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36890606 | PMC9996866 | pmc | 3,977 | {
"abstract": "Background Arbuscular mycorrhizal fungi (AMF) are key soil organisms and their extensive hyphae create a unique hyphosphere associated with microbes actively involved in N cycling. However, the underlying mechanisms how AMF and hyphae-associated microbes may cooperate to influence N 2 O emissions from “hot spot” residue patches remain unclear. Here we explored the key microbes in the hyphosphere involved in N 2 O production and consumption using amplicon and shotgun metagenomic sequencing. Chemotaxis, growth and N 2 O emissions of isolated N 2 O-reducing bacteria in response to hyphal exudates were tested using in vitro cultures and inoculation experiments. Results AMF hyphae reduced denitrification-derived N 2 O emission (max. 63%) in C- and N-rich residue patches. AMF consistently enhanced the abundance and expression of clade I nosZ gene, and inconsistently increased that of nirS and nirK genes. The reduction of N 2 O emissions in the hyphosphere was linked to N 2 O-reducing Pseudomonas specifically enriched by AMF, concurring with the increase in the relative abundance of the key genes involved in bacterial citrate cycle. Phenotypic characterization of the isolated complete denitrifying P. fluorescens strain JL1 (possessing clade I nosZ ) indicated that the decline of net N 2 O emission was a result of upregulated nosZ expression in P . fluorescens following hyphal exudation (e.g. carboxylates). These findings were further validated by re-inoculating sterilized residue patches with P . fluorescens and by an 11-year-long field experiment showing significant positive correlation between hyphal length density with the abundance of clade I nosZ gene. Conclusions The cooperation between AMF and the N 2 O-reducing Pseudomonas residing on hyphae significantly reduce N 2 O emissions in the microsites. Carboxylates exuded by hyphae act as attractants in recruiting P . fluorescens and also as stimulants triggering nosZ gene expression. Our discovery indicates that reinforcing synergies between AMF and hyphosphere microbiome may provide unexplored opportunities to stimulate N 2 O consumption in nutrient-enriched microsites, and consequently reduce N 2 O emissions from soils. This knowledge opens novel avenues to exploit cross-kingdom microbial interactions for sustainable agriculture and for climate change mitigation. \n Video Abstract Supplementary Information The online version contains supplementary material available at 10.1186/s40168-023-01466-5.",
"conclusion": "Conclusions Our study provides novel insights into the importance of AMF in mediating nitrogen transformation processes conducted mainly by denitrifiers that lead to cascading effects on soil N 2 O emission. We demonstrate that AMF enriched the N 2 O-reducing Pseudomonas in the hyphosphere, which was responsible for the decline in N 2 O emissions in the residue patches. Notably, carboxylates exuded by hyphae acted as attractants recruiting P . fluorescens JL1 and as stimulants triggering the expression of nosZ gene. These insights provide a novel mechanistic understanding of the intriguing interactions between AMF and microbial guilds in the hyphosphere, and collectively indicate how these trophic microbial interactions substantially affect the denitrification process at microsites. This knowledge opens novel avenues to exploit cross-kingdom microbial interactions for sustainable agriculture and climate change mitigation.",
"introduction": "Introduction Nitrous oxide (N 2 O) is a very powerful and long-lived greenhouse gas with 273 times the global warming potential of CO 2 and is the most important ozone-depleting substance present in the atmosphere [ 1 ]. However, constraining the global atmospheric N 2 O budget remains challenging as N 2 O fluxes at the soil-atmosphere interface are highly dynamic and variable, characterized by “hot spots” and “hot moments” at microscales that are often < 1 cm 3 in volume and associated with crop residue patches in agriculture [ 2 ]. Estimates of N 2 O emission factors of crop residues vary widely, ranging from 0.17 to 2.9% [ 3 ], depending on residue properties [ 4 ] and multiple environmental factors such as C/N ratio, soil type, water-filled pore space (WFPS) and temperature [ 5 ]. The high spatiotemporal dynamics of N 2 O fluxes are due to the complex microbial processes underlying N 2 O production and consumption, and how these are affected by other biotic and abiotic factors [ 6 ]. As such, uncovering microbial interactions at the microscale level that mediate the episodic N 2 O emissions is critical for the development of mitigation strategies. The production of N 2 O in soils is driven mainly by microbial driven processes such as nitrification and denitrification [ 6 ]. Denitrification is regarded as the predominant N 2 O source from agricultural soils [ 7 ] including soils where crop residues are returned, as the provision of degradable organic matter stimulates microbial respiration, resulting in oxygen depletion and soil anaerobiosis [ 2 , 5 ]. Denitrification is a facultative process that enables the maintenance of microbial respiration. It involves a multistep reaction catalyzed by multiple enzymes and the relevant functional genes that used to characterize microbes, as denitrifiers are highly diverse and complex. Denitrifiers can produce N 2 O using two types of dissimilatory nitrite reductase encoded by the nirS and nirK genes that catalyze the reduction of soluble NO 2 − to gaseous NO, followed by rapid conversion to N 2 O as a detoxification approach [ 8 ]. Complete denitrifiers also synthesize the N 2 O reductase (nosZ) encoded by the nosZ gene and yield N 2 as the end product of denitrification, which is an important biotic sink for N 2 O [ 9 ]. The nosZ protein phylogeny has two distinct groups, clade I and the newly described clade II. The clade I nosZ -possessing microorganisms are more likely to be complete denitrifiers, as 83% of genomes with clade I nosZ also possess nirS and/or nirK genes [ 10 ]. In contrast, the majority of microorganisms possessing clade II nosZ appear to be non-denitrifying N 2 O reducers which represent another important N 2 O sink without contributing to N 2 O production [ 10 – 12 ]. Hence, soil N 2 O emissions at the soil-atmosphere interface are highly dynamic, resulting from simultaneously occurring production and consumption processes. An in-depth understanding of the mechanisms by which soil microbial guilds govern the balance of these key processes is important for the development of effective N 2 O mitigation strategies. Microbial N 2 O production and consumption in crop residue patches and surrounding soil are part of a complex suite of processes carried out by a consortium of microbiomes, including plant-associated microbes such as arbuscular mycorrhizal fungi (AMF). AMF are key organisms with a dual niche in host roots and in the bulk soil beyond the rhizosphere [ 13 ]. The extraradical fungal hyphae represent an important component and can proliferate into micropores inaccessible to plant roots and increase carbon flow into the soil [ 14 ], generating a unique microhabitat-hyphosphere, an extension of the rhizosphere where hyphae and other microbes interact intensively in a similar manner to rhizosphere hotspots [ 15 ]. This was shown by the positive feedback between AMF and hyphosphere phosphate-solubilizing bacteria in enhancing the mineralization of organic phosphorus [ 16 , 17 ]. Hyphal exploration of residue patches may prime decomposition and increase nitrogen acquisition from plant residues [ 18 ]. In addition, AMF hyphae reduce N 2 O emission from residue-affected soil [ 19 – 21 ], which is attributable to AMF-mediated substrate changes and/or the alteration of the hyphosphere microbiome, for instance ammonium-oxidizing microbes [ 19 , 22 ] or denitrifiers [ 20 , 21 , 23 ]. Previous studies have shown that AMF indirectly affect denitrifying microorganisms by promoting water absorption [ 24 ] or promoting soil aggregation [ 25 ]. However, direct evidence in support of AMF interacting with the hyphosphere microbiome, especially complete denitrifiers, remains ambiguous. Given that AMF receive 4–20% of total photosynthetic C from plants [ 26 ] and that hyphae form a network redistributing C into unexplored nonrhizosphere zones [ 14 ], this knowledge gap has important implications for the potential exploitation of the soil microbiome in terms of the development of suitable management practices to increase nutrient use efficiency while mitigating N 2 O emission. This is especially important in sustainable agriculture because current intensive agricultural practices result in a substantial decline in AMF diversity and abundance [ 27 , 28 ] and hence hamper their potential to mitigate N 2 O emission. Here, we have tested the underlying mechanisms responsible for AMF hyphae-mediated reduction of N 2 O emission, with special emphasis on the microbial taxa capable of complete denitrification in the hyphosphere. We first identified the major players and main pathways by integrating quantitative real-time PCR of the functional genes and amplicon sequencing based on DNA and RNA analysis. We then isolated the most responsive bacterial genus ( Pseudomonas in this case) and tested the chemotaxis, growth and N 2 O consumption of the isolated strains in response to hyphal exudates using in vitro cultures. Subsequently, the target strain was reinoculated into sterilized residue patch soils to validate the results of the in vitro cultures. Finally, we tested whether a positive correlation between AMF abundance and nosZ gene copies occurred in agricultural fields. We hypothesized that bacteria colonizing hyphae, e.g. nosZ -type complete denitrifiers, were the major players responsible for reduced N 2 O emissions. Specifically, hyphal exudates, in particular carboxylates, elicited the recruitment of complete denitrifiers by AMF hyphae and stimulated their functions in the hyphosphere. We envisage that a mixture of hyphosphere microbes in conjunction with hyphal metabolites have great potential to reduce N 2 O emission.",
"discussion": "Discussion Returning crop residues to the field is an effective measure to increase carbon sequestration in agricultural ecosystems but this gain can be offset by high N 2 O emission, especially when residues of N 2 -fixing legumes are returned [ 40 ]. Crop residues in soils create unique micro-environmental conditions that are conducive to denitrification by absorbing water from surrounding soil and by stimulating microbial respiration due to dissolved organic carbon released during decomposition [ 2 , 5 ]. The current study clearly demonstrates that (i) interactions between AMF and N 2 O reducers mitigate N 2 O emissions in residue patches, as evidenced by the alteration in N 2 O flux and the changes in the abundance and community composition of hyphosphere microbiota in the two pot experiments; and (ii) carboxylates exuded by hyphae recruited complete denitrifier ( P . fluorescens ) and triggered the nosZ gene (encoding N 2 O reductase) expression of P. fluorescens , as evidenced by the chemotaxis, growth, and N 2 O production in the in vitro cultures and the inoculation experiment. Interactions between AMF and N 2 O reducers mitigate N 2 O emission in patches In pot expt 1, the presence of AMF hyphae suppressed N 2 O concentrations in the unsterilized faba bean (NSfaba) patches after NO 3 − application but not after NH 4 + application (Fig. 2 A and Fig. S 1 B). In pot expt 2, the size of the patches was enlarged to 202 g and NO 3 − was supplied as basal fertilizer to all chambers including patch chambers to minimize N diffusion. The residue rate (10 g kg −1 ) was comparable to crop residues used in previous studies under field and condition-controlled conditions [ 41 – 43 ]. Here again AMF hyphae consistently and significantly reduced the N 2 O flux from residue patches from day 8 after patch placement until the end of the experiment (Fig. 2 B). The consistent results in the two experiments provide compelling evidence that AMF hyphae reduced N 2 O emissions in the residue patches, primarily by mediating the denitrification pathway, although the relative importance of this pathway among other processes may merit further exploration [ 6 ]. Our results are in line with previous studies showing AMF-mediated reduction of N 2 O emission from soil with residue amendment [ 20 , 21 ] or without residue amendment under high soil moisture conducive to denitrification [ 23 , 24 , 44 ]. The diversity and activity of the N 2 O-producing ( nirK or nirS type) and N 2 O-reducing ( nosZ type) microbial communities ultimately determine net N 2 O emissions. The relative abundance of bacteria possessing the nosZ gene is a good proxy of the N 2 O/ (N 2 + N 2 O) ratio [ 45 ]. In pot expt 1, AMF hyphae significantly increased the abundance of clade I nosZ, the nirS gene, and the nosZ I/( nirK + nirS ) ratio in the NSfaba patches (Fig. 3 A). As there was higher frequency of co-occurrence of nosZ with nirS [ 9 ], these results indicate that AMF hyphae may promote the growth and expression of N 2 O reducers (clade I) in residue patches. This was further supported by pot expt 2 where AMF significantly increased the abundance and expression of clade I nosZ , and the transcript ratio of nosZ I/( nirK + nirS ) at the second but not at the first harvest (Fig. 3 B, C). Synergies between AMF and N 2 O reducers may therefore explain the decline in N 2 O production in residue patches. In pot expt 2 at the first harvest, the increase in the expression of the nirK gene (Fig. 3 C) might be a response to imposing anaerobiosis which primes an initial pulse of emission. Hence, research efforts on dynamic changes of N 2 O reducer/producer community are required in future. In our experiment, no significant difference in the abundance and expression of clade II nosZ was observed between the −AMF and +AMF treatments (Fig. 3 B, C), suggesting these bacteria may be of relatively minor importance compared to clade I type. Previous studies showed that the clade I nosZ was dominant in the rhizosphere while clade II was in the soils [ 46 ]. It is likely that in similar fashion to (mycor-)rhizosphere, hyphosphere generated by the proliferation of AMF into the residues is favorable for the clade I nosZ community. The N rate applied to the patches (approximately 200 mg kg −1 ) was equivalent to the amount of fertilizer N typically used for cereal crops [ 47 , 48 ]. High concentrations of NO 3 − in soil almost completely inhibit N 2 O reduction to N 2 [ 49 ], as NO 3 − reductase outcompetes N 2 O reductase for electrons [ 50 ] supplied by labile organic carbon including AMF exudates. A recent study shows that the reduction in the rate of N 2 O emissions in the presence of AMF under normal N inputs was higher than that under high N inputs in conventional soil, but the opposite trend occurred in organically managed soil [ 44 ]. Aside from the well-reported substrate-controlled denitrification process [ 49 ], the interactions of AMF and hyphospheric microbes are also shown to be regulated by nitrogen availability [ 22 ]. Yet this remains largely unexplored. It is therefore particularly desirable to investigate AMF-mediated denitrification mechanisms in the context of environmental controls in order to maximize the N 2 O mitigation potential of AMF. Exudation of carboxylates by AMF hyphae recruits P. fluorescens and triggers nosZ gene expression in P. fluorescens Soils contain diverse denitrifying bacteria such as Citrobacter , Pseudomonas , Ochrobactrum , and Burkholderia [ 51 , 52 ]. A previous study reported that only a few members of the bacterial community (~10%) in residue patches responded to AMF colonization according to 16S rRNA gene microarray analysis [ 53 ]. The results obtained from amplicon and metagenomic sequencings in pot experiments and isolation in the in vitro cultures supported the conclusion that AMF hyphae consistently increased the relative abundance of N 2 O-reducing Pseudomonas , which was predominant in residue patches (Figs. 4 A and 5 A and Fig. S 3 ). Moreover, cumulative N 2 O emissions were negatively correlated with the relative abundance and activity of Pseudomonas (Fig. 4 C). This is the first report of N 2 O-reducing Pseudomonas directly and positively responded to AMF hyphal proliferation being responsible for low N 2 O emissions in residue patches. Pseudomonas spp. are fast-growing r -strategists enriched in nutrient-rich environments such as the rhizosphere [ 54 ] and hyphosphere [ 55 ]. In a similar fashion to the rhizosphere, the hyphosphere provides a unique niche in which microbial communities differ from those in the bulk soil due to hyphal exudates [ 53 , 56 ], as supported by the increased patch DOC concentrations in the +AMF treatment (Fig. S 1 C). Most Pseudomonas isolates cultivated in vitro possessing the nosZ gene belonged to P. fluorescens (Fig. S 4 A). The three isolates ( P . fluorescens JL1, JL2, and JL3) selected for draft-genome sequencing possessed all denitrifying genes and were complete denitrifiers. P. fluorescens F113 was previously reported as a typical “true denitrifier” [ 12 ]. P. fluorescens is effectively attached to AMF hyphae (Fig. S 5 A), as was also observed in a previous study [ 57 ]. Taken together, these results imply that the enrichment and stimulation of complete denitrifying P. fluorescens in the hyphosphere can be attributed to AMF hyphal exudates. AMF hyphae exude organic carbon, mainly in the form of sugars, carboxylates, and amino acids [ 58 , 59 ]. Previous studies show that AMF hyphal exudates promoted the growth of phosphate-solubilizing bacteria and that fructose exuded by AMF stimulated the expression of phosphatase genes in Rahnella aquatilis [ 16 , 17 ]. Here, we found that glucose, fructose, trehalose, glutamine, glutamic acid, citrate, and malate were abundant in hyphal exudates (Table S 6 ), corroborating with previous studies [ 59 , 60 ]. AMF hyphal exudates significantly promoted the chemotaxis and growth of P. fluorescens (Fig. 6 A and Fig. S 5 B), reduced N 2 O emissions, and upregulated the expression of the nosZ but not of the nirS gene (Fig. 6 B, C and Fig. S 5 C). Moreover, the role of carboxylates in bacterial chemotaxis, N 2 O emissions, and gene expression was similar to that of hyphal exudates (Fig. 6 ). Together, these results demonstrate that carboxylates exuded by hyphae are attractants in recruiting P . fluorescens and also act as stimulants triggering nosZ gene expression, resulting in a significant decline in N 2 O emissions. This was further validated in the inoculation experiment in which cumulative N 2 O emission and nosZ gene expression in the citrate addition treatment were similar to those in the +AMF treatment and in which N 2 O emission lower and nosZ gene expression higher than in the glucose or H 2 O addition treatments (Fig. 7 C, D). Thus, an N 2 O-reducing microbiome in residue patches has been developed by carboxylates exuded by AMF hyphae. A similar situation with reduced N 2 O emissions after the addition of carboxylates such as citrate, succinate, and acetate but not glucose to soils [ 61 ] or to pure cultures of Pseudomonas [ 62 ] was previously observed. The N 2 O reductase encoded by the nosZ gene is a weak competitor for electrons compared to other denitrifying reductases [ 50 ]. NADH, the usual direct electron donor mainly produced in the citrate cycle, is more conducive to electron transfer to N 2 O reductase. Carboxylates such as citrate and malate in hyphal exudates are directly involved in the citrate cycle, while the metabolic use of glucose requires enzymatic conversions and consumes extra energy [ 63 , 64 ]. Moreover, AMF increased the relative abundances of key genes involved in citrate cycle of bacteria, especially P. fluorescens in residue patches (pot expt 2, Fig. 5 B, C). Taken together, these results imply that hyphal exudates (with carboxylates as major components) promote the citrate cycle, trigger complete denitrification, and subsequently reduce N 2 O emissions by P . fluorescens . The results of the current study may be relevant for diverse ecosystems. The values of HLD in the present study fall within the range of 200–600 cm cm −3 (approximately 1.5–5.0 m g −1 ) in farmland soil but were lower than in woody and non-woody systems (2400 and 2700 cm cm −3 on average, respectively) [ 14 ]. The global decline in the abundance and diversity of AMF due to increasing land use intensity [ 65 ] is potentially alarming. This decline may disrupt the extensive connections between AMF and their associated microbiomes, with cascading negative effects on ecosystem functioning, specifically with respect to the underappreciated role of co-colonization by AMF and Pseudomonas in the mitigation of N 2 O emissions. To counter this adverse development, the restoration of AMF diversity in agricultural ecosystems may be achieved by the development of sustainable management practices such as diversified cropping [ 66 ], organic farming [ 67 ], or conservation agriculture [ 68 ]. To verify that sustainable agriculture practices may indeed stimulate co-colonization by AMF and N 2 O reducers, we analyzed soil samples taken from an 11-year-long intercropping field experiment. In the maize/faba bean intercropping soils, the HLD and the gene abundance of clade I nosZ were significantly higher than those in the faba bean monoculture, and the clade I nosZ gene abundance was significantly positively correlated with HLD (Fig. 8 C). Similar situations, i.e., low mineral N and high organic C availability, may also occur in grassland and forest soils, where uptake of atmospheric N 2 O is observed [ 69 ]. We speculate that the mechanisms we describe in the present study may explain this phenomenon, as AMF are abundant in these ecosystems. Our study demonstrates that reinforcing synergies between AMF and the hyphosphere microbiome may have far-reaching implications for both sustainable agriculture and the mitigation of N 2 O emissions from cropping systems and, thus, for the mitigation of climate change. We envisage that indiscernible and variable N 2 O fluxes occurring in soil microenvironments can be substantially reduced by AMF and the hyphosphere microbiome. Our study therefore also advances our understanding of the multiple functions delivery by AMF beyond promoting uptake of soil nutrients."
} | 5,670 |
35520230 | PMC9062995 | pmc | 3,978 | {
"abstract": "Due to the characteristics of renewable and carbon-neutral, lignocellulose is considered to be one of the most potential, feasible, and ample resources for biofuel production on the Earth. However, the low energy conversion capacity of microorganisms is the primary bottleneck for utilizing lignocellulosic biomass to produce biofuel. In the present study, a mesophilic bacterial strain Cel10 identified as Clostridium lentocellum, according to 16S rRNA sequence homology, which can produce hydrogen from lignocellulose was isolated and characterized. The optimal conditions of hydrogen production from carboxymethylcellulose (CMC) are 37 °C, pH 7.0, and 5.0 g L −1 . The H 2 production peaked at 5.419 mmol H 2 g −1 CMC under these conditions, which is relatively high compared to the other reported mesophilic bacteria that use cellulose as a substrate. Moreover, the H 2 -producing performance of strain Cel10 using cassava residues, a type of natural lignocellulosic feedstock, was also investigated. The results show that the hydrogen production peaked at 4.08 mmol H 2 g −1 after 72 h of incubation, which is almost 1.2–3.8 times higher than the production of other mesophilic and thermophilic strains, while the highest cassava residues degradation rate reached 45.43%. The results validate that Clostridium lentocellum strain Cel10, newly isolated from Ailuropoda melanoleuca excrement, can offer a new method for directly converting lignocellulosic biomass to bio-hydrogen.",
"conclusion": "Conclusions \n Clostridium lentocellum Cel10, a strictly anaerobic mesophilic bacterium, was isolated from Ailuropoda melanoleuca excrement, and then characterized by biochemical and molecular biological identification. Strain Cel10 could efficiently convert cellulose to hydrogen. The optimal dark fermentation conditions were determined to be 37 °C and pH 7.0 with 5.0 g L −1 CMC. Furthermore, the hydrogen productivity of strain Cel10 from cassava residues showed that the highest cassava residues degradation rate and hydrogen yield reached 45.43% and 4.08 mmol H 2 g −1 after 72 h of incubation. In general, this strain offers a new and potentially useful method for direct hydrogen production from various lignocellulosic materials.",
"introduction": "Introduction In the past few decades, most countries have relied on fossil resources. 1,2 However, this energy system, which depends on fossil fuels, can cause negative trends such as global warming, air pollution, and extreme weather phenomena. 3–5 In view of this situation, an economically viable and sustainable clean energy system should be found and established to solve the crisis. 6 Bio-hydrogen is an alternative and prospective clean energy source compared to conventional fossil resource utilization. 7–9 Therefore, the utilization of wastes such as lignocellulosic biomass to produce bio-hydrogen has been developed worldwide. 10 Lignocellulosic biomass, in the forms of woods, plants, and other natural vegetation, is the second largest component on Earth. 11 Over 200 billion tons of lignocellulosic biomass are produced worldwide every year, which has potential to be converted to biofuels, including bio-hydrogen. 10,12 Bio-hydrogen production from lignocellulosic biomass can conform to the current energy demand and mitigate climate change. 13,14 However, lignin possesses the drawback of difficult conversion of the cellulose and hemicellulose of lignocellulosic biomass into bio-hydrogen due to its resistance to biodegradation. Hence, several pre-treatments have been streamlined to ensure that lignocellulosic biomass can be broken down into oligosaccharides that can be more readily utilized by hydrogen-producing microbes. 15 However, current pre-treatment methods based on acid, alkali or cellulase have conspicuous disadvantages, such as high consumption, strict conditions, time-consuming processes and formative fermentation inhibitors. 16 A highly integrated one-step process named consolidated bioprocess (CBP) has been investigated for several years. During this process, specific bacteria can directly produce bio-hydrogen using the hydrolysates from the hydrolysis of lignocellulosic biomass by itself. 17 Due to its benefits of low consumption and low demand for the pre-treatment of the lignocellulosic biomass, CBP has been identified as one of the feasible methods for lignocellulosic hydrogen production. 18 Bio-hydrogen production requires more elaborate investigations, particularly in terms of discovering and isolating microbes that have the effective capability to directly produce H 2 from lignocellulosic biomass. To date, a few microorganisms capable of producing hydrogen, which prefer oligosaccharides to cellulose, have been identified. 15,19–21 Therefore, to make lignocellulosic hydrogen production competitive, more microorganisms that can produce lignocellulosic hydrogen without pre-treatment should be developed. In the present study, a novel isolated mesophilic bacteria strain, Clostridium lentocellum Cel10, which can rapidly and efficiently convert lignocellulose to hydrogen was isolated and characterized. The main objective of the study was to validate that Clostridium lentocellum strain Cel10 can play an effective role in directly producing hydrogen from lignocellulosic biomass.",
"discussion": "Results and discussion Isolation and characterization of strain Cel10 Enrichment culture of Ailuropoda melanoleuca excrement was established in the CMC medium at pH 7.0 and 37 °C. A strain named Cel10 that can directly convert cellulose to hydrogen was isolated. The sequence analysis results showed that this strain belongs to the genus Clostridium . The phylogenetic analysis results indicated that Cel10 had a 98% sequence similarity to the sequence of Clostridium lentocellum DSM 5427 ( Fig. 1 ). The physiological characteristics of Clostridium lentocellum Cel10 are shown in Table 1 . Strain Cel10 cells are rod-shaped (0.5 μm by 3.0–5.0 μm), motile, have tufted flagella and belong to the strict anaerobic Gram-negative bacteria. Strain Cel10 can not only utilize common substrates, such as glucose, xylose, and fructose to produce H 2 , but can also hydrolyze other cellulosic materials, such as CMC and Avicel ( Table 1 ). Fig. 1 Phylogenetic relationships between Cel10 and other related species according to 16S rRNA gene sequence. Identifying characteristics of Clostridium lentocellum Cel10 Feature Result a Substrate utilization Result a Gram staining — Glucose + Xylose + Fructose + Arabinose + Galactose + Morphology Short rod-shaped, spore Maltose + Motility + Mannose — Anaerobic growth + Sucrose + Nitrate reduction — Xylan + Sulfate reduction — Cellobiose + Gelatin hydrolysis — Starch + Catalase test — CMC + Metabolic products with cellulose Acetate, butyrate, ethanol, hydrogen, carbon dioxide Avicel + a + Positive; − negative. Effects of key factors on cellulosic hydrogen production using dark fermentation by strain Cel10 Temperature With regard to dark fermentation, temperature is a crucial factor for a mesophilic anaerobic microorganism to degrade cellulose. As shown in Fig. 2 , the H 2 production, CMC degradation rate and cell mass were investigated at different temperatures (25–50 °C). Both the cellulose degradation rate and hydrogen production increased as the temperature changed from 25 °C to 37 °C, and then decreased as the temperature changed from 40 °C to 50 °C. Moreover, at temperatures below 25 °C or above 50 °C, cellulose was not degraded. The optimal temperature for strain Cel10 to produce hydrogen was 37 °C. Furthermore, both the cell concentration and the rate of cellulose degradation also peaked at 37 °C. The maximum cellulose degradation rate, hydrogen production and cell concentration were 51.42 ± 0.02%, 5.52 ± 0.04 mmol g −1 , and 0.24 ± 0.03 g L −1 , respectively. This finding indicates that 37 °C is both the optimum growth and hydrogen production temperature for Cel10. In view of the above results, in the following tests, 37 °C was set as the optimum temperature. Fig. 2 Cellulosic H 2 production by strain Cel10 at different temperatures. pH Initial cultivation pH played a key role in the H 2 production during fermentation and the activities of hydrogen-producing microbes by affecting metabolism pathways during the bio-hydrogen production 30 and the activity of hydrogenase. 31,32 On the basis of research by Fang et al. , a high initial cultivation pH can result in a low hydrogen production due to inhibition in the activity of hydrogenase. 33 In addition, a low initial cultivation pH can inhibit the bacterial growth and activity by reducing the intracellular ATP level. 34,35 As shown in Fig. 3 , the H 2 production, CMC degradation rate and cell mass were investigated at different initial cultivation pH values (5.0–8.0). As shown in Fig. 3 , H 2 production increased from 0.64 ± 0.02 mmol g −1 to 5.42 ± 0.11 mmol g −1 as the initial cultivation pH changed from 5.0 to 7.0, which is the maximum, and then decreased from 4.85 ± 0.08 mmol g −1 to 1.16 ± 0.02 mmol g −1 as the initial cultivation pH changed from 7.5 to 8.0. Fig. 3 Cellulosic H 2 production by strain Cel10 at different initial cultivation pH values. The CMC degradation and cell mass exhibited similar changing trends. The CMC degradation increased from 6.01 ± 0.12% to 51.90 ± 1.41% when the initial cultivation pH increased from 5.0 to 7.0, which is the maximum, and then decreased from 46.69 ± 2.05% to 11.24 ± 1.56% when the initial cultivation pH increased from 7.5 to 8.0. The maximum value of cell mass occurred at pH 7.0. Increase in the initial pH from 7.0 to 8.0 led to a decrease in the cell mass. This result is similar to those of Ahmad's and Sheng's, 15,35 who found that a neutral initial cultivation pH range is usually optimal for hydrogen production. The use of different microorganism(s), fermentation conditions and substrates may lead to different reports of optimal cultivation initial pH for hydrogen production. 36 Our findings indicate that proper control of the initial cultivation pH is crucial for increasing hydrogen production because a high or low initial cultivation pH can inhibit the activity of hydrogenase or change the corresponding metabolic pathway in the hydrogen fermentation process. 16 CMC concentration CMC concentration is another crucial factor that affects the H 2 production on account of the close relationship between the H 2 production and cellulose degradation activity. A low or high CMC concentration may decrease the economic benefits or bind the active site of cellulase that lead to a poor fermentative efficiency. 37 The hydrogen production process of Cel10 includes two steps: cellulose hydrolysis and hydrogen production. Therefore, the inefficient cellulose hydrolysis limited the hydrogen production. As shown in Fig. 4 , the H 2 production, CMC degradation rate and cell mass were investigated with different CMC concentrations (3.0 to 10.0 g L −1 ). Fig. 4 Cellulosic H 2 production by strain Cel10 with different CMC concentrations. Approximately 86.12 ± 0.56% CMC degradation was obtained at 3.0 g L −1 , while CMC degradation decreased to 26.24 ± 0.92% at 10.0 g L −1 . However, the cell mass remained stable at approximately 223 to 243 mg L −1 irrespective of how the CMC concentrations changed in the range of 3.0 g L −1 to 10.0 g L −1 , which was inconsistent with the variation trend of cellulose degradation. Both the maximum hydrogen yield and cell concentration reached at a CMC concentration of 5.0 g L −1 . In view of the above results, in the following tests, 5.0 g L −1 was set as the optimum CMC concentration. Cellulose degradation and hydrogen production characteristics of strain Cel10 under optimal culture conditions The kinetics of the cellulose degradation, hydrogen yield and cell mass at 5.0 g L −1 CMC, pH 7.0, and 37 °C over time during dark fermentation within 72 h were analyzed, as shown in Fig. 5 . Strain Cel10 grew well during batch fermentation. It first showed a lag phase of about 12 h, then grew exponentially during 12–32 h, and finally reached the stationary phase during 32–48 h. The maximum cell concentration reached 0.243 ± 0.004 g L −1 at 36 h. Due to the fact that cellulose can be hydrolyzed in hot water, trace cellulose degradation was obtained before the test began. 38 The cellulose concentration gradually decreased from 4.889 ± 0.03 g L −1 at 0 h to 2.405 ± 0.02 g L −1 at 36 h and remained nearly stable after 36 h due to the accumulation of inhibitory metabolites generated during dark fermentation 39,40 or the consumption of some nutrients in the culture medium. 41 The hydrogen production profile was consistent with the cellulose concentration. After an 8 h lag phase, hydrogen production began. The H 2 production rate peaked at about 2.1 mmol h −1 L −1 at 28 h. Thereafter, the H 2 production rate promptly decreased, while H 2 accumulation gradually increased. The H 2 production peaked at approximately 5.419 ± 0.04 mmol H 2 g −1 CMC at 36 h and remained steady afterward. Unlike the hydrogen production and cellulose degradation, the cell mass concentration maximized earlier. This illustrates that the key factor to hydrogen production is not microorganism growth but the biological activity of the microorganism. Fig. 5 Kinetics of cellulose degradation, hydrogen yield and cell mass over time during dark fermentation within 72 h. \n Fig. 6 presents the GC analysis about metabolites of Cel10 produced during dark fermentation. As displayed in Fig. 6 , the main metabolite was acetate, followed by butyrate, ethanol, butanol, and propionate, which were produced and gradually increased up to 48 h. These results suggest that Cel10 can produce hydrogen though butyric-type fermentation because the ratio of butyrate to acetate reached about 1/2. 42 Fig. 6 Metabolites of cellulose degraded by Cel10 over time during dark fermentation within 72 h. \n Fig. 7 presents the cellulase activity of Cel10 at 5.0 g·L −1 CMC, pH 7.0, 37 °C within 72 h. The cellulase activity was obtained after 4 h and gradually increased to a maximum at 36 h, then gradually decreased. The variation trend in the cellulase activity was in accord with the trends of the H 2 production and cell mass. The cellulase activity peaked at 36 h, which contained 0.28 U exo-1,4-β- d -glucanase, 0.13 U endo-1,4-β- d -glucanase, and 0.11 U β-1,4-glucosidase. All the aforementioned results indicated that Clostridium lentocellum Cel10 exhibited good cellulose degradation and hydrogen production capacities ( Table 2 ). Fig. 7 The cellulase activity of Cel10 over time during dark fermentation within 72 h. Comparison of reported H 2 yields from different cellulosic substrates by different microbial cultures Microbial species Substrate Concentration (g L −1 ) Temperature (°C) H 2 yield (mmol g −1 ) References \n Clostridium cellulolyticum \n Cellulose MN301 5.0 35 7.0 \n 43 \n \n Clostridium cellulolyticum \n Microcrystalline cellulose 5.0 35 6.2 \n 43 \n \n Clostridium acetobutylicum X9 Microcrystalline cellulose 10.0 37 3.0 \n 44 \n \n Clostridium populeti \n Cellulose MN301 5.0 35 6.8 \n 43 \n \n Clostridium populeti \n Microcrystalline cellulose 5.0 35 5.9 \n 43 \n \n Clostridium termitidis CT1112 α-Cellulose 2.0 37 3.9 \n 45 \n \n Clostridium lentocellum Cel10 CMC 5.0 37 5.4 This study Lignocellulosic hydrogen production by strain Cel10 using raw materials To measure the ability of Clostridium lentocellum to produce H 2 from lignocellulose, four different natural lignocellulosic materials were selected as substrates, namely, cassava residues, rice straw, corn stalks, and corncob. In summary, the yields of H 2 from the four substrates were comparable. The maximum H 2 yield of strain Cel10 was 4.08 ± 0.25 mmol H 2 g −1 , which was obtained from cassava residues, followed by corn stalks, corncob, and rice straw ( Fig. 8 ). Clostridium lentocellum Cel10 had the capacity to convert the carbohydrates in the raw lignocellulosic materials to H 2 . The hydrogen yield of strain Cel10 was higher than those of some mesophilic bacteria and even some thermophilic bacteria. These results indicated that the hydrogen yield of Clostridium lentocellum Cel10 from raw lignocellulosic materials is almost 1.2–3.8 times greater than those of other mesophilic and thermophilic strains ( Table 3 ). Fig. 8 Hydrogen production by Clostridium lentocellum Cel10 from raw lignocellulose materials. Comparison of reported H 2 yields from different lignocellulosic substrates by different microbial cultures Microbial species Substrate Concentration (g L −1 ) Temperature (°C) H 2 yield (mmol g −1 ) References \n Ruminococcus albus \n Sweet sorghum 3.0 37 2.7 \n 46 \n \n Clotridium butyricum \n Steam-exploded corn straw 5.0 35 3.0 \n 47 \n \n Clostridium thermocellum 7072 Corn stalk 20.0 55 2.76 \n 48 \n \n Thermoanaerobacterium thermosaccharolyticum M18 Corn cob 5.0 60 3.23 \n 49 \n \n Clostridium thermocellum 27405 Dried distillers' grain 5.0 60 1.07 \n 50 \n \n Caldicellulosiruptor saccharolyticus DSM 8903 Wheat straw 10.0 70 1.58 \n 51 \n \n Clostridium lentocellum Cel10 Cassava residues 5.0 37 4.08 This study"
} | 4,300 |
24724055 | PMC3971182 | pmc | 3,980 | {
"abstract": "Biofilms are characterized by a dense multicellular community of microorganisms that can be formed by the attachment of bacteria to an inert surface and to each other. The development of biofilm involves the initial attachment of planktonic bacteria to a surface, followed by replication, cell-to-cell adhesion to form microcolonies, maturation, and detachment. Mature biofilms are embedded in a self-produced extracellular polymeric matrix composed primarily of bacterial-derived exopolysaccharides, specialized proteins, adhesins, and occasionally DNA. Because the synthesis and assembly of biofilm matrix components is an exceptionally complex process, the transition between its different phases requires the coordinate expression and simultaneous regulation of many genes by complex genetic networks involving all levels of gene regulation. The finely controlled intracellular level of the chemical second messenger molecule, cyclic-di-GMP is central to the post-transcriptional mechanisms governing the switch between the motile planktonic lifestyle and the sessile biofilm forming state in many bacteria. Several other post-transcriptional regulatory mechanisms are known to dictate biofilm development and assembly and these include RNA-binding proteins, small non-coding RNAs, toxin-antitoxin systems, riboswitches, and RNases. Post-transcriptional regulation is therefore a powerful molecular mechanism employed by bacteria to rapidly adjust to the changing environment and to fine tune gene expression to the developmental needs of the cell. In this review, we discuss post-transcriptional mechanisms that influence the biofilm developmental cycle in a variety of pathogenic bacteria.",
"conclusion": "Conclusions Biofilm formation and development is a fascinatingly intricate process involving finely altered gene expression, requiring complex and well-coordinated regulation to accomplish the process with high efficiency both spatially and temporally. In this review we have exemplified several of the well characterized powerful contributions that post-transcriptional regulation makes to rapidly adjust and fine tune gene expression to the developmental needs of the cell during biofilm formation. These mechanisms confirm that bacterial signal integration and gene regulation at the mRNA level might be equally sophisticated as its transcription-factor based counterpart acting at the DNA level, with 5' UTRs of mRNAs playing an analogous role to that of complex promoters. It is however clear that with the growing body of discoveries about the complexities of post-transcriptional regulation we should expect that many new pathways and molecules play critical roles in biofilm formation. This serves as grounds for encouragement for the continued surge into biofilm regulation research which will definitely shed more light on the complex intricacies of this biological process.",
"introduction": "Introduction During their life cycles bacterial pathogens must often transit between different habitats and have to respond to continually changing environmental conditions. Rapid adaptation to these changing conditions is a key factor for survival and replication. Some bacterial pathogens exhibit multicellular behaviors as a conserved strategy for long-term bacterial survival in nature and during infections. One of these multicellular behaviors is biofilm formation (Mah and O'Toole, 2001 ; Matz and Kjelleberg, 2005 ; Anderson and O'Toole, 2008 ). Biofilm represents a mode of growth that enables bacteria to establish persistent relationships with their surroundings providing protection against environmental stressors, antibiotics, predation, and host immunity (Stoodley et al., 2002 ). This phenomenon has been observed in diverse Gram-negative and Gram-positive bacterial species. Although mixed-species biofilms predominate in most environments, single-species biofilms exist in a variety of infections. To understand the role of biofilm formation in infections there has been notable research focused on pathogenic biofilm-producer organisms in such diverse genera as Pseudomonas , Vibrio , Escherichia , Salmonella , Listeria , Streptococcus , Staphylococcus , Yersinia , and Mycobacteria . Biofilm formation has a significant impact in medical and industrial settings. The formation of biofilm on many medical and technological devices may cause severe complicating problems affecting human health and industrial processes. The growth of bacterial biofilm on human tissues results in chronic infections which are challenging for antimicrobial therapies because they are extremely resistant to antibiotic treatment. This is primarily due to the increased prevalence of dormant cells, known as persisters, within the biofilm (Lewis, 2005 ; Hatt and Rather, 2008 ; Hall-Stoodley and Stoodley, 2009 ). This negative impact of biofilm has stimulated research aimed to identify specific components of the physical biofilm structure and regulatory aspects of the process of biofilm development toward creating anti-biofilm strategies (Sommer et al., 2013 ). On the other hand, despite the detrimental impact of biofilm, they are useful in engineering applications and in many natural settings where they are favored for promoting beneficial microbial associations (Currie, 2001 ; Singh et al., 2006 ; Kreth et al., 2008 ). Understanding the mechanisms of biofilm formation can therefore lead to its manipulation for either its enhancement or eradication. With the recent advances in molecular biology, understanding the underlying molecular basis of biofilm formation has become possible and this provides novel opportunities to disrupt/enhance biofilm formation."
