gut microbiomes caused increased susceptibility to infection as well as an increase in gut lipid storage, suggesting metabolic remodeling. Our proof-of-concept experiments support the feasibility of bacteria-assisted host adaptation and suggest that it may be prevalent. The results also highlight trade-offs between toxin adaptation and other traits of fitness.",
"discussion": "Discussion Using neomycin as a convenient model for environmental toxins - toxic to the C. elegans host and effectively altering the gut microbiome, our results demonstrate that the gut microbiome can provide protection from toxicity. In the context of a full community, protection was conferred by the most resistant member of the community, a Stenotrophomonas indicatrix strain, which persisted in the affected worm gut and took over the gut microbiome. In addition, exposed worms sought relief from the toxin, driven by avoidance behavior that depended on the stress-activated JNK homolog gene kgb-1, and that when given a choice resulted in preference for protective bacteria. Thus, two distinct mechanisms converge to facilitate colonization by protective bacteria. In this toxin-adapted microbiome, the enrichment for neo-resistant strains (primarily Stenotrophomonas ) described a significant deviation from the baseline gut microbiome composition, representing dysbiosis. The effects of this dysbiosis on host fitness were limited, leaving development rate, fecundity and lifespan largely unaffected. However, it did increase the susceptibility of hosts to the pathogen Pseudomonas aeruginosa , driven by loss of pathogen-protective but neomycin-sensitive strains, and further altered metabolism leading to increased lipid storage. Our results demonstrate the feasibility of microbiome-dependent host adaptation to environmental toxins. They further demonstrate that this adaptation could be facilitated through more than one mechanism, either in bacteria or in the host, and that the mechanisms involved are of general purpose - interbacterial competition and avoidance of harmful environments, together increasing the likelihood that adaptation will occur. Our results focus on adaptation to an environmental toxin, but similar mechanisms could give rise to adaptation to other types of environmental stress. At the same time, our results highlight the trade-off that may take place between short-term adaptation to the toxin and other adaptive traits, some of which with potential long-term consequences. While bacterial environmental availability can be affected by neomycin toxicity, environmental availability of the protective strain was not the main factor responsible for gut microbiome enrichment with Stenotrophomonas , as this occurred also in worms first colonized by CeMbio members and only subsequently exposed to the toxin. The increased bacterial load observed in the toxin-adapted worms is in line with a release from competition and suggests that the mechanism through which Stenotrophomonas becomes enriched is decreased competition or competitive exclusion of less-resistant gut bacteria. While previous studies of the bean bug adaptation to pesticide linked host resistance to acquisition of environmentally-enriched protective bacteria 16 , our results demonstrate that when biochemical capabilities pre-exist in the gut microbiome, toxin-induced stress could be sufficient for microbiome remodeling and host adaptation, independent of environmental availability. The choice of neomycin as the model toxin and concentrations selected for testing was to ensure microbiome changes in a community with somewhat limited diversity and to ensure observable effects on hosts. In the environment, antibiotic concentrations are usually far lower than those used here 33 , 34 . Nevertheless, there are examples of antibiotics, specifically aminoglycosides, used in the environment in concentrations as high as those we used 35 . Thus, the mechanisms that we identified as taking part in worm adaptation to neomycin might play similar roles in natural contexts. These mechanisms are of general purpose. On the bacterial side, aminoglycoside modifying enzymes are common among bacteria, including in the human gut 36 – 39 . On the host side, the C. elegans stress-activated MAP kinase KGB-1, a JNK homolog, is a conserved protein involved in diverse stress responses as well as in behavioral modulation 40 – 42 . Together, such mechanisms could facilitate bacteria-assisted adaptation to toxic antibiotics in nematodes in the wild, as well as in other animals. Adaptation to other toxins may rely on different bacterial toxin-modifying enzymes but could be similarly feasible. And when appropriate enzymes are not as common as those involved in antibiotic resistance, environmental exposure to the toxin could significantly increase availability of bacteria expressing the appropriate enzyme, as found for the pesticide-resistance bean bug discussed earlier 16 . While remodeling of the worm gut microbiome provided relief from neomycin toxicity, some trade-offs were observed, i.e. increased lipid storage and susceptibility to infection. Maintaining gut microbiome composition within certain boundaries (still ill-defined) is essential for maintaining gut homeostasis 43 . Deviations, often observed upon disruption of immune signaling, lead to dysbiosis and pathology 22 , 44 , 45 . The Stenotrophomonas enrichment in neomycin-affected worms represents a significant deviation from the typical composition of the gut microbiome assembled from CeMbio and is sufficient to cause the observed increase in lipid storage, even without neomycin exposure. A previous study reported higher lipid storage upon worm infection with the opportunistic pathogen Stenotrophomonas maltophilia 46 . However, our results with the non-pathogenic P. indicatrix suggest that metabolic remodeling might be distinct from the pathogenicity of S. maltophilia , and potentially associated with other interactions between C. elegans and members of the Stenotrophomonas genus. Host metabolism seems to be sensitive to changes in microbiome composition 47 . The effects of Stenotrophomonas enrichment are but one example, but added to previous reports of gut-dysbiosis-induced metabolic remodeling, i.e. metabolic syndrome and obesity 44 , 48 , it may suggest that metabolic remodeling might be a common consequence of microbiome-assisted adaptation to toxins. The results presented here support the notion that microbiome-assisted host adaptation to environmental toxins is straightforward, can be achieved through distinct routes and as a consequence, is probably more prevalent than currently appreciated. Increases in the spread of environmental toxins are only one facet of global change, perhaps representing a change in which bacteria are particularly likely to play a role. However, gut bacteria could contribute to any aspect of ecological adaptation. The microbiome was previously proposed as a potential source for adaptive novelty 49 . It seems that helping hosts adapt to a changing environment may be one such contribution. It might be happening all around us, and may further be a yet unaccounted cause of health issues stemming from trade-offs with such adaptation."
} | 2,170 |
36339794 | null | s2 | 9,059 | {
"abstract": "Neurons in the brain are complex machines with distinct functional compartments that interact nonlinearly. In contrast, neurons in artificial neural networks abstract away this complexity, typically down to a scalar activation function of a weighted sum of inputs. Here we emulate more biologically realistic neurons by learning canonical activation functions with two input arguments, analogous to basal and apical dendrites. We use a network-in-network architecture where each neuron is modeled as a multilayer perceptron with two inputs and a single output. This inner perceptron is shared by all units in the outer network. Remarkably, the resultant nonlinearities often produce soft XOR functions, consistent with recent experimental observations about interactions between inputs in human cortical neurons. When hyperparameters are optimized, networks with these nonlinearities learn faster and perform better than conventional ReLU nonlinearities with matched parameter counts, and they are more robust to natural and adversarial perturbations."
} | 262 |
37234932 | PMC10206485 | pmc | 9,060 | {
"abstract": "Microbial tolerance to toxic compounds formed during biomass pretreatment is a significant challenge to produce bio-based products from lignocellulose cost effectively. Rational engineering can be problematic due to insufficient prerequisite knowledge of tolerance mechanisms. Therefore, adaptive laboratory evolution was applied to obtain 20 tolerant lineages of Bacillus subtilis strains able to utilize Distiller's Dried Grains with Solubles-derived (DDGS) hydrolysate. Evolved strains showed both improved growth performance and retained heterologous enzyme production using 100% hydrolysate-based medium, whereas growth of the starting strains was essentially absent. Whole-genome resequencing revealed that evolved isolates acquired mutations in the global regulator c odY in 15 of the 19 sequenced isolates. Furthermore, mutations in genes related to oxidative stress ( katA , perR ) and flagella function appeared in both tolerance and control evolution experiments without toxic compounds. Overall, tolerance adaptive laboratory evolution yielded strains able to utilize DDGS-hydrolysate to produce enzymes and hence proved to be a valuable tool for the valorization of lignocellulose.",
"conclusion": "4 Conclusions This study demonstrated that TALE could efficiently be applied to obtain B. subtilis strains with increased tolerance to biomass hydrolysate-associated inhibitory compounds. Production experiments showed that evolved isolates did not only show improved growth performance, but were also able to produce protein. Whole-genome resequencing of independently evolved isolates revealed codY is likely related to the improved tolerance, while katA and loss of flagella functions are expected to be associated to the employed cultivation conditions. As B. subtilis is a well-known industrial chassis organism, the obtained results are relevant for the use of lignocellulose for the manufacturing of bio-based products.",
"introduction": "1 Introduction As governments and organizations around the globe have committed to comply with ambitious climate goals, the production of Dried Distillers Grains with Solubles (DDGS) is expected to rise in the coming years ( IEA, 2021 ; RFA, 2020 ; Shukla et al., 2022 ). Being a major by-product of the bioethanol industry, the selling of DDGS as animal feed is of vital importance to the economic viability of the bioethanol industry ( Chatzifragkou and Charalampopoulos, 2018 ). However, as the animal feed market is expected to be saturated, there is a growing need for first generation bioethanol plants to convert DDGS into alternative high value products to diversify their outputs and secure the profitability of their assets ( Beri et al., 2020 ; Chatzifragkou and Charalampopoulos, 2018 ). In recent years, there has been an increased focus on the use of DDGS as a potential substrate for microbial fermentation to generate value to the bioethanol production process. The rich nutritional composition of DDGS in terms of carbon, nitrogen, and other micronutrients is expected to be an ideal starting point for the bio-manufacturing of a variety of products, including organic acids, biofuels, and hydrolytic enzymes ( Iram et al., 2020 ). While DDGS contains a considerable amount of carbohydrates, pretreatment of DDGS is required to fractionate and hydrolyze the lignocellulosic fibers to release the fermentable sugars. A multitude of chemical, physical, and biological pretreatment methods and conditions are described in literature ( Iram et al., 2020 ). Often, biomass pretreatment involves the undesirable formation of lignocellulose-derived by-products, which have negative effects on fermentation and lead to a decrease in overall sugar yield. These inhibitory compounds include, amongst others, furan derivatives, organic acids, and phenolic compounds ( van der Pol et al., 2016 ). Detoxification of lignocellulosic hydrolysate is possible, but leads to increased costs and concomitant loss of sugars. The development of microbial strains with increased tolerance has the potential to minimize the degree of detoxification required. Unfortunately, tolerance is a complex trait, involving the coordinated action of hundreds of genes ( Lastiri-Pancardo and Utrilla, 2017 ). As biomass hydrolysates contain a plethora of different toxic compounds, rational design is challenging due to the lack of prerequisite knowledge. Even if the exact tolerance mechanism can be rationally engineered, it can be challenging to fine-tune the expression of the genes involved to deliver the desired phenotype ( Sandberg et al., 2019 ). In contrast, tolerance adaptive laboratory evolution (TALE) enables strain optimization without a priori knowledge about the genetic changes necessary to increase tolerance towards hydrolysate-associated inhibitory compounds. By serial passaging of cells in conditions with increasing selective pressure, one can select cells, which have acquired beneficial mutations for the chosen environment. The recent development of using of automated liquid handler systems allow crucial dynamic control of the applied stress during the experiment to maintain a strong selection pressure, while not crashing the cultures ( Sandberg et al., 2019 ). In this study, TALE was applied as a tool to generate Bacillus subtilis strains with improved tolerance towards the toxic compounds present in DDGS-hydrolysate. B. subtilis (and other closely related species like Bacillus licheniformis ) is recognized as one of the work horses in both industrial biotechnology and academia, due to its robustness in industrial fermentations, well-defined endogenous metabolism, distinct genetic background combined with established and emerging genetic manipulation tools, and GRAS-status (generally recognized as safe) ( Liu et al., 2013 ). However, previous work has shown that B. subtilis is severely inhibited by compounds commonly present in biomass hydrolysate ( van der Maas et al., 2021 ). Although ALE has been used to obtain tolerant strains for species like Saccharomyces cerevisiae , Escherichia coli , Clostridium thermocellum and Corynebacterium glutamicum , this method has scarcely been applied to yield B. subtilis strains tolerant towards hydrolysate-associated inhibitory compounds ( Almario et al., 2013 ; Linville et al., 2013 ; Qin et al., 2016 ; Wang et al., 2018 ). Prior to the TALE experiment, steam explosion pretreatment and enzymatic hydrolysis of the DDGS biomass were performed to produce the DDGS-hydrolysate. Subsequently, the inhibitory effect of compounds present in the pretreated hydrolysate medium was assessed. The TALE experiments were executed with four independent clonal biological replicates for each of the five starting strains. To select the best performing evolved strains a growth screening and a subsequent protein production screening were performed. Lastly, whole-genome-sequencing data of selected evolved isolates were compared and key mutations related to the improved phenotypes were identified.",
"discussion": "3 Results and discussion Industrial-scale manufacturing of bio-based products and energy by microbial cell factories using lignocellulose will play an important role to realize the global sustainability agenda ( IEA, 2021 ; Noorman and Heijnen, 2017 ; Shukla et al., 2022 ). However, the use of lignocellulose as a fermentation feedstock is currently hampered by toxic compounds that are released during the biomass pretreatment process. Consequently, the development of microbial strains with increased tolerance towards these toxic compounds is indispensable to realize second-generation bio-manufacturing processes. 3.1 DDGS-based hydrolysate Steam explosion is one of the most widely studied pretreatment strategies in both lab-scale and different pilot plants, and is considered a cost-effective method near commercialization ( Galbe and Wallberg, 2019 ). As it is an established method, steam explosion pretreatment and a subsequent enzymatic hydrolysis were applied to valorize the DDGS biomass used in this study. The obtained DDGS-based hydrolysate contained sugars, protein, and inhibitory compounds, including furan derivatives, organic acid, and phenolic compounds ( Table 2 ). While the presence of both sugars and protein makes DDGS an appealing starting point for microbial fermentation, the formation of toxic by-products poses a well-known hurdle for B. subtilis that needs to be overcome ( Iram et al., 2020 ; van der Maas et al., 2021 ). Table 2 Composition of hydrolysate-based medium. Table 2 Compound Concentration (g L −1 ) Glucose 29.1 ± 1.83 a Xylose 9.9 ± 0.67 a Arabinose 5.1 ± 0.33 a Protein 10.5 ± 0.56** 5-HMF 0.3 ± 0.01** Furfural 0.9 ± 0.10** Acetic acid 2.0 ± 0.44** Phenolic compounds 3.3 ± 0.46** a Standard deviation of *3 replicates from different hydrolysate batches and **6 technical replicates from the pooled hydrolysate used throughout the study. 