} | 1,416 |
28018309 | PMC5156726 | pmc | 3,981 | {
"abstract": "We used microsensors to study the regulation of anoxygenic and oxygenic photosynthesis (AP and OP, respectively) by light and sulfide in a cyanobacterium dominating microbial mats from cold sulfidic springs. Both photosynthetic modes were performed simultaneously over all H 2 S concentrations (1–2200 μM) and irradiances (4–52 μmol photons m -2 s -1 ) tested. AP increased with H 2 S concentration while the sum of oxygenic and anoxygenic photosynthetic rates was constant at each light intensity. Thus, the total photosynthetically driven electron transport rate was solely controlled by the irradiance level. The partitioning between the rates of these two photosynthetic modes was regulated by both light and H 2 S concentration. The plastoquinone pool (PQ) receives electrons from sulfide:quinone:reductase (SQR) in AP and from photosystem II (PSII) in OP. It is thus the link in the electron transport chain where both pathways intersect, and the compound that controls their partitioning. We fitted our data with a model of the photosynthetic electron transport that includes the kinetics of plastoquinone reduction and oxidation. The model results confirmed that the observed partitioning between photosynthetic modes can be explained by a simple kinetic control based on the affinity of SQR and PSII toward PQ. The SQR enzyme and PSII have similar affinities toward PQ, which explains the concurrent OP and AP over an astonishingly wide range of H 2 S concentrations and irradiances. The elegant kinetic control of activity makes the cyanobacterium successful in the fluctuating spring environment. We discuss how these specific regulation mechanisms may have played a role in ancient H 2 S-rich oceans.",
"introduction": "Introduction Oxygenic photosynthesis (OP) is a process where light energy is used to extract electrons from water to reduce CO 2 . The evolution of this type of photosynthesis was predated by anoxygenic photosynthesis (AP), a process that uses another compound (e.g., H 2 S) as electron donor for the reduction of CO 2 ( Blankenship, 2010 ). While the more ancient AP requires only one photosystem (PSI) to drive the electron flow, OP requires the combined power of two photosystems (PSI+PSII), primarily because of the high energy demand in the water splitting reaction. OP probably evolved in cyanobacteria ( Mulkidjanian et al., 2006 ) inhabiting microbial mat-like structures. In these systems alternative electron donors for photosynthesis such as H 2 S were likely abundant ( Nisbet and Fowler, 1999 ; Buick, 2008 ) and remained available until the end of the Proterozoic ( Canfield, 1998 ). Therefore, it has been hypothesized that AP performed by obligate anoxygenic phototrophs and cyanobacteria capable of both AP and OP (referred to as versatile cyanobacteria) was an important photosynthetic mode on a global scale before the complete oxygenation of the Earth’s atmosphere and oceans during the Neoproterozoic oxidation event ( Johnston et al., 2009 ). It is therefore intriguing how oxygenic phototrophs were finally so successful in oxygenating Earth despite the widespread availability of electron donors for anoxygenic phototrophs and the toxic effects of H 2 S on the components of OP, especially considering that AP is a biochemically less complicated and energetically less demanding process than OP ( Miller and Bebout, 2004 ; Klatt et al., 2015a ). New insights into possible mechanisms that allowed outcompetition of anoxygenic phototrophs by oxygenic phototrophs in the presence of H 2 S can be gained by studying adaptations of extant cyanobacteria living in sulfidic environments. The cold, light-exposed sulfidic springs at Frasassi, Italy ( Klatt et al., 2016 ), which harbor thin microbial mats inhabited by diverse anoxygenic, oxygenic and versatile phototrophs, are one example of such an environment. Our recent studies of cyanobacteria isolated from this system revealed two novel cyanobacterial adaptations to H 2 S. The first adaptation mechanism, observed for a versatile cyanobacterium Pseudoanabaena str. FS39, included partitioning between AP and OP that is regulated kinetically by H 2 S through the apparent affinity of the electron transport components involved in AP [sulfide:quinone:reductase (SQR)] and OP [photosystem II (PSII)] toward plastoquinone, which is where both electron transport pathways intersect ( Figure 1 ; Klatt et al., 2016 ). OP in this cyanobacterial strain is active only when the electron transport chain is not fully used by AP, which occurs when H 2 S is limiting. The second type of adaptation, observed for the obligatory oxygenic cyanobacterium Planktothrix str. FS34, included acceleration of the recovery of OP by H 2 S after prolonged exposure to darkness and anoxia combined with an enhancement of OP rates by H 2 S at low irradiance and a temporary resistance to H 2 S toxicity ( Klatt et al., 2015b ). FIGURE 1 Simplified diagram of the model describing partitioning between AP and OP in versatile cyanobacteria, as proposed by Klatt et al. (2015a) . The AP and OP pathways intersect at plastoquinone (PQ) and their partitioning is regulated by the PQ redox state. In the AP pathway, PQ is reduced in a light-independent reaction by the enzyme sulfide:quinone:reductase (SQR), which obtains the electrons from the oxidation of H 2 S to zero-valent sulfur. In contrast, PQ reduction in the OP pathway is driven by the light-dependent activity of photosystem II (PSII), with electrons originating from the oxidation of H 2 O to O 2 . In both pathways PQ oxidation is driven by the light-dependent activity of photosystem I (PSI). I PSI and I PSII denote light energy harvested in PSI and PSII, respectively. The rate-laws describing the kinetic regulation of the rates of OP (k oxy ), AP (k anoxy ), H 2 S oxidation by SQR (k H2S ) and of the total photosynthetic electron transport (k PSI ) are shown by the formulae. The microbial mats in the Frasassi sulfidic springs are characterized by a microenvironment with rapidly fluctuating availability of light and H 2 S ( Klatt et al., 2016 ). Although both Pseudanabaena str. FS39 and Planktothrix str. FS34 have adaptations that could make them successful in such environment, microscopic observations revealed that neither of them appeared to be abundant in the system. Instead, the mats where dominated by yet another, morphologically very distinct, cyanobacterium. The aim of this study was to understand the adaptations responsible for the success of this dominant cyanobacterium in the system. We hypothesized that the dominant cyanobacterium possesses a mechanism that allows it to rapidly switch between AP and OP based on the instantaneous availability of light and H 2 S and thus be adapted to the rapidly fluctuating microenvironmental conditions in the mats. However, we expected that the specific regulation by these parameters differs from that found in Pseudanabaena str. FS39, given that the abundance of this strain in the mats is very low. To test this hypothesis, we quantified the combinatory effects of light and H 2 S on the partitioning between AP and OP performed by the dominant cyanobacterium. Because our cultivation attempts were not successful, we performed our measurements in a natural mat sample dominated by the cyanobacterium.",
"discussion": "Discussion The cyanobacterial layer in the studied mat performed OP and AP simultaneously over a wide range of H 2 S concentrations and light intensities. The regulation of the total photosynthetic electron transport given by the sum of electron transports driven by AP and OP was astonishingly simple. Specifically, the total electron transport rate increased linearly with irradiance and did not depend on H 2 S at all ( Figure 6H ). The partitioning between oxygenic and anoxygenic modes seemed more complex as it was controlled by both H 2 S levels and light intensities ( Figures 6A–G ). Using our numerical model of the electron transport reactions, we found that the observed activity patterns in this mat can be explained by kinetic controls. Thus, synthesis or degradation of cell components, such as pigments and photosystems, is not needed as an explanation for the complex light- and H 2 S-dependency of photosynthetic rates. We furthermore exclude changes in the abundance of cell components as an explanation for our data, because all our measurements were performed within a short time (∼6 h) and because the observed pattern emerged even though we did not follow a strict order (e.g., either gradually increasing or gradually decreasing) of light intensities and H 2 S concentrations. Also, we repeated the first measurements at the end of our experiments and showed that the physiologic properties of the mat, i.e., the overall photosynthetic rate and the ratio between AP and OP, had not significantly changed. We therefore conclude that the adjustment of rate and rate partitioning in response to the momentary microenvironmental light and H 2 S conditions were instantaneous and the result of kinetic control. The specific H 2 S and light dependent partitioning between OP and AP can be explained by considering that the light-driven electron transport from PSII and the H 2 S-driven electron transport from SQR intersect in the plastoquinone (PQ) pool ( Figure 1 ). The electron transport rates are controlled by the affinities governing the rates of PQ reduction by PSII (k oxy in Figure 1 ) and SQR (k anoxy ). We determined that the apparent affinity of SQR to H 2 S has to be very low (K M > 1) (see notation in Figure 1 ). More importantly, the apparent affinities of SQR and PSII to PQ are in the same range. This means that PSII and SQR can compete equally well for oxidized PQ. As a consequence, OP is performed simultaneously with AP irrespective of the light intensity and H 2 S concentration ( Figure 8A ), even at H 2 S concentrations that are higher than ever observed in situ in the naturally occurring mats ( Klatt et al., 2016 ). FIGURE 8 Partitioning between AP and OP predicted by the model shown in Figure 1 for the cyanobacterium studied here (A) and for Pseudanabaena str. FS39 (B) at low and high H 2 S concentrations. We have observed such kinetic regulation mechanism previously in another cyanobacterium: Pseudanabaena str. FS39, a versatile cyanobacterium enriched from the same environment ( Klatt et al., 2015a ). As the apparent affinities of SQR and PSII toward PQ, however, fundamentally differ from the cyanobacterium studied here, a completely different H 2 S- and light-dependent activity pattern emerges ( Figure 8B ). In Pseudanabaena str. FS39 the apparent affinity of SQR to H 2 S is very high, with the corresponding K M at least two orders of magnitude lower than in the cyanobacterium studied here. Moreover, in Pseudanabaena str. FS39 the affinity of SQR to oxidized PQ is at least two orders of magnitude higher than that of PSII (K PSII /K SQR ≥ 100). In other words, OP is kinetically outcompeted by AP. This is manifested by the fact that OP is only performed in addition to AP when H 2 S is limiting SQR activity. As a consequence, Pseudanabaena str. FS39 switches from exclusive AP to simultaneous AP and OP at substantially lower H 2 S concentrations and/or higher light intensities than the cyanobacterium studied here (compare Figures 8A,B ). The striking differences between the affinities of SQR to PQ and H 2 S in Pseudanabaena str. FS39 and the dominant spring cyanobacterium suggest that their SQRs belong to different enzyme structure classes ( Gregersen et al., 2011 ). The affinities of PSII to PQ also differ among the two cyanobacteria. Protein D1, which is a core component of the photosystem II reaction center, shapes the kinetics of quinone reduction. Different isoforms of this protein exist and are expressed dependent on oxygen concentration and light ( Cardona et al., 2015 ). We therefore suggest that Pseudanabaena str. FS39 and the cyanobacterium studied here might employ fundamentally different types of D1. Thus, there might be a relationship between the type of D1 and regulatory mechanisms for AP, which might have far-reaching implications for research on the evolution of AP in cyanobacteria. The phylogeny of genes encoding for the well-conserved D1 proteins was successfully used to reconstruct their evolutionary history ( Cardona et al., 2015 ). Such reconstruction is challenging when based only on SQR genes due to their history of intensive lateral gene transfer ( Theissen et al., 2003 ). Genes encoding for several isoforms of D1 have recently been detected in the genome of Geitlerinema sp PCC 9228 (formerly Oscillatoria limnetica ) ( Grim and Dick, 2016 ), the most intensively studied photosynthetically versatile cyanobacterium, which further underlines the intriguing question if usage of different D1 types might be an important tool for cyanobacteria in the regulation of AP. It is very unlikely that the observed activity pattern emerged from the simultaneous activity of a mix of several physiologically distinct cyanobacterial species or strains. The studied mats were dominated by a single cyanobacterial morphotype. The complex experimental data could be fitted by a simple kinetic model, thus by one kinetic expression per reaction step. Any residual uncertainty does, however, not invalidate the general conclusion that the most successful cyanobacterial population in the sulfidic spring can perform simultaneous OP and AP over a complete diurnal cycle unless H 2 S becomes entirely depleted within the photosynthetically active zone. The range of H 2 S concentrations and irradiances over which OP and AP are performed concurrently in the studied mats is substantially wider than in Pseudanabaena FS39. In fact, it is even exceptional compared to other previously studied versatile cyanobacterial strains. It was shown that Geitlerinema PCC9228, for instance, performs simultaneous OP and AP only below a 80 μM H 2 S concentration threshold when exposed to 400 μmol photons m -2 s -1 ( Cohen et al., 1986 ). Cohen et al. (1986) also report that in an Oscillatoria sp. from Stinky Hot Springs and in Microcoleus chtonoplastes ( Geitlerinema ) from Solar Lake, AP and OP occur concurrently below 550 μM H 2 S and 1000 μM H 2 S, respectively, at the same light intensity. For the case of the Frasassi sulfidic spring cyanobacterium, our model predicts that the OP:AP ratio would still be 0.9 at 1000 μM H 2 S and that exclusive AP is not possible at all at around 400 μmol photons m -2 s -1 . This astonishing coverage of H 2 S concentrations and light intensities inspires an intriguing question: what is the advantage of simultaneous AP and OP in general, and specifically in the Frasassi sulfidic springs? As opposed to obligate anoxygenic phototrophs, both obligate oxygenic phototrophs and versatile cyanobacteria are generally never limited by electron donor availability. There is, however, a major difference between versatile and obligate oxygenic cyanobacteria: AP is driven by only one photosystem (PSI), whereas OP is driven by two photosystems (PSI+PSII). Thus, theoretically, the photon flux required to drive a certain electron transport and growth rate is twice as large for OP as for AP. Due to this lower energy demand of AP, one could expect that AP is favorable for cyanobacteria when H 2 S is not limiting. However, this expected advantage of AP seems not to necessarily hold true in versatile cyanobacteria. For the studied cyanobacterium and also for Pseudanabaena str. FS39 we have shown that the total electron transport rate driven by a specific photon flux is independent of H 2 S concentrations and the photosynthetic mode. A constant electron transport implies that the light energy harvested in PSII is basically wasted during AP. This is because only PSI is involved in anoxygenic electron transport and photons harvested in PSII are therefore not efficiently used to drive photochemical reactions. AP would only be advantageous if the excitation energy were transferred from PSII to PSI or if the photosystem stoichiometry changed ( Klatt et al., 2015a ). This does not seem to occur in the cyanobacterium dominating the Frasassi sulfidic springs as the sum of photosynthetic electron transport rates is constant. Thus, AP does not appear to provide any energetic advantage to this phototroph. Considering that quantum efficiency in cyanobacteria can be constant irrespective of the photosynthetic mode, cyanobacteria that perform only one mode of photosynthesis therefore can, from a thermodynamic perspective, theoretically be as successful as versatile cyanobacteria. However, obligate oxygenic phototrophs in the Frasassi sulfidic springs (e.g., Planktothrix str. FS34, Klatt et al., 2015b ) do not seem to dominate the photosynthetic community. Similarly, cyanobacteria that would perform only AP for most of the diurnal cycle (e.g., Pseudanabaena str. FS39, Klatt et al., 2015a , Figure 8B ) are not abundant. Instead, the key to success appears to lie in the simultaneity of both photosynthetic modes. Production of oxygen in the presence of sulfide is tied to severe toxification risks by reactive oxygen species (ROS) generation ( Latifi et al., 2009 ; Hoffman et al., 2012 ). A counterbalancing advantage of such adaptation strategy remains mysterious to us – especially in the modern world where potential competitors for space and resources [e.g., SOB and obligate anoxygenic phototrophs ( Klatt et al., 2016 )] as well as microorganisms that might affect this competition via feedback mechanisms on the S- and C-cycle (e.g., sulfate reducers) have developed sophisticated strategies to cope with fluctuating oxygen and sulfide concentrations (e.g., Blankenship and Matsuura, 2003 ; Baumgartner et al., 2006 ; Berghoff et al., 2011 ). We can therefore only speculate that the advantage of versatility might be understood by considering that cyanobacteria are not an independently operating entity but almost always rely on the interaction with other microbes, which is most apparent in the frequent failure of axenic cultivation of cyanobacteria. In this scenario a close beneficial interaction with aerobs and/or oxidizers of the products of cyanobacterial AP, i.e., intermediately reduced sulfur compounds ( Cohen et al., 1975 ; de Wit and van Gemerden, 1987 ; Rabenstein et al., 1995 ), is plausible and represents a hypothesis that warrants testing. While the advantage of continuous O 2 production and sulfide consumption at virtually any light intensity and H 2 S concentration in contemporary ecosystems remains to be understood, the capability to perform OP whenever there is a glimpse of light might have provided the ancestors of extant cyanobacteria with a crucial advantage in the microbial mats that covered Earth’s costal oceans for much of the Proterozoic and likely already during the Archean. These mats represent the stage for the evolution and proliferation of OP ( Buick, 2008 ; Lyons et al., 2014 ), a process which must have been a catastrophe for microbial life in an anaerobic world but also triggered the co-evolution of aerobic life. Thus, even the earliest aerobic life-style must have been able to thrive in the fluctuating redox conditions of microbial mats. Overall, our study emphasizes that the evolution of cyanobacterial adaptations strategies and the resulting cyanobacterial activity, i.e., both the gross and net O 2 production rates in microbial mats, were tightly coupled to the evolution of Earth’s redox environment (that is, the availability of alternative electron donors for photosynthesis), the energy supply in the form of light and chemical energy and likely the co-evolution of competitive and beneficial microbial interactions."
} | 4,956 |
34611201 | PMC8492804 | pmc | 3,983 | {
"abstract": "Many pheromone sensing bacteria produce and detect more than one chemically distinct signal, or autoinducer. The pathways that detect these signals are typically noisy and interlocked through crosstalk and feedback. As a result, the sensing response of individual cells is described by statistical distributions that change under different combinations of signal inputs. Here we examine how signal crosstalk reshapes this response. We measure how combinations of two homoserine lactone (HSL) input signals alter the statistical distributions of individual cell responses in the AinS/R- and LuxI/R-controlled branches of the Vibrio fischeri bioluminescence pathway. We find that, while the distributions of pathway activation in individual cells vary in complex fashion with environmental conditions, these changes have a low-dimensional representation. For both the AinS/R and LuxI/R branches, the distribution of individual cell responses to mixtures of the two HSLs is effectively one-dimensional, so that a single tuning parameter can capture the full range of variability in the distributions. Combinations of crosstalking HSL signals extend the range of responses for each branch of the circuit, so that signals in combination allow population-wide distributions that are not available under a single HSL input. Dimension reduction also simplifies the problem of identifying the HSL conditions to which the pathways and their outputs are most sensitive. A comparison of the maximum sensitivity HSL conditions to actual HSL levels measured during culture growth indicates that the AinS/R and LuxI/R branches lack sensitivity to population density except during the very earliest and latest stages of growth respectively.",
"introduction": "Introduction Bacteria communicate with each other and sense their environment by exchanging small diffusible pheromone molecules known as autoinducers. Although this signaling mechanism was initially interpreted as a means of triggering phenotypic changes in response to population density, pheromone sensing networks often have elaborate architecture that indicates their function is more complex than simply sensing population or “quorum” 1 – 3 . These pathways respond not only to extracellular concentrations of autoinducer, but also to other environmental cues, metabolic parameters, and signals from other species 4 , 5 . In addition, many bacteria synthesize and sense more than one chemically distinct autoinducer 6 , 7 . They detect these signals using multiple receptor pathways in interlocked configurations that often involve feedback, and use them to regulate multiple phenotypes. The question of how such configurations extend the sensing capabilities of these networks remains of great interest 8 . These sensing pathways can be subject to crosstalk between the different signals and detection mechanisms. In Gram-negative bacteria, the autoinducers are often N-acylated homoserine lactones (HSLs), which may be produced or detected with different degrees of specificity 5 , 8 . One form of crosstalk occurs when receptors in one branch of a pathway interact with non-cognate HSLs produced by another pathway in the same organism. Crosstalk may also occur in system architectures where receptors for several different autoinducers drive the same downstream outputs, so that information arriving from different autoinducers is merged into a common output from a regulatory pathway. One obstacle to understanding how a cell's sensing functions benefit from the presence of multiple, interacting pathways is the heterogeneity of gene expression: given a well-defined concentration of autoinducer in the environment, the response of individual cells exhibits a statistical distribution 9 . For example, even when Vibrio fischeri are provided precisely-controlled autoinducer concentrations, the response of the pheromone controlled bioluminescence pathway may differ by an order of magnitude from one cell to another 10 . Although such variability may provide a fitness benefit at the population level 11 , it makes the behavior of an individual cell an unreliable indicator of the input signals it is receiving. In addition, a population-averaged measurement of behavior cannot capture the diversity of individual cell behaviors that occur in response to a signal input. This raises the question of how crosstalk between two interacting pathways affects the sensitivity of those pathways and the range and statistical distributions of the outputs. It also raises the question of how subtle effects of crosstalk can be detected or characterized. For example it is conceivable that crosstalk could modulate the sensitivity of a pathway to environmental cues, not by changing the mean response of the population, but through changes in the distribution of responses, which affect phenotypic variability and bet hedging 12 . To understand how crosstalk affects sensing, it is necessary to look beyond average population responses and determine whether and how multiple signals reshape the statistical distribution of individual cell responses. Here we have measured how crosstalking HSL signals affect the heterogeneous response of two branches of the V. fischeri pheromone sensing network. The AinS/R and LuxI/R pathways in V. fischeri comprise two distinct but interacting, sensing pathways that are important to colonization of the microbe's animal host. They are linked in a generally sequential fashion 13 , but they also interact through several different crosstalk mechanisms. Figure 1 gives an overview of these mechanisms 14 . The AinS/R branch of the system controls expression of litR . It synthesizes (via AinS) and detects (via AinR) the autoinducer N -octanoyl- l -homoserine lactone (C8HSL). When C8HSL is absent or extremely dilute, AinR phosphorylates LuxU, which phosphorylates LuxO, which in turn activates transcription of qrr1 . The sRNA Qrr1 represses litR, which encodes the master regulator LitR. At higher C8HSL concentrations AinR dephosphorylates LuxU, the phosphorylation cascade is reversed, and LitR production increases. LitR has a broad regulon that affects colonization of the symbiotic host, flagellar motility and chemotaxis, exopolysaccharide production, and other factors 15 – 17 . Figure 1 Schematic of the Vibrio fischeri AinS/R and LuxI/R pheromone sensing systems and their crosstalk . (AI2 signaling via LuxP/Q is not shown.) AinS and AinR are the synthase and cognate receptor respectively for C8HSL. At low extracellular C8HSL concentrations, AinR drives the LuxU/LuxO phosphorylation cascade which stimulates transcription of the regulatory RNA Qrr, which posttranscriptionally inhibits expression of litR . At high C8HSL concentrations, LuxU and LuxO are dephosphorylated and qrr transcription is suppressed, allowing production of LitR. LitR controls colonization and motility phenotypes. LuxR is the intracellular receptor for the autoinducer 3OC6HSL, produced by LuxI. LuxR interacts with 3OC6HSL to form a dimeric transcriptional activator complex that binds the lux box site, which controls expression of the lux operon, luxICDABEG. The lux operon controls synthesis of the bacterial luciferase and its substrate, which are responsible for bioluminescence. The AinR/S and LuxI/R pathways are subject to crosstalk through several mechanisms, which are indicated by dashed curves: C8HSL interacts with LuxR both alone and in combination with 3OC6HSL; 3OC6HSL influences ainSR transcription through a LuxR-dependent interaction; LitR activates luxR transcription. LitR also activates luxR, which encodes the intracellular receptor LuxR of the LuxI/R branch of the system. LuxI/R controls expression of the lux operon, luxICDABEG, by synthesizing (via LuxI) and detecting (via LuxR) the autoinducer N-(3-oxohexanoyl)- L- homoserine lactone (3OC6HSL). The lux operon is responsible for both 3OC6HSL production (LuxI) and bioluminescence (LuxCDABEG) 14 . V. fischeri also detects a third autoinducer, AI2, through the LuxS/P/Q detection system which also feeds into qrr . However, under the conditions that have been tested AI2 has only a modest effect on colonization and luminescence 18 . We do not consider it further in this study. One mechanism of crosstalk in this system is that AinS/R stimulates the LuxI/R branch by upregulating luxR via LitR . Therefore C8HSL detected by the AinS/R system sensitizes the pathway that detects 3OC6HSL. Another mechanism occurs via the receptor LuxR, which can form the transcriptional activator for lux through binding of either C8HSL or 3OC6HSL. Different combinations of these autoinducers activate lux with different effectiveness 19 . A third mechanism arises through 3OC6HSL, which acts with LuxR to repress ainSR , apparently by binding upstream of its promoter, hence indirectly suppressing qrr 20 , 21 . The presence of these crosstalk mechanisms suggests that combinations of HSLs may have complex effects on the response of each branch. The positive feedback that exists in both systems could accentuate these interactions. If mixtures of the two HSLs allow fine tuning of the joint response, they could enable additional modes or levels of activation during colonization of the host animal. Several prior studies have explored the effects of multiple driving inputs on statistical distributions of quorum-regulated gene expression, typically by characterizing the mean and variance in expression of a reporter 22 – 24 . However, mean and variance may be insufficient to describe changes in these statistical distributions, especially as the distributions need not follow any known form. The relevant parameters, or even the number of relevant parameters, that describe the distribution are not necessarily known. Common parameters like mean and variance may be correlated or may fail to capture fundamental changes in the shape or asymmetry of a distribution, such as a transition to bimodality. Here we use a data-based, dimension-reduction approach to explore how individual cell behavior changes when different HSLs are present in combination. Dimension reduction allows easier visualization of complex datasets and facilitates interpretation and modeling of that data 25 . Using promoter activity of qrr and luxI as readouts, we collected histograms of individual-cell activity in the AinS/R and LuxI/R branches respectively, for different combinations of the two HSLs. Applying principal component analysis (PCA) to these histograms allows us to assess whether the two-dimensional (two-HSL) space of signal inputs generates a similar, multidimensional space of possible output distributions of each branch. The dimensional-reduction provided by PCA, and especially nonlinear PCA 26 , facilitates clear visualization of how noisy cell behavior is shaped by combinations of input signals. This in turn allows us to map the HSL concentrations for which the distribution of qrr and luxI reporter activity is most sensitive or responsive, providing insight into the environmental inputs that the V. fischeri sensing system appears attuned to detect.",
"discussion": "Discussion Bacterial pheromone sensing systems typically have a complicated structure that links multiple signals and their detection pathways through crosstalk and regulatory feedback. This complexity raises questions of what information these systems gain by detecting more than one autoinducer species, what environmental changes they are tuned to detect, and how interactions between incoming signals modify the range of responses of each sensing pathway. Single cell measurements have shown that phenotypic heterogeneity is substantial in these sensing systems and that it may play an important role in pheromone sensing strategies 40 . The analysis of the information flow in a multiple autoinducer system should address how the crosstalking signals and receptors affect the statistical distribution of individual cell response, rather than just average behaviors. Although combinations of multiple receptor channels can tune phenotypic heterogeneity 24 , the detection of more than one HSL does not itself increase the information available to an individual cell, as might be expected if the multiple signals served a coincidence detection function 41 . However, because the output of a pathway is statistical in character, it can be difficult to visualize and quantify the effects of combinations of autoinducer signals on sensing function. The LuxI/R and AinS/R branches of the V. fischeri pheromone sensing pathway are linked by crosstalk in the form of noncognate HSL-receptor interactions, upstream regulation of LuxR via LitR, and transcriptional repression of qrr (in addition to feedback effects). Here we have used dimension-reduction to explore and visualize how crosstalk modifies the statistical distribution of output of each branch. The activity of a lux reporter provided an experimental readout for the LuxI/R system. Because qrr is directly driven by the LuxO/LuxU phosphorelay and is the immediate regulator of litR 28 , we used qrr promoter activity as a readout of the response of the AinR/S-controlled pathway. We used PCA to perform a model-free, dimension-reduction of the responses of individual cells. This method characterizes changes in the qrr and lux reporter distributions without making assumptions about what statistical measures, such as mean or variance, have greatest significance in the population-wide response of cells. The analysis shows that for both the AinR/S and LuxI/R pathways, the full set of statistical distributions of output activity can be accurately represented in a low-dimensional space; in fact they can be represented as points embedded in a low-dimensional space, where these points fall closely along a simple threading curve. The curve takes a more complex form for lux , where it is nonmonotonic in each of the principal component dimensions, than for qrr . Distributions of individual cell behavior can be shaped by many mechanisms, and both the lux and qrr branches of the system are presumably subject to intrinsic and extrinsic noise as well as crosstalk, which may combine in various ways to generate the observed distributions. The qualitative difference between the qrr and lux trajectories in Fig. 6 a,c may reflect the fact that HSLs impact lux activity through both a regulatory/transcriptional pathway and by direct binding to the LuxR receptor. That is, a higher level of lux activity could be achieved both by higher 3OC6HSL levels binding to existing LuxR—an effect driven by the 3OC6HSL inputs—and by higher LitR levels leading to increased production of LuxR—an effect driven largely by C8HSL. Both of these effects would be expected to increase average lux activity, but as they involve different LuxR copy numbers they would be expected to lead to differences in lux variance. That is, variance in lux activity can be seen as having both intrinsic (due to 3OC6HSL-LuxR interactions) and extrinsic (due to LitR and LuxR levels) origins. At the same time, the effect of C8HSL on LitR (and hence LuxR) can be ameliorated to some extent by the crosstalking effects of 3OC6HSL on qrr. Thus the architecture of the system appears to allow the mean and variance of lux activity to be manipulated through multiple, but not entirely independent, routes. Given that the HSLs modulate both qrr and lux through such interlocked mechanisms, it is surprising that the full range of population-wide responses to varying two signal inputs tunes the output in an essentially one-parameter fashion. An interesting line of further study could be to explore the robustness of this result under perturbation of the system, using mutant strains. One could investigate for example whether the same general family of distributions represented in Fig. 6 are still present in mutant strains where some of these crosstalk mechanisms are disrupted, such as by constitutive expression of luxR . In some other, well studied systems where the crosstalk between autoinducer signals is very pronounced it has been possible to identify distinct roles for individual signals. For example, Vibrio harveyi detects three signals (including two HSLs) in a mostly parallel mode where information from the three dedicated receptors merges in a common phosphorylation cascade. The three signals have been interpreted as intraspecies, intragenus, and interspecies signals, respectively 42 . They accumulate at different rates during the growth curve 11 and drive the outputs with different efficiency, so that the regulated phenotypes are expressed with different profiles during the growth curve. Similarly in Vibrio cholerae the intragenus and interspecies autoinducers appear to act jointly in the decision to disperse from a biofilm 43 . Consequently those multi-signal circuits may provide information about timing and species composition as a microbial community develops. The V. fischeri pathway has a more sequential structure in which the AinS/R and LuxI/R branches have distinct regulatory outputs. This has led to its interpretation as a two-stage mechanism that serves a timing function, with colonization behaviors triggering earlier due to AinS/R and bioluminescence induced later through LuxI/R 13 , 44 . Nevertheless the multiple mechanisms of crosstalk between the two branches raises the question of how interactions between the HSLs tune the overall response and sensitivity. Our finding that two dimensions of input stimulus elicit only a one-dimensional output from each branch could mean that the combinations of crosstalking autoinducers do not change the possible responses of the sensing system beyond what is observed with a single autoinducer. However that appears not to be the case. Instead we find (for both lux and qrr ) that the crosstalking (second) autoinducer drives the system's representative point (or the value of S qr r or S lux ) through portions of the response curve (Fig. 6 a,c) that are not sampled when only the first autoinducer is present. In the case of qrr , mixtures of both HSLs allow the system to travel further along the one-dimensional curve than it would in the presence of only one HSL: The presence of 3OC6HSL forces qrr into a more strongly OFF state than occurs even at high C8HSL concentrations. In the case of lux , the presence of C8HSL allows the level of lux expression to be more finely tuned between ON and OFF states: C8HSL allows a more gradual, less all-or-nothing, switching of the population-wide response of lux . The fact that V. fischeri senses two HSL autoinducers raises the question of whether the relative contributions of the two sensing pathways changes in a continuous fashion as HSL levels increase, allowing the two systems work together to control behavior at different stages of colonization 44 . The low-dimensionality of the response to HSLs simplifies the problem of determining when each pathway is maximally sensitive to the HSL inputs, and this may allow some insight into the functionality that is gained through the two HSLs. Our PCA analysis and our measurements of actual HSL concentrations together indicate that in ES114 both the lux and qrr outputs are mostly switched off during the overwhelming majority of the growth curve. The ES114 strain does not pass through either of the HSL regimes of high sensitivity except at the very earliest and latest stages of growth. Other than an early switching OFF of qrr (before OD = 0.10), and a very late switching ON of luxI (after OD = 1.0), there are few changes in either the qrr or lux histograms during the overwhelming majority of the growth curve in vitro. Consequently, although the system could be described as having a timing function, it may be useful to distinguish between a clock, which continuously reports the passage of time, and an alarm, which does not. Aside from early switching of AinS/R, the joint output of the two branches appears insensitive to the changes in HSL concentrations that would signal progression of ES114 through various intermediate population densities. Without the crosstalking effect of C8HSL, the statistical distribution of lux activity would shift as OD increases, and so the behavior of lux would contain information about the culture density. In fact however, we find that crosstalk makes the response of lux surprisingly insensitive to the age or density of a growing culture, at least until OD > 1. In this sense crosstalk between the two HSLs provides a strong delay functionality to the AinS/R/LuxI/R system although it actually reduces the system's ability to detect or respond to intermediate population densities. Finally we note that HSL production by different V. fischeri strains is highly variable 45 . In addition, the LuxR-HSL interactions are highly tunable through sequence variations in LuxR 31 , 46 , while the luxI-luxR intergenic region that regulates lux is highly divergent in comparisons between different V. fischeri strains 47 . Accordingly different strains should vary rather considerably, not only in the shape of the HSL sensitivity contours for their LuxI/R and AinS/R branches, but also in the trajectory with which they cross these contours during growth and colonization. It is an interesting question how this may allow V. fischeri strains other than ES114 to sense and respond to different combinations of environmental variables in optimal fashion."
} | 5,389 |
36692900 | PMC9999432 | pmc | 3,984 | {
"abstract": "Polymeric materials produced from fossil fuels have been\nintimately\nlinked to the development of industrial activities in the 20th century\nand, consequently, to the transformation of our way of living. While\nthis has brought many benefits, the fabrication and disposal of these\nmaterials is bringing enormous sustainable challenges. Thus, materials\nthat are produced in a more sustainable fashion and whose degradation\nproducts are harmless to the environment are urgently needed. Natural\nbiopolymers—which can compete with and sometimes surpass the\nperformance of synthetic polymers—provide a great source of\ninspiration. They are made of natural chemicals, under benign environmental\nconditions, and their degradation products are harmless. Before these\nmaterials can be synthetically replicated, it is essential to elucidate\ntheir chemical design and biofabrication. For protein-based materials,\nthis means obtaining the complete sequences of the proteinaceous building\nblocks, a task that historically took decades of research. Thus, we\nstart this review with a historical perspective on early efforts to\nobtain the primary sequences of load-bearing proteins, followed by\nthe latest developments in sequencing and proteomic technologies that\nhave greatly accelerated sequencing of extracellular proteins. Next,\nfour main classes of protein materials are presented, namely fibrous\nmaterials, bioelastomers exhibiting high reversible deformability,\nhard bulk materials, and biological adhesives. In each class, we focus\non the design at the primary and secondary structure levels and discuss\ntheir interplays with the mechanical response. We finally discuss\nearlier and the latest research to artificially produce protein-based\nmaterials using biotechnology and synthetic biology, including current\ndevelopments by start-up companies to scale-up the production of proteinaceous\nmaterials in an economically viable manner.",
"conclusion": "5 Outlook and Conclusions Polymeric materials\nare intricately linked to all aspects of modern\nsocieties and technologies, contributing to countless essential goods\nof our daily life. But this dependence has come with undeniable caveats.\nSynthetic polymers are based on fossil fuels and their poor degradability\nand general lack of recyclability are causing major harm to our ecosystems.\nThus, there is a pressing demand to develop more sustainable solutions\nthat will mitigate these issues. Nature has countless examples of\nbiopolymers synthesized using the complex machinery of living cells,\nand we have much to learn from such materials. Before one can attempt\nto replicate natural protein-based materials, a first important step\nis to identify the complete sequences of the protein building blocks.\nAs discussed in the first section of this review, it took decades\nof work to fully sequence the early model systems of natural protein-based\nmaterials. Thanks to technological breakthroughs in NGS and proteomics,\nit is now possible to sequence structural proteins in a much shorter\ntime scale. Multiple examples of natural protein-based materials exist\nin the living world, and while non-exhaustive, the model biological\nsystems presented in this review are representative of the major classes\nof load-bearing materials found in Nature, including stiff or extensible\n(bioelastomers) fibers, adhesives, and bulk materials. More often\nthan not, biological materials are multi-functional, such as mussel\nfibers: a single byssal thread is both stiff and extensible, and it\ncontains multiple adhesive proteins for efficient underwater attachment\nas well as a hard proteinaceous coating. The molecular designs unveiled\nin the past decades (see Figure 2 for the recent discovery pathway) and described in\nthis review offer countless opportunities to design from the bottom\nup to a whole new range of biopolymers. By combining building blocks\nfrom multiple model systems in a modular fashion, the range of achievable\nmechanical and physicochemical functional properties can be broadly\nexpanded well beyond those observed in the native system, in principle\nenabling the fabrication of truly multi-functional materials that\nmay find usage in a wide range of applications, as exemplified in Figures 12 and 13 . Biotechnology and genetic engineering are\nindispensable tools in\nour quest to harness the molecular designs of natural biological materials\nand replicate them synthetically using an increasing range of expression\nhosts ( Figure 14 ),\nenabling the production of biopolymers with single-molecule precision\nand monodispersity. In the past decade, some of the most noticeable\nimprovements in the field have been the cost and speed of gene synthesis.\nCurrently, the cost of codon optimization and gene synthesis is as\nlow as eight cents per base pair, and it is expected to decrease by\nanother factor of two in the next five years, that is nearly 20-fold\ncheaper than a decade ago. Instead of making modifications to an existing\ngene, different variants of the same sequence can be easily and cheaply\nsynthesized. Furthermore, laboratories with relatively low budgets\ncan place an order for thousands of natural or mutated designs and\nscreen for potentially viable candidates. It is now possible to quickly\ngo beyond optimization of the original sequence and to create completely\nnewly designed sequences de novo , which once expressed\ncould potentially outperform naturally occurring structural proteins.\nThe other important advancement in the field has been the integration\nof automation and one-step precision cloning techniques. Conventionally,\nit could take up to a month for a skillful molecular biologist to\nsuccessfully carry out the cloning of a single gene using multi-step\ncloning techniques. This was further prone to complication depending\non the complexity of the gene, sequence length, transformation efficiency,\nstability of cloning-expression vectors, and cloning-expression host.\nToday a single operator with a general understanding of molecular\nbiology using a laboratory standard robotics arm can perform parallel\ncloning of hundreds of variants in a single week. Combined with accessibility\nto a substantially large selection of expression hosts, the chance\nof successful expression of any orthogonal genes has never been greater.\nTo overcome some of the remaining challenges of expressing difficult\nproteins, metabolic engineering of the host using the synthetic biology\ntoolkit is a favored option to improve the yield and quality of the\ndesired proteins, which has been made possible thanks to the availability\nof the entire genomes of almost all the expression hosts and their\nsub-variants. Furthermore, state-of-the-art gene editing techniques\nsuch as CRISPR/Cas9 have been streamlined, as well as larger-scale\nand programmable chromosome fusion which can target thousands of genes\nat once. These exciting enabling technologies could result in the\ncreation of completely new synthetic hosts that could be programmed\nand specifically designed to express the target proteins. There\nare several challenges ahead before artificial materials\nreplicating the model systems described in this review can become\na reality in daily life applications. The spatiotemporal pathways\nby which biology precisely regulates molecular assembly from the cellular\nlevel to the final, multi-scale material structure are still largely\nunknown with a few exceptions such as silk fibers and mussel threads,\nfor which breakthroughs in our understanding of their biofabrication\nhave been achieved in recent years (see Rising and Harrington in this\nthematic issue 1000 ). The role of many PTMs\nalso remains elusive in many model systems. Toward replicating the\ngreen chemistry principles by which biologicals process extracellular\nmaterials, it will be crucial in the coming years to elucidate how\nstructural precursor proteins are secreted in the extracellular milieu\nand transported to their final destination; how they specifically\ninteract with other building blocks (other proteins, polysaccharides,\nmetal ions, and minerals) of the mature structure; and how they are\neventually chemically stabilized to build robust materials. Multiple\nlength scales will need to be carefully investigated, including at\nthe intracellular level (different vesicles secrete specific proteins),\nthe glandular tissues where the precursor proteins are concentrated\nand subjected to various microenvironments (pH, ionic strength, etc. ), conditions and/or mechanical stresses, and the tissue\nlevel during deposition. With regard to artificial production\nof protein-based materials,\ncurrent microbial fermentation processes mainly involve the conversion\nof readily available carbon sources such as plant-based simple sugars\nand starch into chemicals, fuels, and biopolymers. One alternative\nsolution is to exploit biological conversion of low-cost CO 2 (atmospheric, industrial waste emissions, and synthetic gas from\ngasification of non-food agricultural wastes biomass) to high-added-value\nchemicals and energy. The latest advances in synthetic biology are\nforecast to offer new tools to improve the properties and artificial\nproduction of these materials. For example, it may be possible to\nalter the metabolism of the microorganisms and increase yields significantly\nor to engineer strains that mostly rely on CO 2 as a carbon\nsource during fermentation. 639 The incorporation\nof non-canonical amino acids to enhance the properties of the materials\nis another promising avenue. Thus, we anticipate that future research\nwill likely require engineering and utilization of entirely new and\nnovel microbial strains to fabricate complex biopolymers. In order\nto deliver the next generation of biopolymers in a cost-effective,\nefficient, and sustainable manufacturing manner, bioprocessing methods\nwill also require ingenuity to interlink high-throughput screening\nplatforms with automation for process optimization using advanced\nmini-reactors. These will then need to be seamlessly integrated into\nlarge-scale fermentation methods such as continuous flow reactors.\nWe are also entering a new era of machine learning and advanced computational\nmodeling. This new in silico toolbox may provide\na wide source of data-driven inquiries and may find exciting applications\nin protein polymer design and manufacturing, for example to enhance\nmetabolic engineering to optimize yields and the final product design.",
"introduction": "1 Introduction Polymer materials represent\na central aspect of everyday life and\nadvanced technologies, from consumer goods to textiles, from high-performance\ncomposites to packaging, and from adhesives to electronic components,\nto name just a few examples. There is literally no modern human activity\nthat does not depend on classical and more advanced polymers, and\ntheir production nowadays exceeds that of steel. Yet we have a fundamental\nambivalence with respect to polymers, because they are also perceived\nas emblematic of a non-sustainable way of life. Indeed, despite our\nenormous reliance on plastics for every aspect of our modern life, 1 they generate much disdain, being perceived as\nmaterials that are “cheap” and polluting. 2 This perception arises from two fundamental reasons.\nFirst, polymers are in their large majority synthesized from fossil\nfuels, i.e. petro-chemical derived chemicals. And\nsecond, many are non-biodegradable and exhibit poor recyclability.\nTheir degradation products can be toxic, which raises serious concerns\nabout their end-of-life disposal, 2 not\nto mention their accumulation in large quantities in the Oceans that\nbadly affect marine ecosystems 3 , 4 or in landfills. 5 , 6 Because of these issues, there is an urgent need to develop new\npolymeric materials that can be more sustainable, i.e. their fabrication does not fully rely on petro-chemical derived\nchemicals, they use less energetic resources, and they can degrade\ninto non-harmful chemicals in the environment. In our quest\ntoward alternative and more sustainable polymer solutions,\nNature perhaps represents the best source of inspiration, exhibiting\nkey advantages over fossil-fuel derived polymers. Biological materials\nare produced in an eco-friendly fashion using natural chemicals. Indeed,\nthe complex machinery of living cells that produces extracellular\ntissues operates in an aqueous environment and at room temperature\nand pressure. The degradable products of these materials are harmless,\nsuch as amino acids in the case of protein-based biopolymers. Thus,\nthe living world abounds in biopolymers with remarkable mechanical\nand physical characteristics that can compete or sometimes exceed\nthe best synthetic polymers. 7 − 9 For example, silk has been known\nfor decades to exhibit outstanding mechanical properties 10 , 11 that surpass those of many synthetic fibers, 12 , 13 and there has been an outburst of activity in producing artificial\nversions of silk using biotechnology processes in the past decade,\nwith a wide range of potential applications explored. 14 , 15 Furthermore, biological polymers are produced via bottom-up “biofabrication”\nprocesses that seamlessly exploit the multi-scale self-assembly and\nsupramolecular chemistry afforded by the versatility of the 20 amino\nacids of proteins and their post-translational modifications (PTMs). 16 The end products are typically multi-functional,\nand when reproduced artificially with de novo gene\ndesign, innovative properties can in principle be achieved such as\nbioactivity and programmed degradability. Altogether, these synergistic\ncharacteristics are still unmatched in synthetic polymers. This\nreview is organized in five sections. In Section 2 , we present methods of protein\nsequencing in the field of protein materials, a critical initial step\nthat has traditionally been a major bottleneck in the field. Earlier\nmethods are first described, in particular those still in use today\nthat yield information that cannot be readily obtained with “omics”\nmethods, before moving to latest developments that are relevant to\nmaterials discoveries. In Section 3 , essential molecular designs of protein-based materials\nare described, with an emphasis on sequence/structure property relationships\nand common biochemical and structural features. The materials presented\nin this section are organized based on their structural functionality\nand illustrate that protein-based materials utilize the whole spectrum\nof secondary structures at the disposal of polypeptides. Some load-bearing\nproteins are mostly intrinsically disordered, 17 such as the bioelastomeric elastin ( Section 3.2.1 ), or in their storage glands prior to\nsecretion, e.g. mussel foot proteins (MFPs, Section 3.3.1 ) or the\nslime of the velvet worm ( Section 3.1.3 ). Others are dominated by β-sheets\nthat are preferentially aligned along the macroscopic fiber such as\nsilk fibroins ( Section 3.1.1 ) or perpendicular to the fiber in the case of amyloid-like\nfibrils; for example barnacle cement proteins ( Section 3.3.2 ) or curli filaments ( Section 3.3.4 ). Yet other\nproteins are mostly made of α-helical coiled-coil regions that\nare reminiscent of intermediate filaments (IFs), including marine\nsnail egg capsule proteins (ECPs, Section 3.2.4 ) and hagfish filaments ( Section 3.1.2 ), or contain\ncollagenous triple-helical domains, such as the core of mussel adhesive\nfilaments ( Section 3.2.3 ). And finally, some extracellular structures are built from\nproteins with both ordered and disordered regions as illustrated by\nthe squid sucker ring teeth proteins called suckerins ( Section 3.4.4 ). In Section 4 , we\nsurvey the bioengineering fabrication of protein-based materials presented\nin Section 3 . The different\ntypes of living hosts used for biofabrication are compared, including\ntheir key respective advantages/disadvantages and current limitations.\nMethods of purification are also described here as this has been,\nand remains in many cases, a bottleneck toward scaling-up of protein-based\nmaterials. Recent efforts by spin-off companies to fabricate protein\nmaterials are described in this section to highlight potential routes\nfor future commercialization. In the final Section 5 , we provide a perspective on future developments\nand major hurdles that will need to be overcome in order to achieve\nprotein materials produced though biotechnology a viable alternative\nto synthetic polymers."