3.2 Characterization of starting strains To confirm the inhibitory effect of DDGS-hydrolysate on the growth performance of B. subtilis, an initial strain characterization was performed using BS168, BS168 xyl, KO7, KO7s and KO7s xyl ( Table 1 ). All starting strains showed decreased growth performance with increasing hydrolysate supplementation ( Fig. S1 ). It is noteworthy that slightly shorter lag phase were observed at 10%–40% hydrolysate supplementation (v v −1 ) compared to the base medium without hydrolysate for the starting strains, indicating that some nutrients present in the hydrolysate medium might be beneficial to the cells. In this context, the trade-off between the advantage of extra nutrients and disadvantage of harmful toxic compounds present in the hydrolysate vary between the starting strains. Cells have several energy-demanding adaptation mechanisms to tolerate toxic compounds, amongst others, pH homeostasis, maintaining the barrier function of the cell membrane and induction of global cellular stress responses and inhibitor degradation ( Ibraheem and Ndimba, 2013 ). Upon higher supplementation of hydrolysate, it is possible that more energy is diverted from growth to various detoxification mechanisms, leading to a decrease in overall biomass accumulation. A minor increase in red values (pixel values that were used as a proxy for relative cell density) were observed for BS168 grown in 100% hydrolysate after 24 h for unknown reasons. Nonetheless, an overall decrease in growth rate and increase in lag phase showed that none of the initial starting strains could cope with high amounts of hydrolysate supplementation, confirming the inhibitory effect of lignocellulosic hydrolysates and the need to develop strains that are more tolerant. 3.3 Fitness trajectory during TALE and ALE experiments As tolerance towards inhibitory compounds is challenging to rationally engineer, tolerance adaptive laboratory evolution (TALE) can offer an elegant alternative to obtain tolerant strains without a priori knowledge about the genes responsible for the desired phenotype. Serial passaging of cells in media with increasing amounts of hydrolysate (i.e. selective pressure) allowed for selection of strains that have acquired beneficial mutations. TALE has previously been shown to be an effective tool to obtain strains tolerant towards hydrolysate-associated inhibitory compounds ( Almario et al., 2013 ; Linville et al., 2013 ; Qin et al., 2016 ; Wang et al., 2018 ). In parallel to TALE, it is an informative practice to include adaptive laboratory evolution (ALE) experiments involving a constant cultivation condition to serve as a control. Mutational analysis of both TALE and ALE experiments allows for differentiating between adaptive mutations related to tolerance and those related to basic media components and/or cultivation conditions ( Mohamed et al., 2017 ). During the TALE experiments, population growth rates fluctuated in response to increasing hydrolysate supplementation ( Fig. 1 A–E). These fluctuations are observed frequently in TALE experiments and have been previously defined as restorative shifts ( Sandberg et al., 2014 ). Upon exposure to higher amounts of hydrolysate, specific inhibition as well as general stress responses can occur, which can result in reallocating resources from cell growth or inhibiting a growth coupled process directly. Through repeated growth and passage cycles, adaptive mutations arise in the population, which overcome such specific inhibition or reallocate the general stress response more efficiently. These mutations enable the adapted cell to move back towards the pre-inhibited physiological state. Specific tolerance responses have been shown to be more energy efficient than global stress responses ( Lastiri-Pancardo and Utrilla, 2017 ). In contrast, ALE control experiments of the BS168 xyl and KO7s xyl backgrounds displayed a more constant increase in growth rate ( Fig. 1 F and G). While the initial growth rate was lower for KO7s xyl background compared to the BS168 xyl background (±0.23 h −1 vs ±0.4 h −1 ), both had similar final growth rates at the end of the experiment (±0.7 h −1 ). After approximately 330 generations, all TALE experiments successfully yielded strains with increased tolerance to lignocellulosic hydrolysate, being able to grow reproducibly in 95–100% hydrolysate supplemented media. Fig. 1 Population growth rates and hydrolysate supplementation concentrations over the course of a set of representative TALE and ALE experiments. Plots for the remaining TALE and ALE replicates are shown in Fig. S2 and Fig. S3 . Fig. 1 3.4 Growth screening of evolved and starting strains In order to select isolates with increased growth performance, heterogeneous evolved populations were grown on plates and single colonies were picked for an initial screen based on growth in a 100% hydrolysate-based medium. For all 20 independent TALE experiments, growth in 100% hydrolysate could be reproduced for multiple endpoint isolates, while no growth was observed in any of the starting strains ( Fig. 2 ). Growth performance for 21 isolates per TALE experiment was qualitatively assessed and up to four isolates were selected for the amylase production screening. Fig. 2 Growth performance of starting strains and four selected isolates per one representative TALE experiment grown in 100% hydrolysate-based medium: A) BS168 xyl, B) BS168, C) KO7s, D) KO7, and E) KO7s xyl backgrounds. Plots for selected isolates from the remaining replicate TALE experiments are shown in Fig. S4 . Fig. 2 3.5 Amylase production screening Although TALE can be used to obtain a phenotype that is able to grow, it does not imply that tolerant evolved strains also have improved capabilities to make the product of interest ( Lennen et al., 2019 ). Protein secretion in B. subtilis involves numerous components, including secretory translocases, chaperones, protein synthesis elements, and proteases, which all could have been affected during the TALE experiments ( Zhang et al., 2020 ). To confirm that evolved strains are not only able to grow, but also capable of producing protein using second-generation carbon sources, an amylase expression cassette was inserted into 61 evolved isolates, which were previously selected during the growth screening (Section 3.4 ). Subsequently, protein production was evaluated based on the amylase activity of culture supernatant of both a hydrolysate-based medium and a defined, rich, non-toxic, synthetic medium (Cal18-2) ( Rasmussen et al., 2000 ). First, evolved isolates were screened for amylase production using a 100% hydrolysate-based medium in 96 well plates ( Fig. 3 A, Fig. S5 ). Second, amylase production of both starting strains and selected evolved strains was compared by experiments using Cal18-2 medium in 24 deep well plates (Cal 18-2) ( Fig. 3 B). Although some evolved strains showed lower amylase activity levels than the starting strains, the production of most of the evolved isolates were either higher or in the same range. Altogether, for most evolved strains, no trade-off between the improved tolerance towards biomass hydrolysate and ability to produce protein was observed ( Fig. 3 B). Fig. 3 Amylase activity of culture supernatant as a measure for enzyme production. A) The amylase production screening was performed in a 96 well plate-format, in which evolved isolates were incubated in 100% hydrolysate-based medium for 24 h. Only the values of the highest producing evolved isolates are shown. B) A verification experiment performed in 24 well plate-format, to determine whether a trade-off exist between tolerance and enzyme production. Starting strains and evolved isolates were incubated in Cal18-2 medium for 48h (B). Comparisons of amylase production for two of the most promising evolved strains in either Cal18-2 medium or the hydrolysate. Cells were incubated in 24 wells for 48h (C). Error bars represent the mean ± s.d of (A) n = two technical duplicates measured during the assay); (B) n = two biological duplicates; (C) n = four biological replicates). Fig. 3 Third, we did a comparative experiment for the most promising evolved strains from each background strain ( B. subtilis 168 and B. subtilis PY79 KO7s), and found that production in the hydrolysate was 40% of the production in the industrially relevant Cal18-2 medium, which is a promising result for further developments towards industrial implementation, given the lower sugar and protein content in the hydrolysate used in the experiments. 3.6 Whole-genome Re-sequencing Subsequent to the screening of the evolved strains, whole-genome re-sequencing is a critical step in the TALE process to decipher the mutational background associated to strains with an improved phenotype in the applied environment. Bioinformatics tools allow comparison of re-sequencing data of both ancestral and multiple independently evolved replicates to determine converged mutations that are likely causal to the improved phenotype ( Phaneuf et al., 2019b ). Following this approach, starting strains and selected evolved isolates were send for whole-genome-resequencing ( Table S1 ). During the quality assessment, one isolate was excluded from further analysis due to sequencing issues. For the remaining 19 evolved isolates, the number of acquired mutations ranged from four to thirteen. Functional annotations of all mutated genes or genetic regions are summarized based on GO terms in a Sankey diagram ( Fig. 4 A , ( “BSubCyc\" )). Almost two-third of the mutated genes are involved in stress response mechanisms, metabolism, transcriptional regulation, sporulation, and/or cell motility, highlighting their importance for the improved phenotype. In addition, converged mutations were identified by comparing clonal isolates of 19 TALE experiments and 8 control ALE experiments. Genes or genetic regions that showed a mutation in >2 independent TALE or ALE experiments, in either replicates from the same or different backgrounds, were considered converged mutations and are summarized in Fig. 4 B. Shared mutations in genes or genetic regions across the independent replicates strongly suggest that they are adaptive ( Sandberg et al., 2019 ). As such, converged mutations that were acquired exclusively during the TALE experiments are likely to be related to tolerance and included the genes codY, mntA , scoC , rpoC , ponA, veg, and oppD . In contrast, mutations in isolates of both TALE and ALE experiments are likely linked to the cultivation conditions and/or media composition. These included genes associated to protection against oxidative stress ( katA , perR ) , and flagellar structure. Overall, there does not seem to be a clear difference between the converged mutations observed for the BS168/BS168 xyl background strains or KO7x/KO7s xyl background strains. This would suggest that the obtained tolerance is not related to the potential to consume more xylose. A more detailed overview of all observed mutations per isolate is given in Table S3 . Fig. 4 Mutational analysis of evolved isolates. A) Sankey diagram showing the relation between gene function, gene name, and the strain backgrounds. B) Heat map of converged mutated genes across independent TALE and ALE experiments for different backgrounds. Numbers indicate the number of evolved isolates in which mutations in the given genes or genetic regions were observed. In the cumulative TALE column, the total number of evolved isolates in which mutations were observed for all TALE experiments are shown. *Genes associated with the flagellar structure are pooled, these include fliG (TALE#9), fliR (TALE#9, #10, ALE #28), fliH (TALE #12, ALE #21), fliF (TALE #15, ALE #23), fliL (TALE #13), fliK (TALE #16, ALE #27), fliY , (TALE #17), fliZ (TALE #18, ALE #24), fliP (TALE #19), flhA (ALE #26). Fig. 4 The most frequently mutated gene, specific for only the TALE experiments, was the transcription factor codY . Remarkably, all eight BS168 strains were found to have amino acid substitutions for exactly the same arginine-214 residue (R214X). As R214 is part of the highly conserved DNA-binding domain (202–222), called the HTH-motif, the observed substitutions will likely influence the transcriptional regulation by CodY. Previous studies showed that substitutions of arginine-214 led to a reduced ability of CodY to bind to the target genes. In addition, it has been shown that the context of the HTH-motif of DNA binding domains may influence the recognition and specificity of HTH-mediated protein-DNA interactions ( Joseph et al., 2005 ). Considering the conserved nature of the codY gene, it is possible that the SNPs observed outside of the HTH-domain in the KO7, KO7s, and KO7s xyl backgrounds (T125I, A186T, E193G, 2xY241C, L245P, L245P), could still influence the regulatory function of the protein ( Fig. 5 A). As the pleiotropic regulator CodY is involved in regulating the expression of several hundred genes ( Sonenshein, 2007 ) ( Fig. S6 , subtiwiki), it is not straightforward to uncover which gene(s) regulated by CodY that could be responsible for the improved phenotype. Fig. 5 A) Structure of the CodY protein (PDB ID: 5loe ). Mutated amino acids and their side-chains are indicated in red and the HTH DNA-binding domain is colored pink. Structure was visualized using PyMOL (Schrödinger LLC). Numbers in the table indicate the number of evolved isolates carrying mutations in the specific residue. B) Pictures of end isolates TALE#5 I17 and TALE#9 I13 after 24h growth in cal-18 medium. The dark brown patches of biofilm were only present for TALE#5 I17. (For interpretation of the references to color in this figure legend, the reader is referred to the Web version of this article.) Fig. 5 As many independent converged mutations suggest to have a causal relation with the improved tolerance of the evolved isolates, it is interesting to reflect on the replicates which did not share the mutations in the codY gene (TALE#16, TALE#17, TALE#18, TALE#19) and attempt to find mutations which could have a similar functional outcome related to tolerance. The evolved isolates of TALE #17, TALE#18, TALE#19, and TALE#20 all showed the exact similar SNP in the rpoC gene (125,619, C→T) ( Fig. 4 B , \n Table S3 ). The expression of rpoC is regulated by CodY and known to regulate stress response genes, including those of extracytoplasmic function (ECF), σ factors (σM, σW, and σX), and the general stress σ factor (σB) ( Lee et al., 2013 ). Moreover, the end isolate of TALE #16 only showed eight SNPs, of which only five were not shared with other evolved isolates. Intriguingly, this included the HTH-domain global regulator gene c ymR . Transcriptome analysis of Δ cymR mutants has shown that many genes related to stress response were altered ( Even et al., 2006 ). Next to codY , TALE-specific converged mutations included mntA , scoC , rpoC , ponA , veg and oppD, which are disucssed in more detail in the supplementary information. Next, converged mutations that were acquired in both TALE and control ALE experiments were identified. Except for TALE#2, all TALE experiments yielded evolved isolates that were either mutated in the promoter region of the vegetative catalase, katA , or its transcriptional repressor perR . Mutations in the katA promoter were either around the −10/-35 regions, or in the regulatory domain called the Per box. In contrast, mutations in the perR gene led to substitutions across the whole length of the gene. In addition, six out of the eight evolved isolates derived from control ALE experiments also showed mutations in either the promoter region of katA or perR . This suggests that the observed mutations are linked to the cultivation conditions of the experiment and the M9extra-medium rather than tolerance towards biomass hydrolysates. As the mutations are so dominantly present across the different evolution experiments, a higher expression of the vegetative catalase katA may be advantageous by protecting the cell from stress-derived oxidative damage. Apparently, the increased ability to ward off reactive oxygen species is not only beneficial when cultivating cells in biomass hydrolysate, but also in the M9extra medium. Eleven different genes encoding for parts of the flagella structure were mutated in both TALE and ALE experiments, and hence are likely to play a role in improving growth in the applied cultivation conditions. Mutations included eight deletions, seven introductions of stop codons, and three substitutions. Although the evolved isolates of the BS168/BS168 xyl backgrounds did acquire mutations in genes of the flagella structure during the ALE control experiment, these were absent when TALE conditions were applied. It is worth mentioning that the absence/presence of flagella-associated mutations had a clear impact on the phenotype and ability to form a biofilm ( Fig. 5 C). It has been extensively described that both the biosynthesis and the operation of flagella represents a considerable cost for the host and that loss of flagella functions can be generally beneficial in well-mixed cultivations ( Lara and Gossett ). As such, improved growth has been observed in both evolutionary studies and rationally designed cell factories ( Mohamed et al., 2020 ). In short, mutations associated with increased tolerance included global regulators ( codY, scoC , rpoC, ponA, veg ) and more specific genes (transporters mntA and oppD) . One of the known key advantages of TALE studies is the discovery of specific SNPs in global regulators, responsible for the tuning of a multitude of gene expression levels that restore robust growth ( Sandberg et al., 2019 ). Although alterations in global regulator genes render it challenging to provide a molecular mechanistic basis for the improved phenotypes, mutations present in many independent experiments (e.g., codY ) are highly likely to be causal and can be used as targets for rational strain design. Identifying the mechanistic impact of the identified mutations on gene expression using additional -omics approaches, such as RNA sequencing, would give valuable insights for future metabolic engineering work. Current work can also be expanded to evolutionary studies focusing on individual inhibitory compounds present in biomass hydrolysate to unravel general and specific chemical tolerance mechanisms systematically. Moreover, additional rational design and evolutionary engineering can generate strains even closer to their biological limit. Nevertheless, as industrial implementation requires high concentration of sugars and concomitantly higher amounts of inhibitors, the realization of a cost-effective bioprocess using lignocellulose demands a multidisciplinary approach looking beyond the cell, fine-tuning both pretreatment, detoxification, and fermentation conditions to keep the concentration of inhibitory compounds within the limits of biology."