} | 4,101 |
37938648 | PMC9723793 | pmc | 3,985 | {
"abstract": "The sea anemone, Exaiptasia diaphana , is a model of coral-dinoflagellate (Symbiodiniaceae) symbiosis. However, little is known of its potential to form symbiosis with Cladocopium —a key Indo-Pacific algal symbiont of scleractinian corals, nor the host nutritional consequences of such an association. Aposymbiotic anemones were inoculated with homologous algal symbionts, Breviolum minutum , and seven heterologous strains of Cladocopium C1 acro (wild-type and heat-evolved) under ambient conditions. Despite lower initial algal cell density, Cladocopium C1 acro -anemeones achieved similar cell densities as B. minutum -anemones by week 77. Wild-type and heat-evolved Cladocopium C1 acro showed similar colonization patterns. Targeted LC-MS-based metabolomics revealed that almost all significantly different metabolites in the host and Symbiodiniaceae fractions were due to differences between Cladocopium C1 acro and B. minutum , with little difference between heat-evolved and wild-type Cladocopium C1 acro at week 9. The algal fraction of Cladocopium C1 acro -anemones was enriched in metabolites related to nitrogen storage, while the host fraction of B. minutum -anemones was enriched in sugar-related metabolites. Compared to B. minutum , Cladocopium C1 acro is likely slightly less nutritionally beneficial to the host under ambient conditions, but more capable of maintaining its own growth when host nitrogen supply is limited. Our findings demonstrate the value of E. diaphana to study experimentally evolved Cladocopium .",
"conclusion": "Conclusions and directions for future research Several implications relevant to reef restoration and future research have emerged from this study. Firstly, better colonization success and nutrient provisioning may occur when the host and algal symbiont are from the same geographic region. Hence, reef restoration practices that utilize algal symbionts should consider the importance of co-evolution and source algal symbionts from locations near the targeted hosts when possible. Secondly, lower initial host colonization is expected when heterologous algal symbionts are used for reef restoration practices. However, their colonization success will likely improve over time and longer-term monitoring (i.e., >1 year) is important. While the Cladocopium C1 acro used is this study is a heterologous symbiont of E. diaphana , it is the most common Symbiodiniaceae genus in Indo-Pacific scleractinian corals [ 21 ] and a homologous symbiont for a wide variety of coral species [ 22 ]. Therefore, heat-evolved Cladocopium C1 acro would likely colonize many coral species at a much faster rate than E. diaphana , and potentially conferring bleaching tolerance to the coral hosts. Evidence so far from the literature and this study suggests that homologous Symbiodiniaceae symbionts are likely more nutritionally beneficial to the host than heterologous symbionts under ambient conditions, yet this dynamic may change under ocean warming which should be a focus of future research. Under elevated temperatures, thermally tolerant heterologous symbionts (e.g., the heat-evolved Cladocopium C1 acro ) may become advantageous and more nutritionally beneficial to the host [ 66 , 67 ]. Due to the significant biomass requirement, omics studies (e.g., metabolomics, proteomics, transcriptomics) on E. diaphana are generally limited to ambient temperature only [ 12 , 14 , 24 ], or limited to one E. diaphana -Symbiodiniaceae combination when multiple temperatures are applied [ 13 ]. In addition to omics studies, future studies on heat-evolved Symbiodiniaceae can also apply tacking methods such as 13 C labelling, which would provide direct evidence on photosynthate translocation from the algal symbionts to the host. Future studies investigating the physiology and metabolite profiles of anemones associated with homologous and different thermally tolerant heterologous algal symbionts under elevated temperatures will provide invaluable insights for reef restoration initiatives.",
"introduction": "Introduction Like corals, the sea anemone Exaiptasia diaphana is a cnidarian that establishes symbiosis with dinoflagellates in the family Symbiodiniaceae. In this symbiosis, the algae translocate products of carbon fixation and nitrogen assimilation as glucose, glycerol, amino acids, alanine and/or organic acids to the host [ 1 – 3 ], and gain host-derived inorganic nutrients such as carbon dioxide, ammonium, amino acids, lipids and fatty acids [ 4 ]. Symbiodiniaceae loss in corals due to ocean warming (i.e., coral bleaching) has significant negative impacts on coral health and the persistence of coral reef ecosystems [ 5 , 6 ], highlighting the importance of studying the coral-Symbiodiniaceae symbiosis. Compared to corals, however, E. diaphana is fast growing, easy to maintain and to render aposymbiotic (i.e., free of algal symbionts), and it can survive longer when bleached. These characters allow researchers to easily establish an E. diaphana population, manipulate their Symbiodiniaceae community and to examine cellular processes that would otherwise be challenging to study with corals [ 7 ]. Hence, E. diaphana is a common a model for coral-Symbiodiniaceae symbiosis. E. diaphana has been used to examine the flexibility of algal symbiont-host pairings [ 8 , 9 ], and the physiological [ 10 , 11 ], transcriptomic [ 12 ], metabolic [ 12 , 13 ] and proteomic [ 14 ] consequences of associating with homologous and/or heterologous (i.e., non-native) algal symbionts under ambient and/or elevated temperatures. Eleven Symbiodiniaceae genera (i.e., Breviolum, Cladocopium, Durusdinium, Effrenium, Fugacium, Freudenthalidium, Gerakladium, Halluxium, Miliolidium, Philozoon, Symbiodinium ) have been formally described [ 15 – 18 ]. For Indo-Pacific E. diaphana , their homologous (i.e., native) Symbiodiniaceae are predominately Breviolum minutum (ITS2: B1) [ 19 ], although Cladocopium and Durusdinium are occasionally found in low abundance [ 20 ]. Atlantic E. diaphana natively associate with Symbiodinium linucheae (ITS2: A4) and B. minutum and occasionally with Cladocopium [ 19 ]. Cladocopium spp. are the most widely distributed algal symbionts of Indo-Pacific scleractinian corals [ 21 ] and are found in >150 cnidarian species on the Great Barrier Reef (GBR) [ 22 ]. Although some heterologous algal symbionts can colonize aposymbiotic E. diaphana [ 8 , 9 , 11 , 12 , 14 , 23 , 24 ], colonization success of Cladocopium spp. is generally poor [ 11 , 25 ] and these are therefore often excluded from E. diaphana experiments [ 8 , 12 ]. However, most studies only monitored host algal cell density up to a few weeks post inoculation [ 23 ]. Nevertheless, a few studies have demonstrated short-term [ 9 ] and long-term (>1 year) [ 23 ] successful colonization of aposymbiotic E. diaphana by Cladocopium (ITS2: C1). All E. diaphana studies so far focus on wild-type Symbiodiniaceae (i.e., Symbiodiniaceae that have been growing under long-term ambient conditions), and none have explored the potential of E. diaphana as a model to study experimentally evolved Symbiodiniaceae. Experimental evolution has been shown to enhance growth, photo-physiological performance and/or the upper thermal limit in many marine microalgal species [ 26 ]. For example, experimentally evolved Cladocopium C1 acro maintained positive growth and produced less reactive oxygen species (ROS) than wild-type Cladocopium C1 acro under elevated temperatures (31 °C) [ 27 , 28 ]. These experimentally evolved heat-tolerant symbionts (hereafter refer to as “heat-evolved” symbionts) can potentially be used to inoculate corals to improve their thermal tolerance [ 29 ]. Buerger et al. [ 28 ] demonstrated that heat-evolved Cladocopium C1 acro can colonize aposymbiotic coral larvae, where three of the ten strains tested conferred enhanced thermal bleaching tolerance on the larvae compared to the wild-type Cladocopium C1 acro while seven did not. However, coral larvae and adults differ significantly in physiology, hence more studies are required to examine the potential benefits and drawbacks of associating with heat-evolved Symbiodiniaceae, particularly in the adult host stage. The values of E. diaphana as a coral model would be enhanced significantly if it can form symbiosis with heat-evolved Symbiodiniaceae and this sea anemone serves as a model for these investigations. Bi-directional exchange of organic and inorganic compounds is critical to the success and stability of the cnidarian-dinoflagellate symbiosis [ 1 ]. Different Symbiodiniaceae strains may translocate different types (e.g., glycerol vs. lipids) and quantities of photosynthate to the host [ 1 ], affecting the host’s nutritional potential and overall fitness. While E. diaphana can be rendered aposymbiotic and be colonized by heterologous Symbiodiniaceae, heterologous associations can be less beneficial to the host than homologous symbioses [ 8 , 10 , 12 ]. However, the nutritional consequences of E. diaphana associated with heterologous Cladocopium —a key algal symbionts in Indo-Pacific corals, and heat-evolved Cladocopium —a potential candidate to improve cnidarian thermal tolerance, remain unknown. This study aims to examine (1) whether E. diaphana from the GBR, which harbours B. minutum as its homologous symbiont, can form a stable symbiosis with heterologous wild-type and heat-evolved Cladocopium C1 acro , and (2) the nutritional consequences of the respective Cladocopium C1 acro associations with specific focus on central carbon metabolism. Since glucose is a key form in which Symbiodiniaceae translocate fixed carbon to the cnidarian host [ 2 , 30 ], particular focus is given to sugar-related metabolites.",
"discussion": "Discussion Heterologous wild-type and heat-evolved Cladocopium C1 acro can establish a functional symbiosis with E. diaphana Despite being heterologous algal symbionts, our results show that wild-type and heat-evolved Cladocopium C1 acro can establish a functional symbiosis with E. diaphana . While Symbiodiniaceae cell density in all Cladocopium C1 acro - anemones was lower than in B. minutum -anemones initially, all anemones achieved the same cell density by week 77. With a few exceptions [ 12 ], the homologous B. minutum is generally more successful in colonizing aposymbiotic anemones than heterologous Symbiodiniaceae [ 8 , 9 , 11 , 12 , 14 , 24 , 43 , 44 ]. For example, B. minutum had faster colonization and higher cell densities in Indo-Pacific anemones than the heterologous S. microadriaticum (ITS2: A1), Durusdinium trenchii (ITS2: D1a), Effrenium voratum (ITS2: E1) and Cladocopium spp. (ITS2: C3) [ 11 ]. Medrano et al. [ 24 ] reported a fourfold higher cell density in anemones colonized by B. minutum compared to D. trenchii , although Matthews et al. [ 12 ] found similar cell density between the two by week 5 post inoculation. Successful long-term symbiosis between E. diaphana and the heterologous Cladocopium is rare. Of the few known cases of Cladocopium uptake, Chen et al. [ 23 ] reported successful colonization of bleached anemones with C. goreaui for >1 year, and the Cladocopium cells were transmitted to their asexual offspring produced via pedal laceration. Another Cladocopium species (ITS2: C3) was observed to successfully colonize anemones initially, but their cell density declined rapidly to ~2.0 × 10 4 cells mg −1 protein by week 8 post inoculation [ 11 ]. Cladocopium was only able to colonize the oral disk and tentacles of the anemones initially (as opposed to the entire body as with the homologous B. minutum ), and was restricted to the oral disk only by week 8 [ 11 ]. Successful short-term (30 days) colonization of Cladocopium C1 acro in GBR E. diaphana has previously been demonstrated, although the cell density was fluctuating over time [ 9 ]. There are several possible explanations for the colonization success of E. diaphana by the heterologous wild-type and heat-evolved Cladocopium C1 acro in this study. Firstly, the heterologous Symbiodiniaceae inocula used in previous studies generally originated from different parts of the world compared to the host [ 8 , 11 , 14 , 25 ], except in Tortorelli et al. [ 9 ], while both the host and Symbiodiniaceae originated from the central GBR in our study. Allopatric divergence in traits required for symbiosis maintenance (e.g., cell–cell recognition) may have hindered the heterologous algal colonization success, although successful colonization by a heterologous Symbiodiniaceae inoculum originated from regions different to that of the host has been reported in some cases [ 12 , 23 ]. The field of Symbiodiniaceae-host recognition is still in its infancy, but the role of glycan–lectin interactions [ 45 , 46 ] and the potential involvement of d-galactose, l-fucose, d-xylose and d-galacturonic acid in the establishment of this mutualism have been shown [ 45 ]. Future studies comparing the recognition molecules of Symbiodiniaceae and host from different regions will shed light on the topic of allopatric divergence and Symbiodiniaceae-host compatibility. Secondly, colonization success of Cladocopium C1 acro in E. diaphana may not have been fully reflected in previous studies due to the relatively short observation periods. At week 9, Symbiodiniaceae cell density observed in our study was consistent with most published works (i.e., lower in the heterologous algae). However, the Symbiodiniaceae cell densities in B. minutum -anemones plateaued by week 21–24, whereas they continued to increase in Cladocopium C1 acro -anemones and had achieved the same level as B. minutum by week 77. The symbiosis established by wild-type and heat-evolved Cladocopium C1 acro was functional and healthy, as indicated by the 100% host survival. Conversely, associations with unsuitable heterologous Symbiodiniaceae can result in significant host mortality [ 9 ]. Our findings highlight the potential of E. diaphana as a model to study cnidarian-dinoflagellate symbiosis with Cladocopium C1 acro , a common and widespread species in Indo-Pacific reef-building corals, as well as with experimentally evolved Cladocopium C1 acro that may enhance holobiont thermal bleaching tolerance [ 28 ]. Wild-type and heat-evolved Cladocopium C1 acro had similar colonization rates and sugar translocation ability Multiple studies have demonstrated that experimental evolution can enhance certain traits of marine microalgae, although trade-offs are sometimes observed [ 26 ]. Earlier studies [ 27 , 28 ] showed that the heat-evolved Cladocopium C1 acro used in this study were able to maintain positive growth and secreted less ROS under elevated temperature (31 °C) in vitro than their wild-type counterparts. At the same time, heat-evolved Cladocopium C1 acro grew slower than the wild-type in vitro under ambient conditions [ 28 ]. We observed no evidence of trade-offs with in vitro growth and ROS secretion in terms of the symbionts’ ability to colonize and translocate sugar to the host, based on the 207 central carbon metabolites examined under ambient condition. It is not known whether the three amino acids enriched in heat-evolved Cladocopium C1 acro in symbiosis with E. diaphana may be related to their enhanced thermal tolerance in vitro [ 28 ]. Arginine, as an proteinogenic amino acid with the highest nitrogen to carbon ratio, is an ideal organic nitrogen storage in plants [ 47 ]. Heat-evolved Cladocopium C1 acro may have greater ability for organic nitrogen storage, which may enable them to maintain growth under elevated temperatures [ 48 ]. However, whether this is beneficial to their host is debatable [ 49 , 50 ] and requires further testing. Heterologous Cladocopium C1 acro may be slightly less nutritionally beneficial to the E. diaphana host than homologous B. minutum under ambient conditions Anemones associated with heterologous algal symbionts have been shown to have lower photosynthesis rates, less growth, pedal laceration [ 11 ], carbon translocation [ 10 ], and an upregulation of innate immunity responses and lipid catabolism [ 12 ]. 13 C labelling showed that all sugar compounds investigated (i.e., maltose, fructose, sucrose and xylose) were solely present in anemones with the homologous B. minutum [ 51 ]. None of these sugar compounds were detected in D. trenchii -anemones, and these also had a lower amount and diversity of 13 C-labelled carbohydrates and lipogenesis precursors. The authors therefore concluded that homologous algal symbionts provide greater fitness benefits to the host than heterologous algal symbionts via increased de novo glucose synthesis and translocation. Such strong contrast was not observed in our data. When the relative abundance of sugar-related metabolites was normalized to the host dry weight alone, a few of the sugar-related metabolites were enriched in B. minutum- anemones compared to Cladocopium C1 acro -anemones at week 9. This may be a consequence of the higher Symbiodiniaceae densities in B. minutum- anemones at the week 9 time point, which may also be responsible for the higher host dry weight at that time point. When the relative abundance of these sugar-related metabolites was normalized to both the host and Symbiodiniaceae dry weight, interestingly, fewer metabolites were enriched in B. minutum- anemones compared to Cladocopium C1 acro -anemones, and one sugar-related metabolite was even enriched in Cladocopium C1 acro -anemones. This indicates that sugar translocation per algal biomass of Cladocopium C1 acro was likely not much lower than that of B. minutum . Heterologous Cladocopium C1 acro , therefore, seems slightly less nutritionally beneficial to the host than homologous B. minutum under ambient conditions, but likely more nutritionally beneficial to the host than heterologous D. trenchii . Several studies have shown that coral dominated by Durusdinium grow more slowly [ 52 , 53 ] and have lower stored lipids [ 54 ] and δ13C values [ 55 ] than conspecifics dominated by Cladocopium in the field; and that Cladocopium translocated more carbon to its host compared to Durusdinium under ambient conditions [ 56 ]. Nevertheless, a few studies observed no difference in the host and symbiont metabolite pool [ 57 ], as well as in heterotrophic nutrition [ 55 ] between Durusdinium and Cladocopium dominated corals. Heterologous Cladocopium C1 acro and homologous B. minutum differ in nitrogen storage ability In the Symbiodiniaceae fraction, the two significantly enriched metabolites in the purine metabolism pathways (i.e., guanine and xanthine) and the most significantly enriched metabolite (i.e., uric acid) in the heterologous Cladocopium C1 acro compared to the homologous B. minutum are all linked to nitrogen storage ability. Purine metabolism plays an important role as an ongoing source of nitrogen in plant growth. In the purine degradation pathway, guanase converts guanine to xanthine, and xanthine oxidase catalyzes the oxidation of xanthine to form uric acid as the end product (Fig. 3 ) [ 58 , 59 ]. Six genes encoding xanthine oxidase/dehydrogenase have been found in a Symbiodiniaceae ( Fugacium kawagutii ) genome, supporting the ability of these algae to form uric acid [ 60 ]. Uric acid functions as a nitrogen reserve in plants and uric acid crystals have been found in Symbiodiniaceae [ 61 ] (Fig. 3 ). When Exaiptasia spp. were treated with an inhibitor of xanthine oxidase, the uric acid crystals of their Symbiodiniaceae disappeared within seven days, hence these nitrogen reserves can be mobilized rapidly when required [ 61 ]. Fig. 3 Diagram of a simplified purine degradation pathway with relevance to Symbiodiniaceae nitrogen storage. The red font represents metabolites enriched in the Cladocopium C1 acro groups (WT10, SS+, SS−) compared to B. minutum (B1) and their relative abundances are shown on the heatmap. The locations of uric acid crystals within a Symbiodiniaceae cell as observed in Clode et al. [ 61 ] are indicated. The colour scale indicates log2 fold change relative to the mean. Nitrogen is vital to the synthesis of amino acids, proteins, nucleotides, nucleic acids, chlorophyll, Rubisco and other enzymes that are involved in carbohydrate production - all of which are critical for cell division and growth [ 62 ]. Compared to free-living Symbiodiniaceae, Symbiodiniaceae in hospite have higher carbon-to-nitrogen ratios and upregulate multiple transcripts involved in the purine degradation pathway [ 43 ]. This suggests Symbiodiniaceae in hospite are nitrogen limited [ 43 ]; and a coral host can control the growth and therefore population density of its Symbiodiniaceae by limiting nitrogen supply [ 63 , 64 ]. Under elevated temperatures, Symbiodiniaceae in hospite may grow more initially due to higher carbon fixation [ 50 ], yet they are unable to use that carbon for their own growth if they are nitrogen limited. When the coral Plesiastrea versipora was starved (i.e., no feeding), nitrogen deficiency became apparent in ≥ 4 weeks in their associated Symbiodiniaceae and their photosynthetic rates declined drastically by ~80% [ 65 ]. The enhanced nitrogen storage ability of the Cladocopium C1 acro compared to B. minutum suggests that they are likely more capable of maintaining photosynthesis for their own growth. One E. diaphana study showed that heterologous Durusdinium cells were more 15 N-enriched than homologous Breviolum cells, yet they provided less carbon to the host under ambient conditions [ 44 ]. The extra nitrogen availability to Durusdinium may have been a consequence of lower carbon translocation of the algae, that resulted in lesser host usage of its nitrogen re-assimilated from catabolism [ 44 ]. The implications of Symbiodiniaceae nitrogen storage ability on the maintenance of their mutualist relations with the host remains unclear and is an important field for future research. Conclusions and directions for future research Several implications relevant to reef restoration and future research have emerged from this study. Firstly, better colonization success and nutrient provisioning may occur when the host and algal symbiont are from the same geographic region. Hence, reef restoration practices that utilize algal symbionts should consider the importance of co-evolution and source algal symbionts from locations near the targeted hosts when possible. Secondly, lower initial host colonization is expected when heterologous algal symbionts are used for reef restoration practices. However, their colonization success will likely improve over time and longer-term monitoring (i.e., >1 year) is important. While the Cladocopium C1 acro used is this study is a heterologous symbiont of E. diaphana , it is the most common Symbiodiniaceae genus in Indo-Pacific scleractinian corals [ 21 ] and a homologous symbiont for a wide variety of coral species [ 22 ]. Therefore, heat-evolved Cladocopium C1 acro would likely colonize many coral species at a much faster rate than E. diaphana , and potentially conferring bleaching tolerance to the coral hosts. Evidence so far from the literature and this study suggests that homologous Symbiodiniaceae symbionts are likely more nutritionally beneficial to the host than heterologous symbionts under ambient conditions, yet this dynamic may change under ocean warming which should be a focus of future research. Under elevated temperatures, thermally tolerant heterologous symbionts (e.g., the heat-evolved Cladocopium C1 acro ) may become advantageous and more nutritionally beneficial to the host [ 66 , 67 ]. Due to the significant biomass requirement, omics studies (e.g., metabolomics, proteomics, transcriptomics) on E. diaphana are generally limited to ambient temperature only [ 12 , 14 , 24 ], or limited to one E. diaphana -Symbiodiniaceae combination when multiple temperatures are applied [ 13 ]. In addition to omics studies, future studies on heat-evolved Symbiodiniaceae can also apply tacking methods such as 13 C labelling, which would provide direct evidence on photosynthate translocation from the algal symbionts to the host. Future studies investigating the physiology and metabolite profiles of anemones associated with homologous and different thermally tolerant heterologous algal symbionts under elevated temperatures will provide invaluable insights for reef restoration initiatives."
} | 6,177 |
31020759 | PMC6852232 | pmc | 3,988 | {
"abstract": "Summary Iron is essential for most living organisms. In addition, its biogeochemical cycling influences important processes in the geosphere (e.g., the mobilization or immobilization of trace elements and contaminants). The reduction of Fe(III) to Fe(II) can be catalysed microbially, particularly by metal‐respiring bacteria utilizing Fe(III) as a terminal electron acceptor. Furthermore, Gram‐positive fermentative iron reducers are known to reduce Fe(III) by using it as a sink for excess reducing equivalents, as a form of enhanced fermentation. Here, we use the Gram‐positive fermentative bacterium Clostridium acetobutylicum as a model system due to its ability to reduce heavy metals. We investigated the reduction of soluble and solid iron during fermentation. We found that exogenous (resazurin, resorufin, anthraquinone‐2,6‐disulfonate) as well as endogenous (riboflavin) electron mediators enhance solid iron reduction. In addition, iron reduction buffers the pH, and elicits a shift in the carbon and electron flow to less reduced products relative to fermentation. This study underscores the role fermentative bacteria can play in iron cycling and provides insights into the metabolic profile of coupled fermentation and iron reduction with laboratory experiments and metabolic network modelling.",
"introduction": "Introduction Iron is a transition metal and an element essential for growth and survival of most microorganisms. Not only it is an important cofactor for the activity of enzymes such as cytochromes and iron–sulfur proteins (Sigel and Sigel, 1998 ) but can also be used directly as an electron donor or acceptor, depending on its valence state (Weber et al ., 2006 ). Thus, microbial metabolism and metabolic pathways are impacted by iron and its availability. This transition metal is cycled between its Fe(III) and Fe(II) state in nature and these forms are taken up differently by bacteria. The reduced form of iron is easier to acquire from the environment due to its higher solubility compared with Fe(III). Additionally, some bacteria can use Fe(III) as an electron acceptor, producing Fe(II). Aside from metal‐respiring bacteria that gain energy directly from electron transport to Fe(III), fermentative iron reducers can use Fe(III) as a sink for excess reducing equivalents as a form of enhanced fermentation (Lovley et al ., 2004 ; Lehours et al ., 2010 ; Dalla Vecchia et al ., 2014 ). However, understanding of the mechanism of iron reduction and the influence of iron on the overall metabolism is limited for fermentative Gram‐positive bacteria. These microorganisms are likely to contribute to iron reduction significantly, particularly in environments where Gram‐negative bacteria fare poorly, such as metal‐contaminated sites or hydrothermal environments (Nepomnyashaya et al ., 2010 ; Burkhardt et al ., 2011 ). Here, we use the soil bacterium Clostridium acetobutylicum as a Gram‐positive model organism for acetone–butanol–ethanol (ABE) fermentation and harness its ability to reduce iron and contaminant heavy metals (Jones and Woods, 1986 ; Gao and Francis, 2008 ) to study the iron reduction process and its impact on fermentation. The bacterium can utilize a range of monosaccharides and polysaccharides, producing organic acids and solvents (Jones and Woods, 1986 ). The life cycle of C. acetobutylicum is characterized by an initial growth phase in which the organism produces acetate and butyrate as major fermentation products (the acidogenic phase). As the pH value decreases due to the production of these organic acids, the bacterium shifts its metabolism to the production of acetone, butanol and ethanol to overcome the acidification of its environment (the solventogenic phase). In addition, the bacterium also produces H 2 and CO 2 (Jones and Woods, 1986 ). The coenzyme nicotinamide adenine dinucleotide (phosphate) (NAD(P)) involved in many cellular redox reactions is reduced to NAD(P)H during glycolysis, but must be re‐oxidized to sustain this glucose oxidation pathway. Thus, NAD(P)H is consumed to generate butyrate during the first phase of the metabolism, but during the solventogenic phase, it is consumed for the production of ethanol and butanol. Furthermore, excess reducing equivalents are transferred onto protons, resulting in H 2 production. If additional electron acceptors such as Fe(III) were provided, the electrons might be delivered to them, instead. The iron reduction process does not contribute significantly to energy conservation, because only a small fraction of excess electrons is directed to iron (Lovley et al ., 2004 ). For that reason, there may be another benefit for fermentative bacteria to reduce heavy metals. A recent study of Orenia metallireducens strain Z6, another fermentative bacterium, suggested that iron reduction during fermentation generates energy, but the most significant advantage is that it stabilizes the pH value due to the consumption of protons during the reduction process. Thus, iron reduction indirectly results in higher glucose consumption and a higher growth yield, but less H 2 is produced (Dong et al ., 2017 ). A second study, this time with Bacillus sp., showed that the products of fructose fermentation were altered in the presence of Fe(III). They observed decreased lactate production, but increased acetate and CO 2 production in iron‐reducing cultures compared to fermentation alone. In addition, the cell density remained constant in stationary phase in iron‐reducing cultures, whereas it decreased with fermentation alone (Pollock et al ., 2007 ). Here, we show that C. acetobutylicum is able to reduce soluble Fe(III), but solid iron reduction is only significant after the addition of an electron mediator. Iron reduction not only buffers pH but also results in an altered carbon and electron flow. Under iron‐reducing conditions, less hydrogen and more butanol are produced during the growth phase compared to fermentation alone. Iron reduction extends the duration of the acidogenic phase resulting in a higher production of organic acid and ATP. Metabolic modelling confirms the experimental data, as a higher flux variability is obtained if iron is provided suggesting that more alternative reactions are possible for the central metabolic pathways of C. acetobutylicum compared with fermentation alone.",
"discussion": "Discussion \n Clostridium acetobutylicum is known for ABE fermentation, but it is also able to reduce metals. Here, we show that the bacterium reduces solid and soluble iron. Whereas soluble iron reduction is very efficient, solid iron is reduced only to a limited extent (Fig. 1 , Fig. S4 ). The iron reduction process is likely different because Fe(III)‐citrate can be transported into the cell (Krewulak and Vogel, 2008 ; Fukushima et al ., 2014 ) where enzymes may reduce it, whereas HFO remains outside the cell requiring either an extracellular electron transport system to the cell surface or an electron shuttling system for the reduction to occur. It is well accepted that fermentative iron reducers deliver excess reducing equivalents to Fe(III) as a form of enhanced fermentation (Dalla Vecchia et al ., 2014 ; Dong et al ., 2017 ). Our results show that with a higher substrate (glucose) concentration, the reduction rate of solid iron could be increased likely due to the higher production of excess electrons (Fig. S2 ). HFO reduction was similar in two media (CBM and MSM) at high glucose concentration, suggesting that the increase in the iron reduction rate (relative to a low glucose system) is a consequence of the higher glucose concentration (Fig. S2 ). Studies of fermentative solid iron reduction by Gram‐positive organisms related to C. acetobutylicum showed efficient iron reduction rates, but they grew in the presence of an electron shuttle, natural groundwater or sediments (the latter two can contain natural exogenous electron shuttles) (Lehours et al ., 2010 ; Shah et al ., 2014 ; Dong et al ., 2016 , 2017 ). Thus, while solid iron reduction by C. acetobutylicum is slow in a laboratory setting, soils and sediments are expected to harbour electron shuttles (e.g., humic substances), which may be used by the organisms to transfer electrons to iron oxides. Here, we used artificial electron mediators including resazurin, resorufin, AQDS or an endogenous mediator, RF. Resazurin can be reduced to resorufin with NAD(P)H, FADH or FMNH and further to dihydroresorufin by an unknown mechanism (Rampersad, 2012 ; Chen et al ., 2018 ). In turn, dihydroresorufin can act as an electron shuttle to reduce HFO, with concurrent oxidation back to resorufin (Fig. S1 ). Indeed, the rate of solid iron reduction increased dramatically in the presence of resazurin, but also with resorufin, AQDS or RF (Fig. 1 ), supporting a role for electron shuttles. During pyruvate fermentation by Desulfotomaculum reducens , endogenous flavins were found to reduce solid iron (Dalla Vecchia et al ., 2014 ). The production of flavins under regulation of a putative ferric uptake regulator (Fur) was reported for C. acetobutylicum (Vasileva et al ., 2012 ). It was found that RF biosynthesis is increased under iron limitation or in absence of Fur. Flavins are also detected in the fermentation growth medium in this study and may account for the fraction of solid iron reduced by C. acetobutylicum in the absence of exogenous shuttles. Flavin secretion is not a known process in Gram‐positive bacteria, hence the presence of flavins extracellularly could be due to release by lysis. We probed the extent of cell lysis by measuring viable counts (CFU mL −1 ) and observed a decrease in CFU mL −1 numbers after 9 h (Fig. S8 ), raising the possibility that some flavins are released by lysis. However, flavins are measured extracellularly starting at 3 h while CFU mL −1 numbers indicate the exponential growth phase. More importantly, the extracellular flavin concentration is comparable to the intracellular concentration and the intracellular concentration decreases while the extracellular one increases. To account for the extracellular concentration, all the cells would have to lyse, which is clearly not true. Thus, we propose that flavins are secreted through an unknown mechanism because lysis alone cannot account for the extracellular concentration of these compounds. The release of FAD by C. acetobutylicum could be due to increased membrane permeability during solventogenesis, which was previously reported (Amador‐Noguez et al ., 2011 ). However, in the present study lower amounts of solvents were detected. In all conditions, FMN is secreted at high concentrations (Fig. 4 D). The only exception is in the presence of both HFO and resazurin. In that case, the concentration of secreted FMN is much lower, and the flavin remains in the cytoplasm (Fig. 4 D). Additionally, all the three measured flavins (RF, FMN and FAD) are excreted during fermentation with resazurin. This suggests that FMN (and to a lesser extent RF and FAD) plays a role as a means to deliver electrons to the extracellular milieu. But, why does FMN accumulate intracellularly when both resazurin and HFO are present? We propose that it remains mostly cytoplasmic in the presence of resazurin, because dihydroresorufin reduces HFO efficiently and replaces FMN in its putative role as an electron mediator. Thus, resorufin is re‐reduced intracellularly by FMNH, maintaining a specific redox potential. In contrast, in the absence of HFO, dihydroresorufin remains a reduced extracellular molecule, which precludes the oxidation of intracellular flavins by resorufin, and leads to FMN secretion to eliminate excess reducing equivalents. FAD is produced under all conditions and is secreted in significant amounts during fermentation alone (Fig. 4 E, F). Surprisingly, FAD disappears from the cytoplasmic fraction under iron‐reducing conditions (i.e., Fe(III)‐citrate, HFO with and without resazurin), and is only detected at low concentrations in the medium (HFO case) or disappears from the secreted fraction at later time points (Fe(III)‐citrate case) (Fig. 4 F). We hypothesize that FAD is hydrolyzed extracellularly to FMN under iron‐reducing conditions and covalently bound to a membrane enzyme with a potential role in iron reduction, since the disappearance of FAD is only observed in the iron‐reducing cultures. The hydrolysis of FAD to FMN with incorporation into a membrane protein was recently proposed for other Gram‐positive bacteria (Buttet et al ., 2018 ). Additionally, a flavin‐based extracellular electron transfer mechanism was proposed for Gram‐positive bacteria, in which FAD is converted to FMN, which is bound to a predicted extracellular electron transfer lipoprotein (Light et al ., 2018 ). Another possibility is that FAD itself gets incorporated in an insoluble enzyme. Because the intracellular flavin measurement only targets the soluble fraction, no insoluble FMN or FAD (such as that associated with membrane proteins) are detected. The metabolic model predicted an increase in the reaction fluxes towards the conversion of RF to FMN and FAD if Fe(III)‐citrate is provided (Table S2 ). Interestingly, adding RF as an exogenous electron mediator increased HFO reduction significantly (Fig. 1 A) whereas no increase in iron reduction was detected by supplementing the medium with FAD or FMN. One hypothesis could be that, it is a result of flavin transport in C. acetobutylicum , which limits the cycling of FMN and FAD if added exogenously. Flavin transporters have not been characterized in C. acetobutylicum but the bacterium encodes genes whose corresponding proteins show homology with RF importers in other Firmicutes (Light et al ., 2018 ). As mentioned above, a recent study reported increased RF concentrations in the culture supernatant of a fur mutant or iron‐deficient culture suggesting a correlation between RF trafficking and iron availability. HFO reduction causes a shift in the metabolism of C. acetobutylicum . As expected, in cultures without HFO, due to the lack of extracellular terminal electron acceptors, electrons are directed towards butanol, as is typical for solventogenic phase (Fig. 2 F). In contrast, in the presence of HFO as an alternative electron acceptor, the electron flow is towards iron and there is a slight increase in the rate production of butyrate and H 2 at intermediate time points (Fig. 2 D, G). The production of lactate is also observed to decrease in the presence of HFO (Fig. 2 E). Lactate production is not typical for fermentation by C. acetobutylicum and is reported under iron‐limiting conditions (which is not the case here, data not shown) (Vasileva et al ., 2012 ; Durán‐Padilla et al ., 2014 ) and requires further consideration. Investigation of the impact of resazurin alone on the products of glucose fermentation by C. acetobutylicum revealed that the electron mediator enhanced acetate, lactate and butanol production substantially (Fig. S3 ). Conversely, it decreased butyrate and H 2 production (Fig. S3 ). Thus, when considering the metabolic shift during HFO reduction (Fig. 2 ), we are actually considering the combined effect of resazurin and HFO on metabolism. Previous studies have documented the shift in metabolism to greater butanol and lactate production in Clostridium sp. due to exogenous electron mediators (Peguin et al ., 1994 ; Peguin and Soucaille, 1995 ; Reimann et al ., 1996 ; Sund et al ., 2007 ; Tashiro et al ., 2007 ; Hönicke et al ., 2012 ; Yarlagadda et al ., 2012 ). In those studies, it was proposed that methyl viologen can replace ferredoxin and thus be preferentially used to generate NADH by the ferredoxin:NAD(P) reductase at the expense of H 2 , requiring activation of the lactate dehydrogenase to consume NADH. However, the redox potential of methyl viologen is −0.446 V, but that of resorufin is only −0.051 V (Tratnyek et al ., 2001 ) making it unlikely that it will replace ferredoxin ( E \n 0 –0.430 V). Thus, it is likely that resazurin increases the NADH/NAD ratio through an unknown mechanism, which results in the production of lactate and butanol. Overall, we observed that HFO blunts the impact of resazurin, reducing the production of lactate and butanol and slightly increasing butyrate and H 2 production. In subsequent experiments, we primarily focused on soluble iron reduction, because of the confounding effect of electron mediators and the highly inefficient reduction of HFO in their absence. C. acetobutylicum is able to efficiently deliver 5% of the electrons produced during glycolysis and acetyl‐CoA formation to Fe(III)‐citrate (provided at a concentration of 40 mM) (Table S1 ). As a consequence, the carbon and electron flows shift. Compared to fermentation alone, the electron and carbon flows are greater towards butyrate and lower towards butanol. This may be a consequence of the ability to maintain the pH at higher values due to the consumption of protons in the iron reduction process. In turn, a more stable pH leads to a prolonged acidogenic phase. By directing excess reducing equivalents to organic acid formation and iron reduction, the production of solvents (such as butanol) is decreased. In cultures with 40 and 50 mM Fe(III)‐citrate, the H 2 concentration decreased compared to fermentation alone (Table 1 ). This was not the case with 20 mM Fe(III)‐citrate. It appears that, depending on the Fe(III)‐citrate concentration, the electron flow towards either butanol and/or H 2 is decreased. This is in accordance with the metabolic network modelling, which includes both the formation of H 2 and butanol in the minimal reaction network for iron reduction (Fig. 6 ). Similarly, the FVA shows a greater flux towards butyrate in the case that includes iron reduction (Fig. 5 ). The highest reduction rate is during the bacterial growth phase, but it is still ongoing after the OD 600 decreases and glucose consumption has stopped. It was observed in a previous study that electrons are released after electron donor depletion in D. reducens during iron reduction (Dalla Vecchia et al ., 2014 ). That study suggested that an intracellular electron storage molecule is involved in the release of electrons to an acceptor. That could be also the case for C. acetobutylicum during fermentation under the conditions provided here. No glucose is consumed after 12 h, but iron reduction is still ongoing until 18 h. Potential candidates for electron storage molecules include flavins, which were detected in our study (see above). Iron reduction buffers the pH as previously described for a fermentative iron‐reducing bacterium (Dong et al ., 2017 ). In that study, they noted that due to pH buffering, more substrate was consumed and the growth yield was greater compared to fermentation alone. Similarly, we observe that C. acetobutylicum cultures stabilize the pH to greater values under iron‐reducing conditions with a pH value up to 0.62 higher than with fermentation alone. However, there is no difference in the consumption of glucose in fermentation with and without iron reduction until 18 h or in the growth yield with C. acetobutylicum in our study. Nonetheless, the FVA indicates that anabolism is expected to be greater in the presence of Fe(III)‐citrate (Table S2 ) and ATP production (in excess of maintenance levels) is predicted and measured to be greater with Fe(III)‐citrate (Table S1 ). The absence of experimental evidence for additional growth with iron is attributable to the difference between the two conditions being too small for detection by the tools available. These findings are consistent with greater energy generation, but only through the diversion of electrons from a pathway that does not generate energy (butanol production) to one associated with ATP formation (butyrate production). Interestingly, at 24 h, the glucose concentration continues to decrease in cultures with fermentation alone, whereas no substrate is further consumed under iron reduction (with 40 mM Fe(III)‐citrate) (Fig. 3 ). Perhaps a second reason for the lack of difference in anabolism between the conditions with and without iron is that elements other than carbon (e.g., nitrogen, sulfur, phosphorus, magnesium and calcium) are limiting glucose consumption (glucose is available in excess). Considering the fact that during iron reduction, electrons must be directed to Fe(III), one would expect that less NADH is available for the production of butyrate (which requires two NADH molecules to reduce acetoacetate). Hence, it is expected that the acetate/butyrate ratio in iron‐reducing cultures would be greater than in cultures with fermentation alone. Interestingly, that is not the case here. In cultures with iron reduction, the acetate/butyrate ratio is 0.27 whereas in cultures with fermentation alone, it is 0.43. However, the increased production of butyrate in iron‐reducing cultures mainly occurs between 6 and 18 h. Rather than the redirection of electrons, a more fitting interpretation here is that the shift to solventogenesis is delayed or does not occur at all due to the higher pH. As a result, butyrate is produced at a higher amount, and solvents are almost non‐detectable in the iron‐reducing cultures. In contrast, in fermentation alone, the organisms switch their metabolism to solventogenesis earlier, directing electrons towards solvent production. The MRS show that (i) iron reduction does not need an additional reaction relative to those for fermentation alone and (ii) iron reduction either via NAD(P)H or reduced ferredoxin provides more alternative pathways for fermentation (Fig. 6 , Fig. S7 ). This flexibility of the organism to have several alternative MRS allows the switch in metabolism due to iron reduction. Overall, we found that C. acetobutylicum uses iron as an alternative electron acceptor causing a reduced decrease in the pH value and allowing acidogenesis to persist for longer. Additionally, there was a shift in the carbon and electron flows as evidenced by the differences in products and the coexistence of more alternative pathways with iron as an electron acceptor in the MRS. Further, C. acetobutylicum is able to use resazurin as an exogenous electron mediator, which enhances solid iron reduction and causes an electron and carbon shift distinct from that generated by iron reduction. The experimental data were consistent with the metabolic modelling. In particular, the acidogenic phase persists longer in fermentation with Fe(III), providing the opportunity for the bacterium to gain more energy, which is consistent with the increase in flux for ATP‐generating reactions (glycolysis, the citric acid cycle) in the model. Thus, overall, this study provides profound insights into the complex mechanism of this versatile bacterium within soil ecosystems."