} | 6,997 |
38361533 | PMC10868416 | pmc | 9,061 | {
"abstract": "ABSTRACT The rapid advancement in intelligent bionics has elevated electronic skin to a pivotal component in bionic robots, enabling swift responses to diverse external stimuli. Combining wearable touch sensors with IoT technology lays the groundwork for achieving the versatile functionality of electronic skin. However, most current touch sensors rely on capacitive layer deformations induced by pressure, leading to changes in capacitance values. Unfortunately, sensors of this kind often face limitations in practical applications due to their uniform sensing capabilities. This study presents a novel approach by incorporating graphitic carbon nitride (GCN) into polydimethylsiloxane (PDMS) at a low concentration. Surprisingly, this blend of materials with higher dielectric constants yields composite films with lower dielectric constants, contrary to expectations. Unlike traditional capacitive sensors, our non-contact touch sensors exploit electric field interference between the object and the sensor’s edge, with enhanced effects from the low dielectric constant GCN/PDMS film. Consequently, we have fabricated touch sensor grids using an array configuration of dispensing printing techniques, facilitating fast response and ultra-low-limit contact detection with finger-to-device distances ranging from 5 to 100 mm. These sensors exhibit excellent resolution in recognizing 3D object shapes and accurately detecting positional motion. Moreover, they enable real-time monitoring of array data with signal transmission over a 4G network. In summary, our proposed approach for fabricating low dielectric constant thin films, as employed in non-contact touch sensors, opens new avenues for advancing electronic skin technology.",
"conclusion": "Conclusions The study successfully employed a pyrolytic synthesis method to fabricate GCN particles, which were subsequently integrated into PDMS composite films via low-concentration doping. Using a dispensing printing technique, touch sensor arrays with serpentine electrodes were developed, enabling the non-contact capacitive sensors to recognise objects’ 3D shape and positional movement. Based on the findings and discussions, the following conclusions can be drawn:\n The incorporation of GCN into PDMS composite films resulted in a noticeable decrease in capacitance values, approximately 11% lower than those of pure PDMS films. This phenomenon can be attributed to two main factors. Firstly, larger GCN particles at a low concentration within the PDMS matrix hinder PDMS molecular chain mobility. This restricted mobility reduces the overall polarisation of the GCN/PDMS composite film, resulting in low capacitance values. Secondly, the interface between GCN and PDMS introduces voids or holes, which further contribute to the weakened polarisation of the composite film. These effects account for decreased capacitance values in the GCN/PDMS composite film. The touch sensor utilised in this study employed a serpentine carbon-based electrode, which was fabricated using a dispensing printing technique to create both the upper and lower layers of the sensor. The serpentine electrode exhibited impressive characteristics, including a rapid response time of 90 ms, excellent linearity across a range of 5 mm to 100 mm, and exceptional durability withstanding 200 pull and release cycles at a large-scale strain of 10%. Moreover, the touch sensor array demonstrated remarkable stability in device performance, maintaining a level of over 98.5% even when subjected to a bending tensile strain of 10%. This outstanding stability can be attributed to the unique design of the serpentine electrode, which effectively converts applied tensile strain into a localised bending motion, ensuring consistent device performance. These features make the touch sensor suitable for various wearable applications. The 5 × 5 touch sensor array demonstrated the ability to accurately recognise the 3D shape and positional movement of objects placed on it. This capability was evident in the XYZ axis direction. The recognition performance was attributed to the properties of the GCN/PDMS composite film, which exhibited a low dielectric constant and a high sensitivity to objects entering the electric field at the edges of the sensor. The finger’s movement in the XY and Z axes was successfully detected, and different objects’ 3D shapes were analysed. Subsequently, the contactless touch sensor was connected to a printed, electronic circuit for signal processing and transmission. The sensor’s output signal was then displayed in real time on a personal mobile terminal using a 4 G transmission module. This achievement is an important milestone in developing electronic skin for wireless real-time monitoring. However, the capabilities of e-skin extend beyond shape and displacement detection. Therefore, future research will focus on developing more functional devices for these applications.",
"introduction": "Introduction Significant progress has been made in developing flexible electronics with unique properties such as reversible bending, twisting, and folding in the past few years [ 1–5 ]. These advancements have resulted in a wide range of possibilities for functional versatility in wearable devices for humans. Notably, the integration of flexible haptic sensors as input and sensing components have emerged as a crucial aspect in developing electronic human skin. These sensors hold immense potential and find extensive applications in various fields, such as health monitoring [ 6–9 ], human-computer interaction [ 10–13 ], and bionic robotics [ 14–16 ]. This widespread utilisation of flexible haptic sensors illustrates their promising prospects and wide range of applications. Printed electronics technology [ 17–19 ] offers significant advantages over traditional photolithography, particularly process efficiency and waste reduction. It proves to be advantageous for mass production. In this regard, dispense printing technology stands out due to its ability to deposit high ink concentrations and achieve flexible patterning, surpassing other printing methods like inkjet and screen printing [ 20–22 ]. Moreover, it enables shorter processing time and higher precision in producing electronic products. Typically, capacitive sensors consist of two parallel electrodes with a dielectric layer in between [ 23 ]. Indium, a tin oxide material commonly used as the electrode material for capacitive sensors, presents challenges in terms of preparation and lacks the required flexibility for wearable sensor applications. On the other hand, since their discovery [ 24 ] in 1991, multi-walled carbon nanotubes (MWCNTS) have gained widespread use due to their exceptional mechanical and electrical properties [ 25 ]. They offer a viable alternative for addressing the flexibility requirements of wearable sensor scenarios. CNTs exhibit covalent sp2 hybridisation bonds between carbon atoms, resulting in their high stiffness and resistance to axial stress. Leveraging these properties, we utilise CNTs as electrode inks in dispense printing. This enables us to meet the requirements of wearable touch sensor applications, including kinking, sliding, and compression. Traditional methods for sensing the three-dimensional shape of objects typically entail the deformation of a capacitive layer through physical contact, posing challenges when aiming to recognize non-contact objects for electronic skin applications [ 26 ]. Non-contact object sensing encompasses various techniques, including the utilization of infrared light [ 27 ], magnetic induction [ 28 ], and ultrasonic methods [ 29 ]. Among these, capacitive sensors have emerged as particularly noteworthy due to their distinct characteristics, including high impedance necessitating minimal input energy, excellent temperature stability, and straightforward structures with unique adaptations. Li et al. [ 30 ] introduced a capacitive non-contact sensor with a ‘sandwich’ configuration. This sensor employs copper electrodes, precisely fabricated through controlled in-situ laser direct patterning. The fabrication process entails the curing of a dielectric material, PDMS, positioned between two orthogonal arrays of electrode layers. This sensor boasts an effective detection distance of 200 mm and achieves a maximum sensitivity of approximately 30%. It is essential to note that non-contact capacitive sensors differ from their conventional contact-based counterparts, often influenced by the surrounding air, which possesses a low dielectric constant [ 31 , 32 ]. Consequently, a capacitive layer with a higher dielectric constant does not necessarily translate to an amplified fringing electric field, leading to diminished device sensitivity. Remarkably, the introduction of slight doping of 2D GCN [ 33 ] into PDMS yields a composite film with a lower dielectric constant. This counterintuitive outcome stems from GCN’s role in restricting the mobility of PDMS molecular chains and creating numerous voids at the interface, collectively reducing overall polarization and hence the dielectric constant [ 34 ]. In the context of fabricating sandwich-structured capacitive sensors, conventional device preparation techniques like photolithography and lasers offer substantial advantages over printed electronics, notably in terms of process efficiency and minimal wastage, holding potential for large-scale device production. Among these techniques, dispensing printing stands out due to its suitability for high-viscosity inks. Carbon-based electrode inks and GCN/PDMS capacitive layer inks, possessing favorable rheology and viscosity, are well-suited for dispensing printing, expediting the creation of snake arrays for touch sensors. This study presents a capacitive touch sensor array, fully prepared via dispensing printing, with multi-walled carbon nanotube (MWCNT) ink serving as the electrode layer and GCN/PDMS ink as the capacitive layer. Intriguingly, the combination of these two high dielectric constant materials results in a decreased dielectric constant, contrary to expectations. The fabricated non-contact touch sensor device exhibits the capability for ultra-low limit object detection. Configured as a 5 × 5 array for gesture recognition and localization, the fully printed capacitive touch sensor is integrated with a printed circuit board (PCB) for wireless data transmission over 4 G networks. This integrated system facilitates remote detection of human movement and supports virtual keyboard applications.",
"discussion": "Results and discussion Characteristics of printed touch sensor The electrodes in the flexible capacitive sensor play a crucial role in its performance. The ink components were carefully optimised to achieve an electrode ink with desirable mechanical properties, electrical properties, and printability. Various weight ratios of CNTs and graphene were tested, including 0.08 g/0.04 g, 0.11 g/0.02 g, 0.11 g/0.03 g, and 0.11 g/0.04 g. These ratios were used to prepare four sets of electrode samples with a width of 1 mm, numbered 1 to 4. Figure S1 illustrates the resistance changes of these electrode sets as the length incrementally increases from 2 mm to 10 mm. The combination of MWCNTS and the conductive network of graphene demonstrates a synergistic effect. The MWCNTS are intercalated within the layer-like structures of graphene, optimising the electron transport properties of the electrodes. Additionally, the tubular structure of MWCNTS provides entanglement, which proves advantageous for meeting the mechanical property requirements of wearable devices. After considering the mechanical properties, electrical properties, and printability of the electrodes, ink with a weight ratio of 0.11 g/0.04 g of MWCNTS to graphene was identified as the optimal formulation for the electrode preparation. Figure 2(a) illustrates the process flow diagram for fabricating a fully printed touch sensor using a dispensing machine. The sensor structure follows a typical sandwich structure, consisting of three main components: (i) polyethylene terephthalate (PET) substrate; (ii) dot-printed carbon-based electrode array with a conductivity of 317.1 ohm/square foot; and (iii) insulating layer comprising a 120 μm thick GCN/PDMS film. Figure 2(b) demonstrates through optical microscopy that the dispensed printed carbon-based electrode exhibits a uniform curve profile even at 20× magnification. It adheres evenly to the surfaces of the GCN/PDMS film. Additionally, Figure 2(c) depicts the GCN/PDMS film at 20× magnification, showing no significant agglomeration of large particles. This indicates that the GCN particles are uniformly blended with the film, forming a high-quality composite film.\n Figure 2. Flexible capacitive touch sensor. (a) Schematic diagram of the printing process of the sensor. (b) OM image of the carbon electrode printed by dispensing. (c) OM image of GCN/PDMS (0.75 wt%) dielectric layer. (d) The physical image of the sensor. (e) The cross-sectional electron microscope image of a sensing unit of the sensor. (f) Water contact angle of dielectric layer before and after UV treatment. FEM strain distribution analysis of the strain distribution along the (g) X-axis and (h) Y-axis. (i) Relative resistance changes under different tensile strains. (j) Resistance of electrodes of length 10 mm at 100 locations. (k) GCN/PDMS with different doping weight ratios at 10 kHz frequency capacitance of the composite film. (l) Relationship between GCN concentration and device capacitance value. Figure 2(d) presents a 5 × 5 touch sensor array comprising 25 channels, with a size of 4 × 4 cm. The patterned carbon-based electrodes have a width of 1 mm, and there is an 8 mm spacing between the electrodes. The electrode design takes the form of a snake shape, allowing for the conversion of applied tensile strain into the local bending motion of the electrodes. This design ensures stable device performance, particularly in wearable applications. Figure 2(e) displays a cross-sectional scanning electron microscopy (SEM) image of the touch sensor structure. It exhibits the sandwich structure, with the capacitive layer having a thickness of approximately 120 μm. The upper and lower electrodes are uniformly attached to the surface of the GCN/PDMS film, fitting closely to the PET substrate. This close attachment ensures the proper functioning of the sensor. Since the electrode ink used in this study utilises a pro-biological water base as the solvent, the surface tension of the water-based ink is often too high to achieve high-precision patterning. Therefore, a high hydrophilic property is required for the printed adhesion layer. UV treatment is employed on the GCN/PDMS film surface to address this. As illustrated in Figure 2(f) , the contact angle undergoes a transition from 114° to 57° following UV treatment. This alteration is attributed to the conversion of a portion of the -OSi(CH 3 ) 2 O- groups on the PDMS surface into -O 4 Si(OH) 4 -n groups. The FTIR spectra of the PDMS membranes, both before and after UV treatment, are presented in Figure S2. The characteristic peaks at 780, 1020, and 1250 cm −1 in the FTIR spectra are indicative of PDMS. Specifically, the bands at 780 cm −1 and 1250 cm −1 correspond to the Si-C wobble vibration and -CH 3 deformation in the Si(CH 3 ) 2 moiety, respectively. UV treatment significantly reduces the intensity of the absorption bands at 780 and 1250 cm −1 due to the oxidation of PDMS. Additionally, the broad intensity band at 1020 cm −1 , representing asymmetric Si-O-Si stretching vibrations, undergoes notable changes in shape and frequency under UV-ozone exposure. This suggests a transformation from Si coordinated with two oxygen atoms in PDMS to Si coordinated with four oxygen atoms, resulting in the formation of SiO x films through PDMS oxidation. The process involves the decomposition of -OSi(CH 3 ) 2 O- groups on the PDMS surface through cleavage and redox reactions, ultimately forming polar hydrophilic groups such as OH, COOH, CO, and COO on the material’s surface. These surface functional groups facilitate better contact between water molecules and the PDMS surface, forming a uniform electrode layer [ 36 ]. Figure S3 provides additional information on the water contact angles of GCN/PDMS composite membranes with different weight ratios before and after UV treatment. This data helps to assess the hydrophilic properties of the membranes. The snake-shaped electrodes in the touch sensor design exhibit resistance to tensile loading in the parallel direction and have a margin of tensile strength for loading in the perpendicular direction to the electrode alignment. This unique feature enhances the attachment of the flexible touch sensor to complex skin surfaces and ensures device stability, particularly at joints. To evaluate the strain distribution under different tensile strains applied in various directions and at different strengths, finite element analysis (FEA) was conducted using a representative volume cell model (Figure S4). Figure 2(g,h) display the simulated structures, illustrating that tensile loads of up to 10% along the X and Y directions in the serpentine electrode array do not lead to device failure. This analysis confirms the robustness and reliability of the touch sensor design under different tensile loading conditions. Adding mechanical strain to a touch sensor can broaden its applications as a wearable electronic device. The serpentine electrode structure in the touch sensor design plays a crucial role. When subjected to tensile stress, the serpentine electrode straightens out, effectively preventing electrode fracture and ensuring the sensor’s integrity. This mechanism enhances the stability of the touch sensor when attached to different parts of the human body, such as the palm, where it may experience varying levels of strain. The inherent hydrophobic nature of the PDMS substrate presents a common challenge in the precise printing of uniform snake-shaped electrodes on its surface without inducing alterations in surface roughness. Furthermore, due to the interfacial properties of loosely adhered electrodes on PDMS, their utilization in flexible electronic devices for wearable applications often results in electrode detachment, consequently leading to device malfunction. As depicted in Figure 2(i) , we observed the variation in sensor electrode line resistance under different bending radii. In this experiment, the bending radius of the touch sensor was systematically reduced from 20 mm to 1.5 mm, and it is noteworthy that the change in electrode resistance remained within a margin of less than 2% throughout this bending process. This observation underscores the exceptional stability and resilience of the touch sensor against bending stress. Furthermore, upon returning the sensor to its original unbent state, it exhibited complete recovery, a behavior in alignment with our simulation results. Figure S5 provides further insights into the behaviour of the touch sensor by showing the variation in relative capacitance and resistance at different bending radii. The uniformity and reproducibility of electrode resistance are crucial for ensuring the reliability of sensor applications. Multiple electrodes were manufactured using the dispensing printing technique, and resistance measurements were conducted at various locations with an electrode length of 10 mm, as depicted in Figure 2(j) . The results from 100 electrode samples demonstrated excellent uniformity and reproducibility, with resistance values centered around 1050 ohms. Additionally, we assessed the resistance of electrodes with varying lengths at different positions, as illustrated in Figure S6. The measurement outcomes affirm the robust stability of electrode resistance across different lengths, underscoring its significance in guaranteeing the reliability of the sensor. To analyse the effect of doping weight ratios on the capacitance performance of GCN/PDMS composite films, various compositions ranging from 0 wt% to 0.75 wt% of GCN were examined at high frequencies (10 kHz). The results indicate that as the mass ratio of GCN increases, the capacitance of the composite films decreases. However, when the GCN mass ratio is further increased to 1 wt%, the capacitance exhibits an increasing trend ( Figure 2(k,l) ). Notably, the dielectric constants of GCN and PDMS are approximately 4.6 and 2.8, respectively, at room temperature. These values contribute to the overall capacitance behaviour observed in the GCN/PDMS composite films. Figure 3(a–d) display the AFM images of pure PDMS with GCN/PDMS nanocomposites (30 × 30 μm). Small bumps of approximately 300 nm in size are observed in the nanocomposites containing GCN, indicating a slight increase in surface roughness compared to pure PDMS (RMS = 34.6 μm). However, there is no significant agglomeration of larger particles, and the dispersion of GCN with larger particles in the polymer matrix is effectively achieved through the mechanical effects of the preparation process. Furthermore, the surface of the nanocomposites exhibits more elliptical and spherical bumps than the lamellar structure observed in the graphite phase of carbon nitride. These rounded bumps are pores and cavities introduced after the composite formation. This change is attributed to the bonding between GCN and PDMS polymers, which is influenced by the weak interaction between PDMS and GCN. As a result, more cavities and pores are formed within the GCN and at the GCN/PDMS interface. Simultaneously, we employed SEM to observe a substantial quantity of cavities within the composite film (Figure S7). These cavities exhibited dimensions in the range of 200–400 nm and were prominently situated at the interface between GCN and PDMS. This observation is in accordance with the findings obtained through AFM characterization, thereby reinforcing the robustness of our results. This observation supports the finding that the dielectric constant of the nanocomposites decreases as the doping concentration of GCN increases at low levels. Moreover, the slight increase in RMS roughness of the nanocomposite leads to an increased contact area between the ink and the surface during printing. This increased contact area enhances the interaction force, which is beneficial for achieving uniform printing on the film surface, especially when using a high concentration of carbon-based ink.\n Figure 3. GCN/PDMS dielectric layer analysis. (a-b) AFM images of pure PDMS and 0.75 wt% GCN/PDMS surface roughness. (c-d) AFM images of pure PDMS and 0.75 wt% GCN/PDMS microstructure; (e) XPS of 0.75 wt% GCN/PDMS dielectric layer spectra. (f) XPS spectrum of GCN/PDMS in C1s region. (g) XPS spectrum of GCN/PDMS in O region; (h) XPS spectrum of GCN/PDMS in Si region. (i) Schematic diagram of the principle of dielectric constant reduction by GCN-doped PDMS. (j) GCN/PDMS at different weight ratios infrared spectra of PDMS; (k) XRD patterns of GCN/PDMS with different weight ratios. (l) Raman diagrams of MWCNT/Graphene electrodes with different ratios. In Figure 3(e) , the XPS spectrum of the GCN/PDMS sample reveals the presence of Si, O, and C elements in the composite. The low concentration of carbon nitride doping results in a small peak of the N element, indicating that the PDMS matrix remains the predominant component in the nanocomposite films with low levels of carbon nitride doping. The C1s spectrum can be deconvoluted using symmetric Gaussian-shaped peaks for mathematical analysis. Figure 3(f) shows the fitted peaks corresponding to C-C/C-H at 284.8 and C-Si at 285.6 eV in the fine spectrum of the C element. In Figure 3(g) , the O1s peak can be deconvoluted into two peaks representing the Si-O bond at 532.5 eV and the C-O bond at 533.9 eV. The Si 2p peak in Figure 3(h) is formed by the convolution of four components: Si 2p 3/2 and the two spin-orbit doublets of Si 2p 1/2 . Four major peaks at 102.4, 103.0, 103.7 and 104.5 eV in the Si 2p region correspond well with silicone 2p 3/2 , 2p 1/2 , silica 2p 3/2 , and 2p 1/2 , respectively. This observation indicates the presence of silica within the PDMS composite, which might have been introduced through the Sylgard 184 system. The presence of silica provides evidence for enhanced hydrophilicity following UV treatment. The theoretical model depicted in Figure 3(i) effectively elucidates the phenomenon of diminishing dielectric constants in both GCN and PDMS materials following their composite formation. This reduction can be attributed to the relatively low doping concentration of carbon nitride, causing the composite material to approach the dielectric constant of the PDMS matrix. The incorporation of GCN via doping creates a novel interconnecting network structure within the composite, thereby constraining the mobility of PDMS molecular chains. Consequently, this restriction hinders the free movement and orientation of these molecular chains, leading to a decrease in the polymer matrix’s polarizability. Conversely, the interaction between GCN and PDMS is predominantly governed by weak van der Waals forces and hydrogen bonding, resulting in the formation of voids at the interfaces between carbon nitride and PDMS. These voids augment the free volume within the hybrid system. When subjected to an electric field, these voids exhibit limited charge storage capacity, resulting in an overall reduction in system polarization. Therefore, the presence of these voids contributes to the decline in the dielectric constant [ 37 , 38 ]. FT-IR spectroscopy characterised different weight ratios (0, 0.25, 0.5, 0.75, and 1 wt%) of GCN/PDMS, as shown in Figure 3(j) . In the 0 wt% GCN/PDMS sample, strong FT-IR peaks were observed at 789–796 cm −1 corresponding to the -CH 3 swing and Si-C stretching in Si-CH 3 ; 1020–1074 cm −1 associated with Si-O-Si stretching; 1260–1259 cm −1 representing CH 3 distortion in Si-CH 3 ; and 2950–2960 cm −1 indicating asymmetric CH 3 stretching in Si-CH 3 . These peaks remain observable even when GCN is incorporated into PDMS at different weight percentages. The newly observed spectral band centered at 3250 cm −1 (highlighted by the red dashed rectangle) exhibits an increasing intensity with higher GCN doping concentrations. The band is associated with the N-H stretching vibrations of the terminal reactive group present in the GCN polymer. Simultaneously, the N-H stretching vibrations corresponding to 1241 and 1624 cm −1 (highlighted by the green dashed rectangle) show significant shifts in their peak positions. These shifts indicate the presence of C-N and C=N stretching vibrations, respectively (Supporting Information, Table S1). Furthermore, the characteristic respiration pattern of the triazine unit is observed at 810 cm −1 , which is associated with the absorption band of the S-triazine ring. The observed spectral changes suggest the formation of hydrogen bonds within the GCN/PDMS nanocomposite. The existence of hydrogen bonding induces localized charge rearrangement, exerting an influence on the polarization effect and ultimately diminishing the overall material polarization. This decline in polarization precipitates a reduction in the dielectric constant of the nanocomposite. These findings effectively corroborate the theoretical model presented earlier. Additionally, the characteristic breathing pattern of the triazine unit at 810 cm −1 is well preserved in all GCN/PDMS samples. However, this pattern is overshadowed by the PDMS signals, such as the -CH 3 wobble peak at 789 cm −1 and the Si-C stretching peak at 796 cm −1, indicated by the red dashed rectangle. The bands observed at 1624, 1553, 1409, and 1241 cm −1 are attributed to the stretching vibration modes characteristic of triazine units derived from repeating units within the GCN/PDMS nanocomposite. It is clear from these vibrational modes of the nanocomposite that triazine units have been incorporated into the structure of the nanocomposite. XRD analysis was performed to investigate the properties of GCN/PDMS composite films with different weight ratios. The XRD patterns obtained at 500°C, 600°C, and 700°C exhibit two distinct peaks located at 2θ = 12.8° and 27.7° (Figure S8). These peaks can be attributed to the hexagonal phase of GCN. It is well-established that GCN is composed of polymerised melem building blocks. The strongest peak at 2θ = 27.7°Corresponds to the interlayer stacking of the (002) melem planes. In the GCN structure, this peak indicates a well-defined stacking arrangement. A peak at 2θ = 2.8° is also observed, which is attributed to the (100) planes. This peak is associated with the in-plane ordering of the nitrogen-linked heptazine units in the GCN structure. A clear sheet structure appeared in the SEM of GCN annealed at 600°C (Figure S9). In Figure 3(k) , the XRD pattern of pure PDMS displays a prominent peak at around 12.11°, indicating the characteristic amorphous nature of PDMS. Additionally, a broad peak is observed around 21.9°, further confirming the amorphous structure of PDMS, especially at higher concentrations. For the composite thin film sample, it is observed that the characteristic peaks at 12.11° and 21.9° increase in intensity gradually. Moreover, the peak positions shift towards higher angles (to the right) as the doping concentration of GCN increases. This shift in peak position is attributed to the presence of GCN in the composite. GCN exhibits strong characteristic peaks at 13.20° and 27.20°, assigned to the (100) and (002) diffraction planes, respectively. The XRD analysis of the composite samples revealed distinct plots for PDMS and GCN without any impurity peaks. This indicates the production of a purer GCN/PDMS composite film. The obtained results prove that GCN is uniformly embedded within these composite films, and the grafting process does not alter the inherent properties of PDMS and GCN. The consistency between the FTIR and XPS characterisation results and the XRD analysis of the GCN/PDMS composite films further confirms the accuracy and reliability of the obtained data. The Raman spectra in Figure 3(l) exhibit two prominent peaks at 1338 and 1579 cm −1 , which can be assigned to the D-band and G-band, respectively, in CNT and graphene. The D-band is associated with the degree of disorder in the system, while the G-band represents carbon atoms with a complete hexagonal structure and sp 2 hybridisation. The intensity ratio (I D /I G ) of the D-band to the G-band is commonly used as an indicator to evaluate the degree of disorder and the presence of defects in the material. Generally, a higher I D /I G ratio indicates that the more disordered phases have larger defects in the material. The calculated I D /I G ratio in the hybrid ink of CNTs and graphene increases as the doping concentration of CNTs increases. This can be attributed to a few reasons. Firstly, a higher concentration of CNTs introduces more defects due to the curvature structure of the sidewalls. These defects increase D-band intensity, leading to a higher I D /I G ratio. Also, the interfacial interaction between CNTs and graphene can trigger charge transfer. This charge transfer process further increases the number of defects in CNTs, thus causing an increase in the I D /I G ratio. The transfer of charge between CNTs and graphene can introduce additional electrons, which alters the electronic density of states and the material’s conductive properties. The observed difference in the electrical properties of electrodes with different mixing ratios can be attributed to these changes in the I D /I G ratio. Defects and charge transfer significantly impact the conductive behavior of hybrid inks, resulting in variations in the properties of the hybrid inks. The transmittance of the pure PDMS film and the GCN/PDMS composite film were tested separately, and the transmittance of the GCN/PDMS composite film was reduced but still had good transmittance performance (Figure S10). Performance of printed touch sensor When a voltage is applied across the sensor electrodes, it induces the generation of an electric field in the region between these electrodes. However, it’s essential to note that a portion of the electric field’s energy disperses into the surrounding space, giving rise to what is commonly referred to as a fringe field. When an external object, such as a finger or another grounded conductor, approaches the sensor without direct contact, it perturbs the fringe field, thereby trapping