} | 5,743 |
29403089 | null | s2 | 3,989 | {
"abstract": "Star-shaped poly(ethylene glycol) (PEG) chain termini were functionalized with alendronate to create transient networks with reversible crosslinks upon addition of calcium ions. The gelation ability of alendronate-functionalized PEG was greatly dependent on the number of arms and arm molecular weight. After mixing polymer and calcium solutions, the formed hydrogels could be cut and then brought back together without any visible interface. After 2 minutes of contact, their connection was strong enough to allow for stretching without tearing through the previous fracture surface. Oscillatory rheology showed that the hydrogels recovered between 70 and 100% of the original storage and loss modulus after rupture. Frequency sweep measurements revealed a liquid-like behavior at lower frequencies and solid-like at high frequencies. Shifting frequency curves obtained at different calcium and polymer concentrations, all data collapsed in a single common master curve. This time-concentration superposition reveals a common relaxation mechanism intrinsically connected to the calcium-bisphosphonate complexation equilibrium."
} | 281 |
29255037 | PMC5776829 | pmc | 3,990 | {
"abstract": "Significance We demonstrate a unique growth mode to form complex 3D shapes in hydrogels by invoking the bottom-up approach analogous to cell enlargement and proliferation found in living animal tissues and plants. For this purpose, we control the oxygen concentration to modulate polymerization of monomers in porous hydrogel, wherein postgelation networks continue to expand––a process similar to the growth of living tissues in nature. The applicability of this experimental technique to a variety of situations in biology is demonstrated with several examples of the formation of complex 3D architectures through successful biomimetics of tissue morphogenesis in both animals and plants. These results offer possibilities for a diverse set of applications in tissue engineering, soft robotics, and flexible electronics.",
"discussion": "Discussion In summary, we demonstrate an approach to generate complex hydrogel-based 3D architectures via controlled molecular self-assembly of monomers and cross-linkers. In general, complex 3D shapes in soft materials can be realized through two distinct approaches. The top-down approach involves engineering heterogeneous, patterned structures (layered, directionally stiffened or softened, residually stressed, etc.) which, upon stimulation or release of constraints, evolve into 3D shapes ( 17 , 24 , 37 , 38 ). The bottom-up approach utilizes the material’s ability to self-assemble or grow into 3D shapes (e.g., tissues and organs of animals, and leaves and flowers of plants). Sometimes combined top-down/bottom-up approaches are needed to achieve special functions or shapes of a soft structure/device. The vast majority of techniques to date make use of the top-down approach. The current study thus demonstrates possibilities for generating 3D architectures in soft materials using a bottom-up method. Our approach relies on the porous nature of cross-linked network, so that continuous transport of monomers and cross-linkers into postgelation network is permitted, facilitating continuous growth of hydrogel. Differential growth of hydrogel can be effectively introduced when mechanical constraints are incorporated into the polymerization system. We demonstrate that this approach can serve as a powerful means to generate biomimetic and other complex soft 3D architectures. Because this unique growth mode is expected to be a general principle for all polymer materials that feature a porous structure after polymerization, our findings are likely to be applicable to a wide variety of fields, such as biomedical engineering, polymer science, soft robotics, and flexible electronics."
} | 655 |
30128245 | PMC6097140 | pmc | 3,992 | {
"abstract": "Abstract Living materials are an emergent material class, infused with the productive, adaptive, and regenerative properties of living organisms. Property regulation in living materials requires encoding responsive units in the living components to allow external manipulation of their function. Here, an optoregulated Escherichia coli (E. coli) ‐based living biomaterial that can be externally addressed using light to interact with mammalian cells is demonstrated. This is achieved by using a photoactivatable inducer of gene expression and bacterial surface display technology to present an integrin‐specific miniprotein on the outer membrane of an endotoxin‐free E. coli strain. Hydrogel surfaces functionalized with the bacteria can expose cell adhesive molecules upon in situ light‐activation, and trigger cell adhesion. Surface immobilized bacteria are able to deliver a fluorescent protein to the mammalian cells with which they are interacting, indicating the potential of such a bacterial material to deliver molecules to cells in a targeted manner."
} | 265 |
37095261 | PMC10125981 | pmc | 3,993 | {
"abstract": "Spider silk fibres have unique mechanical properties due to their hierarchical structure and the nanoscale organization of their proteins. Novel imaging techniques reveal new insights into the macro- and nanoscopic structure of Major (MAS) and Minor (MiS) Ampullate silk fibres from pristine samples of the orb-web spider Nephila Madagascariensis . Untreated threads were imaged using Coherent Anti-Stokes Raman Scattering and Confocal Microscopy, which revealed an outer lipid layer surrounding an autofluorescent protein core, that is divided into two layers in both fibre types. Helium ion imaging shows the inner fibrils without chemical or mechanical modifications. The fibrils are arranged parallel to the long axis of the fibres with typical spacing between fibrils of 230 nm ± 22 nm in the MAS fibres and 99 nm ± 24 nm in the MiS fibres. Confocal Reflection Fluorescence Depletion (CRFD) microscopy imaged these nano-fibrils through the whole fibre and showed diameters of 145 nm ± 18 nm and 116 nm ± 12 nm for MAS and MiS, respectively. The combined data from HIM and CRFD suggests that the silk fibres consist of multiple nanoscale parallel protein fibrils with crystalline cores oriented along the fibre axes, surrounded by areas with less scattering and more amorphous protein structures.",
"conclusion": "Conclusions This work examined the micro- and nanostructures of spider silk fibres from the orb-weaving spider Nephila madagascariensis using several novel microscopy techniques. The results of CARS, Laurdan, and confocal microscopy revealed that both MAS and MiS fibres exhibited a lipid-rich outer region with a thickness of over 500 nm. This is thicker than the values reported by Sponner et al. 6 . We note that the silks used here were pristine and untreated while the lipid layer identified by Sponner appeared to be detaching from the fibre due to the sample preparation and labeling procedure used. However, it is important to note that the present experiments only show a lipid rich hydrophobic region, not a pure lipid layer. This means that this region could well consist of outer lipid layers followed by a mixed lipid glycol protein layer as suggested by Ref. 6 . Further support for this interpretation comes from the HIM images which show emerging fibres after just 100–200 nm of surface sputtering. Hydrophilic dyes such as Rhodamine B and FITC label the inner protein layers of the fibres. Rhodamine B was found to have a higher affinity towards the inner core proteins as almost no labeling was observed towards the outer layers but a high amount of labeling within the center of the fibres. However, FITC had increased labeling towards the edges showing that this dye has a higher affinity towards the proteins in the outer layers. The different affinities of the dyes suggest that the fibres have an outer and inner protein layer with different physical chemical properties (Fig. 6 ). The protein core structure in MAS and MiS fibres was examined using scanning HIM and CRFD microscopy techniques. Both HIM and CRFD microscopy revealed that the protein cores of MAS and MiS fibres consist of fibrils aligned parallel to the long axis of the fibre. Fibril diameters were found to vary between 145 nm ± 18 and 116 nm ± 12 depending on the fibre and fibre type, suggesting that the fibres exhibit considerable natural diversity. This is supported by recent results using AFM 17 and SEM 43 . Furthermore, studies in different spider species also show considerable variations 37 . From the HIM images two distinct inner layers could also be observed in MiS fibres: one layer appearing after removal of the lipid layer and another appearing after removal of the first layer. This indicates a multilayered structure of the silk fibre. While HIM could only image the outermost fibrils, CRFD microscopy was able to visualize parallel crystalline protein fibrils oriented along the fibre axes throughout the whole fibre surrounded by less scattering and more amorphous protein structures. The nanoscopic fibril structure and organization found in this work demonstrates the importance of studying samples at multiple size scales, not just the molecular structure and macroscopic properties, but also the nanoscopic structures linking the two. The relevance of the nanoscopic structures for spider silk’s macroscopic properties still needs further studies. However, we assert that these hierarchical structures will be highly relevant in any attempt to consolidate structure function relationships. Taking these kinds of studies further will also be crucial when trying to create and analyze artificial silk inspired polymer filaments.",
"introduction": "Introduction During the construction of its web, a typical orb-weaver spider uses two types of silk for the scaffolds of the structure that support the sticky capture spiral that holds any prey. The Major Ampullate silk (MAS) is used primarily for the radii spokes of the web, whereas the Minor Ampullate silk (MiS) is used principally for a temporary scaffold during web construction but also accompanies MAS silks in radii and safety lines, always dragged behind by the spider 1 . For several reasons MAS is the silk type most studied although MiS fibres are gaining scientific attention as they share gland morphology and some protein motifs with MAS fibres but display rather different mechanical properties 2 – 4 . Our comparisons of the two types of silk provide novel insights into functional relationships by demonstrating how small structural changes at the molecular level give rise to large differences in morphometric properties, which in turn can potentially be linked to fundamental structure–function relationships. Here we focus on the structure of the innermost layer referred to as 'the protein core', which comprises a layered structure containing several different proteins 5 , 6 . The MAS fibres of the orb-weaver Nephila clavipes display an outermost lipid layer of 10–20 nm thickness surrounding the protein core 6 , 7 . The structure of the protein core is more difficult to image as it is (apparently) rather more complex. Attempts of visualization include Atomic Force Microscopy 8 – 12 , Light Microscopy 13 , Confocal Laser Scanning Microscopy 14 , Scanning Electron Microscopy and 11 , 14 , 15 , and Transmission Electron Microscopy 15 , 16 . All these techniques have their own drawbacks, which limit their data concerning full disclosure of the structural nature of spider silk while overall providing important insights. For example, TEM requires thin sectioning and thus the sample to be glutaraldehyde fixed or deep frozen. This in turn causes artefacts such as cavities and fractures within the silk fibres 15 . For AFM imaging the outer layers of the silk must be removed either mechanically or chemically 11 , as AFM only allows for surface imaging. Cross sectioning and subsequent AFM imaging reveal protein fibrils with a diameter of around 100–150 nm in MAS fibres from Nephila clavipes. However, for those measurements’ samples were also cryogenically frozen before imaging, fostering a misinterpretation of cavities as 'fibrils' 10 . Fibral widths of down to 50 nm have been reported for Loxosceles laeta silk 17 . In light microscopy studies of silk structure the samples were submerged in urea and studied under super contraction conditions, which supports unwanted delamination processes 18 – 20 . While all the microscopy observations are useful to dissect the structures of the silk, they also include artifacts, which taken on their own can lead to misinterpretations. In this article, we focus on pristine, i.e., untreated spider silk fibres and report results obtained with alternative i.e. less invasive techniques such as Coherent Anti-Stokes Raman Scattering (CARS) microscopy 21 , 22 , Confocal Microscopy, Ultra-resolution Confocal Reflection Fluorescence Depletion Microscopy (CRFD) 23 – 27 and Scanning Helium Ion Microscopy (HIM) as well as Helium Ion Sputtering 28 – 30 . These methods allow us to image the samples at near-physiological conditions, with minimal sample preparation and unprecedented resolution. CARS microscopy enables us to image specific chemical bonds without labeling 21 , 22 , whereas confocal microscopy provides complementary information via labelling and subsequent imaging of specific molecules. However, both of these techniques are limited to a resolution of around 200 nm 31 . As the fibrils are expected to be around 150 nm in diameter 10 , 11 , we have applied (CRFD) microscopy 23 – 27 and scanning Helium Ion microscopy (HIM) 28 – 30 . With the latter technique it is possible to achieve lateral resolutions on the order of 1 nm in spider silk. Using the sputtering option, removal of the outermost layers is possible 30 , 32 , 33 . CRFD microscopy is a novel combination of two optical techniques, allowing us to image the fibrils throughout intact fibres with a resolution of 100–120 nm 23 – 27 . Laurdan Generalized Polarization (GP) measurements 34 , 35 in addition provide information on the phase of the lipids in the outermost layers of the silk. In the following we present the data from investigations of pristine MAS and MiS fibres from the orb-weaving spider Nephila madagascariensis . We aim to obtain novel insights into the structure of spider silk at different size scales leading to a refined model for these fibres."
} | 2,345 |
35214825 | PMC8880547 | pmc | 3,994 | {
"abstract": "Lignocellulosic biomass from the secondary cell walls of plants has a veritable potential to provide some of the most appropriate raw materials for producing second-generation biofuels. Therefore, we must first understand how plants synthesize these complex secondary cell walls that consist of cellulose, hemicellulose, and lignin in order to deconstruct them later on into simple sugars to produce bioethanol via fermentation. Knotted-like homeobox ( KNOX ) genes encode homeodomain-containing transcription factors (TFs) that modulate various important developmental processes in plants. While Class I KNOX TF genes are mainly expressed in the shoot apical meristems of both monocot and eudicot plants and are involved in meristem maintenance and/or formation, Class II KNOX \n TF genes exhibit diverse expression patterns and their precise functions have mostly remained unknown, until recently. The expression patterns of Class II KNOX TF genes in Arabidopsis , namely KNAT3, KNAT4, KNAT5, and KNAT7 , suggest that TFs encoded by at least some of these genes, such as KNAT7 and KNAT3 , may play a significant role in secondary cell wall formation. Specifically, the expression of the KNAT7 gene is regulated by upstream TFs, such as SND1 and MYB46, while KNAT7 interacts with other cell wall proteins, such as KNAT3, MYB75, OFPs, and BLHs, to regulate secondary cell wall formation. Moreover, KNAT7 directly regulates the expression of some xylan synthesis genes. In this review, we summarize the current mechanistic understanding of the roles of Class II KNOX TFs in secondary cell wall formation. Recent success with the genetic manipulation of Class II KNOX TFs suggests that this may be one of the biotechnological strategies to improve plant feedstocks for bioethanol production.",
"conclusion": "2. Concluding Remarks and Future Perspectives Recent studies have indicated that Class II KNOX genes are expressed during SCW formation in Arabidopsis and other higher plants. The expression of these genes in tissues undergoing SCW thickening and the effects of mutations in KNAT3 and KNAT7 genes on SCW synthesis clearly suggests their role in the transcriptional regulation of the genes involved in SCW formation. A clear understanding of the role of KNAT4 and KNAT5 in this process still awaits; if those genes are redundant in function, then their functions need to be ascertained using mutant complementation analysis with other Class II KNOX genes. Although this review focused on SCW formation, a few other metabolic processes in the life cycle of a plant, such as mucilage production, have been associated with Class II KNOX genes. As Romano et al. [ 53 ] suggested, KNAT7 appears to be a major hub where several pathways converge to coordinate multiple aspects of resource allocation in plants. Some ambiguity still exists around whether KNAT7 acts as a transcriptional activator or suppressor in SCW development. The suppression of KNAT7 function increased SCW formation in interfascicular fibers but resulted in reduced cell wall synthesis in xylary fibers with collapsed vessels, suggesting that it is a transcriptional suppressor [ 13 , 15 ]. Quite contrasting results were observed by other authors, who suggested that KNAT7 is a transcriptional activator [ 12 , 14 , 15 , 17 , 31 , 33 ]. Recent reports by Wang et al. and Qin et al. [ 15 , 16 ] reconciled these observations, suggesting that KNAT7 acts as a suppressor in interfascicular fibers but as an activator in vessels and xylary fibers. How the same TF plays these two contrasting roles is still unknown. These studies showed a differential regulatory role for KNAT7 depending on the tissue and cell type and its interacting partners. It is also possible that there are species-specific variations in KNAT7 function in SCW biosynthesis. More studies are required to answer the questions addressing the functional ambiguity of KNAT7 and how it interacts with cell wall TFs and other KNOX II proteins to regulate SCW formation. Furthermore, a detailed investigation into the regulatory network and downstream targets of Class II KNOX TF proteins is required to understand the transcriptional regulation of SCW formation. These studies will help us to modify cell wall formation in transgenic plants and enhance saccharification, as we recently showed [ 14 , 17 ]. Our understanding of the molecular controls of the deposition of each call wall component will help us to design cell walls for improved biomass production and reduced recalcitrance to bioconversion to ethanol. The modification of identified TFs through genetic engineering could help in overcoming some of the current bottlenecks leading to the realization of renewable bioenergy.",
"introduction": "1. Introduction Increasing global demand for petroleum-based transportation fuels has created an imperative need for the search and development of alternative, sustainable, and renewable sources of bioenergy. First-generation biofuels are produced from starch and sugars that come from agricultural crops. Such applications are often associated with direct competition with food resources and are with some important ethical, ecological, and societal issues [ 1 ]. Second-generation biofuels are produced from lignocellulosic biomass derived from the secondary cell walls (SCWs) of plants that can be used to produce alternative transportation fuels, such as bioethanol. Despite its abundance, only a small portion of lignocellulosic biomass is presently used for bioethanol production, owing to its recalcitrance for the bioconversion to bioethanol. Additionally, converting woody biomass into fermentable sugars still requires high input technologies involving extensive pre-treatments and expensive enzymes [ 2 , 3 ]. Hence, a clear understanding of the plant metabolic processes influencing SCW properties will assist in improving plant feedstocks for bioethanol production [ 3 ]. Second-generation biofuels have become an important component of the global bioenergy agenda [ 2 ]. The use of plant biomass for the production of bioethanol has an enormous potential to revolutionize the global bioenergy outlook. Scientists have discovered novel ways of improving lignocellulosic biomass production in bioenergy crops and trees, such as switchgrass and poplars, that could be used for efficient biofuel production [ 4 , 5 , 6 ]. The SCW is mainly composed of cellulose, hemicelluloses, and lignin; one of the primary roles of SCW is to confer mechanical strength to plant tissues [ 6 ]. However, the main carbohydrate components of SCWs—cellulose and hemicellulose—can be deconstructed into simple sugars (saccharification), and these sugars can subsequently be fermented to produce bioethanol [ 3 ]. During the last two decades, several studies have been initiated to understand and modify the biosynthesis of cellulose, hemicellulose, and lignin through the manipulation of genes involved in these pathways [ 6 ]. In addition, several members of the NAC, MYB, and KNOX transcription factor (TF) families have been studied to elucidate their regulatory roles in SCW biosynthesis [ 7 , 8 , 9 , 10 ]. These TFs function by regulating the SCW biosynthetic genes that encode cellulose synthases (CesAs), xylan synthases, and lignin biosynthetic pathway enzymes. One of the Class II KNOTTED1-like homeodomain ( KNOX ) genes, KNAT7 , has recently gained attention for its potential role in the transcriptional network regulating SCW biosynthesis [ 11 , 12 , 13 , 14 , 15 , 16 , 17 ]. This comprehensive review focuses on the recent developments in our understanding of the transcriptional networks involving Class II KNOX TFs in the regulation of SCW biosynthesis. 1.1. KNOX Genes and Encoded KNOX Proteins in Plants The KNOX genes are members of one of the ancestral gene families involved in the transition of plants from an aquatic to a terrestrial habitat during evolution [ 18 ]. KNOX genes encode homeodomain (HD)-containing TFs involved in various developmental processes. Typical HD proteins contain 60 amino acids, while the HD of KNOX proteins contains a highly conserved 63-amino acid stretch consisting of three ∝-helices that form a helix-turn-helix-type DNA binding motif [ 19 ] ( Figure 1 ). Due to the presence of three extra amino acids between the first and second helices, all KNOX TF proteins are included in the TALE (three amino acid loop extension) superclass, the members of which are evolutionarily conserved from single-cell algae to higher plants [ 20 ]. The sequence immediately upstream of the HD, the ELK domain, has been suggested to function as a nuclear localization signal and be involved in protein–protein interactions [ 20 ]. In addition to the HD and ELK domains, a stretch of 100 amino acids located at the N terminus of almost all KNOX proteins, the MEINOX domain, also functions in protein–protein interactions [ 20 ]. This MEINOX domain in plants consists of two smaller domains, KNOX1 and KNOX2, separated by a poorly conserved linker sequence ( Figure 1 ). Plant KNOX genes are divided into three subclasses based on their sequence similarity within the HD encoding regions, intron positions, expression patterns, and phylogenetic analysis [ 21 , 22 , 23 , 24 ]. Class I KNOX genes are similar to the knotted1 gene of maize [ 25 ] and are mainly expressed in the shoot apical meristems (SAMs) of both monocot and eudicot plants. The Class I KNOX genes STM , KNAT1 / BP , KNAT2 , and KNAT6 in Arabidopsis play an important role in the transcriptional regulation of meristem development, leaf shape control, and hormone homeostasis [ 26 ]. Loss-of-function mutations in these genes affect meristem maintenance and/or formation [ 27 ]. The only member of Class III KNOX gene, KNATM , is involved in the regulation of leaf polarity, leaf shape, and compound leaf development [ 28 ]. Four Class II KNOX genes ( KNAT3, KNAT4, KNAT5, and KNAT7 ) in Arabidopsis form a separate monophyletic group and have several orthologues in higher plant genomes with few known functions [ 23 , 24 , 29 ]. Interestingly, Class II KNOX genes have been suggested to regulate the haploid-to-diploid morphological transition in land plants [ 18 ]. The first plant homeobox gene was discovered over 25 years ago; however, we only recently began to decipher the roles of Class II KNOX genes in higher plant growth and development. This review focuses on the functions of Class II KNOX genes and their encoded proteins in higher plants. 1.2. The Expression Patterns of Class II KNOX Genes in Plants Provide Some Clues about Their Functionality in SCW Formation The only Class II KNOX gene that has recently been well characterized and extensively studied is KNAT7 [ 12 , 13 , 14 , 15 , 16 , 30 , 31 ]. The role of KNAT7 TF as a regulator in SCW biosynthesis was first reported in Arabidopsis through the observation of the irx (irregular xylem) phenotype that occurred in a loss-of-function knat7 mutant, irx11 [ 30 ]. At the same time, the tight co-expression of the KNAT7 TF gene along with SCW-specific CesA genes was reported using microarrays of Arabidopsis inflorescence stems undergoing SCW formation [ 11 , 32 ]. Promoter-GUS expression studies of AtKNAT7 in Arabidopsis showed that it is highly expressed in developing xylem, phloem fibers, and cambium cells of inflorescence stems [ 13 ]. Wang et al. [ 15 ] recently examined whether several Class II KNOX genes from Arabidopsis , KNAT3, KNAT4, KNAT5, and KNAT7 , were expressed during SCW deposition. All these Class II KNOX gene promoters regulated GUS expression in the vascular bundles in younger stems and intrafascicular fibers and vessel cells in older stems. These observations suggest that these Class II KNOX genes have similar expression patterns during the deposition of the SCWs. Qin et al. [ 16 ] also showed that while KNAT7 expression was much higher in stem tissues, KNAT3 expression remained similar in all tissues examined. Promoter-GUS fusions confirmed that KNAT3 and KNAT7 genes are co-expressed in developing xylem and interfascicular fibers in the Arabidopsis stem. In poplar ( Populus balsamifera ), the expression of PtKNAT 7 gradually increases from the primary cell wall expansion stage to the mature xylem tissue formation stage, and from the youngest to the older internodes of stem [ 13 ]. Cotton GhKNL1 was reported to be preferentially expressed in developing cotton fibers during SCW biosynthesis [ 33 ]. Switchgrass KNAT7 also appears to be a functional ortholog of Arabidopsis KNAT7 , based on its expression patterns [ 34 ]. In our laboratory, we studied the expression patterns of two Class II KNOX genes, KNAT3 and KNAT7 , in tobacco ( Nicotiana benthamiana ) [ 14 ]. Higher expression of NbKNAT7 was seen in older stems of tobacco showing secondary growth followed by young stems and old leaves, while NbKNAT3 displayed higher expression in older leaves followed by roots and young leaves. These two Class II KNOX genes were also found to be highly expressed during tension wood formation in aspen. The expression of NbKNAT3 and NbKNAT7 in young and old stems indicates that they play a role in wood formation. Thus, Class II KNOX genes are associated with SCW formation during xylem and fiber development. 1.3. Genetic Mutations in Class II KNOX Genes Further Clarify Their Role in SCW Formation Until 2005, KNAT7 was not often discussed in mutation studies of the Class II KNOX genes; however, a number of Class II KNOX mutations have recently been studied in detail ( Table 1 ). A T-DNA insertion in the intron of the KNAT7 gene resulted in a loss-of-function mutant, irx11 , that showed only a moderately weak growth phenotype. The irx11 mutant also exhibited the typical irx phenotype in xylem vessels that were collapsed due to weak SCW formation. The irx11 mutant did not have significantly altered cellulose or xylan content compared to controls. No lignin content of these mutants was reported at that time. While discovering a set of novel TFs involved in SCW biosynthesis, Zhong et al. [ 12 ] associated KNAT7 expression with SCW formation, and the dominant repression of KNAT7 (DR- KNAT7 mutants) affected SCW formation in both xylem and fiber cells ( Table 1 ). Curiously, they did not observe the typical irx phenomenon in these DR- KNAT7 mutants, a tell-tale sign of weak SCW formation; however, the cell wall thicknesses of both xylem vessels and fibers were reduced compared to controls (28% down in interfascicular fibers (IF), 26% down in vessels (V), and 80% down in xylary fibers (XF)). Several monosaccharides from the cell walls of DR- KNAT7 mutants were reduced by 20–30%, except for arabinose, which was increased by 18%. The overexpression of KNAT7 did not increase the SCW thickness of fibers and vessels. These results indicated that KNAT7 could be a positive regulator of SCW formation in Arabidopsis . However, Li et al. [ 13 ] reported a contrasting observation that loss-of-function mutants in the AtKNAT7 gene resulted in differential thicknesses of interfascicular and xylary fibers compared to vessels (58% up in IF, 35% down in V, and 31% up in XF; Table 1 ). The vessels walls were thinner, resulting in collapsed xylem vessels that showed the irx phenotype (similar to [ 30 ]); however, the interfascicular fibers were significantly thicker than in the wild type control, suggesting that KNAT7 is a transcriptional repressor of fiber SCW formation (but a transcriptional activator of vessel SCW formation). KNAT7 overexpression lines exhibited thinner fiber walls (57% down in IF) with normal vessel and xylary fiber cell walls. Interestingly, even though many SCW-specific cellulose and xylan synthesis genes were upregulated in these mutants, no quantitative changes in cellulose or xylan were reported. All ten lignin synthesis genes tested were upregulated along with an 11% increase in lignin content of cell walls from the stem. Li et al. [ 30 ] speculated that KNAT7 interacts with different partner proteins in different cell types to form functionally distinct complexes. Recently, the regulatory roles of other members of the Class II KNOX gene family, KNAT3, KNAT4, and KNAT5 , in SCW formation were explored in Arabidopsis inflorescence stems [ 15 , 16 ] ( Table 1 ). Loss-of-function mutants of knat3, knat4, and knat5 did not produce any irx phenotype, as observed in the case of loss-of-function mutants of knat7 [ 15 ]. This could be due to the functional redundancy of KNOX II genes. However, knat3/knat7 double mutants displayed an enhanced irx phenotype compared to single knat7 mutants. These double mutants had thinner interfascicular fiber cell walls compared to the single mutants and wild-type plants (40% down in IF) indicating a potentially positive regulatory role of KNAT3 in combination with KNAT7 in xylem SCW development. Even though many SCW genes were highly expressed in the knat3/knat7 double mutants, the cellulose and xylan contents of their cell walls were reduced by 19% and 43%, respectively, and the changes in lignin content were not significant. The Syringyl to Guaicyl (S/G) lignin ratio was down by 83%; however, it was not possible to correlate all these cell wall content changes with the changes in gene expression patterns. In addition, the severe irx phenotype in these double mutants indicated the overlapping roles and partial functional redundancy of KNAT3 and KNAT7 in xylem vessel development during SCW formation. Furthermore, KNAT3 overexpression in Arabidopsis resulted in thickened interfascicular fibers in the SCW of inflorescence stems [ 15 ]. This study described KNAT3 as a potential transcriptional activator, working together with KNAT7 to promote SCW biosynthesis in xylem vessels. A synergistic interaction of KNAT3 and KNAT7 to regulate monolignol biosynthesis in Arabidopsis was also reported in another study [ 16 ]. Most importantly, they attempted to link S-lignin formation with KNAT3 and KNAT7 expression; however, they could not show the direct transcriptional regulation of a key gene, ferulate 5-hydroxylase ( F5H ), involved in S-lignin formation by KNAT3 or KNAT7. Similar to the earlier observation by Wang et al. [ 15 ], the overexpression of KNAT3 also caused thickening in the interfascicular fiber walls, indicating the positive regulation of interfascicular fiber wall development by KNAT3. These studies by Wang et al. and Qin et al. [ 15 , 16 ] reconciled the paradoxical observations about KNAT7 mutants in Arabidopsis and indicated that KNAT3 and KNAT7 might be working synergistically in fibers, but antagonistically in vessels, during the regulation of SCW biosynthesis ( Table 1 ). Similar observations regarding the function of KNAT7 in SCW formation were reported recently in rice ( Table 1 ). Wang et al. [ 35 ] characterized the KNAT7 transcription factor gene that controls SCW wall thickening in the stem. Interestingly, KNAT7 also regulates cell expansion in rice grains. An Osknat7 CRISPR/CAS9 mutant had a thicker wall in fiber cells than that in the wild type, similar to the Arabidopsis knat7 mutant, and transgenic rice plants overexpressing KNAT7 had opposite effects. Interestingly, the Osknat7 mutant also exhibited a larger grain size due to cell expansion in spikelet bracts. The authors proposed that KNAT7 plays a negative regulatory role in SCW formation, similar to Arabidopsis [ 13 ]. The negative regulation of SCW formation by KNAT7 TF was also supported by Gong et al. [ 33 ] in cotton fibers ( Table 1 ). The dominant repression of cotton KNAT7 ( GhKNL1 ) resulted in abnormal fibers of shorter length in the cotton mutant compared to the controls, suggesting that cell elongation and SCW formation are also related to the function of KNAT7 in cotton. The overexpression of cotton KNAT7 in Arabidopsis produced thinner interfascicular fibers without any changes in the vessel or xylary fiber thickness. Thus, these Class II KNOX genes are involved in SCW formation in various plant species. 1.4. Targeted Genetic Manipulations in Class II KNOX Genes Confirm Their Role in SCW Formation Apart from the detailed study of Class II KNOX gene mutants, targeted genetic manipulations of Class II KNOX genes, especially, KNAT7 genes have offered some additional clues regarding the functions of these genes ( Table 2 ). While the overexpression of KNAT7 in Arabidopsis did not produce any specific SCW phenotype [ 12 ], subsequently, Li et al. [ 13 ] reported that such experiments produced thin interfascicular fibers without any changes in wall thickness of vessels suggesting that KNAT7 TF is indeed a regulator of SCW formation. The successful complementation of Arabidopsis knat7 mutants with the overexpression of the cotton GhKNL1 gene [ 33 ] and poplar PtKNAT7 [ 13 ] rescued the defective irx phenotype of the knat7 mutants, suggesting the functional conservation of KNAT7 genes among Arabidopsis, cotton, and poplar. The overexpression of cotton GhKNL1 in Arabidopsis resulted in thinner interfascicular fibers and slightly thinner vessels walls without any change in the xylary fibers compared to control plants [ 33 ]. The overexpression of cotton GhKNAT7 significantly reduced the deposition of lignocellulose in the interfascicular fibers of Arabidopsis [ 24 ]. However, the SCWs of the xylem fibers and vessels in the transgenic plants did not show any difference from the control plants. The dominant repression of the same cotton KNAT7 orthologue in Arabidopsis produced thinner interfascicular fibers, but thicker vessels and xylary fiber walls, suggesting that KNAT7 can act as a negative or positive regulator of SCW formation in different cell types. In our laboratory, we generated RNAi lines of tobacco ( N. benthamiana ) that exhibited reduced expression of KNAT7 [ 14 ]. NbKNAT7 downregulated through a transient virus-induced gene silencing (VIGS) system resulted in increased xylem proliferation with thin-walled fiber cells. The glycome analyses of the cell walls showed increased polysaccharide extractability in 1 M KOH extracts of the VIGS- NbKNAT7 lines, suggestive of SCW loosening. In addition, there were increased saccharification rates (40% higher than control) in stems of VIGS- NbKNAT7 lines, which indicated the alteration of cell wall composition in VIGS lines downregulated for the NbKNAT7 gene. Similar to the VIGS results, the stems of stable RNAi lines also showed increased xylem area in their stems as compared to control stems [ 14 ]. The cell walls of xylem fibers were thinner (over 50%) in the RNAi lines as compared to vector control lines. The stems of KNAT7 repression lines in tobacco showed reduced expression of SCW genes that resulted in thinner fiber cell walls with altered cell wall composition [ 14 ]. All these results suggested that KNAT7 TF might act as a positive regulator of SCW formation in tobacco. In a recent study performed in our laboratory by Ahlawat et al. [ 17 ], transgenic poplar plants overexpressing PtKNAT7 and AtKNAT7 genes showed enhanced expression of the SCW genes CesA8, IRX9, PAL, and CCR, and reduced expression of the same genes in the poplar PtKNAT7 antisense plants. These results further suggested a positive regulatory role of KNAT7 in SCW formation in poplars. In addition, the genetic suppression of KNAT7 in transgenic poplar stems reduced lignin content by about 6% and altered the lignin composition (S/G ratio) of poplar wood with increased saccharification ability (44–53% higher saccharification efficiency over control plants). Yoo et al. [ 36 ] also reported a negative correlation between lignin content and the saccharification efficiency of woody tissues and a positive correlation between the S/G ratio and the saccharification efficiency of SCW biomass. Therefore, a change in the S/G ratio and reduction in lignin content might be important for improving the saccharification efficiency of SCW biomass. All the studies reported so far in Arabidopsis and other higher plants suggest that KNAT7 acts differentially as a negative and positive regulator of SCW biosynthesis in different cell types of the same plant or in different plant species. 1.5. Transcriptional Network of the Class II KNOX Genes Involved in SCW Formation A complex network of transcription factors regulates SCW biosynthesis in plants [ 8 , 9 , 37 , 38 , 39 , 40 ]. Among these, some Class II KNOX TFs also regulate SCW biogenesis. The major constituents of the SCW are cellulose, lignin, and hemicelluloses [ 6 ]. Cellulose is a polymer of glucose synthesized at the plasma membrane by the cellulose synthase (CesA) complex [ 41 ], while lignin is composed of guaiacyl (G), syringyl (S), and p-hydroxyphenyl (H) units that are synthesized through the phenylpropanoid pathway [ 42 ]. Xylan is the major hemicellulose component in the SCW and consists of a linear backbone of β-(1–4)-linked D-xylosyl (Xyl) residues and α-linked (OMe(methyl)) glucuronic acid (GlcA) side branches [ 43 ]. Many specific genes involved in cellulose, hemicellulose, and lignin biosynthesis pathways have previously been identified in plants (e.g., [ 43 , 44 , 45 ]) and it was anticipated that Class II KNOX TF proteins might directly regulate the expression of some of these genes. The first direct evidence of KNAT7-mediated regulation of xylan biosynthesis in the SCW was reported only recently by He et al. [ 31 ], who demonstrated that KNAT7 physically binds to the promoters of the xylan biosynthetic genes, IRREGULAR XYLEM 9 ( IRX9 ) , IRX10, IRX14L , and FRAGILE FIBER 8 (FRA8 ; Figure 2 ). Wang et al. [ 46 ] also reported the involvement of KNAT7 in xylan synthesis during mucilage production. While various cellulose and lignin biosynthesis genes have been shown to be differentially expressed in various knat7 mutants and during the ectopic expression of the KNAT7 gene in transgenic plants, the direct regulation of any of these SCW genes by KNAT7 TF has not yet been reported. In addition, no information is currently available on transcriptional regulation by the TFs encoded by the other three Class II KNOX genes, namely KNAT3 , KNAT4 , and KNAT5, or their orthologs in any other plant species. 1.6. Upstream Top- and Mid-Level Master Switches Control the Expression of KNAT7 The expression of KNAT7, a lower-level TF, is directly regulated by top and middle-level upstream TFs, such as NAC and MYB proteins [ 9 , 38 ]. SCW-associated NACs, such as SND1, NST1, NST2, VND6, and VND7, are top-level master switches that directly control KNAT7 expression [ 12 ] ( Figure 2 ). Zhong et al. [ 47 ] reported that SND1, a master switch of SCW formation in Arabidopsis fibers, directly controls KNAT7 expression. The downregulation of SND1 and its homolog NST1 also caused the downregulation of KNAT7 expression [ 48 ]. Zhong et al. [ 12 ] identified the direct targets of SND1, and they discovered that the expressions of KNAT7, MYB46, MYB103, and SND3 are directly under the control of SND1. In addition, the SND1 homologs NST1, NST2, VND6, and VND7 were also found to directly activate KNAT7, among many other TFs. Zhong et al. [ 49 ] also identified 19-bp- secondary wall NAC binding elements (SNBEs); the KNAT7 promoter has three such SNBEs at -616, -507, and -331 positions relative to the start codon. Interestingly, Zhong et al. [ 50 ] further showed that SND1 also directly regulates the expression of another mid-level master switch TF, MYB46 ( Figure 2 ). Furthermore, a recombinant SND1 protein was able to bind to the MYB46 promoter fragment and caused a mobility shift. Chromatin immunoprecipitation assays (ChIP) also enriched MYB46 promoter fragments 3–5-fold, suggesting that SND1 directly binds to the MYB46 promoter. Finally, the overexpression of MYB46 also upregulated KNAT7 , and MYB46 appears to be a common target of secondary wall-associated SND1 homologs, including NST1, NST2, VND6, and VND7. Thus, in addition to SND1 and its homologs, MYB46 is also able to directly induce the expression of KNAT7 ( Figure 2 ). Zhong and Ye [ 50 ] showed that a 7-bp long consensus secondary wall MYB-responsive element (SMRE), ACC(A/T)A(A/C)(T/C) in KNAT7 is directly involved in the MYB mediated activation of KNAT7 , and the KNAT7 promoter has three such SMREs located at the -802, -763, and -656 positions upstream of the translation initiation codon. Kim et al. [ 51 ] identified an eight bp motif that has one additional (T/C) before the SMRE and named it M46RE; KNAT7 promoters have two such motifs. Ko et al. [ 52 ] comprehensively reviewed the literature regarding the functions of MYB46 and its close homolog, MYB83, and concluded that the expressions of many important genes involved in cellulose, hemicellulose, and lignin synthesis are directly regulated by MYB46/MYB83. Therefore, it appears that the defects in SCWs of the knat7 mutant might also be due to complex regulation by SND1 homologs and MYB46/83-regulated KNAT7 activities. KNAT7 functions as a common hub in several transcriptional networks that are involved in xylem differentiation and mucilage production, including the network that involves AtMYB61 [ 53 ]. The loss of AtMYB61 function in a mutant resulted in defective xylem production, and it was shown that the MYB61 protein binds directly to an AC-rich element (ACC(A/T)A(A/C/T) in the promoter of AtKNAT7 ; there are three such AC-rich elements in the KNAT7 promoter at the -704, -665, and -558 positions upstream of the transcription start site. Interestingly, there are high similarities between these AC-rich elements, SMREs, and M46REs. Thus, MYB61 appears to be another upstream regulator of KNAT7 in Arabidopsis ( Figure 2 ). 1.7. Physical Interactions of Class II KNOX TF Proteins with Other Proteins As homeodomain proteins, Class II KNOX proteins possess a DNA binding capacity, and many accessory proteins are known to physically interact with them ( Table 3 ). Studies have reported that in at least four different plant species, namely Arabidopsis, rice, cotton, and poplars, the general scheme of interactions remains similar, while a number of species-specific variations have also been reported ( Table 3 ). In Arabidopsis, BEL1 encodes a TALE homeodomain-containing TF that heterodimerizes with KNOX proteins via interactions between the N-terminal region and the homeodomain and MEINOX domain of KNOX proteins [ 54 ]. Interestingly, no interactions were evident between BEL1 and KNAT3, KNAT4, and KNAT7 proteins; however, positive interactions were observed between BEL1 and KNAT5 and a few Class I KNOX proteins [ 54 ]. Furthermore, the C-terminal domain of BEL1, including the homeodomain, appears to be important for such specific interactions. However, Hackbush et al. [ 55 ] subsequently discovered that BEL1 and KNAT5 do not interact, but BLH (BELL-LIKE HOMEODOMAIN) proteins, such as BLH9/KNAT3 and BLH9/KNAT7, interact. In fact, out of four Class II KNOX proteins, eight BLH-proteins interacted with KNAT3, only BLH6 interacted with KNAT4, nine BLH proteins interacted with KNAT5, and two BLH proteins (BLH5 and BLH7) interacted with KNAT7. Another group of proteins that are known to interact with KNOX proteins are the ovate family proteins (OFPs) that are repressors of transcription and are involved in plant growth and development [ 55 , 56 , 57 , 58 , 59 ]. According to Hackbush et al. [ 55 ], five OFPs interact with KNAT3 and four different OFPs interact with KNAT4, KNAT5, and KNAT7. However, Li et al. [ 57 ] reported that only OFP4 showed strong Y2H interactions with KNAT7, while OFP1 showed only weak interactions. However, bimolecular fluorescence complementation (BiFC) and mutation data confirmed that KNAT7, OFP1, and OFP4 interact and play an important transcriptional repressor role during SCW formation ( Table 3 ). Thus, interactions among BLH, OFPs, and KNOX proteins appear to play some major roles in plant development, including in SCW formation. Contrary to some of these findings, Liu et al. [ 60 ] showed that BLH6 specifically interacts with KNAT7, which represses commitment to SCW formation, and this interaction of TFs modulates the expression of the homeodomain-ZIP (HD-ZIP) TF gene, Revoluta ( Figure 2 ). KNAT7 is a putative transcriptional repressor in Arabidopsis leaf protoplasts, and its repression is enhanced by physical interaction with OFP1 and OFP4 [ 57 ]. This was confirmed by the presence of irx vessels and altered fiber cell wall phenotypes displayed by ofp4 single and ofp4/ knat7 double mutants, similar to knat7 single mutants. OFP1 and OFP4 are also components of the BLH6–KNAT7 multi-protein complex and may modulate the activity of the BLH6–KNAT7 complex [ 58 ]. KNAT7 also physically interacts and forms functional complexes with MYB75 and BLH6, which are involved in SCW formation [ 61 , 62 ] ( Table 3 ). blh6 knockout mutants displayed thicker cell walls in their interfascicular fibers, similar to knat7 mutants [ 62 ], suggesting its role as a transcriptional repressor controlling SCW formation in interfascicular fibers through its interactions with KNAT7. Arabidopsis Class II KNOX TFs are also known to interact with each other. The Y2H data from Hackbush et al. [ 55 ] showed that KNAT3 physically interacts with KNAT4, KNAT4 interacts with KNAT7, and KNAT5 interacts with KNAT7. Recently, KNAT7 was reported to form a functional heteromeric complex with KNAT3 and regulate SCW formation, possibly via F5H , a syringyl lignin gene in Arabidopsis ( Figure 2 and Table 3 ). Qin et al. [ 16 ] showed that a significant downregulation of the F5H gene, a key gene known to play a significant role in S-lignin formation, occurred in a KNAT3 / KNAT7 double mutant and as a result, the S/G lignin ratio was reduced by 83–84% compared to wild type stems. However, yeast-one-hybrid (Y1H) experiments did not show direct binding of either the KNAT7 or KNAT3 protein with the F5H gene promoter. They suggested that a larger complex (including KNAT3 and/or KNAT7) might regulate F5H gene expression in Arabidopsis . They also reported that KNAT3, but not KNAT7, can physically interact with the known top-level master regulators NST1 and NST2, but not SND1 ( Table 3 ). However, neither NST1 nor NST2 alone or in combination with KNAT3 could activate the F5H promoter, suggesting that some other factors required for the formation of this complex were still missing in their experiments. In the poplar genome, there are two closely related F5H (or CAld5H) genes [ 63 , 64 ]. Wang et al. [ 64 ] discovered that 12 TFs are co-expressed with CAld5H genes. Only BLH6a and BLH6b are specifically bound to the CAld5H2 promoter, and BLH2 is bound to both the promoters. BLH6 is also a transcriptional repressor. No mention of any KNOX II TFs in the BLH complex was made in this work. Bhargava et al. [ 65 ] showed that MYB75 and MYB5 both interact with KNAT7 ( Table 3 ). Ma et al. [ 24 ] reported interactions among GhBEL1-like and GhKNOX II proteins from cotton ( Table 3 ). GhBEL1, GhBLH1, and GhBLH6 interact with GhKNAT7. Moreover, GhKNAT7 interacts with GhMYB75, GhOFP1/5/4, and GhBLH1/5/6, forming heteromers. KNAT7 can form heterodimeric interactions (KNAT7–BLH and KNAT7–MYB) and at the same time can form trimeric interactions (KNAT7-BLH-OFP) to regulate SCW biosynthesis, and the functional conservation of these interactions in different plant species will help us to understand the complex regulatory network of SCW formation. Wang et al. [ 66 ] recently showed that the microtubule-associated GhIQD14 protein also interacts with the GhKNL1 protein (GhKNAT7) to regulate SCW formation; Arabidopsis and rice have similar genes encoding similar IQD14 proteins ( Table 3 ). MYB61 is one of the TFs that directly regulates the expression of KNAT7 in Arabidopsis [ 53 ], ( Figure 2 ). In rice, a gibberellin-mediated DELLA-NAC signaling pathway regulates cellulose synthesis [ 67 ], and KNAT7, BELL, and OFP2 are known to interact during vasculature development [ 68 ]. NAC29/31directly regulates the expression of MYB61, which in turn activates CesA expression ( Table 3 ). Wang et al. [ 35 ] recently showed that interactions between KNAT7 and NAC31 suppress the activation of MYB61 expression, suggesting that the order of signal transduction in SCW formation may have changed during the evolution of dicots and monocots [ 40 ]. Similarly, biochemical and gene expression studies in rice revealed that KNAT7 negatively regulates cellulose biosynthesis and cell expansion by interacting with NAC31 and a cell growth master regulator, growth regulating factor 4 (GRF4), which is known to control the expression of the expansin genes that regulate grain size ( Table 3 ). In a recent report, it was shown that KNAT7 and MYB6 heterodimers repressed SCW development in poplar and Arabidopsis while promoting anthocyanin synthesis [ 69 ]. The overexpression of MYB6 in transgenic poplar resulted in reduced SCW deposition, accompanied by the repressed expression of SCW biosynthetic genes. MYB6 has a DNA binding domain and interacts with the bHLH protein. KNAT7 also interacts with MYB6, MYB75, and MYB115 based on Y2H and BiFC data ( Table 3 ). Therefore, it appears that the complex interactions of KNAT7 proteins with other cellular proteins play a major role in SCW formation in higher plants."