a portion of the electric charge. This perturbation results in a measurable decrease in the sensor’s capacitance value. For visual clarification, please refer to Figure 4(a) , which presents a schematic representation illustrating the evolving electric field as a finger gradually approaches the sensor. In an ideal parallel-plate capacitor, the value of the device capacitance depends on the dielectric, the relative area and the distance between the electrodes, and the stripe effect is generally neglected. If the stripe field is considered, the overall capacitance consists of two parts: the classical capacitance equation (C 0 ) and the modified equation (ΔC) for a square parallel-plate capacitor [ 39 , 40 ]: (1) C = C 0 + Δ C = ε 0 ∗ l ∗ w d + ε 0 ∗ w 2 π ln 2 π ∗ l d \n Figure 4. Electrical properties and performance of the sensor. (a) Schematic diagram of a finger approaching the sensor. (b) The relationship between the capacitance change and time of touch and proximity at a distance of 0–150 mm between the finger and the sensor. (c) The relative capacitance change between the sensor and the finger (ΔC/C 0 ) and the distance. (d) Electric field simulation diagram at different distances between the finger and the sensor. (e) Capacitance of the sensor under 200 cycle tests; (f) response time of the sensor. (h) Capacitance of the sensor under different stretching variety. (g) Ultra-low limit detection of capacitive sensors. Where ε 0 denotes the relative dielectric constant, w and l denote the width and length of the electrodes, and d denotes the distance between the parallel plate electrodes. The mutual capacitance (C mc ) resulting from the interaction of the fringe electric field with the target object varies with the distance between the electrodes and the target object as given in the following equation: (2) C mc = ε 0 ∗ w mc 2 π ln 2 π ∗ l mc d mc Where ε 0 denotes the relative dielectric constant, wmc and lmc denote the width and length of the target object, and dmc denotes the distance between the electrode and the target object. When the material’s dielectric constant (ε 0 ) is smaller between the capacitive plates, the capacitance (C) value will decrease. In the capacitance equation, the fractional term involving the dielectric constant (ε 0 ) is in the denominator. As ε 0 decreases, the entire fractional term decreases, resulting in a decrease in capacitance. Accordingly, a capacitive layer with a smaller dielectric constant will exhibit a larger change in capacitance for a given change in the material or object being measured. High sensitivity to changes in capacitance is advantageous in certain applications where a precise measurement or detection of small changes is required. The preceding discourse has revealed that, within the specified conditions, the capacitance of the 0.75 wt% GCN/PDMS composite film registers the lowest value. In the context of our device response tests encompassing pure PDMS, 0.25 wt%, and 0.75 wt% GCN/PDMS as dielectric layers, we now present evidence indicating that the 0.75 wt% doping concentration yields the highest response sensitivity (Figure S11). This empirical observation faithfully corroborates the earlier mentioned theoretical prediction. Figure 4(b,c) present the measurement results of the change in mutual capacitance for different distances between the finger and the touch sensor. These figures also depict the ratio between the capacitance change and the undisturbed value. In particular, according to Equation (2), there is a logarithmic relationship between capacitance and distance.Therefore, in Figure 4(c) , the horizontal coordinates are expressed in logarithmic terms, and the results show that when the distance is expressed in logarithmic terms, the linearity of the curve is high, with a coefficient of determination (R 2 ) as high as 0.989.The functional relationship between capacitance and distance was then derived from the parameters of the fitted model: (3) C C 0 = 0 .066 ∗ ln D + 0 .680 The distance can be calculated in real time by measuring the capacitance change of the device for various interaction scenarios. For the contact measurement, when the finger is in direct contact with the touch sensor surface, a change in capacitance (ΔC) of 0.72 pF was measured at a baseline capacitance of 2.19 pF. This change corresponds to a mutual capacitance change of 32.8%, indicating a high sensitivity of the touch sensor. The sensor demonstrated a strong response to the presence and touch of a finger, accurately detecting and measuring the capacitance change. During performance tests in a non-contact system, the touch sensor demonstrated the ability to perceive the distance and three-dimensional shape of approaching objects. The capacitance value measured at different distances between the finger and the sensor remained relatively stable. This stability allows for estimating distance based on the corresponding change in capacitance, enabling distance measurement functionality. For example, when the distance between the finger and the sensor is 5 mm, a capacitance change (ΔC) of 0.43 pF was observed. The distance between the finger and the sensor can be determined by analysing the change in capacitance. Similarly, even when the distance between the hand and the sensor is as large as 100 mm, a capacitance change (ΔC) of 0.064 pF was detected, indicating that the touch sensor has a detection range exceeding 100 mm and a wide response range. The sensing unit of the sensor was carefully selected, as shown in Figure 4(d) . To analyse the effect of the sensor on the electric field at the edge of the measured object, a finite element method was employed using COMSOL software. Simulating the electric field at the edge of the capacitive sensor showed that the electric field decreases when the finger enters the electric field. As the finger enters the electric field, it disturbs the electric field. Furthermore, when the distance between the finger and the sensor is reduced from 5 cm to 1 cm, the electric field experiences a noticeable compression, reflecting the impact of proximity on the electric field distribution. In addition, the touch sensor exhibits excellent stability even after 200 cycles of testing. The initial capacitance is fully recovered after the finger is removed, indicating the sensor’s ability to maintain stable performance over multiple usage cycles ( Figure 4(e) ). The response and relaxation times, as depicted in Figure 4(f) , are determined to be 80 ms and 90 ms, respectively, indicating the sensor’s rapid and efficient performance. The serpentine electrode structure employed in the sensor design allows for proper functioning even under moderate stretching conditions. Based on the results obtained from previous tests and simulations, it has been determined that the sensor electrodes can withstand up to 10% tensile strain without experiencing failure. To assess the capacitance change of the sensor, measurements are conducted using a 2% increment gradient of tensile strain, as illustrated in Figure 4(h) . Under the maximum tensile strain applied along the X and Y axes, a slight decrease of approximately 5.5% in relative capacitance is observed. This reduction can be attributed to the weakening the interference effect between adjacent electrodes caused by the stretching of the sensor. However, it should be noted that the strain-induced capacitance change can potentially interfere with the sensor’s accurate touch-sensing capability. To address this issue, integrating a strain sensor with the touch sensor can be implemented, allowing error compensation and calibration of the strain’s effect on capacitance. Through this integration, accurate and reliable touch sensing can be achieved, even in the presence of strain. In order to assess the ultra-low limit function of the proposed sensor in a contact system, a series of water drops weighing 10 mg each was carefully dispensed drop by drop using a precision micropipette. As shown in Figure 4(g) , it is evident that the touch sensor exhibits a response even when a single drop of water is present. The capacitance shows a linear increase from 2.2 pF to 2.6 pF as the number of water drops increases from 1.0 Pa (1 drop) to 5.0 Pa (5 drops), respectively. This behaviour demonstrates the high sensitivity of our proposed sensor to detect and respond to extremely low external loads. 3D recognition and IoT wearable device Non-contact touch sensors with 3D recognition capabilities have greater potential for advancement than touch pressure sensors. They enable precise detection of objects in non-contact scenarios, making them particularly valuable for applications such as electronic skin on robots. Our proposed capacitive sensor can detect nearby objects’ positions and 3D shapes in a non-contact system. Figure 5(a) shows the measurement of finger proximity as a 3D conductive object, demonstrating the sensor’s capability in this regard. As the finger approaches the touch sensor, the mapping data clearly identifies its 3D shape. The finger’s shape becomes more distinct as the distance between the finger and the sensor decreases from 10 mm to 5 mm. Concurrently, the capacitance gradually decreases from −5.6% to −9.7% ( Figure 5(b) ). Figure 5(c) visually demonstrates the finger’s movement from the centre to the edge of the sensor array in the X-Y plane. These results highlight the sensor array’s (5 × 5) ability to detect and determine the shape and position of the object along all three axes. To assess the spatial resolution of the non-contact sensors, separate measurements were conducted on a circular table and a trigonal prism ( Figure 5(d,e) ). The mapped image of the round table distinctly reveals the variations in shape between the bottom and sides, allowing it to be differentiated from the mapped image of the finger. This demonstrates the sensor’s capability to recognise and distinguish different shapes. The sensing array consistently retains over 90% of its performance even after undergoing 1,000 rigorous bending fatigue tests. This resilience can be primarily attributed to the effective compensation provided by the tensile margin within the serpentine array structure, a critical factor for ensuring the applicability and durability of the array in wearable scenarios (Figure S12). Additionally, separate measurements were conducted on the trigon object, and the resulting mapped image exhibited a distinct valley-like depression shape that precisely corresponded to the actual shape of the tested object. Moreover, as a wearable device, the sensor array showcased exceptional stability throughout a wide temperature range while maintaining an impressive performance level of 98.3%, even within the temperature range of the human body’s surface. This outstanding performance signifies its significant potential for human smart skin technology applications, as shown in Figure S13.\n Figure 5. 3D measurement of approaching objects. (a) Schematic diagram of 3D measurement in non-contact mode. The finger is used as the measured object. (b) 3D mapping of the relative capacitance change at two different distances (10 and 5 mm) between the finger and the sensor. The plotted surface shows the mapping result of the relative capacitance change of the 5 × 5 capacitive sensor array. (c) 3D mapping of the sensor’s relative capacitance change after changing the finger’s position. The distance is 5 mm. Detection of various shapes, such as the (d) round and (e) trigonal tables. The sensor’s centre is 5 mm away from all objects under test. (f) Block diagram and operating principle of the integrated sensing system. (g) Schematic diagram of the principle of 3D recognition sensor. (h) Real-time response signals of finger movement are measured by the sensing and displayed on a phone. Building upon the outstanding performance of the 3D recognition sensor array, we have successfully achieved a seamless integration of the sensor array with the circuit board, resulting in a unified system capable of remotely monitoring human motion. This advanced system comprises three key modules, namely the 4 G module, the MCU (Microcontroller Unit), and the sensors. These modules establish wireless communication with various devices such as smartphones, computers, and smartwatches, leveraging the power of 4 G networks. The underlying operational principle of the system is illustrated in Figure 5(f) . The electronic skin is permanently affixed to the wrist, ensuring a continuous connection with a device dedicated to capturing and transmitting the 3D shape and displacement signals of objects using 4 G technology ( Figure 5(g,h) ). We employ a mean filtering algorithm in the data acquisition process, aimed at mitigating interference by smoothing the noise signal generated in the environment through averaging the data over a specific time range. This approach serves as a substitute for conventional shielding methods, enabling precise and highly sensitive responses. The acquired data can be seamlessly displayed in real-time on a mobile phone or any other mobile terminal, thereby facilitating remote monitoring and analysis of the test signal. As demonstrated in the Supplementary Video, the developed sensor array exhibits accurate recognition of multiple movement patterns on the mobile device. This technology holds significant potential across various application scenarios, particularly those requiring virtual keyboard input and high-precision shape recognition scanning."
} | 11,559 |
38927101 | PMC11201641 | pmc | 9,062 | {
"abstract": "In recent years, there has been growing interest in the development of metal-free, environmentally friendly, and cost-effective biopolymer-based piezoelectric strain sensors (bio-PSSs) for flexible applications. In this study, we have developed a bio-PSS based on pure deoxyribonucleic acid (DNA) and curcumin materials in a thin-film form and studied its strain-induced current-voltage characteristics based on piezoelectric phenomena. The bio-PSS exhibited flexibility under varying compressive and tensile loads. Notably, the sensor achieved a strain gauge factor of 407 at an applied compressive strain of −0.027%, which is 8.67 times greater than that of traditional metal strain gauges. Furthermore, the flexible bio-PSS demonstrated a rapid response under a compressive strain of −0.08%. Our findings suggest that the proposed flexible bio-PSS holds significant promise as a motion sensor, addressing the demand for environmentally safe, wearable, and flexible strain sensor applications.",
"conclusion": "4. Conclusions In this study, we introduced a biocompatible material, DNA-curcumin, as a flexible strain-sensitive layer on a graphene/PET substrate using innovative and bio-inspired cutting-edge technology. The utilization of DNA-curcumin provides a cost-effective, tunable, and feasible approach to fabricating a biopolymer-based piezoelectric strain sensor (bio-PSS). Our proposed bio-PSS demonstrates highly sensitive, super mechanical behaviors while enabling bending functionalities. Specifically, it displayed compelling sensitivity, boasting a strain gauge factor 8.67 times greater than that of a conventional metal gauge under an applied compressive strain of −0.08%. Moreover, the bio-PSS demonstrated a rapid response time of 0.8 s under the same compressive strain. According to our analysis, the strain-modulated flexible bio-PSS based on biopolymer materials, such as DNA-curcumin, presents significant commercial viability for future applications in wearable/flexible electronics such as biomedical devices, soft robotics, and artificial intelligence.",