} | 9,404 |
23176474 | null | s2 | 3,996 | {
"abstract": "The chemical and electrochemical gradients in biofilms play a critical role in electron-transfer processes between cells and a solid electron acceptor. Most of the time, electron-transfer processes have been investigated in the bulk phase, for a biofilm electrode or for an isolated component of a biofilm. Currently, the knowledge of chemical and electrochemical gradients in living biofilms respiring on a solid surface is limited. We believe the chemical and electrochemical gradients are critical for explaining electron-transfer mechanisms. The bulk conditions, an isolated part of a biofilm or a single cell cannot be used to explain electron-transfer mechanisms in biofilm systems. In addition, microscale gradients explain how the reactor configuration plays a critical role in electron-transfer processes."
} | 203 |
21643511 | null | s2 | 3,997 | {
"abstract": "The general topic of this review is protein-based underwater adhesives produced by aquatic organisms. The focus is on mechanisms of interfacial adhesion to native surfaces and controlled underwater solidification of natural water-borne adhesives. Four genera that exemplify the broad range of function, general mechanistic features, and unique adaptations are discussed in detail: blue mussels, acorn barnacles, sandcastle worms, and freshwater caddisfly larva. Aquatic surfaces in nature are charged and in equilibrium with their environment, populated by an electrical double layer of ions as well as adsorbed natural polyelectrolytes and microbial biofilms. Surface adsorption of underwater bioadhesives likely occurs by exchange of surface bound ligands by amino acid sidechains, driven primarily by relative affinities and effective concentrations of polymeric functional groups. Most aquatic organisms exploit modified amino acid sidechains, in particular phosphorylated serines and hydroxylated tyrosines (dopa), with high-surface affinity that form coordinative surface complexes. After delivery to the surfaces as a fluid, permanent natural adhesives solidify to bear sustained loads. Mussel plaques are assembled in a manner superficially reminiscent of in vitro layer-by-layer strategies, with sequentially delivered layers associated through Fe(dopa)(3) coordination bonds. The adhesives of sandcastle worms, caddisfly larva, and barnacles may be delivered in a form somewhat similar to in vitro complex coacervation. Marine adhesives are secreted, or excreted, into seawater that has a significantly higher pH and ionic strength than the internal environment. Empirical evidence suggests these environment triggers could provide minimalistic, fail-safe timing mechanisms to prevent premature solidification (insolubilization) of the glue within the secretory system, yet allow rapid solidification after secretion. Underwater bioadhesives are further strengthened by secondary covalent curing."
} | 501 |
21643511 | null | s2 | 3,998 | {
"abstract": "The general topic of this review is protein-based underwater adhesives produced by aquatic organisms. The focus is on mechanisms of interfacial adhesion to native surfaces and controlled underwater solidification of natural water-borne adhesives. Four genera that exemplify the broad range of function, general mechanistic features, and unique adaptations are discussed in detail: blue mussels, acorn barnacles, sandcastle worms, and freshwater caddisfly larva. Aquatic surfaces in nature are charged and in equilibrium with their environment, populated by an electrical double layer of ions as well as adsorbed natural polyelectrolytes and microbial biofilms. Surface adsorption of underwater bioadhesives likely occurs by exchange of surface bound ligands by amino acid sidechains, driven primarily by relative affinities and effective concentrations of polymeric functional groups. Most aquatic organisms exploit modified amino acid sidechains, in particular phosphorylated serines and hydroxylated tyrosines (dopa), with high-surface affinity that form coordinative surface complexes. After delivery to the surfaces as a fluid, permanent natural adhesives solidify to bear sustained loads. Mussel plaques are assembled in a manner superficially reminiscent of in vitro layer-by-layer strategies, with sequentially delivered layers associated through Fe(dopa)(3) coordination bonds. The adhesives of sandcastle worms, caddisfly larva, and barnacles may be delivered in a form somewhat similar to in vitro complex coacervation. Marine adhesives are secreted, or excreted, into seawater that has a significantly higher pH and ionic strength than the internal environment. Empirical evidence suggests these environment triggers could provide minimalistic, fail-safe timing mechanisms to prevent premature solidification (insolubilization) of the glue within the secretory system, yet allow rapid solidification after secretion. Underwater bioadhesives are further strengthened by secondary covalent curing."
} | 501 |
38572077 | PMC10986841 | pmc | 3,999 | {
"abstract": "Establishing microbial cell factories has become a sustainable and increasingly promising approach for the synthesis of valuable chemicals. However, introducing heterologous pathways into these cell factories can disrupt the endogenous cellular metabolism, leading to suboptimal production performance. To address this challenge, dynamic pathway regulation has been developed and proven effective in improving microbial biosynthesis. In this review, we summarized typical dynamic regulation strategies based on their control logic. The applicable scenarios for each control logic were highlighted and perspectives for future research direction in this area were discussed.",
"conclusion": "4. Concluding Remarks and Furfure Perspectives Dynamic regulation is a promising approach for coordinating heterologous gene expression and rearranging the expression of endogenous competing genes to increase the productivity of microbial cell factories. By mimicking the natural metabolic network, the dynamic regulation circuits were applied in the engineered host, endowing cells the intelligence to coordinate gene expression and repression autonomously. As summarized in this review, two-phase dynamic regulation and autonomous dynamic regulation, including positive feedback control, oscillation, and multi-functional dynamic control, have been applied ubiquitously in metabolic engineering to achieve remarkable improvements in titers and yields of value-added products [ 57 ]. Each regulation logic has its advantages and disadvantages, which have been pointed out in related sections. One obvious factor that constrains the application of dynamic regulation is the limited number of biosensor systems available as controllers. As discussed in the sections of positive feedback control-based and oscillation-based dynamic regulation, new biosensors can be characterized or engineered to sense an increasing number of metabolites to expand the applicable scenarios of dynamic regulation. Besides mining for novel biosensor systems, another way to address the limited number of biosensors is to mine and develop central metabolites-based biosensors (for example, acetyl-CoA and pyruvate) [ 51 ]. As most of the microbial biosynthetic pathways start from central metabolites, developing central metabolite-responsive biosensor systems would further expand the applicable scenarios of dynamic regulations, although there are still challenges on utilizing these central metabolites-based biosensor. First, such central metabolites-triggered dynamic controller may start the autonomous regulation early due to the earlier accumulation of inducers. Moreover, the concentrations of central metabolites are often tightly regulated by endogenous regulation networks, and the integration of heterologous pathways will result in diverse interference with the accumulation of central metabolites, causing fluctuated dynamic regulation performance. Furthermore, endogenous natural pathways are regulated at DNA, RNA, and protein level to provide reasonable and timely control. However, most of the dynamic regulation exerted in metabolic engineering is at the DNA or RNA level [ 57 , 102 ]. For gene activation, the dynamic control at DNA or RNA level will be more straightforward and effective in starting gene expression, but gene repression will be less effective at the DNA or RNA level, especially when the translated proteins are stably maintained in the cells [ 16 ]. These proteins can still work normally, which affects the regulation effect. Developing an expansive set of protein level dynamic regulation tools, such as protein degradation tags, degrons, or proteases, achieves fast and accurate control toward target proteins, which may boost the efficiency of dynamic regulation and optimization of engineered metabolic pathways [ 58 , 103 , 104 ]. In the future, dynamic regulation will see combinatory optimization by combing diverse control logics at DNA, RNA, and protein level.",
"introduction": "1. Introduction Metabolic engineering manipulates microbial metabolism to produce value-added products and maximize productivity to fulfill the high demands of industrial production [ 1 , 2 ]. Recent years have witnessed the development of metabolic engineering for the biosynthesis of natural products [ 3 ], pharmaceuticals [ 4 ], cosmetics [ 5 ], and bulk chemicals [ 6 ] in microbial cell factories. By introducing heterologous pathways into the microbial hosts, such as Escherichia coli, Bacillus subtilis, Saccharomyces cerevisiae , and Corynebacterium glutamicum [ 6 – 10 ], inexpensive feedstocks can be converted into valuable products. For example, Zhang et al. constructed a biosynthetic pathway for the production of the anti-cancer drug vinblastine in yeast using glucose as the carbon source [ 3 ]. While diverse compounds were produced in microbes, foreign pathways compete with the endogenous metabolism in the hosts, affecting cell growth and impairing product titer. To achieve higher productivity, various approaches have been used to optimize enzyme expression and carbon flux distribution, including protein engineering to increase the enzyme activity [ 11 ], tailoring enzyme expression through ribosome binding site (RBS) or promoter engineering for optimized strength [ 12 , 13 ], and host engineering to block the competing pathways to hijack carbon source for cell production [ 14 – 18 ]. Although these techniques have improved the productivity of microbial cell factories, issues continue to hinder the establishment of efficient microbial systems. One such issue is the lack of real-time regulation in heterologous pathways, leading to unbalanced enzyme expression and metabolic congestion, which impair productivity [ 19 ]. Additionally, some heterologous reactions compete with the endogenous essential pathways for precursors or co-factors, resulting in conflicts between cell growth and production [ 20 , 21 ]. However, deleting these competing pathways directly jeopardizes cell growth as well as productivity [ 22 ]. Furthermore, the gradual accumulation of toxic intermediates during the biosynthesis of target products in some pathways can cause growth retardation [ 23 ]. In such cases, delaying the expression of heterologous genes, downregulating the expression of endogenous essential genes, or minimizing the synthesis of toxic intermediates during the fermentation were required for constructing productive microbial cell factories. Thus, dynamic pathway regulation, including two-phase dynamic regulation and autonomous dynamic regulation, has been developed to effectively solve those problems through designed gene regulation circuits. In the two-phase dynamic regulation, the fermentation is manually split into two phases: a growth phase for biomass accumulation, followed by a production phase for heterologous pathway expression. The shift from growth to production is regulated by adding extracellular inducers, including chemical inducers and physical inducers, at pre-determined times to trigger the dynamic controller for production activation and competing pathway repression. In autonomous dynamic regulation, specific gene activation and repression can be initiated by the cells without manual control. With cell growth, the carbon flux can be autonomously siphoned into heterologous pathways by an intracellular inducer-triggered dynamic controller, mimicking the “just-in-time transcription” prevalent in natural metabolic networks [ 24 ]. Additionally, the dynamic controller can autonomously repress the expression of competing genes, enhancing the carbon flux towards target products. Both two-phase dynamic regulation and autonomous dynamic regulation require a dynamic controller, which contains a signal to reflect cellular metabolisms such as pH, temperature, light, and metabolites, a biosensor to detect the signal, and a control valve (promoter) to process the sensor input and transform it into specific output [ 25 ]. Here, we reviewed recent advances in dynamic regulation to improve the biosynthesis of value-added compounds. Notable examples in dynamic regulation that increased the productivity of microbial cells are listed in Table 1 . We first summarized studies on two-phase dynamic regulation enabled by inducible systems. Next, we analyzed the examples of autonomous dynamic regulation triggered by intracellular signals. Based on the difference in control logic, the common autonomous dynamic regulations were categorized into positive feedback control-based dynamic regulation, oscillation-based dynamic regulation, and the multi-functional dynamic regulation. Finally, future perspectives and outlooks in dynamic regulation were discussed."
} | 2,171 |
34646398 | PMC8491711 | pmc | 4,000 | {
"abstract": "The self-healing behavior of two supramolecular polymers based on π–π-interactions featuring different polymer backbones is presented. For this purpose, these polymers were synthesized utilizing a polycondensation of a perylene tetracarboxylic dianhydride with polyether-based diamines and the resulting materials were investigated using various analytical techniques. Thus, the molecular structure of the polymers could be correlated with the ability for self-healing. Moreover, the mechanical behavior was studied using rheology. The activation of the supramolecular interactions results in a breaking of these noncovalent bonds, which was investigated using IR spectroscopy, leading to a sufficient increase in mobility and, finally, a healing of the mechanical damage. This scratch-healing behavior was also quantified in detail using an indenter.",
"conclusion": "Conclusion Supramolecular polymers based on π–π interactions were synthesized and characterized in detail. The mechanical and thermal behavior was studied revealing an activation of the supramolecular interactions at 125 °C. This finding could also be verified by temperature-depending IR-spectroscopy indicating a broadening of the aromatic signals at 150 °C, which correlates to the changes of the molecular structure. Furthermore, the scratch healing was analyzed in detail showing that only one of the two polymers studied, polymer P1 is able to heal scratches in a sufficient manner at temperature higher than the activation of the π–π interaction. In contrast, polymer P2 could not be damaged in a sufficient manner (under the utilized conditions) due to the polymer design. In particular, the poly(ethylene glycol) block resulted in a sufficient elastic recovery. Consequently, the material could not be analyzed via scratch testing in sufficient manner. The current study reveals a strong correlation between the molecular structure of the supramolecular building units and the healing behavior of such polymers. Thus, the polymer backbone influences the healing behavior of the materials significantly and, consequently, this aspect is also highly important for the design of novel self-healing materials. However, further studies are required in order to understand the influence of the utilized polymer backbone in more detail.",
"introduction": "Introduction Damage inflicted on different materials is omnipresent. Consequently, nature established a mechanism dealing with this problem [ 1 ]. The regeneration after a damage is one of nature´s great abilities. For instance, a broken bone is healed [ 2 ] and sometimes even whole limbs can be regenerated as known from the amphib axolotl [ 3 ]. Additionally, nonliving natural materials can also be healed such as mussel byssus threads [ 4 ]. This specific process is based on reversible interactions, which are integrated in the chemical structure of the proteins of the thread [ 5 ]. Zinc–histidine metal complexes which are part of the protein’s structure enable the material to regenerate its mechanical performance after a damage event [ 1 , 6 ]. Besides the examples of self-healing/regeneration that exist in Nature, the general concept could also be transferred to different synthetic materials. Hereby, two concepts can be distinguished. In extrinsic self-healing materials, a material flow is achieved by the encapsulation of microcapsules [ 7 ] or microchannels [ 8 ] filled with liquid healing agent. In contrast, intrinsic self-healing [ 9 ] and, thus, regeneration of the materials without any additional required healing agents, can be obtained by the integration of dynamic covalent bonds or [ 10 ], as known from Nature, by supramolecular ones [ 11 – 12 ]. In previous studies, several of these interactions were already applied such as metal–ligand interactions [ 13 – 14 ], hydrogen bonds [ 15 – 16 ] or halogen bonds [ 17 ]. Furthermore, π–π interactions also feature a reversible behavior and were therefore utilized for the design of different self-healing polymers [ 18 – 20 ]. In this context, mainly the interaction between π-electron-deficient diimide groups and π-electron-rich pyrene moieties was applied resulting in a very strong and stable supramolecular bond [ 21 – 22 ]. The noncovalent interaction was found to be reversible and, therefore, enabled healing of scratches [ 18 ]. However, little is known about the exact healing mechanism on the molecular scale and the correlation to the macroscopic properties of such polymers. For this purpose, the current study will focus on the design of polymers containing π–π interactions and the quantification of the healing behavior as well as the in-depth characterization of the molecular behavior and the macroscopic properties, which reveals new insights into the self-healing materials based on π–π interactions.",
"discussion": "Results and Discussion Polymer synthesis For the synthesis of supramolecular polymers based on π-π interactions a literature reported procedure was utilized (see Scheme 1 ), which described the synthesis of polypropylene glycol-based polymers featuring aromatic diimides [ 23 ]. Following the procedure, perylene-3,4,9,10-tetracarboxylic dianhydride was converted with poly(propylene glycol) bis(2-aminopropyl ether) with a molar mass of approximately 2000 g/mol resulting in polymer P1 . In order to study the influence of the polymer backbone on the material’s properties, the diamine containing polymer was exchanged to a triblock copolymer of poly(propylene glycol)- block -poly(ethylene glycol)- block -poly(propylene glycol) (PPG 3 -PEG 39 -PPG 3 ) featuring also two amine groups as end groups. The molar mass of this reactant was 1900 g/mol. The conversion with perylene-3,4,9,10-tetracarboxylic dianhydride resulted in polymer P2 . In both synthesis protocols imidazole was applied as a catalyst in order to obtain higher molar masses. Scheme 1 Schematic representation of the polymer synthesis of P1 and P2 . Subsequently, both polymers were characterized regarding their structure. For this purpose, size exclusion chromatography (SEC) was performed revealing a molar mass of M n = 11,400 g/mol for P1 and M n = 17,400 g/mol for P2 with respect to a PEG-standard. The SEC traces of both polymers are depicted in Supporting Information File 1 . Furthermore, the polymers were analyzed using NMR spectroscopy. Herein, all signals could be assigned to both moieties within the polymers, the perylene and the polymer backbone. All spectra are shown in Supporting Information File 1 . Characterization of the polymers After the synthesis of the polymers, the material and structural properties were analyzed in detail in order to study the molecular behavior and to correlate these results later with the healing behavior of the polymers. Firstly, the thermal properties of both polymers were investigated via differential scanning calorimetry (DSC) and thermogravimetric analysis (TGA). The TGA revealed a high thermal stability up to a temperature of 370 °C (for curves see Supporting Information File 1 ). The temperature was determined at a residual mass of 95%. The DSC on the other hand indicates several thermal transitions (see Figure 1 ). Both polymers feature a glass transition temperature ( T g ) at −58 °C ( P1 ) and −51 °C ( P2 ), respectively. Furthermore, the polymers have an endothermic transition at 129 °C ( P1 ) and 126 °C ( P2 ). This transition is associated with the activation of the perylene domains, which was also reported in literature [ 23 ]. During cooling, the reformation of the perylene domain was also observed. Finally, P2 featured a second endothermic transition at 13 °C, which is based on the melting of the short PEG-block [ 24 ]. Figure 1 DSC-analysis of the polymers P1 and P2 (second heating and cooling cycle; 20 K/min for heating and cooling) with a glass transition temperature ( T g ) at −58 °C ( P1 ) and −51 °C ( P2 ) and the endothermic transition at 129 °C ( P1 ) and 126 °C ( P2 ). In addition, P2 shows a T m at 13 °C. Furthermore, both polymers were characterized via rheology and dynamic mechanical thermo-analysis (DMTA). The DMTA of P1 and P2 is depicted in Figure 2 , revealing a network structure below temperatures of 120 °C. Above this temperature, a sharp transition (within a very small temperature range) and a significant drop of storage and loss modulus could be observed. Accordingly, this transition is associated with the endothermic signal measured in the DSC and based on the activation of the π–π interactions. Such a behavior could also be observed for other supramolecular polymers; however, the temperature window, in which the drop of the storage and loss moduli occurred, is rather small compared to other self-healing supramolecular polymers, e.g., metallopolymers [ 25 ]. Figure 2 DMTA analysis of P1 and P2 showing the transition at around 130 °C due to the reversible π–π interactions. Supramolecular polymers feature certain temperature ranges, in which the noncovalent bond is activated. The degree of reversibility can be determined by the supramolecular bond lifetime [ 26 ]. For example, a study regarding ionomers revealed a strong correlation of the bond lifetime with the healing behavior [ 27 ]. A similar behavior was also observed for metallopolymers [ 13 ]. Consequently, the polymers P1 and P2 were also studied by frequency sweeps at certain temperatures (see Figure 3 ). At temperatures below the endothermic transition at 125–130 °C, no crossover of G' and G'' could be observed indicating no active supramolecular bonds. Furthermore, at this temperature (80 °C) G' is higher than G'' indicating a network structure of the polymers. This finding correlates with the DSC results, since the π–π interactions are not activated and, therefore, the polymer network is intact. Figure 3 Frequency sweeps of polymers P1 (left) and P2 (right). Within the transition, the frequency sweeps revealed a crossover of storage and loss modulus showing the activation of the π–π interactions, which goes hand in hand with the DSC results. Thus, a dynamic network structure could be revealed. The supramolecular bond lifetime was determined to be 15.87 s at 135 °C ( P1 ) and 10.18 s at 130 °C ( P2 ), respectively. The calculation was performed according to literature and Equation 1 [ 27 ]. [1] Supramolecular bond lifetime = 1 /frequency ( crossover ) However, at higher temperatures also no crossover could be observed, which is also in line with findings for other supramolecular bonds like ionic interactions [ 27 ]. In this temperature range, G'' is higher than G' showing that the polymer is uncrosslinked. Thus, the mobility is very high, which is a precondition for the healing. To get further insight into the molecular behavior of P1 and P2 , temperature dependent IR spectroscopy experiments of drop casted films of the respective polymers were carried out. The respective polymers were heated to 150 °C and an IR spectrum was recorded every 20 K. Afterwards the polymers were air cooled and further spectra at 100, 70, and 25 °C were recorded. Figure 4 displays the aromatic C=C (1570–1605 cm −1 ) and C=O stretching (1640–1710 cm −1 ) region of the infrared spectra of P1 recorded during heating. These regions are specific to the perylene moieties in the polymers and, therefore, allow a direct observation of the π–π interactions in the polymer. Both the C=C and C=O vibrations are sensitive to the electron density in the perylene systems, which changes depending on the strength of π–π interactions [ 28 – 30 ]. Figure 4 Temperature dependent IR spectra of P1 drop casted on KBr in the C=C (1570–1605 cm −1 ) and C=O stretching region (1640–1710 cm −1 ). During heating, slight shifts in the position of all bands (1578 cm −1 : +1 cm −1 ; 1594: −1.5 cm −1 ; 1656 cm -1 : +0.8 cm −1 ; 1698: +1.5 cm −1 . These shifts are partially reversed while cooling the polymer, indicating a reversible cause for the shifts. Additionally, all bands exhibit broadening during heating, especially noticeable at 150 °C, indicating a broader distribution of species contributing to the IR spectrum. During heating, the C=C stretching vibrations located at 1578 and 1594 cm −1 show opposite behavior regarding their wavenumber position: While the band at 1578 cm −1 shifts to slightly higher wavenumbers (indicating more electron density in the perylene rings), the band at 1594 cm −1 shifts to slightly lower frequencies (indicating less electron density in the perylene rings). This seemingly counterintuitive behavior can be explained by the fact that the perylene-moieties act as both π-donors and -acceptors. Weakening of π–π interactions therefore results in higher electron densities in some part of the perylene moiety, while in other parts the electron density decreases. The C=O vibrations at 1656 and 1698 cm −1 on the other hand both shift to higher wavenumbers, indicating a strengthening of the carbon-oxygen bond. This is caused by a weakening of inter-perylene C–H–O interactions that also contribute to the stacking behavior [ 28 – 29 ], which in turn increases the electron density in the C=O bond. In addition to these shifts in band positions, all bands show noticeable broadening during heating, which is most significant for the C=O vibration at 1656 cm −1 . This indicates a broader distribution of species contributing to the IR spectrum, which is consistent with increased mobility of the perylene moieties which allows for more possible geometries. Furthermore, it is evident that the broadening of the band shows an intensive increase at 150 °C. This nonlinear behavior indicates a drastic change in molecular structure around this temperature range, which corresponds to the observed signals in the DSC measurements and the findings of the DMTA analysis. The slight difference in temperature can be explained by the different experimental setups (open system for IR measurements, closed system for DSC) and the different sample preparations as well as different applied heating rates. For P2, the observations (see Supporting Information File 1 ) are generally the same; however; these changes are much weaker for lower temperatures. While for P1 a slight band shift can be observed even for 50 and 70 °C, P2 only shows noticeable shifts at higher temperature. This aspect is consistent with the higher rigidity of P2 at lower temperatures, caused by the presence of a second phase transition of the PEG moieties observed in the DSC. Nevertheless, at 150 °C, P2 also shows the clear broadening of bands, which is consistent with the very similar positions for the perylene π–π interaction signal in the DSC. All these findings clearly support that at increased temperatures the perylene–perylene π–π interactions are significantly weakened, which increases the mobility of the chains. Furthermore, the reversible nature of these processes is indicated by the recovery of the band shifts and band broadenings upon cooling of the polymers to room temperature. Self-healing behavior Finally, the healing behavior of the polymers was studied in detail. For this purpose, an established method was applied enabling the detailed analysis of the scratch healing behavior by investigating the volume of the scratch [ 31 – 32 ]. A scratch was introduced into the material by using an indenter, afterwards, the sample was twisted to 90° and the profile was measured using an indenter resulting in the possibility to calculate the volume of the scratch. The subsequent heating at a certain temperature (80 °C, 125 °C or 150 °C) resulted in a healing behavior, which was quantified afterwards by measuring the profile again. Using this approach, P1 was studied first and the results are summarized in Table 1 . For P1 , a nearly complete healing at 150 °C was observed for the first scratch (see Figure 5 ) and a partial healing for the second scratch (see Supporting Information File 1 ). The healing behavior at 80 °C was significantly lower compared to 150 °C (see Supporting Information File 1 ) and the scratch could still be detected after 36 h at 80 °C. Furthermore, the healing was studied at 125 °C, which corresponds to the temperature, at which the change of the mechanical properties and flow behavior was started (see results of DMTA). Hereby, a partial healing was also observed (healing efficiency 50.64%, for pictures see Supporting Information File 1 ). Looking closer at the 3D-profiles, it can be seen that the depth of the scratch was reduced by more than 60% (from max. 64 µm to max. 23 µm). However, the width and the length of the scratch is nearly unchanged. Thus, the overall healing efficiency is lower compared to the reduction of the scratch depth. Table 1 Overview of the healing of P1 . Scratch Healing time/ temperature Volume before healing [µm³] Volume after healing [µm³] Healing efficiency a \n \n 1 18 h; 150 °C 120,934,901 41,574 99.97% 2 18 h; 150 °C 33,233,081 8,757,225 73.65% 3 b 18 h; 80 °C 23,741,395 12,086,157 49.09% 18 h; 80 °C 12,086,157 11,194,985 7.37% 4 18 h; 125 °C 22,119,541 10,917,396 50.64% a The healing efficiency was calculated based on a literature reported equation [ 31 – 32 ]. b The third scratch was healed at 80 °C for 18 h and afterwards, it was further healed again for 18 h at 80 °C. The overall healing efficiency is 52.85%. Figure 5 Schematic representation of the first healing of P1 at 150 °C. In contrast, the analysis of the healing behavior of P2 was just impossible. The scratching of the material resulted in no measurable scratch, which is presumably associated with the melting of the PEG-block at temperatures below room temperature (see Supporting Information File 1 ). Thus, the material seems to feature a highly efficient elastic recovery (see Supporting Information File 1 for the “scratch” analysis) resulting in a (fast) crack closure behavior without the necessity of activating the supramolecular π–π interactions. Consequently, the healing of P2 could not be analyzed in detail since the polymer backbone seems to influence the mobility behavior of the material significantly. The observed healing behavior of P1 goes hand in hand with the structural analysis of the material before. Since the healing behavior is based on π–π interactions, a sufficient healing could only be observed at temperatures above the activation of the π–π interactions. At temperatures below the activation, the healing was incomplete and presumably associated with the elastic recovery of the material. Consequently, for the first time, a correlation between the structure behavior of polymers featuring reversible π–π interactions and the healing behavior could be obtained."