"introduction": "1. Introduction In recent years, flexible devices have attracted significant interest in future electronics/optoelectronics, which has notably boosted their commercial value [ 1 ]. These devices are continually being introduced in an array of advanced functional devices with sensing mechanisms, facilitating the emergence of wearable human–machine systems, soft robotics, and energy harvesting [ 2 , 3 , 4 ]. Strain-controlled flexible devices can be broadly classified into optical, resistance-based, and piezoelectric devices [ 5 ]. Among these, piezoelectric-based flexible devices stand out due to their rapid response time, superior sensitivity, and robust durability. Typically, an electrical strain sensor functions by converting mechanical energy into a specified quantity of electrical energy. The development of strain-controlled sensors incorporating nanomaterials such as nanowires, nanotubes, nanoparticles, and thin films has attracted significant interest [ 6 , 7 ]. For instance, strain-controlled sensors comprising zinc oxide nanowires, graphene, and carbon nanotubes are potential alternatives for the fabrication of new strain-controlled sensors owing to their appealing properties [ 7 , 8 , 9 , 10 ]. In graphene-based strain-controlled sensors, the electrical conductance and principal vibrational frequency of graphene actively depend on its topological structure, which can be controlled by applying strain, making it useful for high-sensitivity strain detection [ 11 , 12 ]. Nanomaterials can serve as structural components and be modified to function as both multifunctional and multidirectional strain sensors at the nanoscale while exhibiting high gauge values. The electromechanical characteristics of these strain-controlled sensors exhibit outstanding functionalities compared to conventional strain sensors, attributed to the combined effects of their excellent electrical properties and large stretching moduli. Recently, conduct polymers (CPs) have been used in the fabrication of sensors [ 13 , 14 ]. Specifically, they are used in different forms such as particles, films, fillers, and matrices. They are also used in the combination of CPs with additives and composites such as polyurethane, cotton, fabric, PDMS, Velostat, Ecoflex, and MXenes [ 13 ]. The development of a non-toxic and biocompatible multifunctional strain sensor that fulfills the requirements of high flexibility, mechanosensitivity, and robustness remains a challenge. Many biocompatible materials, including carbon dots, fluorescent proteins, and deoxyribonucleic acid (DNA), have been previously explored [ 15 , 16 , 17 ]. However, these biocompatible materials present limitations such as the extraction processing methods and protocols for carbon dots and fluorescent proteins. Nonetheless, the development of biocompatible strain-controlled sensors using DNA as the strain-sensing material remains a promising approach [ 18 , 19 ]. Moreover, it is possible to modify the electrical properties of thin-layered DNA-based biomaterials for applications in innovative electronic devices [ 20 , 21 ]. Because of their unique advantages, including molecular wires, variable nanoscale lengths, and self-assembly, DNA biomaterials are excellent alternatives for cutting-edge biocompatible device technologies [ 22 ]. Stemming from their wide energy bandgap (4.7 eV), DNA biomaterials exhibit diverse transport modes such as tunneling (super-exchange), long-range hopping (multi-step), and hopping (single-step) [ 23 , 24 ]. Compared to inorganic materials, DNA has many benefits such as light weight, low-cost preparation protocols, fabrication, and flexibility [ 25 , 26 ]. Several researchers have developed high-performance electronic devices based on DNA biomaterials [ 27 , 28 , 29 ]. DNA may act as a hole transport and electron-blocking agent at the interface of the heterojunction, realizing the conversion of detected photons into electron–hole pairs with a huge conversion efficiency [ 23 ]. Moreover, DNA-based strain-operated devices employing mechanical forces at the nano/micro scale in modern bioscience technology, such as attachable and movable sensors in the human body, have been recently investigated. Curcumin, the most economically accessible material globally, is a naturally occurring yellow-orange compound extracted from the roots of Curcuma Longa. It finds widespread use in food spices, traditional medicines, and cosmetics in Asian countries [ 30 ]. Renowned for its potent anticancer, antitumor, antibacterial, and antioxidant properties [ 31 ], curcumin is also used as a chromophore that generates efficient luminescence in biohybrid light-emitting diode technology [ 29 ]. Researchers have extensively explored the incorporation of curcumin into hydrophilic or biocompatible polymers to produce bioactive polymer composites. The loading of curcumin onto polymeric materials to form electrospun nanofibrous scaffolds or mats has also been pursued [ 32 ]. Interestingly, the mechanical properties of electrospun materials mainly depend on the composition of the polymer matrix and the concentration of curcumin [ 33 ]. In this study, we fabricated a biopolymer-based strain sensor (bio-PSS) using a contemporary pure DNA biopolymer endowed with high feasibility, flexibility, and strain sensitivity. To fabricate the bio-PSS device, we utilized a pure DNA biopolymer extracted from salmon fish sperm and a solvent extract of turmeric (i.e., curcumin). To our knowledge, there are no existing reports on DNA-curcumin biopolymer sensors integrated into polyethylene terephthalate (PET) substrates for the fabrication of flexible bio-PSS devices.",
"discussion": "3. Results and Discussion SPM was used to determine the surface morphology of the DNA/graphene/PET, as illustrated in Figure 2 b. The root-mean-square surface roughness of the sample was approximately 30.64 nm. The thickness of the multi-layer graphene layer (i.e., four layers) and DNA/graphene (i.e., three layers) were ~1.8 nm and ~150 nm on the PET substrate, respectively. XRD measurements of the DNA-curcumin/graphene/PET samples were performed to assess their structural phases. Raman spectroscopy was used to examine the spatial scattering modes of vibrations in a measured sample to detect the graphene, DNA, curcumin, and PET substrates. The Raman spectrum of the flexible DNA-curcumin/graphene/PET sample is presented in Figure 2 c. The strong peaks at 1289 ± 1 cm −1 (C–O band) and 1725 ± 1 cm −1 (C=O) were correlated with the PET substrate. Similar characteristic PET peaks have been reported previously [ 36 ]. The two broad peaks corresponding to the G- and 2D-band were correlated with the graphene conducting layer. One peak at 1586 ± 1 cm −1 (G-band) appeared as a major in-plane vibrational mode. This mode occurs because of the two neighboring carbon atoms in a single layer of graphene. In addition, the second peak at 2685 ± 1 cm −1 (2D-band) is related to the doubly generated resonance linking of the two iTO phonons [ 37 ]. The two distinctive peaks identified at 959 ± 1 cm −1 and 1625 ± 1 cm −1 corresponded to the curcumin sample. These characteristics peaks were also observed by Nong et al. [ 38 ] and reported as νC=O vibration (959 ± 1 cm −1 ) and νC=O and νC=C vibration (1625 ± 1 cm −1 ) in curcumin molecules, respectively. The peak at 1094 ± 1 cm −1 corresponds to the symmetric stretching vibration mode of PO 2 − in the DNA backbone and is considered an internal intensity standard for DNA content [ 39 ]. FTIR microscopy was performed to identify the stretching vibration interactions and harmonics in the DNA-curcumin/graphene/PET sample (refer to Figure 3 a). The stretching vibrations of the bonds at 3200–3500 (O–H group), 1430 (C=C aromatic), and 1277 cm −1 (ν(C–O)) corresponded to curcumin [ 40 , 41 ]. The stretching bands at 2916 (CH 2 asymmetric), 2851 (CH 2 symmetric), and 916 cm −1 (phosphate-ribose skeletal motion) were ascribed to DNA components [ 42 ], and the bonds at 1725 (C=O) and 1406 cm −1 (O – H) originated from the graphene layer [ 42 , 43 ]. The bonds at 1082 (ester C=O stretching) and 1010 cm −1 (benzene-related in-plane vibration) were attributed to the PET substrate [ 7 ]. Figure 3 b illustrates the transmission spectrum of the DNA-curcumin/graphene/PET sample. The strong transmission peak (at 683 nm) was found to have an optical energy bandgap value of 1.81 eV. We compared our sample with a sample without graphene, and the results showed an optical energy bandgap of 1.79 eV at a significant transmission peak of 693 nm. Therefore, the lower bandgap (~20 meV) of the DNA-curcumin/graphene/PET sample may be due to the graphene layer. A comparable reduction in the optical energy bandgap was observed for carbon-based materials [ 44 , 45 ]. A UTM instrument was used to analyze the mechanical flexibility of the DNA-curcumin/graphene/PET sample. Here, both ends of the measured sample were held using the gripping inside the fixtures of the UTM machine as shown inset of Figure 4 . Using a normal stretching strain-stress curve of the measured sample was carried out in a quasi-static state at a strain rate of 0.16 mm/s. However, the UTM measurements were performed under homogeneous uniaxial stretching conditions, and it was observed that the yield point occurred at approximately 22 ± 0.5 GPa, as shown in Figure 4 . There were two distinctive plastic deformations in regions I (approximately 3.26 GPa) and II (approximately 0.07 GPa). Approximately 3.18 times the yield stress point was found at 111 ± 2% of the elongation break point. These results suggest that the mechanical and flexibility qualities were improved by applying strain. Consequently, the DNA-curcumin effect on flexible graphene/PET substrates is due to the enhancement induced by the strain. These features are important for flexible devices. Figure 5 a,b presents the I-V curves under initial and distinct strains (i.e., compressive and tensile directions) for the biopolymer-based flexible DNA-curcumin/graphene/PET strain sensor (bio-PSS). In Figure 5 a,b, the output current of the sensor gradually increases with an increasing applied compressive strain and decreases with an increasing applied tensile strain. To evaluate the real-time working mechanisms and control of the flexible bio-PSS with applied strain, we assessed the injection current and strain of the device in the steady state (I 0 ), change-in state (ΔI = I C − I 0 ), and relative deformation state (ΔI/I 0 = I C − I 0 /I 0 ), where I C and I 0 are the initial and applied strains in the compressive and tensile directions, respectively. The correlation between ΔI/I 0 and the applied strains in the compressive and tensile directions is shown in Figure 5 c,d. These relationships were predicted based on the I-V characteristics ( Figure 5 a,b). The gauge factor is often used to describe the sensitivity of a strain sensor and can be evaluated as (ΔI/I 0 )/ε, which is the relative deformation in the current divided by the applied strain. Figure 6 a,b shows how the applied strains in the compressive and tensile direction loads caused an increase in the gauge factor values. The evaluated gauge factors for the compressive strains of −0.08%, −0.16%, −0.22%, and −0.27% were 268, 322, 383, and 407, respectively, and 323, 347, 362, and 366 for the predicted tensile strains of 0.08%, 0.16%, 0.22%, and 0.27%, respectively. The measured strain gauge values were higher than the standard gauge values (i.e., 2) [ 46 , 47 ]. This illustrates that the strain gauge values of 268 (2 8.06 ), 322(2 8.33 ), 383(2 8.58 ), and 407 (2 8.67 ), which were 8.06, 8.33, 8.58, and 8.67 times higher than the traditional gauge value, were determined by the induced compressive strains of −0.08%, −0.16%, −0.22%, and −0.27%, respectively. Furthermore, the gauge factor values of 323 (2 8.33 ), 347(2 8.44 ), 362(2 8.5 ), and 366 (2 8.52 ) were obtained for the tensile strains of 0.08%, 0.16%, 0.22%, and 0.27%, respectively, which were 8.33, 8.44, 8.5, and 8.52 times higher than the conventional value. In actuality, the gauge factor values are dependent on an applied bias and the strain to control the piezoelectric effect. At a certain value of combined applied bias and strain, the pathways with low activation energy are already conductive (i.e., high current) and cannot be changed with an increasing strain. The values of the gauge factor are restricted due to certain strains already having reached a high conductive state. Further, the gauge factor value influences the materials’ characteristics such as the gauge factor of the graphene layer that ranges from 10 to 15, which is dependent on the number of graphene layers (1–5 layers) [ 48 ]. Furthermore, a DNA/graphene/GaN/PEN hybrid device demonstrates a high gauge factor of 898 [ 45 ]. Moreover, we did not use semiconductor materials in our present device (DNA/graphene/PET) and attained a high gauge factor of 407. This is the first approach we have used in which no semiconductor material is used. When compared to the current results, we will obtain higher gauge factors in future devices. Figure 6 c,d illustrates the features of the response findings of the flexible bio-PSS under compressive and tensile strains. The current versus time plot with applied strains under compressive and tensile loads has a close resemblance in shape, indicating that the bio-PSS responded quickly and well. At an applied compressive strain of −0.08%, the approximate response time was 0.8 s. Further, at an applied tensile strain of 0.08%, the response time of the sample was 1 s. Thus, based on these strain outcomes, the bio-PSS is a promising active sensor that could meet the needs of the development of wearable/flexible sensors in the future."
} | 3,969 |
32893469 | null | s2 | 9,063 | {
"abstract": "Chemoautotrophic bacteria from the SUP05 clade often dominate anoxic waters within marine oxygen minimum zones (OMZs) where they use energy gained from the oxidation of reduced sulfur to fuel carbon fixation. Some of these SUP05 bacteria are facultative aerobes that can use either nitrate or oxygen as a terminal electron acceptor making them ideally suited to thrive at the boundaries of OMZs where they experience fluctuations in dissolved oxygen (DO). SUP05 metabolism in these regions, and therefore the biogeochemical function of SUP05, depends largely on their sensitivity to oxygen. We evaluated growth and quantified differences in gene expression in Ca. T. autotrophicus strain EF1 from the SUP05 clade under high DO (22 μM), anoxic, and low DO (3.8 μM) concentrations. We show that strain EF1 cells respire oxygen and nitrate and that cells have higher growth rates, express more genes, and fix more carbon when oxygen becomes available for aerobic respiration. Evidence that facultatively aerobic SUP05 are more active and respire nitrate when oxygen becomes available at low concentrations suggests that they are an important source of nitrite across marine OMZ boundary layers."
} | 297 |
26413054 | PMC4568871 | pmc | 9,064 | {
"abstract": "Native rhizobia are ideal for use as commercial legume inoculants. The\ncharacteristics of the carrier used to store the inoculants are important for the\nsurvival and symbiotic potential of the rhizobia. The objective of this study was to\ninvestigate the effects of peat (PEAT), perlite sugarcane bagasse (PSB),\ncarboxymethyl cellulose plus starch (CMCS), and yeast extract mannitol supplemented\nwith mannitol (YEMM) on the survival, nodulation potential and N 2 fixation\ncapacity of the native strains Sinorhizobium mexicanum ITTG\nR7 T and Rhizobium calliandrae LBP2-1 T and\nof the reference strain Rhizobium etli CFN42 T . A\nfactorial design (4 × 3) with four repetitions was used to determine the symbiotic\npotential of the rhizobial strains. The survival of the strains was higher for PEAT\n(46% for strain LBP2-1 T , 167% for strain CFN42 T and 219% for\nstrain ITTG R7 T ) than for the other carriers after 240 days, except for\nCFN42 T kept on CMCS (225%). All the strains kept on the different\ncarriers effectively nodulated common bean, with the lowest number of nodules found\n(5 nodules) when CFN42 T was kept on CMCS and with the highest number of\nnodules found (28 nodules) when ITTG R7 T was kept on PSB. The nitrogenase\nactivity was the highest for ITTG R7 T kept on PEAT (4911 μmol\nC 2 H 4 per fresh weight nodule h −1 ); however, no\nactivity was found when the strains were kept on YEMM. Thus, the survival and\nsymbiotic potential of the rhizobia depended on the carrier used to store them.",
"conclusion": "Conclusions Peat and perlite sugarcane bagasse were shown to be the most appropriate carriers to\nstore the rhizobial strains (2 × 10 9 cells g −1 ) and to maintain\ntheir survival. Strains Sinorhizobium mexicanum ITTG R7 T ,\n R. calliandrae LBP2-1 T and R. etli \nCFN42 T kept on perlite sugarcane bagasse induced the largest number of\nnodules in the common bean; however, their N 2 fixation capacity was lower\nthan when the strains were kept on peat. Consequently, no direct relationship existed\nbetween nodule formation in the host plant and N 2 fixation capacity.",