} | 4,683 |
33146374 | PMC7875005 | pmc | 4,001 | {
"abstract": "Abstract Photosynthetic dinoflagellates of the Family Symbiodiniaceae live symbiotically with many organisms that inhabit coral reefs and are currently classified into fifteen groups, including seven genera. Draft genomes from four genera, Symbiodinium , Breviolum , Fugacium , and Cladocopium , which have been isolated from corals, have been reported. However, no genome is available from the genus Durusdinium , which occupies an intermediate phylogenetic position in the Family Symbiodiniaceae and is well known for thermal tolerance (resistance to bleaching). We sequenced, assembled, and annotated the genome of Durusdinium trenchii , isolated from the coral, Favia speciosa , in Okinawa, Japan. Assembled short reads amounted to 670 Mb with ∼47% GC content. This GC content was intermediate among taxa belonging to the Symbiodiniaceae. Approximately 30,000 protein-coding genes were predicted in the D. trenchii genome, fewer than in other genomes from the Symbiodiniaceae. However, annotations revealed that the D. trenchii genome encodes a cluster of genes for synthesis of mycosporine-like amino acids, which absorb UV radiation. Interestingly, a neighboring gene in the cluster encodes a glucose–methanol–choline oxidoreductase with a flavin adenine dinucleotide domain that is also found in Symbiodinium tridacnidorum . This conservation seems to partially clarify an ancestral genomic structure in the Symbiodiniaceae and its loss in late-branching lineages, including Breviolum and Cladocopium , after splitting from the Durusdinium lineage. Our analysis suggests that approximately half of the taxa in the Symbiodiniaceae may maintain the ability to synthesize mycosporine-like amino acids. Thus, this work provides a significant genomic resource for understanding the genomic diversity of Symbiodiniaceae in corals.",
"introduction": "Introduction Symbiotic dinoflagellates of the Family Symbiodiniaceae, are keystone photosynthetic organisms in coral reef ecosystems ( LaJeunesse et al. 2018 ). The diversity of symbiotic dinoflagellate populations and their relationships with hosts have been analyzed and discussed ( Baker 2003 ; Coffroth and Santos 2005 ; Coffroth et al. 2006 ; Pochon and Gates 2010 ; Green et al. 2014 ; Pochon et al. 2014 ). Dinoflagellate populations in stony corals, which form modern reefs, have attracted particular attention ( Abrego et al. 2009 ; Thornhill et al. 2014 ; Shoguchi et al. 2020 ), because breakdown of coral-dinoflagellate symbiosis causes coral bleaching, decimating coral reef communities (coral holobionts) ( Weis et al. 2008 ; Stat and Gates 2011 ). Although many reasons have been discussed for collapse of this symbiotic relationship ( Nakamura and van Woesik 2001 ; Iguchi et al. 2012 ), the main trigger is likely rising surface seawater temperatures (SSTs) caused by climate change ( Weis et al. 2008 ). Possible bleaching has been also reported in other hosts, such as giant clams ( Mies 2019 ). Recently, discussions of coral bleaching due to increasing SSTs have focused on heat-tolerant species of the genus Durusdinium (Symbiodiniaceae) (a member of previous clade D), because genetic variability of dinoflagellates in corals is thought to be a major factor in the bleaching phenomenon ( Berkelmans and Van Oppen 2006 ; Stat and Gates 2011 ; Lesser 2019 ). Horizontal transmission types of symbiosis may be more adaptive than vertical transmission types ( Weis et al. 2001 ; Yamashita et al. 2013 ; Hidaka 2016 ; Yuyama et al. 2018 ). Coral holobionts resulting from coral- Durusdinium symbiosis may be better adapted to rising SSTs than other types of coral holobionts. \n Durusdinium includes heat-tolerant strains ( Rowan 2004 ; Stat and Gates 2011 ). A metabolic analysis of cultured Symbiodiniaceae showed that D. trenchii has a low level of the sterol metabolite, C 29 Stanol 2, suggesting metabolic differences among members of the family Symbiodiniaceae ( Symbiodinium microadriaticum , Symbiodinium psygmophilum , and B. minutum ) ( Klueter et al. 2015 ). A recent report on effects of light and thermal stress indicates that the pan-tropical species, D. trenchii , is more thermotolerant than others so far examined ( S. microadriaticum , B. minutum , and Cladocopium goreaui ) ( Lesser 2019 ). In addition, the heat-stress response of D. trenchii was compared between free-living and symbiotic cells and transcriptional activity in symbiotic dinoflagellates was drastically altered by thermal stress ( Bellantuono et al. 2019 ). Genomes of several taxa within the Symbiodiniaceae have been deciphered ( Shoguchi et al. 2013 , 2018 ; Aranda et al. 2016 ; Liu et al. 2018 ; Li et al. 2020 ) and genome evolution of this family has been discussed ( González-Pech et al. 2019 ). However, no Durusdinium genome is available and the genetic basis for thermal tolerance remains unknown ( Baker 2003 ; Weber and Medina 2012 ; Hidaka 2016 ). To provide a genomic resource for Durusdinium , we isolated D. trenchii from the coral, F. speciosa , in Okinawa, which will be useful for analyzing Durusdinium in coral holobionts. One of the early-diverging lineages of the family Symbiodiniaceae is the genus Symbiodinium ( LaJeunesse et al. 2018 ), which includes species having the ability to synthesize MAAs ( Banaszak et al. 2000 ). Both Symbiodinium and Durusdinium have been known to enhance thermal tolerance of holobionts ( Reynolds et al. 2008 ; Kemp et al. 2014 ; Aihara et al. 2016 ). The genome of Symbiodinium tridacnidorum has a cluster of genes for enzymes involved in MAA biosynthesis ( Shoguchi et al. 2018 ). On the other hand, species in later-diverging groups ( Breviolum and Cladocopium ) appear not to have this metabolic pathway, as no MAA gene cluster has been found in their genomes. Therefore, a draft genome of Durusdinium , one of an intermediate group of seven genera in the family Symbiodiniaceae, may help to clarify when the ability to synthesize MAAs was lost during diversification of the Symbiodiniaceae. To explore the genetic background of the coral symbiont, Durusdinium , here we examined the genome and associated transcriptomes to determine whether Durusdinium also has this gene cluster.",
"discussion": "Results and Discussion Draft Genome of Durusdinium Three genomic libraries with insert sizes ranging from 500 bp to 19 kb were constructed from the cloned Durusdinium ( supplementary table S1 , Supplementary Material online). Short read sequencing (2 × 101 bp) produced ∼76 Gb of total sequencing data, which were assembled into a total length of 695 Mb. Thirty-three scaffolds, which were likely to be contaminant sequences, were removed from the initial assembly ( supplementary table S2 , Supplementary Material online). The final draft genome of D. trenchii (version 1.0) had a total length of 670.4 Mb with a scaffold N50 of 97.5 kb ( table 1 ). Completeness of the D. trenchii genome was checked using CEGMA ( Parra et al. 2007 ) and BUSCO ( Simão et al. 2015 ). The 48% (145/303 BUSCO genes) hits on the D. trenchii proteins was comparable to other reported dinoflagellate genomes (44–71%) ( supplementary fig. S1 , Supplementary Material online). The GC content of the draft genome was 47.4%, comparable to GC contents of Symbiodinium (∼50%) and Cladocopium (∼44%) ( table 1 ). Table 1 Genomic Compositions of Seven Genomes of the Family Symbiodiniaceae \n Durusdinium trenchii \n \n Symbiodinium microadriaticum \n \n a \n \n \n Symbiodinium tridacnidorum \n \n b \n \n \n Breviolum minutum \n \n c \n \n \n Fugacium kawagutii v3 \n \n d \n \n \n Cladocopium goreaui \n \n e \n \n \n Cladocopium sp. (C92) b A total assembled length of assembly (Mb) 670.43 808.24 766.65 615.52 936.98 1,027.79 704.77 G + C content (%) 47.4 50.5 49.9 43.6 45.5 44.8 43.0 No. of genes 30,054 49,109 69,018 41,925 45,192 35,913 65,832 Average length of genes (bp) 15,030 12,898 8,834 11,959 7,242 6,967 8,192 No. of exons per gene 19.6 21.8 13.4 19.6 12.6 10.0 11.3 Average length (bp) of exons 90 110 105 100 126 176 130 Average length (bp) of introns 704 505 561 499 479 575 622 a Aranda et al. (2016). b Shoguchi et al. (2018). c Shoguchi et al. (2013). d Li et al. (2020). e Liu et al. (2018). Genome Annotations Two RNA-seq libraries were constructed and sequenced. Reads of 2 × 134 bp produced ∼11 Gb of total sequencing data ( supplementary table S1 , Supplementary Material online). The de novo assembly produced 64,183 contigs with a GC content of ∼55%, similar to that of clade D from reported transcriptomes ( González-Pech et al. 2017 ). Using transcriptome data as hints, 30,054 protein-coding genes were predicted ( table 1 ), a number comparable to that of C. goreaui ( Liu et al. 2018 ), but less than some other dinoflagellate genomes. A recent report indicated that a consistent gene-prediction approach is crucial for comparative genomic analysis, suggesting the difficulties of computational gene prediction for dinoflagellate genomes ( Chen et al. 2020 ). Therefore, long-read transcriptomic data from various conditions are likely to be needed in future comparative genomic studies. Assembled genomic and transcriptomic data and annotation information are accessible from the following genome browser: https://marinegenomics.oist.jp/gallery ( Koyanagi et al. 2013 ). The 28S rDNAs and ITS2 sequences (TRINITY_DN41397_c4_g2_i5) from the assembled sequences corresponded to the nuclear ribosomal ITS1/5.8S/ITS2 (KJ019889) in D. trenchii LaJeunesse sp. nov. ( LaJeunesse et al. 2014 , 2018 ), confirming that the clone is D. trenchii . Gene Cluster for Sunscreen Biosynthesis Analysis of the S. tridacnidorum (previously Symbiodinium sp. clade A3) genome identified a gene cluster for enzymes involved in MAA biosynthesis in Shoguchi et al. (2018) . In addition, comparative analysis suggested that orthologs of these genes have been lost in the common ancestor of Breviolum and Cladocopium . To determine whether such losses occurred in the Durusdinium lineage, we performed BLAST and Pfam domain searches. Scaffold 2498 of the draft assembly contained a gene cluster for MAA biosynthesis, expression of which was supported by transcriptomic data ( fig. 1 a ). Moreover, gene order was conserved between S. tridacnidorum and D. trenchii . The orthologous relationship between S. tridacnidorum and D. trenchii was confirmed in molecular phylogenetic analysis of the DDG synthase family ( supplementary fig. S2 , Supplementary Material online). In addition, we found that the neighboring gene to D-Ala D-Ala ligase homolog on the 3′ side of the cluster encoded an enzyme resembling the GMC oxidoreductase family. The homolog was also found in the genome of S. tridacnidorum and is located adjacent to the MAA gene cluster ( fig. 1 a ), suggesting syntenic conservation of metabolic genes among members of the Symbiodiniaceae ( Liu et al. 2018 ). Fig . 1 The dinoflagellates, Symbiodinium tridacnidorum and Durusdinium trenchii , both possess a probable gene cluster for MAA biosynthesis. ( a ) A gene cluster in the D. trenchii genome and a potential evolutionary scenario for MAA biosynthesis in the family Symbiodiniaceae. Topology of the tree is based on the phylogenetic tree of the DDG synthase family with bootstrap support >90%, as shown in green circle. The detail is shown in supplementary figure S2 , Supplementary Material online. The positions of clades B and C with no MAA biosynthetic gene cluster are assumed based upon previous 28S rDNA phylogenies ( Shoguchi et al. 2018 ). ( b ) A molecular phylogeny of GMC family enzymes showing evolutionary relationships of the proteins. Proteins from the neighboring GMC oxidoreductase in ( a ) the MAA biosynthetic gene cluster are shown in red. Genes for choline dehydrogenase are encoded in dinoflagellate genomes and others in the Symbiodiniaceae are unclassified enzymes in the GMC family. ( c–e ) 3D structures of the enzymes and their use of flavin adenine dinucleotide (FAD) as a cofactor were predicted using I-TASSER ( Zhang 2008 ). ( c ) Fatty acid photodecarboxylase (FAP), a light-activated enzyme from Chlorella variabilis . ( d ) g1386 of D. trenchii . ( e ) s314_g32.t1 of S. tridacnidorum . The predicted ligase had domains for the GMC oxidoreductase family (GMC_oxred_N of PF00732 and GMC_oxred_C of PF05199), which includes proteins having diverse catalytic activities. A molecular phylogeny of GMC oxidoreductases indicated that this one does not belong to a subfamily with known functions and that it may constitute a sister group of alcohol oxidases and glucose oxidases and dehydrogenases ( fig. 1 b ). Recently, it has been shown that GMC oxidoreductases in algae include photoenzymes ( Sorigué et al. 2017 ; Björn 2018 ), which have the light-capturing flavin adenine dinucleotide (FAD) as a cofactor ( fig. 1 c ). Using I-TASSER software, prediction of the 3D structure of Symbiodiniaceae GMC oxidoreductases showed that they likely also carry FAD ( fig. 1 d and e ), suggesting the possibility of a photoenzyme ( Sorigué et al. 2017 ; Björn 2018 ). Future studies may clarify the relationship between light intensity and MAA biosynthesis. Coral genomes also have genes for MAAs ( Shinzato et al. 2011 , 2014 ), but they do not seem to have GMC oxidoreductase. If coral bleaching is triggered by high SSTs and insolation ( Lesser 2019 ), the Symbiodiniaceae capacity for MAA biosynthesis may contribute to bleaching resistance."
} | 3,378 |
30855227 | PMC6411370 | pmc | 4,002 | {
"abstract": "The physical interactions of growing bacterial cells with each other and with their surroundings significantly affect the structure and dynamics of biofilms. Here a 3D agent-based model is formulated to describe the establishment of simple bacterial colonies expanding by the physical force of their growth. With a single set of parameters, the model captures key dynamical features of colony growth by non-motile, non EPS-producing E. coli cells on hard agar. The model, supported by experiment on colony growth in different types and concentrations of nutrients, suggests that radial colony expansion is not limited by nutrients as commonly believed, but by mechanical forces. Nutrient penetration instead governs vertical colony growth, through thin layers of vertically oriented cells lifting up their ancestors from the bottom. Overall, the model provides a versatile platform to investigate the influences of metabolic and environmental factors on the growth and morphology of bacterial colonies.",
"introduction": "Introduction Bacteria often form dense biofilms with complex spatiotemporal structures ( Costerton et al., 1995 ; Nadell et al., 2016 ; O'Toole et al., 2000 ; Stoodley et al., 2002 ). Mechanical and biochemical interactions, together with cell growth, motility, and signaling, are some of the common elements underlying the rich variety of patterns and behaviors observed. Biofilms often play important roles in diverse settings ranging from environment to human health ( Costerton et al., 1999 ; Jayaraman and Wood, 2008 ; Potera, 1999 ). But they are notoriously difficult to study experimentally because of their opaqueness, high heterogeneity and complex organization, involving multiple spatial and temporal scales ( Roberts et al., 2015 ; Stewart and Franklin, 2008 ). In addition, biofilm-bound bacteria alter their micro-environment by secreting various polysaccharides, forming heterogeneous matrices of filaments that bind cells together within biofilms ( Branda et al., 2005 ; Flemming and Wingender, 2010 ). Over the years, various computational models have been constructed to capture different aspects of biofilm development ( Alpkvist et al., 2006 ; Espeso et al., 2015 ; Ginovart et al., 2002 ; Klapper and Dockery, 2002 ; Kreft et al., 2001 ; Kreft et al., 1998 ; Picioreanu et al., 2004 ; Seminara et al., 2012 ; Tierra et al., 2015 ). However, most of these models are ‘descriptive’ in nature – the complexity of the biofilms makes it difficult to make quantitative comparison between experimental data and model predictions. In recent years, an increasing body of literature has been devoted to simpler, stripped down versions of the biofilm which can be more readily compared to experimental studies. The simplest among these is the growth of a simple bacterial colony on hard agar surface, with cells pushing against each other by the force of their own physical growth, without motility and without extracellular polysaccharides ( Boyer et al., 2011 ; Cole et al., 2015 ; Farrell et al., 2013 ; Ghosh et al., 2015 ; Grant et al., 2014 ; Jayathilake et al., 2017 ; Rudge et al., 2013 ; Rudge et al., 2012 ; Volfson et al., 2008 ) In addition to serving as simpler models of biofilms, the growth of such colonies has been increasingly used in recent years as a model of microbial range expansion in studies of population genetics and ecology ( Hallatschek et al., 2007 ; Hallatschek and Nelson, 2010 ; Korolev et al., 2012 ). Although the growth of such simple colonies has been investigated experimentally many decades ago ( Cooper et al., 1968 ; Lewis and Wimpenny, 1981 ; Mitchell and Wimpenny, 1997 ; Palumbo et al., 1971 ; Pirt, 1967 ; Reyrolle and Letellier, 1979 ; Wimpenny, 1979 ), surprisingly, there has not yet been a common quantitative understanding of the basic elements controlling their growth, for example what factors determine the radial and vertical expansion speeds. In this study, we develop a conceptually simple, yet physically realistic three-dimensional computational model, incorporating the elements of nutrient diffusion, cell-cell and cell-agar mechanical interactions, and introducing a unique cell-level model of surface tension. Our model is efficiently implemented with a parallel algorithm, enabling the simulation of a colony comprising a few million cells within 24 hr. The model is able to capture many observed features of the growing colonies, including the conic shape, the linear growth of the colony radius and height, and their dependence on the cell growth rate. Extensive analysis of the results reveals key driving forces underlying these observations, especially on the role of surface tension and the dynamic form of cell-agar friction, allowing us to make distinct predictions on how various biochemical and mechanical effects alter physiological features of the colony and generate macroscopic spatiotemporal patterns of the growing colony. To guide the construction of our model and validate our simulations, we conducted a series of experiments on the growth of colonies on agar using non-motile E. coli . A set of minimum media with various carbon sources was used to vary the cell growth rate.",
"discussion": "Discussion In this work, we presented a detailed quantitative study of the growth of a bacterial colony on hard agar surface starting from a single cell. For non-motile bacteria incapable of producing extracellular polysaccharides, the colony is driven primarily by the force of their own growth. Key factors involved are nutrient diffusion, mechanical interactions between cells, friction between cell and agar, and the surface tension holding the cells to the agar. We developed a continuum model for nutrient diffusion and implemented it with a multi-resolution numerical technique. With a discrete agent-based model, we captured mechanical interactions, including elasticity and dynamic friction. Most importantly, the surface tension of the liquid in the colony is implemented by introducing a restoring force on cells protruding from a smoothened colony surface. Our model is able to capture quantitatively some of the characteristic features observed for bacterial colony growth, including the conic shape of the colony, the linear expansion of colony radius and height, and both the linear and sublinear dependence of the speed of radial expansion and that of vertical expansion, respectively, on the cell growth rate. The model makes a number of important predictions on the expanding colony as summarized in Figure 10 : The growth zone is predicted to be disc-like and extended throughout the bottom of the colony, contrary to common belief (see below). Radial growth is driven by cells at the outer perimeter of the growth zone; these cells are predicted to form a thin layer, oriented parallel to the agar due to the downward pull of surface tension, with the width of the region determined by the onset of the buckling transition (which occurs when radial compression due to cell-agar friction overwhelms the surface tension). In the colony interior, cells are predicted to orient vertically and are mainly pushed upward by elongating cells in the bottom growth zone. 10.7554/eLife.41093.022 Figure 10. A schematic summary of key mechanisms in the growth of an E.coli colony. After an initial, exponential monolayer growth, buckling occurs at the center of the colony. Cells then grow actively only in the bottom layers (red vertical arrows) whose thickness ( H S ) is determined by the nutrient penetration level (dashed blue line). Cells lying above them are passively pushed up. Throughout this yellow triangular region, cells are oriented vertically. Near the colony edge (cyan region), the cells are oriented planarly and grow outward (horizontal red arrow) continuously in a spread mode to expand the colony in the radial direction. The width of this annulus ( W b ) is determined by mechanical effects arising from the surface tension which pulls the thin layer of cells into the agar, and cell-agar friction which builds up the pressure from the outer edge of the layer, eventually causing buckling at an inner radius where cells transition to the vertical orientation (the green region). These two characteristic parameters, H S and W b , set the speeds of radial and vertical expansions, V R and V H , respectively, as shown in red. The growth rate dependence of these parameters is shown in blue. Capturing all these behaviors within a single model and with a fixed set of parameters is a non-trivial task despite the seeming simplicity of this problem. Many aspects of our model are taken from what are commonly adopted in the extensive literature devoted to this class of problems over the past decade ( Boyer et al., 2011 ; Cole et al., 2015 ; Farrell et al., 2013 ; Ghosh et al., 2015 ; Grant et al., 2014 ; Jayathilake et al., 2017 ; Rudge et al., 2013 ; Rudge et al., 2012 ; Volfson et al., 2008 ). These include the basic modeling of metabolism and cell growth ( Cole et al., 2015 ; Farrell et al., 2013 ; Rudge et al., 2012 ), and the use of Hertzian elasticity to describe cell-cell elastic interaction ( Boyer et al., 2011 ; Farrell et al., 2013 ; Ghosh et al., 2015 ; Grant et al., 2014 ; Volfson et al., 2008 ), all incorporated as computational power increases to reach ever increasing colony sizes ( Cole et al., 2015 ; Rudge et al., 2013 ; Rudge et al., 2012 ). Unique to our study is the treatment of mechanical interactions, specifically friction and cell-level surface tension, which we believe are at the root of all behaviors described above, including the forms of radial and vertical colony growth. A key result of our study is that the linear radial growth is driven by the growth of a thin layer of radially oriented cells located at the colony periphery, whose width is determined by mechanical buckling. Although the linear radial expansion of bacterial colonies has been known for about 50 years ( Pirt, 1967 ), for a long time this was attributed to a ring-shaped growth zone at the outer colony periphery due to nutrient diffusion ( Lewis and Wimpenny, 1981 ; Pirt, 1967 ; Wimpenny, 1979 ). Only quite recently has the notion been made that mechanical effects might also lead to linear radial growth ( Farrell et al., 2013 ; Su et al., 2012 ). ( Su et al., 2012 ) showed experimental results that implicated the interplay of forces in the radial expansion of colonies. ( Farrell et al., 2013 ) proposed mechanical effects as a colloquial rationalization of numerical results generated by toy models with unrealistic details, for example a ‘gravity-like’ adhesion force acting on all cells in the colony. In our study, the adhesion of cells to the agar surface is provided by the surface tension of the liquid surrounding cells in the colony. We introduce a novel cell-level model of surface tension which acts only on cells at the colony surface, distinct from common models of surface tension which depends on the macroscopic curvature of the colony surface and cannot describe thin layers. It is this unique surface tension model that enables us to capture the dynamics from the initial single-layer cell growth, through buckling, to the growth of a macroscopic colony. This cell-level surface tension, responsible for pressing cells into the agar thereby generating friction that eventually causes buckling, cell reorientation and vertical colony growth, is thus the source of all mechanical interactions in the colony. A strong, uniform force such as the ones used in ( Farrell et al., 2013 ) would lead to artificially flattened colonies, especially at the colony center where the height is the highest, since the force is proportional to the height in that model. We regard the characterization of colony growth for different nutrients (which give rise to different cell growth rates) as a unique contribution by our study. The knowledge of the dependence of colony growth on cell growth allows us to discriminate different models of colony growth. As an example, an important component of our model that makes a quantitative difference to the outcome is the form of the friction used. Viscous drag (i.e., friction proportional to the velocity difference) is the form adopted in most models of cell dynamics ( Farrell et al., 2013 ; Ghosh et al., 2015 ; Rudge et al., 2012 ). We instead adopt a form commonly used in modeling granular solids ( Brilliantov et al., 1996 ; Cundall and Strack, 1979 ; Kuwabara and Kono, 1987 ; Shäfer et al., 1996 ). It involves a static friction depending on relative velocity, capped by a dynamic friction which is independent of the velocity. This form, introduced in one of the first models of 2D colony growth ( Volfson et al., 2008 ), exerts a pressure which is independent of the speed of radial expansion, leading to a growth rate-independent buckling width and hence a radial expansion speed that is proportional to cell growth rate, in agreement with our experiments. In contrast, a model based on static friction would have the buckling width reducing with increasing cell growth rate, giving a sublinear dependence of radial expansion speed on cell growth rate which is not compatible with the data in Figure 1I . Indeed, in a model with static friction alone, a much weaker growth-rate dependence of radial expansion speed was obtained ( Figure 8F blue triangles). Along a different line, Fisher-Kolmogorov (FK) dynamics has been used as a phenomenological model to describe radial colony expansion, and has been successful in describing certain spatial patterns formed in growing colonies ( Cao et al., 2016 ). However, FK dynamics would predict a square-root dependence of the radial expansion speed on the cell growth rate ( Fisher, 1937 ; Kolmogorov et al., 1937 ), which will need to be reformulated to conform to the observed dependences. In addition to the well-known linear radial growth, the linear vertical growth of the colony is dissected for the first time qualitatively here since it was first reported ( Lewis and Wimpenny, 1981 ; Wimpenny, 1979 ). Our analysis shows that the vertical expansion speed is limited by the depth that nutrient can penetrate upward into the colony from the agar. Accompanying our result of vertical growth is the predicted vertical orientation of cells in the colony interior, which transitions from the radial orientation at the outer periphery (i.e., the monolayer zone colored in cyan in Figure 10 ). Cell verticalization has been observed experimentally for Vibrio parahaemolyticus ( Enos-Berlage and McCarter, 2000 ) and for Vibrio Cholerae ( Beroz et al., 2018 ; Yan et al., 2016 ). In both cases, vertical orientations could be seen already for very small bacterial colonies, possibly due to their production of extracellular polysaccharide substance (EPS). In this work, verticalization is predicted to occur for plain bacterial colonies as well, without the need of any EPS, but at much larger colony sizes. We have not been able to observe verticalization directly for our colonies due to multiple scattering associated with very dense colonies we are studying. This is left as a challenge for future studies. In our model, verticalization results from an interplay among colony surface tension, cell-agar friction and the physical force of expansion due to cell growth. ( Beroz et al., 2018 ) also introduced a discrete model to describe cell verticalization. In their model, verticalization resulted from a similar mechanical instability due to the interplay between in-plane compression force and cell-agar adhesion. Due to the different energy barriers against verticalization, the length scales of verticalization between our model and that of ( Beroz et al., 2018 ) are very different: The colonies in Beroz et al. spread very slowly radially ( ~ 3 μ m / h ), and verticalization occurs at a colony radius of ~ 5 - 10 μ m . Colonies in our model spread much faster ( ~ 14 μ m / h ), and substantial verticalization occurs at a radius of ~ 250 μ m ; see Figure 4—figure supplement 2 . Although we have restricted our study to colonies growing in rather simple conditions, insight from our model can be readily used to make qualitative predictions in a variety of other conditions. Generally, we expect the radial expansion speed to be controlled by the buckling width and vertical expansion speed be controlled by the thickness of the growth zone. Thus, if agar hardness or ambient humidity is changed, the effect on air-liquid surface tension is expected to affect the buckling width and the ratio of the radial and vertical expansion speeds, hence changing the colony aspect ratio. Also, during later stages of colony growth when oxygen becomes limiting in the colony interior, the obligatory excretion of large amounts of fermentation product associated with anaerobiosis is predicted to lower the pH in colony interior and thereby slow down vertical colony growth while not affecting the radial growth. Our observations shown in Figure 1H and Figure 1—figure supplement 1 are in qualitative agreement with the expectation. A quantitative study of this late regime ( t > 24 h for the growth condition used in Figure 1H ) requires a much more detailed model of anaerobic metabolism, pH effect, and growth transition kinetics, well beyond the scope of the current study, and will be reported elsewhere. Note that recent series of colony-based microbial range expansion studies ( Hallatschek et al., 2007 ; Hallatschek and Nelson, 2010 ; Korolev et al., 2012 ), which involve much larger colony sizes and longer periods of colony growth, are likely in this late regime where vertical growth has ceased. Nevertheless, the radial expansion of these large colonies may still be governed by the same factors discussed in this work. While our work is exclusively on bacterial colonies without EPS, key results we learned from this study shed light on the more complex dynamics of heterogeneous biofilms. First, we establish that the radial growth of our colonies is not limited by nutrient as commonly believed, but by the interplay of surface tension and cell-agar friction ( Figure 9 ). Given that biofilms have typically much lower bacterial densities, nutrient limitation will be even less of a problem. Also, EPS secreted by the bacteria could modify both the surface tension and cell-agar friction to control the radial expansion speed. Second, nutrient supply is limiting for the vertical growth of our colonies ( Figure 9AC ). This becomes less of a problem for the loosely packed biofilms. Moreover, biofilms are said to form channels in their interior ( Wilking et al., 2013 ), which would further alleviate the supply of nutrient, thereby allowing for faster vertical expansion. Finally, verticalization of cells in the interior, which is important for vertical growth but occurs at rather large colony sizes according to our model ( Figure 4—figure supplement 1 ), also occurs in biofilms but at much smaller colony sizes ( Beroz et al., 2018 ; Enos-Berlage and McCarter, 2000 ; Yan et al., 2016 ). While the precise nature of the forces driving verticalization may be different in the two cases, the underlying origins may be similar — mechanical instability due to in-plane compression resulting from colony expansion and cell-agar friction. In light of these comparisons, we see that the additional ingredients provided by biofilms enable the colonies to expand faster both horizontally and vertically. The model presented here, with results quantitatively comparable to experimental data, can be used to interpret large-scale data being generated by high-throughput colony growth assays to track the growth of different strains in different conditions ( Takeuchi et al., 2014 ). Our model can be used as a launching pad, not only to include the more complex effects of metabolism and cell growth mentioned here, but also other factors such as extracellular matrix to allow the simulation of biofilms, and multiple interacting species to explore microbial ecology in compact space. Finally, it will be an interesting challenge to develop coarse-grained hydrodynamic models that incorporate the unique features of surface tension and dynamic friction discussed here, and capture the radial and vertical colony growth characteristics, both their temporal behaviors and their dependences on cell growth rates and other environmental factors."
} | 5,117 |
31579631 | PMC6768060 | pmc | 4,003 | {
"abstract": "Background Heliopora coerulea , the blue coral, is a reef building octocoral that is reported to have a higher optimum temperature for growth compared to most scleractinian corals. This octocoral has been observed to grow over both live and dead scleractinians and to dominate certain reefs in the Indo-Pacific region. The molecular mechanisms underlying the ability of H. coerulea to tolerate warmer seawater temperatures and to effectively compete for space on the substrate remain to be elucidated. Methods In this study, we subjected H. coerulea colonies to various temperatures for up to 3 weeks. The growth and photosynthetic efficiency rates of the coral colonies were measured. We then conducted pairwise comparisons of gene expression among the different coral tissue regions to identify genes and pathways that are expressed under different temperature conditions. Results A horizontal growth rate of 1.13 ± 0.25 mm per week was observed for corals subjected to 28 or 31 °C. This growth rate was significantly higher compared to corals exposed at 26 °C. This new growth was characterized by the extension of whitish tissue at the edges of the colony and was enriched for a matrix metallopeptidase, a calcium and integrin binding protein, and other transcripts with unknown function. Tissues at the growth margin and the adjacent calcified encrusting region were enriched for transcripts related to proline and riboflavin metabolism, nitrogen utilization, and organic cation transport. The calcified digitate regions, on the other hand, were enriched for transcripts encoding proteins involved in cell-matrix adhesion, translation, receptor-mediated endocytosis, photosynthesis, and ion transport. Functions related to lipid biosynthesis, extracellular matrix formation, cell migration, and oxidation-reduction processes were enriched at the growth margin in corals subjected for 3 weeks to 28 or 31 °C relative to corals at 26 °C. In the digitate region of the coral, transcripts encoding proteins that protect against oxidative stress, modify cell membrane composition, and mediate intercellular signaling pathways were enriched after just 24 h of exposure to 31 °C compared to corals at 28 °C. The overall downregulation of gene expression observed after 3 weeks of sustained exposure to 31 °C is likely compensated by symbiont metabolism. Discussion These findings reveal that the different regions of H. coerulea have variable gene expression profiles and responses to temperature variation. Under warmer conditions, the blue coral invests cellular resources toward extracellular matrix formation and cellular migration at the colony margins, which may promote rapid tissue growth and extension. This mechanism enables the coral to colonize adjacent reef substrates and successfully overgrow slower growing scleractinian corals that may already be more vulnerable to warming ocean waters.",
"conclusion": "Conclusions Continued warming of the oceans has resulted in declining coral growth and calcification rates ( Cantin et al., 2010 ; Cooper et al., 2008 ). Under present and future ocean scenarios, only corals with a high thermal resistance, rapid growth, and low mortality are likely to persist ( Edmunds et al., 2014 ). The ability of H. coerulea to rapidly grow over substrates under warmer seawater conditions allow it to outcompete slower-growing reef organisms for benthic space. This may have contributed to the present-day dominance of the blue coral at the study site in the Bolinao-Anda Reef Complex in northwestern Philippines. Other factors, such as a reduction in coral recruitment or an increase in the mortality of other corals, may have also contributed to changes in coral community structure at the study site. Although the persistence of H. coerulea may compensate for some ecosystem functions that are lost due to the decline of scleractinians ( Richards et al., 2018 ), the long-term impact of H. coerulea dominance on other reef-associated marine organisms remains to be determined. Competition with H. coerulea can negatively affect the growth, fecundity, and survival of other coral species ( Romano, 1990 ). H. coerulea may also inhibit scleractinian coral recruitment through allelopathy or other mechanisms ( Atrigenio, Aliño & Conaco, 2017 ). Moreover, H. coerulea may have a different calcification rate that could limit its ability to contribute to reef growth ( Perry et al., 2015 ). Further studies are needed to investigate the tolerance limits of H. coerulea to temperature, as well as to other local stressors, such as salinity shifts and eutrophication. It would also be important to examine the interactions of the blue coral with other reef biota to understand how its dominance may ultimately affect reef biodiversity.",
"introduction": "Introduction The increasing scale and frequency of mass coral bleaching events linked with unusually warm water has greatly contributed to the decline of coral cover across the globe. Since the 1980s, rising sea surface temperatures have resulted in three pan-tropical bleaching events in 1998, 2010 and 2015–2016 ( Heron et al., 2016 ). Recent reports showed that even the most highly protected reefs are not resistant to extreme heat stress ( Hughes et al., 2017 ). Recurrent bleaching leads to less recovery time for corals and, as a consequence, the community structure on some reefs has changed dramatically ( Hughes et al., 2017 , 2018 ). If severe bleaching events continue, it is predicted that only 10% of the world’s coral reefs will survive beyond 2050 ( Heron et al., 2016 ). Nevertheless, it has become increasingly evident that coral susceptibility and resilience to bleaching is highly variable ( Grottoli et al., 2014 ; Guest et al., 2012 ; Marshall & Baird, 2000 ; Sampayo et al., 2008 ). Coral genera that are able to withstand or recover from heat stress can repopulate affected reef areas and drive changes in coral reef community structure ( Edmunds et al., 2014 ; Hoegh-Guldberg et al., 2007 ; Mumby & Van Woesik, 2014 ). Corals that are able to tolerate stressors or survive bleaching events are valuable models for revealing the mechanisms underlying differences in resilience ( Van Oppen et al., 2015 ). Analysis of gene expression through transcriptome sequencing provides a means to evaluate the contribution of phenotypic plasticity and local adaptation to the coral environmental response ( Kenkel & Matz, 2016 ). Transcriptome sequencing approaches have revealed high levels of gene expression variation in adult corals from different environments ( Barshis et al., 2013 ; Maor-Landaw et al., 2017 ), as well as altered expression for many coral genes in response to temperature stress ( Bellantuono, Hoegh-Guldberg & Rodriguez-Lanetty, 2011 ; DeSalvo et al., 2008 , 2010a ; Kaniewska et al., 2015 ; Parkinson et al., 2015 ; Seneca & Palumbi, 2015 ). Most of these differentially expressed transcripts were derived from the host coral, with only a small proportion originating from the dinoflagellate symbionts ( Barshis et al., 2013 ; Parkinson et al., 2018 ). Coexpression of genes that function within similar cellular pathways reveal processes that are critical for mounting the coral stress response ( Bay & Palumbi, 2017 ; Rose, Seneca & Palumbi, 2015 ). Although transcriptome responses vary by species and treatment regime, common biological functions that have been found to be responsive to temperature conditions include protein folding chaperones, removal of damaged macromolecules, redox signaling, apoptosis, calcium homeostasis, and modifications to the actin cytoskeleton and extracellular matrix ( DeSalvo et al., 2010a ; Kaniewska et al., 2015 ; Meyer, Aglyamova & Matz, 2011 ; Parkinson et al., 2015 ; Seneca & Palumbi, 2015 ). Resilient corals typically expressed higher levels of thermal tolerance genes, particularly heat shock proteins, antioxidant enzymes, apoptosis regulators, tumor suppressors, innate immune response genes, and cell adhesion molecules ( Barshis et al., 2013 ). It should be noted that most of these studies have been conducted on scleractinian corals, with limited reports for octocorals ( Pratlong et al., 2015 ; Sammarco & Strychar, 2013 ). Transcriptome sequencing of alcyonacean octocorals, such as Gorgonia ventalina and Corallium rubrum , revealed expression of immune response genes related to pattern recognition, anti-microbial peptides, and wound repair in response to pathogen exposure ( Burge et al., 2013 ), as well as gene expression signatures of thermal adaptation ( Pratlong et al., 2015 ). The reef-building octocoral Heliopora coerulea is an example of a coral species that survives bleaching events better than most scleractinian corals. Commonly known as the blue coral, H. coerulea is thought to be highly resistant to temperature stress and bleaching ( Harii et al., 2002 ; Kayanne et al., 2002 ; Richards et al., 2018 ). This coral exhibits considerable morphological plasticity with laminar and digitate forms ( Villanueva, 2016 ; Yasuda et al., 2014 ), as well as an encrusting form that is observed along colony margins. In contrast, H. hiberniana , a newly described Heliopora species from north Western Australia, has a distinctive slender branching growth form with a white skeleton ( Richards et al., 2018 ). Heliopora coerulea is found in the Indo-Western Pacific region between 25°N and 25°S ( Zann & Bolton, 1985 ). Specifically, H. coerulea thrives in waters with a mean annual minimum temperature above 22 °C, which is considerably higher than the 18 °C marginal isotherm for many corals ( Zann & Bolton, 1985 ). Recently, the northernmost populations of H. coerulea have been discovered in Tsukazaki, Japan where the lowest temperature is around 18 °C ( Nakabayashi et al., 2017 ). H. coerulea can dominate large reef areas although, in most cases, its colonies are patchily distributed due to its short larval duration ( Atrigenio, Aliño & Conaco, 2017 ; Harii et al., 2002 ). It has also been observed that adult H. coerulea can inhibit the settlement of other scleractinian larvae in its vicinity ( Atrigenio, Aliño & Conaco, 2017 ). In the Bolinao-Anda Reef Complex in northwestern Philippines facing the South China Sea, H. coerulea coral cover has increased from just 1% in the 1990s to about 50% after 20 years ( Atrigenio, 1995 ; Vergara, 2009 ), during which time two mass bleaching events were reported ( Arceo et al., 2001 ; Shaish et al., 2010 ). The increasing prevalence of H. coerulea coincides with rising sea surface temperature in the South China Sea region, which was estimated at 0.50 ± 0.26 °C per decade from 1993–2003 ( Fang et al., 2006 ) and 0.31 °C per decade from 2003–2017 ( Yu et al., 2019 ) based on high-resolution satellite data. The ability of H. coerulea to compete for space on the reef may be attributed to various factors, chief among which could be resistance to environmental stressors affecting the area, which include temperature variability ( Penaflor et al., 2009 ), reduced salinity ( Cardenas et al., 2010 ), and eutrophication ( Ferrera et al., 2016 ). However, little is known about how these factors influence the growth of H. coerulea . Furthermore, no studies have yet been conducted to examine gene expression dynamics in this coral under different temperature conditions. To understand the molecular mechanisms governing the response of H. coerulea to varied temperatures, we observed the growth rate of the coral at temperatures spanning the typical range experienced at the study site. We then analyzed changes in the patterns of gene expression both in the coral host and its symbionts. The findings of this study reveal the underlying processes that control the rapid growth of H. coerulea over the reef.",
"discussion": "Discussion Heliopora coerulea can tolerate prolonged exposure of up to 3 weeks to conditions approximating the mean summer temperature at the site. Blue coral colonies did not show any obvious signs of bleaching stress in the form of tissue whitening and necrosis or tissue sloughing throughout the entire duration of the experiments. Results of the controlled temperature experiments were supported by field observations that showed less prevalence of bleaching for H. coerulea colonies compared to scleractinian corals in the same area. Similar observations on the bleaching resistance of H. coerulea have been reported by other groups ( Harii et al., 2002 , 2014 ; Kayanne et al., 2002 ; Richards et al., 2018 ; Shaish et al., 2010 ). Heliopora coerulea colonies were observed to grow faster over substrate when subjected to warm temperatures (28 or 31 °C) than when exposed to cold (26 °C), both in situ and in aquaria with controlled seawater temperature. Corals subjected to 26 °C revealed low or negative growth at the margins, suggesting loss or shrinkage of living tissue. This suggests that the distribution of H. coerulea may be limited by its apparent susceptibility to cooler temperatures, although more studies are needed to investigate the cold tolerance limits of this species. The average in situ horizontal growth rate of H. coerulea was 0.41 ± 0.18 mm per week (approximately 21 mm per year) and could reach 0.65–0.72 mm per week during the warmest months of the year. These rates of growth are greater than what has been reported for massive Porites (about 0.20 per week or approximately 10 mm per year) ( Lough & Barnes, 2000 ). In the eastern Pacific, growth rates ranging from 13.9 to 19.3 mm per year were reported for the encrusting growth form of Porites lobata , although this rapid growth was shown to correlate only with longer light period and higher salinity but not with differences in temperature ( Guzmán & Cortés, 1989 ). The correlation between H. coerulea growth and temperature suggests that, under future ocean conditions where temperatures may increase by 1.2–3.2 °C ( IPCC, 2014 ), H. coerulea will have the advantage over slower-growing scleractinians in colonizing available reef substratum. Coral growth and mineralization is biologically controlled and involves cycles of extension and skeletal thickening ( Cuif & Dauphin, 2005 ). Extension is the secretion of a mineralizing matrix consisting of a mixture of proteins, polysaccharides, and glycoproteins, while skeletal thickening is the crystallization of mineral material onto the organic framework. The spatial organization of the organic framework upon which calcification occurs is determined by cell-cell and cell-substrate adhesion mediated by the extracellular matrix, which contains collagen and cadherins ( Helman et al., 2008 ; Mass et al., 2014 ). Cytoskeletal components, such as actin, control cell shape and are important for vesicular transport and cellular movement ( Svitkina, 2018 ). Thus, differential activation of growth and mineralization processes in corals can be inferred through comparative transcriptome profiling across different tissue regions or across different treatment conditions. Transcriptome analysis revealed that the vertical digitate and horizontal extension regions of the coral exhibit very different expression profiles. However, these tissues show an enrichment of symbiont-related functions, such as photosynthesis, carbohydrate metabolism, nitrogen utilization, superoxide metabolic process, and ATP synthesis, suggesting that symbiont metabolism is active throughout the coral. In the vertical region, enrichment of calcium ion transport and iron ion sequestration functions may be related to calcification of the blue-pigmented H. coerulea skeleton. Some transcripts encoding enzymes for the synthesis of the blue pigment, biliverdin IXα ( Hongo, Yasuda & Nagai, 2017 ), were relatively more abundant in the vertical region of the coral. Enrichment of chitin metabolism in the vertical region indicates its importance in formation of the coral skeleton. Chitin, along with other sulfur-containing proteins, has been shown by Raman spectroscopy to form part of the organic matrix that controls aragonite crystal size, shape, and orientation in the fibers of the H. coerulea skeleton ( Zhang et al., 2011 ). Tissues at the H. coerulea growth margin were enriched for transcripts that may enhance cell migration. For example, the matrix metallopeptidase with hemopexin domains has been reported to promote cell migration through a non-proteolytic mechanism in epithelial cells ( Dufour et al., 2008 ). The CIB protein, on the other hand, is known to positively regulate cell migration and focal adhesion complex formation ( Naik & Naik, 2011 ). Furthermore, upon exposure to warmer temperatures, transcripts encoding proteins with roles in extracellular matrix formation were upregulated, including peroxidasin and fibrillar collagen. Peroxidasin is an oxidative stress response gene that is often reported as differentially expressed in many coral heat stress studies ( Barshis et al., 2013 ; Louis et al., 2017 ; Voolstra et al., 2011 ). In myofibroblasts, peroxidasin is secreted into the extracellular space where it helps form the extracellular matrix as a means of wound repair and tissue fibrosis ( Peterfi et al., 2009 ). Peroxidasin has also been reported to be strongly upregulated during symbiont colonization of coral tissue ( Yuyama et al., 2018 ). Fibrillar collagens, on the other hand, provide mechanical strength and stability to tissues. The unique arrangement of fibrillar collagens in octocorals is an important hydroskeleton structure to support soft coral tissues ( Orgel et al., 2017 ). This suggests that warmer temperature may promote the production of proteins required for the extracellular matrix and cell migration at colony margins. The organic matrix laid down by migrating cells at the colony margin serves to promote nucleation of aragonite crystals that eventually build up its massive skeleton. The ability to shift from one form to another in order to compete for substrate has been previously observed in the scleractinian coral, Montipora aequituberculata , which can overgrow the sponge, Terpios hoshinota , by shifting from foliose to encrusting morphology ( Elliott et al., 2015 ). Interestingly, genome sequencing of Montipora capitata , a coral that also exhibits an encrusting morphology at its base, revealed enrichment for functions related to proteinaceous extracellular matrix, collagen trimer, and cell-matrix adhesion in the set of genes under diversifying selection ( Shumaker et al., 2019 ). Proliferation of the encrusting or plating growth form of some corals may eventually lead to reduction of reef rugosity and complexity ( Magel et al., 2019 ). Upregulation of transcripts encoding proteins involved in the extracellular matrix, cytoskeleton, and cell migration or morphogenesis has been reported in other scleractinian corals subjected to elevated temperature conditions, although these studies did not look specifically at transcripts expressed at colony growth margins. Upregulation of extracellular matrix genes were observed in Acropora palmata subjected to 2 °C above ambient for 24–48 h ( DeSalvo et al., 2010b ), as well as in A. hyacinthus subjected to 4 °C above ambient for 5 or 20 h ( Seneca & Palumbi, 2015 ). However, in contrast to the upregulation of collagens at the growth margin of H. coerulea subjected to 28 to 31 °C for 3 weeks, collagen transcripts were downregulated in heat-stressed A. hyacinthus ( Seneca & Palumbi, 2015 ). In addition, enrichment of functions related to translation, adhaerens junction, cytoskeleton, and morphogenesis were observed in Stylophora pistillata exposed to 2 °C above ambient for 1 week ( Maor-Landaw et al., 2017 ). On the other hand, decreased cytoskeletal and cell adhesion functions were reported in Montastrea faveolata subjected to 3 °C above ambient for up to 9 days ( DeSalvo et al., 2008 ). Similarly, Galaxea fascicularis subjected to 7 °C above ambient for 18 h showed downregulation of transcripts involved in the regulation of cell migration and cell morphogenesis ( Hou et al., 2018 ). In these latter two studies, the downregulation of cytoskeleton, cell adhesion, and cell migration functions may be linked to tissue damage and visible coral bleaching. It should be noted, however, that the differences in gene expression response reported in these studies may be due to the different treatment conditions that were used. Further studies that apply similar conditions, approximating either natural temperature maxima or bleaching thresholds, to investigate the differential response of diverse coral species are warranted. The calcified digitate tissues of H. coerulea exhibited a diverse gene expression profile, with enrichment for genes that function in translation, cell-matrix adhesion, oxidation-reduction processes, photosynthesis, carbohydrate metabolic process, and calcium and iron ion transport. This indicates that calcified tissues of the coral are invested in energy generation and biomineralization, with photosynthetic activity of the symbionts playing a central role. It is likely that the enrichment of oxidative response genes in calcified coral tissues is a mechanism to counteract the negative effects of reactive oxygen species generated by the photosynthetic activity of the symbionts ( Baird et al., 2009 ). Short-term exposure (24 h) to 31 °C resulted in upregulation of transcripts encoding peptides involved in oxidation-reduction, carbohydrate metabolic processes, cholesterol transport, and neuropeptide signaling. These changes suggest that short term fluctuations in temperature may trigger signaling cascades that induce expression of transcripts encoding proteins that protect against oxidative stress, modify cell membrane composition, and mediate intercellular signaling pathways that potentially modify coral behavior. Upregulation of protective oxidation-reduction enzymes and signaling pathways is consistent with observations in other corals subjected to heat stress ( Barshis et al., 2013 ; DeSalvo et al., 2008 ; Seneca & Palumbi, 2015 ). Three weeks of exposure to 31 °C resulted in a global decline in gene expression, as demonstrated by the downregulation of thousands of transcripts. This effect may be attributed to the reallocation of energy towards activation of other cellular pathways, the elevated cost of basal metabolism, and inhibition of pathways for energy generation as the organism nears its thermal tolerance limits ( Kaniewska et al., 2015 ; Sokolova, 2013 ). Nevertheless, we observed upregulation of some transcripts involved in immune response, protein catabolism and vesicle exocytosis, which may be linked to cellular repair mechanisms that are induced by protein denaturation under warmer conditions. Sustained exposure to 31 °C also resulted in upregulation of metabolic functions that originate from the symbionts, such as tricarboxylic acid cycle. This suggests that symbiont functions remained intact under the treatment conditions, which is supported by the lack of significant change in photosynthetic efficiency. In fact, only a few symbiont sequences showed significant transcriptional response to 31 °C in H. coerulea and a greater proportion (7.07%) were found in the upregulated set as compared to the downregulated set of transcripts (0.58%). This is in agreement with other reports indicating that stress triggers a greater shift in gene expression in the coral host rather than in the symbionts in hospite due to a host buffering effect ( Barshis et al., 2014 ; Leggat et al., 2011 ). Taken together, our results revealed that H. coerulea is able to withstand temperatures of up to 31 °C. Although sustained exposure to this condition resulted in a general decline in gene expression, coral symbionts appeared to remain functional. This suggests that they continue to provide energy to the coral host and thus support the rapid tissue extension that is observed at colony margins. Horizontal growth of the blue coral colony was correlated with enhanced expression of cell matrix, cytoskeleton, and cell migration transcripts at the growth margins. By prioritizing tissue growth and colony margin extension, the blue coral can continue to colonize substrate even under conditions that may be stressful to many scleractinian corals. Whether this enhanced growth is sustained at temperatures above 31 °C warrants further studies."