"introduction": "Introduction The inoculation of the plant rhizosphere or seeds with rhizobia, i.e. ,\nN 2 -fixing bacteria, to stimulate plant growth has been used for a long\ntime ( Lopez-Lopez et al. , 2010 ).\nSymbiosis between the N 2 -fixing bacteria and the plant reduces the need for\ninorganic N fertilizer applications. The use of native rhizobia has been recommended\nbecause these bacteria adapt easily to the specific environmental conditions, which\nfacilitates their survival and the successful nodulation of the host plant ( Romdhane et al. , 2008 ; Topre et al. , 2011 ). The rhizobial inoculants are kept on a support or a carrier so that these bacteria can\nbe stored for a long period and used when required ( Albareda et al. , 2008 ). The material used as a carrier\nshould allow the survival of the rhizobia and preserve their capacity to form nodules\nand to fix N 2 . A high-grade carrier should have high water retention and\nstable pH, and it should be inexpensive, constitutive, nontoxic for the strain or\nenvironment and easy to sterilize ( Swelim et\nal. , 2010 ). Peat is one of the most commonly used carriers ( Albareda et al. , 2008 ), although\nother substrates have been used. For instance, sugarcane bagasse and perlite were tested\nas carriers for Bradyrhizobium japonicum strain CB1809 ( Khavazi et al. , 2007 ). When the carrier was\nstored at 4 °C for six months, the bacterial inoculant survival was high, and a density\nof 10 9 cells g −1 was maintained. Mixtures of carboxymethyl\ncellulose and starch maintained a stable cellular concentration of B.\njaponicum strain BR3267 when stored at 20–26 °C for 180 days ( Fernandes-Júnior et al. , 2009 ). A\nstable rhizobia population of Sinorhizobium fredii SMH12 was also\nobtained when the cells where kept in yeast extract mannitol supplemented with 1%\nmannitol (YEMM) at 25 °C for 100 days ( Albareda\n et al. , 2008 ). While these carriers were able to maintain the rhizobia population, considering other\nfactors, such as the stability and viability of the biofertilizer, which might vary\nbetween the strains used as biofertilizer, is necessary ( Fernandes-Júnior et al. , 2012 ). Studying how the different\ncarriers affect the biological activity of microorganisms, the infectivity of rhizobia\ninoculants and the symbiotic potential of the strains used as inoculants is also\ndesirable ( Hungria et al. ,\n2005 ). Therefore, the objective of the present study was to determine the effects\nof peat (PEAT) and perlite sugarcane bagasse (PSB) as solid carriers and of\ncarboxymethyl cellulose plus starch (CMCS) and YEMM as liquid carriers on the survival,\npotential for nodulation of the common bean ( Phaseolus vulgaris L.) and\ncapacity for N 2 fixation of the native strains Sinorhizobium\nmexicanum ITTG R7 T and Rhizobium calliandrae \nLBP2-1 T and of the reference strain Rhizobium etli \nCFN42 T .",
"discussion": "Results and Discussion Physical characteristics of the carriers The pH of the peat used in this study was 3.8. This carrier normally has a pH ranging\nfrom 3.5 to 4.5 ( Somasegaran and Hoben, 1985 ).\nThe pH was adjusted to 6.7 with 35 g Na 2 CO 3 so that a near\nneutral pH was obtained, which maintains the viability of the rhizobia ( Vincent, 1970 ). The WHC of peat in this study was\n282%, which is higher than the 120% reported by Somasegaran and Hoben (1985) . The origin of the peat might have resulted\nin a higher WHC ( Tittabutr et al. ,\n2007 ). The pH of the PSB was 7.7, which is appropriate for the growth of\nrhizobia ( Albareda et al. ,\n2008 ). The WHC of the PSB was 512%, which is higher than the value reported\nfor perlite (400%) ( Khavazi et al. ,\n2007 ). The high WHC of both carriers favors the enzymatic processes\ninvolved in the degradation of the organic material that provide important nutrients\nsuch as phosphorus for the rhizobial bacteria. The carrier CMCS, which is prepared by mixing carboxymethyl cellulose and starch,\nallowed the formation of a polymer with a viscosity of 414 cP. This viscosity favors\nthe survival of the rhizobia. However, the initial pH was 10.8, which decreases the\nviability of the bacteria; thus, MgO was added. This addition adjusted the pH to 6.7,\nwhich is the pH recommended for rhizobia carriers ( Fernandes-Júnior et al. , 2009 ). The YEMM liquid carrier\n(pH 6.7) had a viscosity of only 1.11 cP. This result suggested that this liquid\ncarrier might decrease the survival of the rhizobia as reported by Tittabutr et al. (2007) and by Albareda et al. (2008) . Survival of rhizobia strains in different carriers The survival of strains S. mexicanum ITTG R7 T , R.\ncalliandrae LBP2-1 T and R. etli \nCFN42 T was determined in two solid and two liquid carriers kept at 25\n°C for 240 days ( Figure 1 ). The survival of the\nrhizobia strains differed between the carriers. After 240 days, the survival of the\nrhizobia was higher in the solid carriers PEAT and PSB than in the liquid carriers\n( Figure 1a and 1b ). In the PEAT and PSB\ncarriers, the cellular concentration of all strains remained at 2 × 10 9 \ncells g −1 , which is recommended for the production of biofertilizers\n( Ben Rebah et al. , 2007 ).\nPSB and PEAT contain high concentrations of organic material and essential nutrients\n( Khavazi et al. , 2007 ),\nmaintaining the viability of the rhizobia. Figure 1 Survival of the ITTG R7 T and LBP2-1 T strains and of\nthe reference strain CFN42 T in the carriers a) PEAT, b) PSB, c) YEMM\nand d) CMCS stored at 25 °C for 240 days The cellular concentration of the R. etli CFN42 T strain\nsignificantly decreased (p < 0.05) in the liquid carrier YEMM after 60 days ( Figure 1c ), while the cellular concentrations of\nthe ITTG R7 T and LBP2-1 T strains remained at >\n10 8 cells g −1 . In the CMCS carrier, the strains maintained a\nviable population of > 10 8 bacteria g −1 until day 240 ( Figure 1d ), which is sufficient for use as\nbiofertilizers ( Fernandes-Júnior et\nal. , 2009 ). The high survival of the rhizobia in this carrier\nmight be due to its rheological and chemical characteristics, e.g. ,\nhigh viscosity and hygroscopicity. Flores da Silva\n et al. (2012) reported that survival of\n Gluconacetobacter diazotrophicus and Azospirillum\namazonense was 10 9 cfu mL −1 in a medium of\nCMC-starch supplemented with MgO after 120 days. Several researchers ( e.g. , Deaker\n et al. , 2004 ; Fernandes-Júnior et al. , 2009 ) reported that different\nphysical factors affect the viability and survival of rhizobia in the carrier. In the\npresent study, the pH, WHC and viscosity were monitored to determine their possible\neffects on the survival and viability of the rhizobia studied ( Table 1 ). After 240 days, the pH of the YEMM liquid\ncarrier decreased from 6.7 to 4.9 when inoculated with the CFN42 T strain;\nto 6.4, with the ITTG R7 T strain; and to 4.8, with the LBP2-1 T \nstrain. The viability of the CFN42 T and ITTG R7 T strains and\ntheir concentrations were negatively affected by a decrease in pH during storage,\nthus decreasing their symbiotic potentials. Table 1 Viscosity (cP), WHC and pH of the carrier and viability (%) of strains\n R. etli CFN42 T , S. mexicanum \nITTG R7 T , and R. calliandrae LBP2-1 T \nkept on PEAT, PSB, CMCS, and YEMM for 240 days \n Rhizobium etli CFN42 T \n \n Sinorhizobium mexicanum ITTG R7 T \n \n Rhizobium calliandrae LBP2-1 T \n \n \n \n \n \n \n Carrier Days pH Viscosity Viability pH Viscosity Viability pH Viscosity Viability YEMM 0 6.7 A a \n 0.8 C 100 A 6.7 AB 0.8 A 100 A 6.6 A 0.8 A 100 A 14 5.5 B 1.5 A 12 B 5.6 E 0.9 A 15 B 5.8 AB 1.1 A 36 B 60 4.8 D 0.9 BC 5 C 6.2 D 1.1 A 15 B 5.7 AB 1.2 A 4 C 120 4.8 D 0.8 C 0 D 6.5 BC 1.2 A 8 C 5.3 BC 1.2 A 3 C 180 5.1 C 0.9 BC 0 D 6.7 A 1.5 A 1 D 6.1 A 1.6 A 1 C 240 4.9 CD 1.0 B 0 D 6.4 CD 1.5 A 7 C 4.8 C 1.3 A 1 C CMCS 0 6.7 C 190.5 A 100 C 6.8 B 190.5 A 100 A 6.7 E 190.5 A 100 A 14 6.7 C 7.2 C 295 B 6.7 B 16.7 BC 30 B 7.4 C 24.3 BC 16 B 60 6.7 C 38.7 B 269 B 7.4 A 33.2 B 27 B 7.7 B 34.6 B 20 B 120 7.1 AB 9.0 C 219 B 7.6 A 30.5 B 6 C 7.9 A 30.6 BC 4 C 180 7.4 A 4.9 C 507 A 6.6 B 7.7 C 2 C 7.7 AB 21.3 BC 5 C 240 7.6 A 3.1 C 225 B 7.6 A 7.7 C 7 C 7.2 D 6.6 C 16 B \n \n Carrier Days pH WHC b \n Viability pH WHC Viability pH WHC Viability \n \n PSB 0 7.7 A 137 A 100 A 7.7 B 123 A 100 AB 7.8 A 134 A 100 A 14 7.5 B 137 A 206 A 7.9 A 123 A 93 AB 7.7 AB 133 A 29 CD 60 7.2 C 113 AB 106 A 7.3 C 150 A 122 A 7.0 D 110 AB 54 BC 120 7.2 C 90 BC 153 A 7.3 C 103 A 114 AB 7.0 D 76 BC 67 B 180 7.2 C 67 C 211 A 7.3 C 156 A 71 B 7.4 BC 60 C 37 CD 240 7.2 C 23 D 139 A 7.3 C 58 A 21 C 7.3 CD 37 C 13 D PEAT 0 6.7 B 120 A 100 C 6.7 D 117 A 100 C 6.7 BC 134 A 100 A 14 6.8 B 120 A 413 AB 6.9 CD 117 A 116 C 7.0 B 134 A 10 C 60 6.9 AB 140 A 492 A 7.2 AB 127 A 204 AB 6.7 C 102 A 37 BC 120 6.9 AB 161 A 553 A 7.3 A 107 A 140 BC 7.2 A 113 A 47 B 180 7.1 A 122 A 203 BC 7.1 AB 171 A 163 ABC 7.2 A 93 A 110 A 240 7.1 A 102 A 167 C 7.1 BC 109 A 219 A 7.3 A 105 A 46 B a Values with the same capital letter do not significantly differ over time,\n i.e. , within the column (p < 0.05) b WHC: Water holding capacity (%). Pearson correlation analysis showed that the pH and viscosity of the liquid carriers\nsignificantly affected the viability of strain LBP2-1 T and that only the\nWHC of the PSB affected viability (p < 0.05) ( Table 2 ). The viability of ITTG R7 T strain significantly\ncorrelated with the viscosity of the liquid carrier and with the pH of the PEAT\ncarrier (p < 0.05). The viability of the CFN42 T strain significantly\ncorrelated only with the pH of the YEMM carrier and with the viscosity of the CMCS\ncarrier (p < 0.05). Table 2 Pearson’s correlation coefficient and p value between viability and\nviscosity, WHC or pH for the strains R. etli CFN42 T ,\n S. mexicanum ITTG R7 T , and R.\ncalliandrae LBP2-1 T kept on PEAT, PSB, CMCS, and YEMM for\n240 days Viability \n \n \n R. etli CFN42 T \n \n S. mexicanum ITTG R7 T \n \n R. calliandrae LBP2-1 T \n \n \n \n \n \n \n Carrier R value p value R value p value R value p value YEMM pH 0.969 < 0.001 0.324 0.189 0.737 < 0.001 Viscosity −0.280 0.261 −0.560 0.019 −0.498 0.036 CMCS pH 0.335 0.175 −0.198 0.432 −0.837 < 0.001 Viscosity −0.609 0.007 0.942 < 0.001 0.966 < 0.001 PSB pH −0.323 0.191 0.053 0.835 0.361 0.141 WHC −0.084 0.740 0.254 0.310 0.495 0.037 PEAT pH −0.140 0.579 0.626 0.006 0.159 0.526 WHC 0.253 0.310 −0.097 0.702 −0.128 0.613 Several strains of Rhizobium produce exopolysaccharides (EPSs),\nwhich facilitate symbiosis ( Luque-Castellane\n et al. , 2014 ). In the present study, EPS production was\nhigher for the CFN42 T strain than for the native ITTG R7 T and\nLBP2-1 T strains when kept in the YEMM carrier (data not shown).\nRhizobial EPSs are composed of different types of monosaccharides and secreted into\nthe environment. Rhizobium leguminosarum strains produce acidic EPSs\nthat are composed of glucose, glucuronic acid and galactose, which may cause changes\nin the pH of the culture medium ( Skorupska et\nal. , 2006 ). Our results indicated that the exopolysaccharides\nproduced by the rhizobia strains used in the present study decreased the pH, thereby\nreducing the viability of the bacteria in the carrier. When the CMCS support was inoculated with the CFN42 T , ITTG R7 T \nor LBP2-1 T strain, the pH was maintained between 6.7 and 7.2 ( Table 1 ), which is suitable for the growth of\nrhizobia cells. In the CMCS carrier, the viscosity decreased significantly from 190.5\ncP to 3.1 cP for the CFN42 T strain, to 7.7 cP for ITTG R7 T and\nto 6.6 cP for LBP2-1 T (p < 0.05). These results indicated that the\nviscosity affected the viability of the ITTG R7 T and LBP2-1 T \nstrains, which could be because the rhizobial cells used the carrier as a C source\n( Fernandes-Júnior et al. ,\n2009 ). The WHC and pH are the factors that primarily affect the survival of rhizobia strains\nin carriers ( Ben Rebah et al. ,\n2002 ). In the present study, the pH remained stable in the inoculated PSB\ncarrier. However, the WHC decreased significantly from an initial value of 137% to\n23% when the CFN42 T strain was added, to 58% when the ITTG R7 T \nstrain was added and to 37% when the LBP2-1 T strain was added ( Table 1 ). The high amount of water retained in\nthe PSB carrier favored the enzymatic processes involved in the degradation of\norganic matter that generates nutrients required for bacterial growth ( Ben Rebah et al. , 2007 ). Peat is the most commonly used carrier to store rhizobia used as biofertilizer ( Khavazi et al. , 2007 ; Kaira et al. , 2010 ). This\ncarrier is excellent for storing microorganisms because peat has a high WHC, chemical\nand physical uniformity, a lack of toxic compounds and no environmental risk ( Ferreira and Castro, 2005 ; Ferreira et al. , 2010 ). In the present\nstudy, the WHC values remained constant when peat was inoculated with the ITTG\nR7 T strain; the viability of this strain increased significantly\ncompared with the other evaluated strains during 240 days of storage (p < 0.05)\n( Table 1 ). Plant growth, nodulation and nitrogen fixation of Phaseolus\nvulgaris inoculated with different biofertilizers Plants treated with strain CFN42 T stored in the CMCS carrier had the\nhighest dry weight (0.83 g) ( Figure 2 ). The\nCMCS carrier is a polymer blend, which favors the survival of the bacteria and the\nnodulation of different legumes, while the starch served as a C substrate ( Fernandes-Júnior, 2009 ). Aeron et al. (2012) reported that\n Mucuna pruriens plants inoculated with Ensifer\nmeliloti RMP6 and Bradyrhizobium sp . \nBMP7 T strains kept in a CMC carrier significantly increased plant\nbiomass, the number of nodules and other plant growth parameters. The R.\netli strain CFN42 T , in combination with other diazotrophic\nbacteria, has a positive effect on the development of various legume and non-legume\nplants ( Rosenblueth and Martinez-Romero,\n2004 ). Figure 2 Plant growth, nodulation and nitrogen fixation of Phaseolus\nvulgaris cv. Jamapa inoculated with different rhizobial\nstrains All the strains kept on the different carriers effectively nodulated bean plants;\nhowever, the number of nodules formed was highest when inoculated with strain ITTG\nR7 T kept on the PSB carrier (p < 0.05). PSB is a carrier that\nprovides stability to the bacterial cells and essential nutrients for symbiotic\nN 2 fixation while maintaining cell viability during infection and\nnodule formation on the host plant ( Khavazi\n et al. , 2007 ). The N fixed by inoculated plants was\nsignificantly different between the treatments (p < 0.05). Plants inoculated with\nLBP2-1 T kept on CMCS fixed the largest amount of N (0.50 mg\nkg −1 ). Rincón-Rosales et\nal. (2013) reported similar findings and found that the\n R. calliandrae strain LBP2-1 T isolated from the\ntropical legume Calliandra grandiflora grown in acidic soil and with\nhigh amounts of aluminum had a high potential for nodulation and nitrogen\nfixation. The nitrogenase activity was higher in bean plants inoculated with the ITTG\nR7 T strain kept on peat. As mentioned before, peat is a commonly used\ncarrier due to its favorable characteristics ( Khavazi\n et al. , 2007 ; Ferreira\n et al. , 2010 ). Lloret\n et al. (2007) reported that the strain ITTG\nR7 T has high nitrogenase activity and nodulation capacity when used to\ninoculate P. vulgaris and other tropical legumes."
} | 4,355 |
29085916 | null | s2 | 9,067 | {
"abstract": "Microorganisms are in constant competition for growth niches and environmental resources. In Gram-negative bacteria, contact-dependent growth inhibition (CDI) systems link the fate of one cell with its immediate neighbor through touch-dependent, receptor-mediated toxin delivery. Though discovered for their ability to confer a competitive growth advantage, CDI systems also play significant roles in inter-sibling cooperation, promoting both auto-aggregation and biofilm formation. In this review, we detail the mechanisms of CDI toxin delivery and consider how toxin exchange between isogenic sibling cells could regulate gene expression."