} | 6,109 |
33290393 | PMC7723297 | pmc | 4,005 | {
"abstract": "Gram-negative bacteria, as well as some Gram-positive bacteria, possess hair-like appendages known as fimbriae, which play an important role in adhesion of the bacteria to surfaces or to other bacteria. Unlike the sex pili or flagellum, the fimbriae are quite numerous, with of order 1000 fimbriae appendages per bacterial cell. In this paper, a recently developed hybrid model for bacterial biofilms is used to examine the role of fimbriae tension force on the mechanics of bacterial biofilms. Each bacterial cell is represented in this model by a spherocylindrical particle, which interact with each other through collision, adhesion, lubrication force, and fimbrial force. The bacterial cells absorb water and nutrients and produce extracellular polymeric substance (EPS). The flow of water and EPS, and nutrient diffusion within these substances, is computed using a continuum model that accounts for important effects such as osmotic pressure gradient, drag force on the bacterial cells, and viscous shear. The fimbrial force is modeled using an outer spherocylinder capsule around each cell, which can transmit tensile forces to neighboring cells with which the fimbriae capsule collides. We find that the biofilm structure during the growth process is dominated by a balance between outward drag force on the cells due to the EPS flow away from the bacterial colony and the inward tensile fimbrial force acting on chains of cells connected by adhesive fimbriae appendages. The fimbrial force also introduces a large rotational motion of the cells and disrupts cell alignment caused by viscous torque imposed by the EPS flow. The current paper characterizes the competing effects of EPS drag and fimbrial force using a series of computations with different values of the ratio of EPS to bacterial cell production rate and different numbers of fimbriae per cell.",
"conclusion": "Conclusions A hybrid computational method was developed for biofilm growth with cells of either spherical and rod-like (spherocylindrical) shapes. The model utilizes continuum mixture theory to simulate the different flow fields of water and EPS (as well as diffusion of nutrients, minerals and other chemicals through the water), while employing an adhesive discrete-element method to resolve interactions between individual bacterial cells. The continuum approach for water and EPS allows us to account for the important influences of osmotic pressure gradient, EPS viscous shear and EPS-water interfacial force, while the discrete simulation of individual cells allows us to incorporate important forces acting on the cells from drag due to motion of the cells relative to the EPS and as well as from forces such as lubrication, collision and adhesion forces between nearby cells. Of particular focus in the current paper is the fimbrial force, in which the hair-like fimbriae appendages of one cell attach to a neighboring cell and exert a tensile force, as well as a related torque, on each attached cell. The fimbrial force is well known from experimental investigations to be of critical importance for biofilm development, but the role of fimbrial force on biofilm structural development has not been studied to date in the computational literature. We report on two related series of simulations designed to illuminate the competing influence of EPS drag and fimbrial force on a growing biofilm bacterial colony. The first computational set examines the significance of EPS flow on the bacterial colony by varying the ratio M ˙ E / M ˙ B of EPS to bacterial production rate from 0 to 8. The bacterial colony is observed to transition from a single tightly-packed colony for small values of this ratio to an asymmetric structure with multiple nodes (or clusters) of cells, connected by thinner strands, for large values of this ratio. The second set of computations was designed to investigate the significance of fimbrial force for cases with relatively large values of M ˙ E / M ˙ B , by varying the number of fimbriae per cell from n fim = 0 to 5000. These computations illustrate well the important role of the fimbriae in holding the bacterial colony together. With no fimbriae, the colony breaks up into small clusters of cells attached to each other by van der Waals surface adhesion, where all of these clusters are suspended in the biofilm by the EPS. As the fimbriae number is increased, these individual cell clusters coalesce into a single agglomerate. Comparing with other simulation studies, our model captures the key advantages of both discrete and continuous biofilm growth models. It captures the effects of EPS osmotic spreading of biofilms under different growth rate ratios, as reported by Seminara et al. [ 41 ] and Yan et al. [ 83 ], and it reduces to a model similar to that Cogan & Keener [ 39 ] when the bacteria are restricted to move with the EPS. In the discrete part of the model, it confirms that cell number in a biofilm is a key parameter affecting colony structure. As the total cell number increases, both the number of cell contacts and the cell orientation match the qualitative trend described in experimental studies [ 81 ]. We have demonstrated that varying local interaction between individual cells, such as the total fimbriae number and EPS growth rate, can lead to qualitative change in the structural form of the bacterial colony. The overall shape of the bacterial colony observed in our simulations is similar to that noted in a number of other experimental studies [ 43 , 49 ] and numerical analyses [ 34 , 37 , 42 ]. The current paper demonstrates that fimbrial force and cell drag associated with EPS production (and related relative flow of EPS past the cells) are significant effects that oppose each other during biofilm bacterial colony development. The ultimate structural form of a colony is largely dependent on the balance between these two competing effects.",
"introduction": "Introduction In bacterial biofilms, bacteria are enmeshed in a self-secreted extracellular polymeric substance (EPS), which is permeated by an aqueous solvent that transports nutrients, minerals and other chemicals through the EPS [ 1 ]. In general, bacteria absorb nutrients and water, using them to grow and to produce EPS. [The water within the biofilm exists in a bound state (i.e., water of hydration associated with the EPS) or in a free state that can flow through the biofilm. For modeling purposes, we regard the former as part of the EPS, and use the term 'water' to refer to water in the latter (free) state.] Bacterial biofilms are important in water treatment processes [ 2 ], in environmental processes such as production of greenhouse gases from the soil [ 3 ], in biofouling of ships and marine structures [ 4 ], and in food processing [ 5 , 6 ]. Biofilms are responsible for the majority of human infectious diseases [ 7 , 8 ], particularly in post-surgical infections or chronic infections. A key feature that enables adhesion of bacterial cells both to each other and to other surfaces is the short hair-like appendages called fimbriae (singular fimbria), which are found on most Gram-negative bacteria and on some Gram-positive bacteria [ 9 – 11 ]. (These appendages are also referred to in some literature as pili or attachment pili). There are on order of 1000 fimbriae on a single cell, each 3–10 nm thick and 1–5 μm long. At the microstructural level, a single fimbria appendage has the form of a coiled helix-shaped protein (pilin), with sticky proteins (adhesins) located on the fimbria tip. The adhesin proteins bind to receptors on other bacteria or on host cells using a 'catch-bond' mechanism, in which the adhesive force becomes stronger (up to a limit) as the tension force acting on a fimbria is increased [ 12 , 13 ]. Once attached, a fimbria can stretch to several times its original length. Experiments characterizing the stress-strain behavior of individual fimbria were reported by Chen et al. [ 14 ] and Forero et al. [ 15 ]. Numerous experimental studies have demonstrated that different types of fimbriae play a critical role in enabling certain bacteria to form biofilms, although the enhancement of bacterial attachment ability and biofilm growth is dependent on both the type of bacteria and the type of fimbriae [ 16 ]. For instance, type 3 fimbriae were found to strongly promote biofilm formation for Klebsiella pneumoniae [ 17 – 20 ]. Bak et al. [ 21 ], Zuberi et al. [ 22 ], and Lasaro et al. [ 23 ] showed that biofilm formation in Escherichia coli is inhibited when type 1 fimbriae are suppressed. Rodrigues and Elimelech [ 24 ] and Wang et al. [ 25 ] examined role of type 1 fimbriae for biofilm formation of E . coli , with fimbriaed, non-fimbriaed and wild bacteria. They found that type 1 fimbriae are not necessary for initial reversible cell attachment, but that they are necessary for irreversible cell attachment and subsequent biofilm development. Cohen et al. [ 26 ] showed that presence of fimbriae enhances aggregation of E . coli with small clay particles. McLay et al. [ 27 ] gradually varied the degree of fimbriation (by varying the number of fimbriae attached to the cells), and showed that the ability of cells to adhere gradually decreases as the degree of fimbriation is decreased. Understanding the dynamics of biofilm systems is challenging because of the large number of parameters involved and the highly nonlinear, complex dynamics exhibited by biofilm systems. Mathematical modeling allows investigators to easily activate and deactivate different biofilm features to gain insight into their impact on the system [ 28 , 29 ]. Both discrete and continuum models have been developed and applied to biofilm systems, both with different advantages and disadvantages [ 30 – 38 ]. Continuum models treat bacteria, EPS and water as interacting continua, for each of which there is an associated continuous concentration and velocity field and related mass and momentum conservation equations [ 35 – 37 , 39 – 41 ]. Discrete models treat biofilms as a collection of individual ‘agents’ (or particles) that interact with each other, with the surface to which the biofilm is attached, and with other surrounding biofilm components (such as EPS and water). With discrete models, it is a simple matter to assign properties, shapes, and behaviors to individual bacteria and then allow the model to determine how these characteristics lead to different collective (emergent) behavior of the biofilm system [ 31 – 34 , 38 , 42 , 43 ]. However, most continuum models do not account for the numerous forces acting between individual bacterial cells, whereas most discrete models (also known as individual based models ) do not account for the separate flow fields of water and EPS past the cells. Both of these types of models tend to over-simplify the cell interaction forces, often omitting important forces for the biofilm dynamics. A new type of hybrid model was recently developed by the current investigators [ 44 ] which surmounts many of these objections. The model uses a discrete approach to follow motion and interaction of individual bacterial cells while using a continuum approach to model EPS, water and nutrient transport around and within the biofilm, including absorption of nutrients and water and EPS production by the bacteria. The continuum model is based on an extension of that of Cogan and Keener [ 39 ], with an improved model for the water-EPS interfacial force. The discrete model is based on an extension of an accurate discrete element method (DEM) for adhesive particle flows [ 45 – 47 ], and includes a wide range of cell-EPS and cell-cell forces and torques for both spherical [ 31 ] and spherocylindrical cell shapes [ 34 , 42 , 43 , 48 , 49 ]. The current paper extends the hybrid model of Jin et al. [ 44 ] to include fimbrial force and non-spherical bacterial cells, and then uses this extended model to examine the influence of fimbrial force and EPS flow on biofilm growth processes. We argue that of the many different forces present, the fimbriae tension and the EPS drag force dominate in determining the structure of the bacterial colony as it develops within the biofilm. The method section gives an overview of the biofilm growth model used in the study, including the continuum models for EPS and water transport and the discrete model for the bacterial cells. The results of the paper include an examination of the effects of varying the ratio of EPS to cell production rates and the number of fimbriae attached to each cell. Conclusions are given in the last section.",
"discussion": "Results and discussion The computations were performed in a cubic domain with 128 3 grid points and side length L = 100 μm. The computational domain extends in the horizontal directions from (−0.5,0.5) in x / L and z / L and in the vertical direction from (0,1) in y / L . The continuum equations were solved using a 'fluid' time step Δ t f = 100 s , and a multiple time-step procedure [ 45 ] was used for solution of the discrete equations with particle time step size Δ t p = Δ t f /50 and collision time step size Δ t c = Δ t p /50. A set of typical ranges and nominal values of a wide variety of parameters for bacterial biofilms is summarized in S1 Table . Dimensionless parameter values for the runs examined in the current paper are reported in Table 3 . Particles were assumed to be rod-shaped with semi-major and semi-minor axes a = 1 μm and b = 0.5 μm. All computations were initialized using a single seed bacterium placed at the center of the bottom surface of the computational domain. 10.1371/journal.pone.0243280.t003 Table 3 Dimensionless parameter values for different computational cases examined. Cases include the ratio M ˙ E / M ˙ B of EPS production rate to bacterial growth rate and the number n fim of fimbriae per bacterial cell. (Case A-4 is the same as Case B-3). Case M ˙ E / M ˙ B n fim A-1 0 1000 A-2 2 1000 A-3 4 1000 A-4 8 1000 B-1 8 0 B-2 8 100 B-3 8 1000 B-4 8 5000 Reference Case (A-2) A baseline computation (Case A-2) was conducted for a case with M ˙ E / M ˙ B = 2 and n fim = 1000, which is typical of common biofilm growth conditions. A bacterial colony grows from the seed cell in a roughly ball-like shape. Cross-sectional plots on the plane z = 0 are shown in Fig 2 at a time when the biofilm is well developed, showing the contour maps of the bacteria concentration α B , EPS concentration α E , water concentration α W , and nutrient mass concentration c S / c 0 . The bacterial colony forms a ball-like shape attached to the wall, with a higher concentration front near the outside of the ball where the nutrient and water availability is highest. Peak bacterial concentration is around 0.22 within the colony. The EPS is produced within the bacterial colony, but it is transported outward via both convection and diffusion, where iso-surfaces of the EPS concentration appear to have approximately hemispherical shapes. The EPS concentration approaches 0.7 within the colony. The water concentration decreases from nearly unity outside of the colony to around 0.1 within the colony. This strong reduction in water concentration is due to absorption of water by the bacteria in order to grow and produce EPS. A similar absorption occurs for the nutrients; however, the nutrient concentration reduces to only about 90% of its ambient value within the colony. The amount of nutrients required to produce a given about of biomatter is determined by the 'yield coefficient' Y B S ≡ − M ˙ S / ( M ˙ B + M ˙ E ) , which was set equal to 0.1 in the current computations [ 64 , 65 ]. 10.1371/journal.pone.0243280.g002 Fig 2 Slice plots at z = 0 of the bacterial colony. Plots show volume fractions of (a) bacterial cells, (b) EPS, (c) water, and (d) nutrient concentration, for Case A-2 when the total number of cells is around 5000. (Only bottom half of computational domain is shown). The rate of production of new cell material and EPS is shown in Fig 3 . We see that both bacterial cell growth and EPS production are highest within a arched region near the outer surface of the colony, and that production M ˙ B and M ˙ E are both observed to decrease in the inner part of the colony due to shortage of both nutrients and water. The components of the EPS and water velocities are shown in Fig 4 . The EPS velocity is oriented outward from the bacterial colony, and acts to push both EPS and bacterial cells away from the colony center. The water velocity field is of larger magnitude than EPS and generally oriented inward toward the bacterial cells. from both the top and sides of the colony. 10.1371/journal.pone.0243280.g003 Fig 3 Slice plots at z = 0 showing the production rates (in ng/h). Plots show (a) bacterial cell ( m ˙ B ) and (b) EPS ( m ˙ E ) for Case A-2 when the total number of cells is around 5000. (Only bottom half of computational domain is shown). 10.1371/journal.pone.0243280.g004 Fig 4 Slice plots at z = 0 showing magnitude of velocity fields and velocity components in the x - and y -directions. Plots show (a) EPS velocity field and (b) water velocity field for Case A-2 when the total number of cells is around 5000. The velocity components in the x- and y- directions are shown as vectors, and velocity magnitude is represented by contour plot. (Only the bottom half of computational domain is shown). Sensitivity to EPS-to-bacteria production rate ratio The significance of EPS on the biofilm growth is dependent on the EPS-to-bacteria growth rate ratio, defined by M ˙ E / M ˙ B . Examples with values of this ratio ranging from about 0.2–4.5 were recorded for different types of biofilms in Refs. [ 78 – 80 ], although values outside of this range are not atypical. The larger the value of this ratio, the more EPS is produced and the higher is the value of the EPS velocity magnitude during biofilm growth. Increase in EPS velocity magnitude results in an increase in outward cell drag force, and hence an increased tendency for the biofilm to break up and disperse. This tendency can be seen in Fig 5 , which compares biofilm structure for three computations with M ˙ E / M ˙ B values of 2 (Case A-2), 4 (Case A-3) and 8 (Case A-4). All other parameters are set the same as in the reference case discussed in the previous section. The top row of the figure shows the locations and orientations of the bacterial cells at a time when the number of cells equals approximately 5000 in each case. The cells are colored based on cell size. The bottom row of the figure gives the iso-surface m ˙ E = 1 ng/h of the EPS production rate, with contour lines and colors to indicate the height above the y = 0 surface. For M ˙ E / M ˙ B = 2, the bacterial colony is compact with a nearly axisymmetric shape. As the value of M ˙ E / M ˙ B increases the colony becomes larger and more loosely structured, even though each run has the same number of cells at the time the figure was drawn. When M ˙ E / M ˙ B = 8, the colony symmetry is broken and it adopts a complex shape with multiple nodes (or clusters) of cells connected by thinner strands. 10.1371/journal.pone.0243280.g005 Fig 5 Comparison of bacterial colony structure for different values of M ˙ E / M ˙ B . Plots for cases (a) M ˙ E / M ˙ B = 2 (Case A-2), (b) M ˙ E / M ˙ B = 4 (Case A-3), and (c) M ˙ E / M ˙ B = 8 (Case A-4), are captured when the total number of cells is around 5000. Top: Bacterial cells colored by their sizes. Bottom: The iso-surfaces of the EPS production rate m ˙ E = 1 ng/h, with contour lines and colors to indicate the height above the y = 0 surface. A number of parameters characterizing the biofilm development are plotted in Fig 6 as functions of the number of cells in the bacterial colony. The data compared in this figure has values of M ˙ E / M ˙ B ranging from 0 to 8. Fig 6A shows the average number of contacts per bacterial cell, with fimbriae contacts indicated by solid lines and cell-cell surface contacts indicates by dashed lines. As might be expected, higher values of M ˙ E / M ˙ B result in fewer of both types of contacts, since the particles become more separated as this ratio increases. The porosity within the bacterial colony is plotted in Fig 6B , which was computed by dividing one minus the volume of all particles by the volume of all grid cells that contain a particle. The porosity is observed to significantly increase as M ˙ E / M ˙ B increases. When M ˙ E / M ˙ B is small, the average number of contacts increases with the total number of bacterial cells and the porosity decreases with the total number of bacterial cells, in agreemnt with the measurement in Ref. [ 81 ]. Fig 6C plots the minimum value of the nutrient concentration within the colony divided by the ambient concentration, or c S ,min / c 0 . The nutrient concentration within the bacterial colony is observed to decrease substantially with even a small amount of EPS production (between the M ˙ E / M ˙ B = 0 and 2 cases), and then not to change much with further increase in M ˙ E / M ˙ B . 10.1371/journal.pone.0243280.g006 Fig 6 Variation as a function of cell numbers of various diagnostic parameters. The ratio M ˙ E / M ˙ B for different cases are M ˙ E / M ˙ B = 0 (black, Case A-1), 2 (blue, Case A-2), 4 (green, Case A-3), and 8 (red, Case A-4). Plots show (a) average number of fimbriae contacts (solid curves) and direct surface contacts (dashed curves) per bacteria, (b) porosity within the bacterial colony, and (c) minimum value of nutrient concentration c S ,min / c 0 . Sensitivity to number of fimbriae per cell The role of fimbrial force on biofilm growth was examined using a series of computations in which the number of fimbriae per cell was increased in steps from 0 to 5000 (Cases B-1 thru B-4), with all other parameters being held the same. The computations were performed for a case with M ˙ E / M ˙ B = 8 , since we wanted to understand the effect of fimbrial force on the more loosely-structured biofilms typical of high EPS production rates. A comparison of the structure of the bacterial colony in the four computations at a time when the number of bacteria was approximately 5000 is shown in Fig 7 , showing both a perspective 3-D view of the bacterial cells and a 2-D slice of the contours of bacteria concentration α B in the z = 0 plane. These 2-D slices also show cells that lie within the region −0.01≤ z / L ≤0.01 surrounding the slice plane. This figure shows that increase in number of fimbriae causes several significant changes in the colony structure. In the case with no fimbriae (Case B-1), the colony has the shape of a slight compressed ball shape, extending to a height of Δ y / L = 0.39 and a width of Δ x / L = 0.47. The cells preferentially lie along the outer part of the colony, with a deficit in the bacteria concentration near the colony center. The cells themselves occur either in small clusters or singly, with neighboring cells having a strong tendency to align with each other. The addition of a small number of fimbriae in Case B-2 (with n fim = 100) causes the colony to flatten more, with the width increasing to Δ x / L = 0.6 while the height remains approximately the same. The colony becomes asymmetrical when the fimbriae number per cell is increases to 1000 (Case B-3) and the fimbriae are observed to cluster into a small number of tightly-packed groups. For the largest value of fimbriae number examined ( n fim = 5000), the colony condenses into a tightly-packed mushroom shape, with a narrow base and a broader 'head'. In this structure, there is very little alignment of nearby particles with each other, but instead particles appear to be nearly randomly oriented. 10.1371/journal.pone.0243280.g007 Fig 7 Comparison of bacterial colony structure for different values of fimbriae numbers per bacterial cell. Plots of cases (a) n fim = 0 (Case B-1), (b) n fim = 100 (Case B-2), (c) n fim = 1000 (Case B-3), and (d) n fim = 5000 (Case B-4), are captured when the total number of cells is around 5000. Top: Three-dimensional scatter plots with bacterial cells colored by their sizes. Bottom: Close-up slices in the z = 0 plane of the bacteria concentration α B . Particles shown in the lower plots lie in the region −0.01≤ z / L ≤0.01 surrounding the slice plane. Fig 8A plots the average fraction of fimbriae per cell that are attached to other cells against the number of cells in the bacterial colony. This number increases rapidly early in the computation, but then appears to flatten out, and in several cases seems to approach an asymptotic value of between 10–25%. The fraction of attached fimbriae increases significantly with increase in total number of fimbriae, which is consistent with the observation that the fimbrial force makes the colony more tightly packed together. In Fig 8B , the average tension of one fimbria attachment is plotted as a function of number of cells. After some initial transients, this measure appears to remain approximately constant at between 25–30% of the detachment tension T d . It is noted that from the values given in Table 1 for uncoiling fimbriae is T uc / T d = 0.46 and for coiling fimbriae is T c / T d = 0.19, so this result suggested that some fimbriae are in a coiling state and others are in an uncoiling state. 10.1371/journal.pone.0243280.g008 Fig 8 Plots showing diagnostics of fimbrial force as a function of number of bacterial cells. The numbers of fimbriae per bacterial cell for different cases are n fim = 100 (blue, Case B-2), 1000 (green, Case B-3), and 5000 (red, Case B-4). Plots show (a) average number of attached fimbriae per cell, (b) average fimbriae tension per cell. Measures of the bacterial colony structure are plotted in Fig 9 as functions of number of bacterial cells. A very significant increase is observed in the number of fimbriae contacts per cell in Fig 9A , which more than doubles as the number of fimbriae is increased from 100 to 5000. The number of cell surface contacts also increases substantially, indicative of the bacterial colony becoming tighter packed by the increasing fimbrial force as n fim increases. The bacterial colony porosity in Fig 9B decreases significantly as the number of fimbriae increases, again evidence that the cells within colony are becoming more tightly packed. In Fig 9C , we see that the minimum value of nutrient concentration is only slightly influenced by the number of fimbriae, suggesting that this parameter is primarily dependent on the number of cells and less sensitive to the colony structure. 10.1371/journal.pone.0243280.g009 Fig 9 Variation as a function of cell numbers of various diagnostic parameters. The numbers of fimbriae per bacterial cell for different cases are n fim = 0 (black, Case B-1), n fim = 100 (blue, Case B-2), n fim = 1000 (green, Case B-3), and n fim = 5000 (red, Case B-4). Plots show: (a) average number of fimbriae contacts (solid curves) and direct surface contacts (dashed curves) per bacteria, (b) porosity within the bacterial colony, and (c) minimum value of nutrient concentration c S ,min / c 0 . A number of orientation measures were introduced by Chesnutt and Marshall [ 82 ] for characterizing alignment of particles in a cluster. In particular, symmetry-axis-angle orientation measure O I was defined to relate the symmetry axis orientation of two contacting spheroidal particles, where O I = 0 indicates that the symmetry axes are perpendicular and O I = 1 indicates that the symmetry axes are parallel. Summing this measure over all contacting pairs of particles gives\n O I = 1 2 N T ∑ i = 1 N ∑ j = 1 N a i j | cos φ i j | , (26) \nwhere the a ij equals unity if the particles are touching and zero otherwise, N T is the number of touching particle pairs, and N is the number of particles. The time variation of O I is plotted as a function of number of bacterial cells in Fig 10A , and observed to be nearly constant as the biofilm grows. However, the value of O I decreases significantly as the number of fimbriae per cell is increased, changing from about 0.92 for the case with no fimbriae (Case B-1) to 0.56 for the case with n fim = 5000 (Case B-4). This parameter provides a quantitative measure of the degree of alignment of nearby cells, and the observed decrease in this measure with n fim is consistent with our previous qualitative observations that cells appear more randomly oriented and less aligned with each other as the fimbriae number increases. The reason for this behavior is that the fimbriae tension exerts a torque on cells in cases where the normal to the contact point of the fimbriae capsule with the cell surface does not pass through the cell center. This torque induces rapid rotation on a chain of particles that touch via the fimbriae connections, causing them to lose alignment with their neighboring particles. For all cases, O I increases with the total number of bacterial cells after the initial random state, which indicates that the local orientation ordering increases at large numbers of cells. This observation is confirmed in the experimental observation in Ref. [ 81 ]. 10.1371/journal.pone.0243280.g010 Fig 10 Variation as a function of cell numbers of two diagnostic parameters. The numbers of fimbriae per bacterial cell for different cases are n fim = 0 (black, Case B-1), n fim = 100 (blue, Case B-2), n fim = 1000 (green, Case B-3), and n fim = 5000 (red, Case B-4). Plots show (a) cell orientation parameter O I and (b) number of agglomerates N agg . Fig 10B plots the number of agglomerates composing the bacterial colony as a function of the number of cells. An agglomerate is defined as an assemblage of particles in which each particle is in contact with at least one other particle in the assemblage, such that a continuous path between any two particles in the assemblage can be traced passing through these connected particles. Fig 10B is based on cell-cell surface contact, and not fimbriae contact. For the case with no fimbriae, the number of agglomerates in the colony is observed to increase with cell number, increasing to approximately 1000 agglomerates by the end of the computation. This behavior is characteristic of a very loose colony formed of dispersed clusters of particles that are held together by the EPS. Inclusion of even a small number of fimbriae changes this structure abruptly. For instance, in the case with n fim = 100 (Case B-2), the colony is composed of a single agglomerate during the initial third of the computation, after which this agglomerate breaks up into 10–40 agglomerates during the latter two-thirds of the computation. For the case with n fim = 1000 (Case B-3), the colony intermittently breaks up into 2–3 agglomerates and then reforms into a single agglomerate. The case with n fim = 5000 (Case B-4) remains as a single agglomerate throughout the computation. Therefore, the local interaction between bacterial cells, such as fimbrial force, has significant influence on the structure and orientation of bacterial clusters, which is also reported for both experiments and modeling by Refs. [ 34 , 43 , 49 ]. Fig 11A and 11B show the long-time asymptotic value of porosity as a function of growth rate ratio M ˙ E / M ˙ B and number of fimbriae per bacterial cell. The porosity is observed to increase with increase in M ˙ E / M ˙ B as the EPS flow causes the bacterial colony to expand, and the porosity decreases with increase in the number of fimbriae per cell as the fimbrial force causes the colony to contract. The lines in Fig 11A and 11B represent best quadratic fits to the data. Fig 11C shows the long-time asymptotic value of fraction of fimbriae that are attached to other cells as a function of the number of fimbriae per cell. The line in this figure is a logarithmic best-fit curve. The fraction of fimbriae attached is observed to increase rapidly with total number of fimbriae when this number is relatively small, varying from about n fim = 0−1000, during which interval the colony is becoming increasingly compressed by the fimbrial force. As the total number of fimbriae becomes large, the elastic repulsion of the bacteria resist further compaction of the colony and the fraction of attached fimbriae is observed to be significantly less sensitive to changes in the total number of fimbriae. 10.1371/journal.pone.0243280.g011 Fig 11 Steady state values of different parameters under different conditions. Plots showing long-time asymptotic values of (a) porosity at different growth rate ratio M ˙ E / M ˙ B , (b) porosity at different numbers of fimbriae per bacterial cell, and (c) average fraction of attached fimbriae at different numbers of fimbriae per bacterial cell. Solid lines indicate best-fit curves of quadratic form in (a) and (b) and logarithmic form in (c)."
} | 8,248 |
40259044 | PMC12011931 | pmc | 4,007 | {
"abstract": "This review aims to examine microbial mechanisms for phosphorus (P) solubilization, assess the impacts of P mining and scarcity, and advocate for sustainable recycling strategies to enhance agricultural and environmental resilience. Phosphorus is an indispensable macronutrient for plant growth and agricultural productivity, yet its bioavailability in cultivation systems is often constrained. This scarcity has led to a heavy reliance on fertilizers derived from mined phosphate rock (PR), which is a finite resource usually contaminated with hazardous elements such as uranium, radium, and thorium. Plants absorb only about 10–20% of P from applied fertilizers, leading to significant inefficiencies and negative environmental consequences. Additionally, the uneven geographic distribution of PR reserves exacerbates global socioeconomic and geopolitical vulnerabilities. Healthy soils enriched with diverse microbial communities provide a sustainable avenue to address these growing challenges. Rhizospheric organisms, including phosphorus-solubilizing and phosphorus-mineralizing bacteria and arbuscular mycorrhizal fungi, are capable and pivotal in the sustainable conversion of inorganic and organic P into bioavailable forms, reducing reliance on synthetic fertilizers. The mechanisms used by these microbes often include releasing organic acids to lower soil pH and solubilize insoluble inorganic phosphorus compounds and the production of enzymes, such as phosphatases and phytases, to break down organic phosphorus compounds, including phytates, into bioavailable inorganic phosphate. Some microbes secrete chelating agents, such as siderophores, to bind metal ions and free phosphorus from insoluble complexes and use biofilms for P exchange. This review also advocates for the recycling second-generation P from organic waste as a sustainable and socially equitable alternative to conventional phosphate mining.",
"conclusion": "Conclusion Phosphorus is a crucial nutrient for plant growth and agricultural productivity, yet its management poses significant environmental challenges. The mining of PR, a non-renewable resource, is the primary means of obtaining P for agriculture, but it brings about habitat destruction, water pollution, and substantial energy consumption. Moreover, the finite nature of PR reserves raises concerns about the long-term sustainability of P supply for global agriculture. The use of mined P in agriculture often leads to low plant uptake efficiency, with a substantial portion of applied P immobilized in the soil. This immobilization contributes to P runoff into water bodies, causing eutrophication, algal blooms, and subsequent water quality degradation. Therefore, effective P management is imperative to minimize these environmental impacts and ensure agricultural sustainability. To address challenges associated with low plant uptake efficiency, P immobilization in soil, environmental impacts like eutrophication and algal blooms, water quality degradation, reliance on finite mined P resources, uneven global distribution of reserves, increased economic costs for farmers, and sustainability concerns, several sustainable P management strategies can be adopted. The strategy includes precision farming, nutrient management planning, development of P-efficient crop varieties, recycling P from organic waste streams (e.g., manure and crop residues), enhancing P bioavailability through microbial processes such as mineralization and mycorrhizal symbiosis, optimizing fertilizer application methods, and promoting struvite recovery from wastewater for use as a sustainable P source. Recycling P from organic waste streams, such as animal manure and crop residues, can reduce dependence on mined P and mitigate environmental impacts. The use of microbial processes, including microbial mineralization and mycorrhizal symbiosis, can enhance the bioavailability of P in soils, improving plant uptake efficiency and reducing the need for synthetic fertilizers. Recent research has emphasized the role of microorganisms in P solubilization and plant uptake. These microorganisms, including PSBs, PMBs, and AMFs, play a vital role in converting insoluble P forms into bioavailable forms, enhancing P acquisition by plants. In addition to microbial strategies, the development of biofertilizers can significantly enhance P availability in soils, promoting sustainable agricultural practices. By incorporating these strategies, agricultural systems can reduce their environmental footprint and contribute to a more sustainable future. The legacy contaminants associated with mined P, including ionizing radiation and heavy metals, present additional challenges to human and environmental health. These issues, coupled with the land fragmentation and degradation resulting from mining activities, underscore the need for stringent regulations and restrictions on P mining. Recycling P from organic waste materials is more cost-effective and environmentally sustainable than continuing mining PR. To mitigate the ecological impacts and evolutionary legacies of P mining, environmental impact assessments and reclamation efforts should be prioritized. Future research should focus on understanding the rhizospheric processes and mechanisms involved in P acquisition by crops, particularly through exploring intra- and interkingdom communication vehicles like extracellular vesicles. This review has contributed toward ensuring sustainable and resilient food and environmental systems and enhancing human health security. Additionally, the formulation and use of phosphobacterium biofertilizers, leveraging AMFs, PMBs, and PSBs, should be considered to improve P management in agriculture.",
"introduction": "Introduction Phosphorus (P), a finite and irreplaceable resource, is the backbone of global food production, yet its unsustainable use has placed humanity on the brink of a “phosphorus crisis.” With over 85% of the world’s P reserves concentrated in a handful of countries, the growing demand for phosphate fertilizers threatens food security and geopolitical stability. Furthermore, inefficient P utilization has led to environmental degradation, including eutrophication of water bodies, making its sustainable management a pressing global challenge (Holtan et al., 1988 ). It plays a key role in cellular processes such as energy transfer, signal transduction, and nucleic acid and phospholipid synthesis (Castagno et al., 2021 ). While P is abundant in the Earth’s crust, it often exists in insoluble inorganic and organic complexes, making it inaccessible primarily to plants (Barrow, 2022 ). The bioavailability of P is a critical factor influencing plant growth and agricultural productivity. In soils, P is primarily present in organic forms and is associated with soil minerals. The availability of P to plants is influenced by various chemical, biological, and physical processes that release P from these complexes (Jungk, 2002 ; Tinker & Nye, 2000 ). Ultimately, plants rely heavily on rhizospheric microbiota to access P, incredibly complex communities containing phosphate-solubilizing bacteria (PSB), phosphate-mineralizing bacteria (PMB), and arbuscular mycorrhizal fungi (AMF), which facilitate phosphorus solubilization and uptake through the secretion of enzymes and organic acids (Barrow & Lambers, 2022 ; Sharma et al., 2013 ). These microorganisms are pivotal in transforming insoluble P compounds into bioavailable forms, enhancing plant nutrient acquisition (Gerke, 2015 ; Liu et al., 2022a , b ). These microorganisms secrete organic acids and enzymes that convert insoluble P into forms that plants can absorb. Recent studies have highlighted the importance of the interaction between plants and rhizospheric microbiota in improving soil fertility, P acquisition, and microbial diversity in maintaining plant health (Blackwell et al., 2019 ; Dolatabadian, 2020 ; Konečný et al., 2019 ; Pantigoso et al., 2022 ). For instance, Konečný et al. ( 2019 ) investigated the role of specific genes involved in the exchange of carbon and P between plants and AMF, demonstrating that AM symbiosis can significantly enhance P uptake by plants. The study underscores the potential of microbial inoculants and genetic strategies to improve P-use efficiency in crops. While biological mechanisms offer a sustainable pathway for P acquisition, modern agriculture predominantly depends on P fertilizers derived from mined phosphate rock (PR), mostly from countries listed in Table 1 . Phosphate rock, predominantly found as sedimentary or igneous deposits, is the primary source of P fertilizers (Ryszko et al., 2023 ). The geopolitical distribution of these PR reserves, concentrated in Morocco, China, and Russia, further complicates global P supply chains (Schoumans et al., 2015 ). Production values have historically fluctuated but continue to experience steady growth (Fig. 1 ). Fluctuations in PR prices and supply disruptions, exacerbated by geopolitical tensions, highlight the urgent need for sustainable P management strategies (Scholz & Wellmer, 2021 ). With concerns over the finite nature of PR reserves, exploring alternative sources and recycling methods is imperative to ensure long-term P sustainability (Nedelciu et al., 2020 ; Zwetsloot et al., 2015a , b ). The extraction and processing of PR contributes to the depletion of finite P reserves and introduces heavy metals and radioactive elements into the environment, posing significant ecological and health risks (Mew et al., 2018 ).\n Table 1 Estimates of world phosphate rock production in 2021 Country Million tons\n USA 25 Morocco 150 China 110 Russia 155 Other countries 220 Source: Adapted from Ryszko et al. ( 2023 ) Fig. 1 Global trend in phosphate rock mining operations between 1998 and 2021. Source: U.S. Geological Survey ( 2022 ) Innovative approaches to P recycling are gaining attention as viable solutions to mitigate the environmental impacts of P mining. Technologies such as struvite precipitation, hydrothermal treatment, and microbial inoculation offer promising avenues for recovering P from waste streams (Jastrzębska et al., 2022 ; Witek-Krowiak et al., 2022 ). Recycling P from agricultural and urban wastes reduces reliance on mined resources and addresses issues of eutrophication and nutrient runoff in aquatic ecosystems (Ryden et al ., \n 1977 ; Schaedig et al., 2023 ). These processes promote two essential concepts—\"first-generation mined P,\"referring to P extracted directly from PR, which has limited sustainability due to its environmental and geopolitical challenges, and\"second-generation P,\"which involves the recycling of P from organic waste materials, offering a more sustainable alternative (Nedelciu et al., 2020 ). Phosphorus recycling from agricultural and urban wastes can reduce the dependence on mined P and mitigate its negative environmental impacts (Jayathilakan et al., 2012 ; Metson et al., 2022 ). Furthermore, excessive use of P fertilizers contributes to environmental issues such as eutrophication, where runoff leads to nutrient overload in aquatic systems, causing harmful algal blooms and dead zones (Schaedig et al., 2023 ). Addressing these challenges requires a shift toward more sustainable P management practices, including the use of microbial solutions and the recovery of P from waste streams (Wang et al., 2023 ). This review assesses the environmental impacts of P mining and explores sustainable strategies for improving P bioavailability and recycling. By highlighting the role of rhizospheric microorganisms and the potential of P recovery technologies, this review seeks to promote resilient and sustainable agricultural systems that reduce reliance on the likely finite PR resources."