} | 160 |
39974203 | PMC11835149 | pmc | 9,068 | {
"abstract": "l -Homoserine embodies significant\nfunctional properties\nas an amino acid of utmost importance, showcasing remarkable utility\nwithin the industrial realm. As synthetic biology and biotechnology\ncontinue to advance, the synthesis of l -homoserine through\nmicrobial fermentation emerges as a compelling and eco-conscious approach.\nThis Review summarized the recent progress in systematic metabolic\nengineering strategies for improving l -homoserine production\nin Escherichia coli , including blocking the competing\nand degrading pathways, strengthening the key enzymes and precursors,\nand genetic modification of transport systems. We discussed and compared\nthese systematic metabolism strategies, which have laid a solid foundation\nfor the microbial industrial production of l -homoserine.",
"conclusion": "Conclusion and Outlook l -Homoserine is an\nimportant functional amino acid and\nhas a high industrial application value. In this Review, the metabolic\nstrategies employed in E. coli for the elevated synthesis\nof l -homoserine are comprehensively outlined, thereby establishing\na solid basis for the industrialization thereof. The current\nstrategies for modifying E. coli to\nproduce l -homoserine are not yet perfect. In-depth research\ncould be carried out on different aspects. A comprehensive analysis\nand optimization of the cellular metabolic synthesis pathways can\nbe achieved via advanced synthetic biology techniques, metabolic network\nanalysis, and transcriptomics analysis. The rationally designed metabolic\npathways can be conducted to effectively coordinate the production\nof l -homoserine and its intermediates, as well as establish\na harmonious relationship between l -homoserine production\nand microbial growth. Furthermore, for the accumulation of intermediates\nby blocking degradation and competing pathways, the strain results\nin deficiencies and impacts cell growth. It necessitates the addition\nof nutrients in large-scale fermentation, thereby increasing production\ncosts. The current research mainly focuses on the genetic modification\nof l -homoserine production strains, with minimal research\non the influence of fermentation conditions. Consequently, the next\nstep should involve systematic optimization of the fermentation process.\nMoreover, C. glutamicum has successfully achieved\nthe efficient production of l -lysine, l -glutamic\nacid, l -threonine, etc. It should also have great potential\nfor the efficient production of l -homoserine. However, there\nis limited research on the production of l -homoserine by C. glutamicum . Therefore, one of the future directions is\nto employ metabolic engineering strategies and improve the production\ncapacity of l -homoserine in C. glutamicum . Additionally, it is also crucial to develop other non-model chassis\nfor the efficient production of l -homoserine. For instance,\nusing the fastest-growing bacterium Vibrio natriegens may greatly shorten the fermentation time. 69 We believe that with the continuous development of synthetic biology\nand metabolic engineering technologies, the biosynthesis and industrialization\nof l -homoserine is expected.",
"introduction": "Introduction Homoserine\nwas first chemically synthesized by Fischer and Blumenthal\nin 1907. 1 l -Homoserine (C 4 H 9 NO 3 ), also known as 2-amino-4-hydroxybutyric\nacid, is a tetracarbon amino acid belonging to the aspartate family,\nand is a non-proteinogenic amino acid, 2 serving as a crucial precursor for the biosynthesis of l -threonine, l -methionine and other essential amino acids,\nwhich are widely used in the fields of medicine, chemical industry\nand agriculture 3 − 6 ( Figure 1 ). It can\nbe used as a precursor to synthesize important compounds such as 1,3-propanediol, 7 2,4-dihydroxybutyric acid, 8 l -homoserine lactone, 9 isobutanol, 9 l -cysteine, 10 etc. Using l -homoserine as a chiral\nsource, the novel herbicide l -glufosinate was also obtained\nthrough chemical processes, resulting in l -glufosinate with\na total yield of 76.5% and an enantiomeric selectivity of 93.8%. This\nsynthetic route exhibits a relatively uncomplicated and feasible operation,\nwith promising prospects for industrialization. l -Homoserine\nis also an essential and functional amino acid, capable of serving\nas an antifungal medication and possessing the potential as a skin\nhydrating agent. 11 It can be used as a\nfeed additive in agriculture to improve the resistance of plants to\ndiseases, 12 exhibiting similar functions\nas l -threonine. 13 Thus, l -homoserine holds significant significance in the realms of biochemistry,\npharmaceuticals, cosmetics, and related sectors. Consequently, the\nmarket’s incessant growth necessitates an urgent expansion\nof the industrial manufacturing of l -homoserine. 14 Figure 1 Representative examples of l -homoserine applications. Traditional production of l -homoserine\nmainly relies on\nchemical synthesis. There are two chemical approaches: dissolving l -methionine in water and placing it together with CH 3 I in a flask, followed by steps such as vacuuming, condensing, refluxing,\npurifying, and drying, resulting in a yield of 65.8% for the product\nhomoserine of 65.8%. Alternatively, by combining γ-butyrolactone\nwith PBr 3 in a flask, heating, reacting, extracting, and\nrecrystallizing, one can obtain homoserine in a yield of 70%. However,\nthe homoserine synthesized through chemical approaches is a racemic\nmixture. To obtain a pure form of l -homoserine, complex separation\nand purification procedures are necessary, significantly increasing\nthe production cost of l -homoserine. 15 Nevertheless, the production of l -homoserine by microbial\nfermentation has the advantages of mild reaction conditions and is\nenvironment-friendly, which is the future technology for industrial\nproduction of l -homoserine. 16 , 17 Since Plachý\net al. first reported that l -homoserine could be produced\nby microbial fermentation from Corynebacterium SP.\nin 1985, 18 people have aroused great interest\nin microbial production of l -homoserine and its derivatives. 19 − 22 Until now, l -homoserine has been successfully produced\nin Escherichia coli ( E. coli ) ( Table 1 ) and corynebacterium\nglutamicum ( C. glutamicum ). 23 , 24 Although C. glutamicum has made some progress in\nfermenting and producing l -homoserine, its application is\nlimited due to its long fermentation cycle and relatively low current\nyield. On the other hand, E. coli has been chosen\nas the host strain by most researchers due to its clear genetic background,\nrapid reproduction, efficient gene manipulation, and relatively simple\ncultivation conditions. 25 − 27 Furthermore, E. coli currently has a higher yield in the fermentation production of l -homoserine compared to C. glutamicum . However,\nin the process of industrialization of l -homoserine production\nby microbial fermentation, it is necessary to further increase the\nyield and reduce the economic cost. With the continuous development\nand promotion of system metabolic engineering technology, the production\nof l -homoserine has been a breakthrough progress. Table 1 Metabolic Engineered E. coli Strains for l -Homoserine Production Chassis Genotype Titer (g/L) Volumetric productivity (g/L/h) Yield (g/g) Ref E. coli W3110 ΔlysA,ΔmetA,ΔthrBC,ΔiclR,ΔgltA,ΔpykA,ΔpykF/Pkk-miniPtac-thrA 35.8 (7 L fermenter) 0.82 0.35 ( 2 ) E. coli W3110 ΔlacI,ΔlysA,ΔmetA,ΔthrBC,Δtdcc/pBRmetl-pNrhtA 39.54 (15 L fermenter) 0.9 0.29 ( 32 ) E. coli W3110 ΔlacI,ycgH::P trc -thrA fbr ,P thrABC ::P fliC ,ydeU::P trc -thrA fbr ,yjhE::P trc -thrA fbr ,P ppc ::P trc ,ylbE::P trc -aspC,ycdN::P trc -aspA,tfaD::P trc -thrA fbr ,yeeL::P trc -ppc,ycjV::P trc -lysCfbr\ncgl ,yjiP::P lpp -rhtA,ilvG::P trc -pntAB,ygaY::P trc -pntAB,yeeP::P trc -asd tmo ,yghX::P trc -adh pae 85.29 (5 L fermenter) 1.78 0.43 ( 33 ) E. coli W3110 ΔmetJ,ΔmetI,ΔmetB,Trc-metL,ΔthrB,ΔmetA,Trc-thrA,ΔlysA,ΔlacI::Trc-rhtA,Trc-rhtA,Trc-eamA,ΔiclR,ΔptsG,\nΔgalR,Trc-glk,Trc-gltB/pACYC-pyc P458S -thrA G433R -lysC 37.57 (5 L fermenter) 0.35 0.31 ( 56 ) E. coli BW25113/F 45 ΔmetAΔlysAΔthrBΔlacIΔsthA::P tac -pntABΔldhAΔpoxBΔpflBΔfliK::P tac -rhtBΔyeeJ::P 119 -rhtBΔptsG::P 119 -glkΔgalR::P 119 -zglfΔompT::P tac -ppcΔiclRΔyjiV::P tac -aspC-gdhApS95s-thrA*-asd-aspA-RBS2800 84.1 (5 L fermenter) 1.96 0.5 ( 44 ) E. coli W3110 P thrB ::P fliC ,ylbe::P trc -thrA fbr ,yjit::P trc -ppc,mbhA::P trc -aspA,rph::P trc -thrA fbr yjip::P trc -thrA fbr ,gapC::P trc -pntAB, ygay::P lpp -rhtA 60.1 (5 L fermenter) 1.25 0.42 ( 34 ) E. coli W3110 ΔlysAΔthrBΔmetAΔlacIΔldhAΔadhE\nΔpflBΔptsGΔP galP ::P lac ΔP ppc ::P trc ΔiclRΔarcAΔP aspA ::P trc ΔP glk ::P lac ΔP asd ::P trc ΔgalP::glf/pBbA1K\nharboring metL gene, controlled by grac/RBS3 promoter/pTrc99A harboring\nrhtA gene, controlled byPrhtA promoter 110.8 (2 L fermenter) 1.82 0.62 ( 50 ) E. coli W3110 ΔlysAΔmetAΔthrBC-ppc(trc)-thrA(trc)-asd(trc)-pntAB(trc)-rhtA(trc)\ncontaining pKK-metL-hok2 44.4 (5 L fermenter) 0.93 0.21 ( 49 ) This Review summarizes recent advances in the systematic\nmetabolism\nstrategies used for l -homoserine production in engineered E. coli strains, including genetic modifications of biosynthetic\npathways and transport systems and also the existing bottlenecks and\nperspectives."
} | 2,311 |
26774999 | PMC4766943 | pmc | 9,070 | {
"abstract": "The tree model and tree-based methods have played a major, fruitful role in evolutionary studies. However, with the increasing realization of the quantitative and qualitative importance of reticulate evolutionary processes, affecting all levels of biological organization, complementary network-based models and methods are now flourishing, inviting evolutionary biology to experience a network-thinking era. We show how relatively recent comers in this field of study, that is, sequence-similarity networks, genome networks, and gene families–genomes bipartite graphs, already allow for a significantly enhanced usage of molecular datasets in comparative studies. Analyses of these networks provide tools for tackling a multitude of complex phenomena, including the evolution of gene transfer, composite genes and genomes, evolutionary transitions, and holobionts.",
"conclusion": "Concluding Remarks: Networks Enhance Our Comprehension of Life's Complexity The complexity and diversity of phenomena acknowledged and investigated by evolutionary biologists is striking, and growing: it now goes well beyond the identification of lineage divergence from a single common ancestor, enhancing what is considered as the Darwinian paradigm. When pushed to its limits, introgression might result in the integration of laterally acquired features into a sustainable structure, controllable by regulatory systems, which may themselves be the result of introgression. A technical and theoretical transition has accompanied this broadening of scope within the evolutionary paradigm. Namely, network models and methods, never truly absent in biological studies [81] , have been developed and implemented. Hence, they now offer powerful complementary approaches to evolutionary studies, which will enhance the exploitation of molecular datasets in multiple directions. The routes and genetic goods of microbial social life, the origins and combination rules of composite genes, and the genetic transformation coupled with major evolutionary transitions, can readily be investigated using powerful, inclusive, comparative network-based tools. The diversity of such tools is itself constantly increasing: the multi-thresholded sequence-similarity networks, (multiplex) genome networks, and the bipartite graphs presented here, allow one to perform multi-agent and multilevel comparative analyses, and may become as familiar to evolutionary biologists as phylogenetic trees in the near future. Importantly, these network tools have not yet been used at their full potential (see Outstanding Questions). In particular, they could also be used to analyze the evolution of communities of synthetic microorganisms, biofilms, and holobionts. These latter collective systems encompass a challenging complexity. For example, holobionts rely on a multiplicity of interacting transmission systems and channels for their development and evolution that differ in the microbes and in their hosts. This heterogeneity complicates the understanding of the causes of holobionts’ collective phenotypes by traditional methods, even in the metazoan world [82] . Applying a network analytical framework to holobiont studies may be an innovative way to decipher what traits, long held as characteristic of a single animal (i.e., species incompatibility, self-immunity, or possibly behavior 83 , 84 ), or of an individual organism/biofilm (i.e., health conditions 85 , 86 or drug resistance), originate from complex interactions, at multiple biological levels, and how these involve microbes and their genes. More generally, network-thinking has lots to contribute to microbiology. Outstanding Questions What are the rules of domain and gene shuffling in microbes? Sequence-similarity networks provide fast and effective means for systematic analyses of the evolution of composite genes, by simultaneously detecting families of components contributing to composite gene families. The phylogenetic origins and the functional categories of these components will show whether microbes are using transferred genes to create new composite genes in their genomes. For example, do the notoriously mosaic haloarchaeal genomes harbor composite genes of bacterial origin? Does the proportion of composite genes in microbes change with the environment? Can one introduce models of nucleotide substitution into sequence-similarity networks in order to make them more realistic with regard to sequence evolution? Is every gene everywhere? Gene-similarity networks applied to large-scale metagenomic data and gene-sharing networks featuring environments instead of genomes as their nodes will provide inclusive novel ways to address this important question. These graphs will show whether similar sequences are found in geographically or ecologically similar environments, and serve to detect ubiquitous and endemic genes sets. What phenotypes in holobionts have multiple origins, that is, did not evolve within a single phylum but emerged from a biological collective? Bipartite graphs with microbial taxa or microbial gene families as bottom nodes and with animal or human hosts as top nodes will immediately allow for the identification of phylogenetically heterogeneous groups of microbes, or groups of gene families in microbes, always associated with a particular host-level phenotype. How do processes of molecular evolution occurring at the level of the microbiota affect eukaryotic hosts? The microbial gene families–eukaryotic host bipartite graphs described above can be refined to take into account information about the molecular evolution of the gene families (e.g., their rate of evolution, or whether to what extent and by what mobile elements each gene family was eventually transferred). This adds an explicit evolutionary dimension to the bottom-level nodes, allowing one to evaluate, for example, the impact of lateral gene transfer, operating at the microbial level, on the phenotypes of the eukaryotic host. For example, it becomes easy to test whether laterally transferred genes, mobilized by a broader range of mobile elements, are more largely distributed in human hosts than are resident gene families of the microbiome. Can one extend the methods from bipartite to tripartite graphs, to account for more levels of biological organization? This defines, as a realistic objective, the implementation of genes–genomes–environments tripartite graphs, which can then be clustered to provide a global yet accurate representation of the structure of genetic diversity on Earth in a single comparative analysis.",
"introduction": "Introducing Bipartite Graphs in Evolutionary Studies The information on the identity of shared edges (here, gene families) can be conserved in a less cluttered fashion by using bipartite ‘gene families–genomes’ graphs. In these graphs, the precise information regarding gene sharing is directly encoded as edges between these two kinds of nodes. Multiplex genome networks can be seen as unimodal projections [38] of such bipartite ‘gene families–genomes’ graphs ( Figure 1 D). Bipartite graphs include the same diversity of genomes as the genome networks described above, but they are more accurate. Importantly, simple specific bioinformatic treatments of these multilevel graphs allow one to rapidly identify which groups of genes are shared by which groups of genomes [39] , and to display and compare different channels of gene transmission, that is, the routes across generations through which hereditary resources or information pass from parent to offspring [31] . As in genome networks, connected components produce an informative partition of the data. This partition can moreover be examined at different levels of similarity by tuning, for example, the sequence identity percentage. When the data consist of all the protein sequences from all the complete viral (3749), plasmidic (4350), and archaeal (152) genomes, together with a representative subsample of the eubacteria (230) from NCBI, we get the numbers shown in Table 1 . Assuming a rough molecular clock, these thresholds are useful for investigating events of different ages. Sequences with ≥90% identity have a relatively weak divergence with respect to sequences with 30% identity; indeed, these latter have likely diverged faster or for a longer period of time. This representation of gene families–genomes bipartite graphs is explicitly multilevel. Interestingly, its analysis does not require any graph clustering algorithm (whose results tend to vary considerably with their implementation). Genetic transmission among microbes can be investigated by simple topological notions of bipartite graphs that result in biologically relevant observations: twins and articulation points \n [40] that we detail below. We apply here these notions only to gene family nodes. ‘Twin’ is a notion of graph theory; applied to gene families–genomes graphs, it singles out ‘fellow travellers’: gene families are twins when they are present in exactly the same set of genomes. In the language introduced in [34] , the support of such a twin defines a club of genomes. Clubs of genomes, when composed of individuals pertaining to different species, could encourage further studies of ‘kin-coevolution’, for example, the fact that genetic divergence affecting multiple ecologically coexisting lineages, that exchanged genes at some point of their evolution, produces multilineage persistent clubs. The bipartite graph can be simplified by grouping together sets of gene families that are shared by exclusive groups of genomes, and by replacing each such group of gene families by a super-node. Nodes that remain untouched by this reduction process are considered as trivial twin classes (and result in trivial super-nodes). Technically, there is no difference between trivial and non-trivial twins, although, from the biological perspective, the latter correspond to groups of gene families that are more likely to be transmitted together. The resulting quotient graph is reduced, because every club of genomes is now defined by one super-node (individual gene family or group of gene families hosted in this club of genomes) while no information is lost ( Figure 2 ). This property means that even very large graphs can be investigated. In the dataset presented in Table 1 , we typically find clubs, such as the one composed of the firmicute Enterococcus faecalis and nine plasmids (present in lactococci or enterococci) that simultaneously and exclusively share the following gene families (at 90% identity): ribose 5-phosphate isomerase RpiB, galactose mutarotase and related enzymes, β-glucosidase/6-phospho-β-glucosidase/β-galactosidase, and phosphotransferase system cellobiose-specific component IIA. These shared mobilized gene families are involved in neighbor pathways of sugar metabolisms (specifically in glycolysis and in the pentose phosphate metabolic pathways), which likely explains their collective mobilization in plasmids. Articulation points in a gene families–genomes bipartite graph correspond to gene families shared by many genomes with otherwise totally distinct gene contents (for a given similarity threshold). Although strictly topological, the notion of an articulation point is thus expected to help detect public genetic goods [34] , that is, genetic material that is being shared by taxonomically distant genomes, which possibly benefit from the properties they confer, for some reason other than genealogy (i.e., genes coding for environmental adaptation or hitch-hiking with those). However, an articulation point can also detect selfish genes, such as the abundant transposases [41] , which are spreading across multiple distantly related genomes ( Box 2 )."
} | 2,934 |
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