} | 2,945 |
36093733 | PMC9827988 | pmc | 4,008 | {
"abstract": "Summary \n While pathogenic and mutualistic microbes are ubiquitous across ecosystems and often co‐occur within hosts, how they interact to determine patterns of disease in genetically diverse wild populations is unknown. To test whether microbial mutualists provide protection against pathogens, and whether this varies among host genotypes, we conducted a field experiment in three naturally occurring epidemics of a fungal pathogen, Podosphaera plantaginis , infecting a host plant, Plantago lanceolata , in the Åland Islands, Finland. In each population, we collected epidemiological data on experimental plants from six allopatric populations that had been inoculated with a mixture of mutualistic arbuscular mycorrhizal fungi or a nonmycorrhizal control. Inoculation with arbuscular mycorrhizal fungi increased growth in plants from every population, but also increased host infection rate. Mycorrhizal effects on disease severity varied among host genotypes and strengthened over time during the epidemic. Host genotypes that were more susceptible to the pathogen received stronger protective effects from inoculation. Our results show that arbuscular mycorrhizal fungi introduce both benefits and risks to host plants, and shift patterns of infection in host populations under pathogen attack. Understanding how mutualists alter host susceptibility to disease will be important for predicting infection outcomes in ecological communities and in agriculture.",
"introduction": "Introduction Protective symbionts – species that provide defensive benefits to their hosts – help to determine the outcome of species interactions and, thus, shape ecological and evolutionary dynamics between hosts and parasites (Brownlie & Johnson, 2009 ; May & Nelson, 2014 ; King et al ., 2016 ; Sochard et al ., 2020 ). Despite their importance, ecological studies examining the role of protective symbionts in influencing host–parasite interactions in natural populations and communities are rare (Oliver et al ., 2014 ; Hafer‐Hahmann & Vorburger, 2021 ). Protection against infectious disease by mutualistic microbes, such as mycorrhizal fungi, has been demonstrated under controlled laboratory conditions in several economically important agricultural plant species (Norman et al ., 1996 ; Pozo et al ., 2002 ; Hao et al ., 2005 ; Li et al ., 2010 ; Song et al ., 2015 ; Berdeni et al ., 2018 ). Although mutualists may also affect disease under field conditions (Newsham et al ., 1995 ), it has not been verified whether protective symbionts mediate infection under natural epidemics, which are characterized by repeated pathogen encounters, as well as by environmental and genotypic diversity. Mycorrhizal associations are widespread among terrestrial plants (Öpik et al ., 2006 ; van der Heijden et al ., 2008 ) and have important impacts on plant fitness and population dynamics (Barea et al ., 2002 ; Koide & Dickie, 2002 ), community composition (Hartnett & Wilson, 2002 ) and ecosystem functioning (Rillig, 2004 ). Understanding how mycorrhizal fungi and other mutualists influence patterns of plant disease is essential given that disease is a major factor shaping the abundance, diversity and distribution of species in plant communities (Bever et al ., 2015 ) and affecting food production (Johansson et al ., 2004 ; Gosling et al ., 2006 ; Pretty et al ., 2011 ; Hohmann & Messmer, 2017 ). Although both plant‐associated pathogenic and mutualistic microbes are ubiquitous across ecosystems, how they interact to determine disease risk in natural, genetically diverse populations is not known. Mycorrhizal fungi produce a suite of growth, nutritional and/or defensive effects that may help protect plants from co‐occurring antagonists, such as pathogenic microbes and herbivores (Delavaux et al ., 2017 ). Association with mycorrhizal fungi often improves plant nutrient and water uptake (Smith & Read, 2008 ), although there is both intra‐ and interspecific variation among plants in their ability to form and benefit from mycorrhizal associations (Thrall et al ., 2011 ; Rasmussen et al ., 2019 ). Increases in host size and nutritional status as a result of mycorrhizal association can improve host tolerance to parasites and abiotic stress (Azcón‐Aguilar & Barea, 1996 ). Arbuscular mycorrhizal fungi can also influence host defenses directly, by upregulating defense gene expression in their host plants (Azcón‐Aguilar & Barea, 1996 ; Pozo & Azcón‐Aguilar, 2007 ; Jung et al ., 2012 ; Goddard et al ., 2021 ). This form of protection, known as defense priming, allows a more efficient activation of defense mechanisms in response to attack by potential enemies and has been shown to reduce the negative effects of interactions with a wide range of antagonist species (Jung et al ., 2012 ; Delavaux et al ., 2017 ). Although mycorrhizal associations occur belowground (at the root–soil interface), the induced resistance response in the host is systemic (Cameron et al ., 2013 ; Goddard et al ., 2021 ), meaning that even strictly aboveground parasites may be affected (Koricheva et al ., 2009 ). It is unclear how often mycorrhizal growth and defensive benefits are conferred together in hosts and how they operate simultaneously to determine the incidence and outcome of interactions between hosts and parasites. Empirical studies in controlled environments have shown that host association with mutualists may also present risks that can influence infection dynamics (Polin et al ., 2014 ). For example, ecological costs may occur when combinations of host and mutualist species or genotypes are mismatched (Klironomos, 2003 ; Hoeksema et al ., 2010 ), resulting in inefficient mutualisms that fail to convert host resources into growth or defensive benefits (Johnson et al ., 1997 ; Jones & Smith, 2004 ; Grman, 2012 ). Furthermore, unfavorable abiotic conditions may reduce or negate potential mutualist benefits (Hoeksema et al ., 2010 ; Qu et al ., 2021 ). In addition, defensive benefits from mutualists may not be effective against all parasite species (e.g. depending on their life history) (Pozo & Azcón‐Aguilar, 2007 ) or durable to changes in parasite traits and/or composition in the environment. Finally, mutualists could also affect patterns of host infection indirectly, for example, via changes in host size that influence parasite contact rates. Hence, the potential ecological risks and/or benefits of mutualist association in the presence of parasites may depend on host genotype and vary among or within host populations and environments; however, this has remained largely unexplored in natural populations. In addition, it is unclear how mutualism‐derived protection acts alongside innate host resistance to determine the outcome of host–pathogen interactions. Host genetic resistance can vary widely among and within natural populations (Salvaudon et al ., 2008 ; Laine et al ., 2011 ) – potentially as a result of costs associated with its maintenance (Brown, 2003 ; Susi & Laine, 2015 ) – and may be under a different set of selection pressures than mutualism (Thompson, 1994 ). Whether symbiosis presents benefits or costs to host individuals and populations could depend on their degree of resistance. In resistant hosts, resources provided to mutualists in return for defensive benefits could represent an unnecessary metabolic cost. However, in susceptible hosts, mutualist‐derived protection could compensate for lack of genetic resistance, presenting a viable alternate strategy for coping with pathogens. Mutualism‐derived protection could be especially beneficial when genetic resistance is costly to maintain or when disease is ephemeral, as it often is in natural populations (Burdon & Thrall, 2014 ). How much of host resistance is derived from innate genetic defenses vs protective symbionts (e.g. defense priming or improved pathogen tolerance), and whether these types of defenses are linked in different species combinations and environmental contexts remain to be seen. Despite general recognition for the impact of mycorrhizal fungi on plant fitness, how mycorrhizal association may impact host infection – and to what extent this varies among plant genotypes and populations – is poorly understood in natural populations. To examine this, we conducted a field experiment to test whether inoculation with arbuscular mycorrhizal fungi affects infection dynamics by a fungal pathogen in a shared host under natural epidemic conditions. Specifically, we ask the following questions: do growth effects resulting from inoculation with arbuscular mycorrhizal fungi vary among host populations and maternal genotypes; does inoculation with arbuscular mycorrhizal fungi influence host infection rate; upon infection, does prior inoculation with arbuscular mycorrhizal fungi affect disease severity; are growth and defensive effects from inoculation with arbuscular mycorrhizal fungi linked in host genotypes; and are disease susceptibility and defensive effects as a result of inoculation with arbuscular mycorrhizal fungi linked in host genotypes? To answer these questions within an ecologically relevant context, we placed mycorrhizal‐inoculated and nonmycorrhizal‐inoculated plants in wild host populations during a natural pathogen epidemic. The experiment was conducted in the long‐term Åland Islands study site (Finland), where infection by a fungal pathogen (powdery mildew) has been surveyed on a large host population network of Plantago lanceolata L. (Plantaginaceae) since 2001 (Jousimo et al ., 2014 ). From prior studies in this pathosystem, we know that several factors, such as spatial context (Laine, 2006 ; Soubeyrand et al ., 2009 ; Jousimo et al ., 2014 ), pathogen genetic diversity (Eck et al ., 2022 ), local adaptation of pathogen strains to sympatric host populations (Laine, 2005 , 2007a ) and abiotic conditions (Laine, 2007b , 2008 ; Penczykowski et al ., 2015 ), are all critical in determining infection, but the impact of mutualistic interactions on infection dynamics has not been determined. To our knowledge, this is the first study of the impact of mycorrhizal fungi on infection by a plant pathogen under natural epidemics and across different host populations and genotypes.",
"discussion": "Discussion While both plant‐associated pathogenic and mutualistic microbes are ubiquitous across ecosystems, how they interact to determine patterns of infection in genetically diverse host populations is not known. In a field experiment placing wild hosts of 30 maternal genotypes in naturally occurring pathogen epidemics, we found that inoculation with a three‐species mixture of arbuscular mycorrhizal fungi produced benefits and risks that influenced aboveground patterns of host infection. Mycorrhizal inoculation increased growth in hosts of nearly every genotype, but also increased infection rates from a foliar fungal pathogen. The effects of mycorrhizal inoculation on disease severity varied over the course of the epidemic, with both protective and negative effects occurring among the host genotypes. Moreover, disease susceptibility and mycorrhiza‐derived defense effects appeared to be linked in the host genotypes: more susceptible host genotypes (in the absence of the mutualists) received stronger protection against disease when inoculated with mycorrhizal fungi. Arbuscular mycorrhizal fungi have been shown to protect agricultural plants against belowground (Azcón‐Aguilar & Barea, 1996 ; Hao et al ., 2005 ) and foliar (Fiorilli et al ., 2018 ; Pozo de la Hoz et al ., 2021 ) pathogens in controlled laboratory conditions, but our results provide the first evidence of how microbial mutualists can shift patterns of host infection in genetically diverse wild populations under pathogen attack. Mycorrhizal fungi also appeared to be linked to a growth–defense trade‐off in the hosts: mycorrhizal‐inoculated plants grew larger and became more infected by the pathogen, with the host genotypes that obtained the greatest growth benefit from mycorrhizal fungi also suffering the largest increases in disease. Together, our results underscore that under natural ecological and epidemic conditions mycorrhizal fungi produce a complex and temporally variable array of positive and negative effects on host growth and infection. Inoculation with mycorrhizal fungi provided growth benefits to host plants from every population and maternal genotype. The magnitude of these effects varied among hosts from different genetic origins before exposure to the field epidemics, but homogenized over time in field conditions. Owing to the positive relationship between plant size and survival, growth is often intrinsically linked to host fitness (Harper & White, 1974 ). Our results are consistent with studies reporting evidence for the importance of mycorrhizal fungi in determining host growth and/or fitness and showing variability in such effects among host genotypes (Rasmussen et al ., 2017 ; Qin et al ., 2021 ). In addition, susceptibility to the pathogen epidemics in the field varied among hosts of different genetic origins, consistent with other studies in this pathosystem (Laine, 2005 , 2007a ; Tack et al ., 2014 ; Susi & Laine, 2015 ) and the broader wild plant disease literature (Carlsson‐Granér, 1997 ; Price et al ., 2004 ). Together, these results provide evidence for the importance of genotype in mediating host–microbe interactions (Eck et al ., 2019 ; Sallinen et al ., 2020 ), although more generalist interactions can also certainly occur (Gilbert & Webb, 2007 ; Halbritter et al ., 2012 ; Hersh et al ., 2012 ). Building upon such studies, we show evidence of changes in host–parasite interactions as a result of prior inoculation with microbial mutualists. Inoculation experiments with agricultural plant species and their pathogens have shown that arbuscular mycorrhizal fungi can reduce disease incidence or severity (Norman et al ., 1996 ; Pozo et al ., 2002 ; Hao et al ., 2005 ; Li et al ., 2010 ; Song et al ., 2015 ; Berdeni et al ., 2018 ). However, symbiotic relationships in cultivars may differ from those of wild plants (Xing et al ., 2012 ); thus, it is not straightforward to predict responses in wild populations from controlled agricultural trials. In this study, mycorrhizal inoculation increased infection rates in hosts of a wild plant species and produced variable effects on disease severity in hosts of different genotypes and over the course of the epidemic. By the end of the experiment, mycorrhizal inoculation was weakly linked to higher numbers of infected leaves in diseased hosts (though variation among genotypes remained). Our results suggest that environmental, temporal and genetic contexts may alter the potential defensive effects related to mycorrhizal association and are consistent with other experimental studies showing that mycorrhizal effects on host infection may vary among host genotypes (Mark & Cassells, 1996 ; Steinkellner et al ., 2012 ). However, in our experiment, the effects of mycorrhizal inoculation on infection were weaker than the effects on host growth. Additional studies that explicitly quantify mycorrhizal colonization are needed to confirm the contribution of the symbiont to host growth, infection and fitness. The potential risks of mycorrhizal association in wild plants are relevant for theoretical studies which speculate as to how mycorrhizal fungi might influence host fitness in the presence of pathogens and affect plant population and community dynamics (Bachelot et al ., 2015 ). In many free‐living organisms, an evolutionary trade‐off exists between growth and defense (Herms & Mattson, 1992 ). In our experiment, additional insights can be gained by examining whether changes in host growth as a result of mutualism are related to changes in host defense across genotypes. In our experiment, mycorrhizal‐inoculated hosts consistently grew larger and were more likely to become infected by the pathogen. This could occur if increases in host size increase pathogen encounter rates, as might be expected for pathogen species with wind‐ or passively dispersed spores (such as P. plantaginis ). In addition, host genotypes that experienced larger growth benefits from mycorrhizal inoculation suffered marginally larger increases in disease severity (although there was considerable variation in this effect). That some host genotypes grew larger and experienced reductions in disease severity following mycorrhizal inoculation suggests that defense priming could occur occasionally. Infected AMF plants also had lower proportions of infected leaves than did NM plants (relative to their size), although it is unclear whether this may offset the costs of having higher numbers of infected leaves in this pathosystem. Changes in host tolerance to pathogens following mycorrhizal inoculation could also explain increases in infected leaf numbers, although mycorrhizal fungi are generally expected to improve host nutritional status or increase leaf toughness (Meier & Hunter, 2018 ), making foliar pathogen spread more difficult. Thus, it is likely that differences in host infection between AMF and NM plants in our experiment were mediated by increases in host size (as host size also predicted some aspects of infection) or defense priming in some genotypes. In addition, our findings indicate that arbuscular mycorrhizal fungi could help susceptible host genotypes to compensate for lack of innate resistance while placing costs on well‐defended genotypes. We found that the magnitude of defense effects following mycorrhizal inoculation were linked to pathogen susceptibility in the host genotypes: host genotypes that were susceptible to more severe infections received stronger disease protection effects when inoculated with the mutualist. By contrast, more resistant host genotypes were likely to experience slight increases in disease load when inoculated. Thus, inoculation with mycorrhizal fungi tended to equalize disease severity between more resistant and more susceptible host genotypes, potentially reducing the relative importance of host genetic resistance in determining pathogen effects. However, the linkages between disease susceptibility and mycorrhizal defense effects in our study (as well as between host growth and these effects) were revealed post hoc and should be confirmed with experiments designed to test these hypotheses. If confirmed, it could indicate that host genotypes may experience trade‐offs in investment in genetic resistance vs mycorrhizal‐mediated resistance. It could also suggest that mycorrhizal association may have been selected for and maintained in host populations partially because it increases the fitness of susceptible host genotypes. In this way, mycorrhizal protective effects could contribute to the maintenance of diversity in host genetic resistance within and among populations (Laine, 2004 , 2007a ; Jousimo et al ., 2014 ). Variation among host populations and genotypes in mycorrhizal benefits and risks could be a result of several factors. These factors include intraspecific differences in hosts' ability to form associations with and derive function from different mycorrhizal species, differences in mycorrhizal colonization rates or community composition, environmental variation or differences in host–pathogen population dynamics over time. Previous studies demonstrated variation in arbuscular mycorrhizal colonization rates among individuals within species – variation that is thought to have a partially genetic component (Plouznikoff et al ., 2019 ; Pawlowski et al ., 2020 ). Although we observed clear differences in host growth and infection as a result of the mycorrhizal inoculation treatment, data on mycorrhizal colonization are needed to confirm mycorrhizas as the mechanism underlying the observed effects. Environmental conditions may also impact plant–microbe interactions (Santoyo et al ., 2017 ). Consistent with other studies in this pathosystem, infection rates varied among field populations and changed over time (Eck et al ., 2022 ). By contrast, the effects of mycorrhizal inoculation on hosts were similar among field populations, although changes over time also occurred. Growth benefits following inoculation with mycorrhizal fungi varied among host populations and genotypes before pathogen exposure but became homogenous over time in the field conditions. Changes in host infection rate and disease severity as a result of mycorrhizal inoculation were also similar among field populations but increased over time. Together, these results suggest that mycorrhizal effects on hosts are more temporally than environmentally sensitive. There is also some chance that environmental mycorrhizal spores could have come into contact with our experimental soils, such that true amounts of mycorrhizal colonization in the nonmycorrhizal treatment could be low (rather than none), and the mycorrhizal communities in the experimental pots could contain species that were not inoculated. The limited duration of the field experiment reduces the likelihood that this could cause strong effects (Sanders & Sheikh, 1983 ); however, if it occurred, it should have occurred evenly among treatments and seed sources. Future studies in which mycorrhizal composition, colonization rates and function are quantified in genetically diverse hosts and in variable environmental conditions over time are necessary to corroborate this work and disentangle the effect of mycorrhizal growth and defensive effects from intraspecific variation in host growth and resistance. Together, our results suggest that symbiosis with arbuscular mycorrhizal fungi produces benefits and alters infection risks from a pathogen during natural epidemics in genetically variable host populations. Altered patterns of host growth and infection as a result of mutualist species may cascade to affect patterns of abundance, diversity and distribution of the associated organisms, as well as ecosystem processes (Brown et al ., 2001 ). Moreover, we are beginning to acknowledge the importance of direct and indirect microbial interactions within hosts in determining host fitness and parasite population dynamics (Kemen, 2014 ; Kemen et al ., 2015 ; Kroll et al ., 2017 ). Belowground soil and rhizosphere processes may also affect aboveground interactions with pathogens and herbivores, and vice versa (van der Putten et al ., 2001 ; Wardle et al ., 2004 ; Frew, 2021 ), and mutualists and parasites may act simultaneously to determine host fitness (Bezemer & van Dam, 2005 ). Our results also highlight the importance of characterizing host–microbe interactions under natural conditions and temporal interaction sequences, which will allow more precise modeling of epidemiological and ecological community dynamics. In addition, if growth and defensive effects as a result of mutualism are common, they should ultimately affect the coevolutionary trajectories of the associated organisms (van Dam & Heil, 2010 ). Understanding how mutualism alters host susceptibility and parasite interactions will be important for understanding, predicting and managing disease in ecological communities and in agriculture."
} | 5,847 |
23861757 | PMC3702539 | pmc | 4,009 | {
"abstract": "Xylonate is a valuable chemical for versatile applications. Although the chemical synthesis route and microbial conversion pathway were established decades ago, no commercial production of xylonate has been obtained so far. In this study, the industrially important microorganism Escherichia coli was engineered to produce xylonate from xylose. Through the coexpression of a xylose dehydrogenase ( xdh ) and a xylonolactonase ( xylC ) from Caulobacter crescentus , the recombinant strain could convert 1 g/L xylose to 0.84 g/L xylonate and 0.10 g/L xylonolactone after being induced for 12 h. Furthermore, the competitive pathway for xylose catabolism in E. coli was blocked by disrupting two genes ( xylA and xylB ) encoding xylose isomerase and xylulose kinase. Under fed-batch conditions, the finally engineered strain produced up to 27.3 g/L xylonate and 1.7 g/L xylonolactone from 30 g/L xylose, about 88% of the theoretical yield. These results suggest that the engineered E. coli strain has a promising perspective for large-scale production of xylonate.",
"conclusion": "Conclusions In this study, a robust xylonate-producing E. coli strain was successfully constructed. Three distinct genetic alterations targeted at the xylose or xylonate metabolic pathways were introduced into the host strain BL21 star(DE3), including knockout of the endogenous xylA and xylB genes, which encodes the xylose isomerase and xylulose kinase, to block the native xylose catabolism; heterologous expression of a xylose dehydrogenase to render E. coli capable of converting xylose to xylonolactone; and further introducing a xylonolactonase to hydrolyze the intermediate xylonolactone to xylonate. Under fed-batch conditions, up to 27.3 g/L xylonate and 1.7 g/L xylonolactone were produced out of 30 g/L xylose by the finally engineered strain BL21ΔxylAB/pA-xdhxylC. The volumetric productivity was as high as 1.8 g/(L·h). This engineered E. coli has a promising application for the industrial-scale production of xylonate.",
"introduction": "Introduction Xylonate is a five-carbon organic acid. In the past few years, xylonate has gained increasing interest due to its potential as an important platform chemical. Xylonate has extensively versatile applications similar to many other sugar acids such as gluconate, and can be used in food, chemical, and pharmaceutical industries [1] . In particular, xylonate could serve as a precursor for 1,2,4-butanetriol synthesis [2] and a concrete water reducer [3] . Xylonate might be produced from the non-food hemicellulose hydrolysate, which provides an inexpensive alternative to gluconate. In a report from the U.S. Department of Energy, xylonate is among the top 30 value-added chemicals manufactured from biomass [4] . Although chemical oxidation of xylose to produce xylonate could be obtained by using platinum or gold as the catalysts [5] , the poor selectivity makes these synthetic routes not economically feasible for industrial purposes. Microbial conversion of xylose to xylonate, which was well characterized in previous studies, has become a research hotspot during recent years. Several bacterial strains, e.g., Enterobacter cloacae \n [6] , Pseudomonas fragi \n [7] , Gluconobacter oxydans \n [8] , were able to produce xylonate in high yields. Compared with the chemical synthetic routes, microbial fermentation offers the potential for benign processing with high specificity and reduced manufacturing cost. Along with the development of modern molecular biology techniques, the metabolic pathway from xylose to xylonate has been largely elucidated. Xylose is first converted to xylonolactone by xylose dehydrogenase or glucose oxidase, and xylonolactone is subsequently hydrolyzed spontaneously or enzymatically by xylonolactonase to yield xylonate [9] . Up to now, genes encoding xylose dehydrogenases have been identified and cloned from different bacterial and fungal strains [10] – [12] . Heterologous expression of these xylose dehydrogenase led to xylonate production in the corresponding hosts [13] , [14] . However, few xylonolactonases have been characterized. Spontaneous hydrolysis of xylonolactone was relatively slow, and its accumulation in the culture broth greatly inhibited the growth of bacteria, thus hampering xylonate production [15] . Recently, the oxidative xylose utilization pathway was discovered in the fresh water bacterium Caulobacter crescentus . Enzymes including an NAD + dependent xylose dehydrogenase ( xdh ) and a xylonolactonase ( xylC ) were identified in a xylose-inducible operon [16] . In this study, the two genes were expressed in a xylose catabolic deficient Escherichia coli mutant strain (knockout of xylA and xylB , encoding xylose isomerase and xylulose kinase) to construct a heterologous xylonate-producing system ( Figure 1 ). Xylonate production by the engineered strain was further evaluated under fed-batch culture conditions. 10.1371/journal.pone.0067305.g001 Figure 1 The metabolic pathway from xylose to xylonate in engineered E. coli . Enzymes encoded by the genes shown are: xdh , xylose dehydrogenase from C. crescentus ; xylC , xylonolactonase from C. crescentus ; xylA , native E. coli xylose isomerase; xylB , native E. coli xylulose kinase.",
"discussion": "Results and Discussion Inactivation of Native E. Coli Xylose Catabolic Pathways \n E. coli BL21 star(DE3) was chosen as the host for xylonate production in this work. Unlike E. coli K12, strain BL21 and its derivatives lack the requisite xylonate dehydratase activity (potentially encoded by yjhG and yagF ). Therefore, they cannot consume xylonate as the carbon source and would be useful for the accumulation of xylonate in the culture broth. In addition, strain BL21 star(DE3) carries a mutated rne gene which encodes a truncated RNase E enzyme and lacks the ability to degrade mRNA, resulting in an increase in mRNA stability. This might be helpful to the Red recombination enzyme activities and thus this strain has been successfully used for gene knockout [20] . E. coli could efficiently utilize xylose as a carbon source for growth. The first two genes responsible for xylose catabolism have been recognized as xylose isomerase (encoded by xylA ) and xylulose kinase (encoded by xylB ) [21] . In order to block the native xylose catabolic pathway, we disrupted xylA and xylB in strain BL21 star(DE3) chromosome using the Red recombination method. Successful gene disruptions were confirmed by PCR amplification ( Figure S1 ). Liquid growth tests on M9 mineral medium supplemented with xylose as the sole carbon source further proved that the xylose metabolism-blocked strain BL21ΔxylAB grew much more poorly than its parent strain. Heterologous Expression of Xylose Dehydrogenase and Xylonolactonase With the aim to express the xylose dehydrogenase and xylonolactonase enzymes, we cloned the coding region of xdh and xylC from C. crescentus into pACYCduet-1 expression vector under T7 promoter, respectively. The recombinant plasmids pA-xdh, pA-xylC and pA-xdhxylC were confirmed by restriction enzyme digestion and DNA sequencing. To verify the expression levels of the recombinant proteins, strain BL21ΔxylAB was transformed by the expression vectors including different genes and grown in liquid LB medium followed by induction using 0.5 mM IPTG. Figure 2 showed the gel electrophoresis patterns of samples from different recombinant strains analyzed with coomassie brilliant blue staining. We noted distinct bands of the expected size from protein extracts of the recombinant strains compared with the control strain harboring pACYCduet-1. SDS-PAGE analysis of the recombinant strain carrying pA-xdh and pA-xylC revealed the recombinant proteins of different sizes (corresponding to the bands of molecular weight 26.6 kDa and 31.6 kDa) while the lysate of strain BL21ΔxylAB/pA-xdhxylC gave both of the two bands. 10.1371/journal.pone.0067305.g002 Figure 2 Expression of the recombinant xylose dehydrogenase and xylonolactonase from C. crescentus . Lane M, prestained protein ladder; lane 1, BL21ΔxylAB harboring pACYCduet-1; lane 2, BL21ΔxylAB harboring pA-xdh; lane 3, BL21ΔxylAB harboring pA-xylC; lane 4, BL21ΔxylAB harboring pA-xdhxylC. Establishment of a Xylose, Xylonate and Xylonolactone Analysis Method for the Determination of Xylose Dehydrogenase and Xylonolactonase Activities In several previous studies, a general high performance liquid chromatography (HPLC) method equipped with an ion exchange column (Aminex HPX-87H, Bio-Rad) was used to determine the extracellular metabolites including xylose, xylonate and xylonolactone. However, these three chemicals displayed similar retention times under the corresponding separation conditions, leading to the inaccuracy of measurement. Here, we developed an ion chromatography (IC) method to separate the three metabolites. Under such a condition, they were generally well separated, except that xylose was eluted only 0.14 min after xylonolactone ( Figure 3A–C ). Then the established IC analysis method was applied to determine the metabolites concentrations in the fermentation culture and the enzymatic products of xylose dehydrogenase and xylonolactonase. As the original xylose dehydrogenase activity has been measured by determining the absorption of NADH at 340 nm [16] , we briefly detected the enzymatic reaction products of the enzyme by the established IC method. As shown in Figure 3D , the reaction mixture of xylose dehydrogenase gave an apparent peak of xylonolactone when xylose was supplemented as the substrate. And the reaction mixture of xylonolactonase showed the peaks of xylonolactone and xylonate, respectively ( Figure 3E ). These results demonstrated that both of the enzymes were expressed in their active forms in the recombinant E. coli strains. 10.1371/journal.pone.0067305.g003 Figure 3 Detection of xylose, xylonate and xylonolactone by ion chromatography. A, 1 ppm xylose, corresponding to the retention time of 2.75 min; B, 200 ppm xylonolactone, corresponding to the retention time of 2.61 min; C, 100 ppm xylonate, corresponding to the retention time of 3.43 min; D, detection of the enzymatic product of xylose dehydrogenase; E, detection of the enzymatic product of xylonolactonase; F, ion chromatogram of the extracellular metabolites of strain BL21ΔxylAB/pA-xdhxylC after being induced for 12 h. Both the enzymatic reaction mixtures and culture broth supernatant were appropriately diluted for ion chromatography analysis. Comparison of Xylonate Productivities of Different Engineered Strains Because the native xylonate-producing strains are not suitable for an industrial process, several heterologous systems have been developed for xylonate production, including Saccharomyces cerevisiae \n [22] and Kluyveromyces lactis \n [14] . Compared with these yeast strains, E. coli genome encodes several xylose transporters [23] and xylonate transport across E. coli cell membrane is also efficient, which might facilitate the consumption of xylose and the accumulation of xylonate. However, E. coli lacks the requisite xylose dehydrogenase activity, and thus wild-type E. coli strain could not convert xylose to xylonate. To construct a xylonate-producing strain, the xylose dehydrogenase from C. crescentus was heterologously expressed in E. coli BL21 star(DE3). As expected, accumulations of xylonolactone and xylonate were found in the cultures of the recombinant strain. In order to reduce the inhibiting effects of xylonolactone and facilitate the IC analysis of metabolites, the substrate xylose was supplemented at a relatively low concentration (1 g/L). As shown in Figure 4 , 0.57 g/L xylonolactone and 0.12 g/L xylonate were produced after being induced for 12 h and the initial xylose was nearly completely exhausted. This productivity was much lower than the theoretical value because E. coli could catabolize xylose through the native phosphate pentose pathway [24] . To reduce the conversion of xylose to biomass, we further disrupted native E. coli xylA and xylB genes, which encode the first two enzymes responsible for xylose utilization [25] . When the native xylose catabolic pathway was blocked in the strain BL21ΔxylAB, the final titers of xylonolactone and xylonate were enhanced to 0.72 g/L and 0.16 g/L, respectively. However, most of the fermentation products were xylonolactone in the strain expressing the xylose dehydrogenase solely. In order to increase the hydrolysis rate of xylonolactone, we further constructed the engineered strain BL21ΔxylAB/pA-xdhxylC. The ion chromatograph of extracellular metabolites of this strain after 12 h-induction was shown in Figure 3F . We could find most of the xylonolactone was converted to xylonate by this strain. The final titers of xylonolactone and xylonate reached 0.10 g/L and 0.84 g/L and the molar yield of xylonolactone and xylonate on xylose also reached 86.0%. 10.1371/journal.pone.0067305.g004 Figure 4 Comparison of xylonate and xylonolactone production of several different strains. Data were obtained after each strain was induced for 12 h in liquid LB medium supplemented with 1 g/L xylose. BL21/pA-xdh, strain BL21 star(DE3) expressing C. crescentus xylose dehydrogenase; BL21ΔxylAB/pA-xdh, knockout of native xylA and xylB while expressing C. crescentus xylose dehydrogenase; BL21ΔxylAB/pA-xdhxylC, knockout of native xylA and xylB while coexpressing C. crescentus xylose dehydrogenase and xylonolactonase. Xylonate Production Under Fed-batch Cultivation Among the industrially important microorganisms, E. coli has been used for various biotechnological processes and production of many valuable chemicals [26] . To investigate the feasibility for larger-scale production of xylonate, the finally engineered E. coli strain BL21ΔxylAB/pA-xdhxylC was cultured in a 5 L-scale laboratory fermenter. Cell density, xylose utilization, and products accumulation were monitored over the course of the experiment. Figure 5 shows the time profiles for cell density, residual xylose, xylonolactone and xylonate concentrations during the fermentation processes. For approximately 16 h post-induction, the bacteria grew very fast. Xylonate accumulated rapidly in the culture media while xylonolactone remained at a relatively low level. The highest xylonate production was obtained after 16 h induction, that is, 27.3 g/L. At this time, the final titer of xylonolactone reached 1.7 g/L and the initial xylose was completely exhausted. The volumetric productivity of xylonate and xylonolactone was 1.8 g/(L·h). The molar yield of xylonate and xylonolactone on xylose was about 88.0%, which was comparable to the shake-flask scale. Both of the titers of xylonate and xylonolactone remained stable during the following culture processes. In contrast, the recombinant strain only expressing xylose dehydrogenase (BL21ΔxylAB/pA-xdh) grew much slower after being induced with IPTG and cell growth ceased at an OD 600 of around 40 even though glycerol was still being consumed (data not shown). 10.1371/journal.pone.0067305.g005 Figure 5 Time profiles for cell density (OD 600 ), residual xylose, xylonate and xylonolactone concentrations in the culture broth during fed-batch culture of the finally engineered strain BL21ΔxylAB/pA-xdhxylC. In two previous studies using yeast as the host organism, S. cerevisiae could only accumulate up to 3.8 g/L xylonate [13] while K. lactis produced 19 g/L xylonate from 40 g/L xylose [14] . Considering that yeast does not have an efficient pentose transport system, xylose uptake and metabolism might be limited in these strains. As for the native xylonate producers, the highest production was reported to be 92 g/L achieved by P. fragi \n [7] , which was much higher than the E. coli strains and the yield of xylonate on xylose reached 92%, which was also comparable to the current study. This might be due to that the wild-type strains could endure high concentrations of xylonate. Therefore, the current strains have the potential to be further engineered to enhance their resistance to xylonate, thus leading to even higher production. On the other hand, E. coli grows much faster in cheap culture medium than the native producers [27] . The whole fermentation process only requires less than 24 h for the engineered strain in this work, while the native producing strains always take several days to reach the maximum titer. This would contribute to reducing the production cost during large-scale fermentation. Conclusions In this study, a robust xylonate-producing E. coli strain was successfully constructed. Three distinct genetic alterations targeted at the xylose or xylonate metabolic pathways were introduced into the host strain BL21 star(DE3), including knockout of the endogenous xylA and xylB genes, which encodes the xylose isomerase and xylulose kinase, to block the native xylose catabolism; heterologous expression of a xylose dehydrogenase to render E. coli capable of converting xylose to xylonolactone; and further introducing a xylonolactonase to hydrolyze the intermediate xylonolactone to xylonate. Under fed-batch conditions, up to 27.3 g/L xylonate and 1.7 g/L xylonolactone were produced out of 30 g/L xylose by the finally engineered strain BL21ΔxylAB/pA-xdhxylC. The volumetric productivity was as high as 1.8 g/(L·h). This engineered E. coli has a promising application for the industrial-scale production of xylonate."
} | 4,383 |
17625513 | PMC1948103 | pmc | 4,010 | {
"abstract": "Biological systems display a functional diversity, density and efficiency that make them a paradigm for synthetic systems. In natural systems, the cell is the elemental unit and efforts to emulate cells, their components, and organization have relied primarily on the use of bioorganic materials. Impressive advances have been made towards assembling simple genetic systems within cellular scale containers. These biological system assembly efforts are particularly instructive, as we gain command over the directed synthesis and assembly of synthetic nanoscale structures. Advances in nanoscale fabrication, assembly, and characterization are providing the tools and materials for characterizing and emulating the smallest scale features of biology. Further, they are revealing unique physical properties that emerge at the nanoscale. Realizing these properties in useful ways will require attention to the assembly of these nanoscale components. Attention to systems biology principles can lead to the practical development of nanoscale technologies with possible realization of synthetic systems with cell-like complexity. In turn, useful tools for interpreting biological complexity and for interfacing to biological processes will result.",
"conclusion": "Conclusion The initial focus in nanoscience on the synthesis of nanomaterials closes the gap between the scales of biological and synthetic systems. The next steps in nano-enabled synthetic biology will be about closing the complexity gap, which is especially challenging, as there is no general theory to guide the organization of nanoscale materials into highly interactive collectives. Instead, this field is most likely to advance through the transfer of biological principles of organization into the bottom-up synthesis of complex synthetic nanoscale materials systems. Undoubtedly, this will require the adoption of design paradigms quite different from usual engineering practice, and instead will embrace the organizational forces of excluded volume effects, stochastic modulation of nonlinear processes, scale-free networking of elements, and interconnectivity through weak and malleable interactions. Yet, these issues faced on the scale of collective behavior come full circle to present a challenge at the scale of individual nanoscale elements: can the synthesis of nanoscale materials be controlled to enhance the self-organization of highly interconnected networks? This question will drive a new emphasis on nanomaterial synthesis and the next steps in nano-enabled synthetic biology. With the continuing integration of nanoscience and technology with biological systems, a nano-enabled synthetic biology emerges and provides the tools to use the time-honored practice of design as a tool to understand complexity.",
"introduction": "Introduction Understanding the organizing principles of complex systems presents a significant challenge. Whether in the synthetic or biological domain, there is a growing awareness that design, the reiterative process of creating function through the intentional interconnection of components, is an indispensable tool for unraveling complexity. Whereas modeling, simulation, and experimental analyses have a tendency to focus attention on the details of individual elements, design requires grappling with the trade-offs and compromises needed to enable system function. Along these lines, synthetic biology efforts follow a strategy of constructing deliberately simplified systems to comprehend molecular and cellular regulatory processes from the bottom up ( Hasty et al, 2002 ; Sprinzak and Elowitz, 2005 ; Andrianantoandro et al, 2006 ; Guido et al, 2006 ). Similarly, efforts towards constructing minimal cells either add, subtract or manipulate components to realize simple systems with desired capabilities ( Forster and Church, 2006 ; Luisi et al, 2006 ). In both cases, iterative design is a fundamental aspect of the approach and represents a major step towards true bottom-up construction of biological complexity. However, these approaches still depend on a platform of an existing cellular environment or the use of biomolecules (nucleic acids, proteins, lipids) to jump start cellular function. Thus, the question remains, what could be learned from a true bottom-up effort to reconstitute cell-like complexity? Can the deliberate design and assembly of synthetic components lead to systems with cell-like characteristics? The large discrepancy between the functional density (i.e., the number of components or interconnection of components per unit volume) of cells and engineered systems highlights the inherent challenges posed by such a question. A simple example compares Escherichia coli (∼2-μm 2 cross-sectional area) with an equivalent area on a silicon-integrated circuit ( Simpson et al, 2001 ). The E. coli cell has an ∼4.6-million base-pair chromosome (the equivalent of a 9.2 megabit memory) that codes for as many as 4300 different polypeptides under the inducible control of several hundred different promoters, whereas the same space on a silicon chip could provide only a very small fraction of this memory or a few simple logic gates. Clearly, the operational scale of biological systems is significantly smaller than that of conventionally engineered systems. Beyond just density alone, it is also the drastically different approach to component assembly, interfacing, and organization that differentiates the biological from the synthetic nanoscale system. In the biological substrate, dynamic systems exploit weak interactions, arranged to provide desired specificity, and take place in a fluid environment. These features lead from simply high spatial density to high functional density and the realization of robust, adaptable systems. As nanoscience and technology advance, the opportunity to match the scale of biological system components becomes feasible. As a first step, nanotechnology presents the ability to directly interface to the working levels of biology, leading to the emergence of new approaches to therapy and diagnostics. Additionally, the emulation of biological design principles using synthetic components becomes feasible. Potentially, as systems of such elements approach biological-scale functional density, they can begin to assume cell-like characteristics including: (1) construction from an inhomogeneous mixture of materials with different properties, modes and strengths of interactions, and relative abundances; (2) the encoding of information within small populations (e.g., biomolecules or electrons); (3) function emerging from an environment with large stochastic fluctuations (a consequence of (2)); and (4) the efficient transduction of information, energy, and materials that emanates from the molecular scale. It is an intriguing possibility that, as our ability to control the synthesis and direct the assembly of synthetic nanoscale elements increases, we may attempt the bottom-up design and construction of nanosystems with cell-like complexity and capabilities. In turn, the design of such systems will lead to an enhanced ability to understand and interface to biological systems. The intersection of nanoscale science and technology with biology has figured prominently in even the early stages of envisioning nanoscience research directions and goals ( Roco, 2003 ). In many ways, the biological cell represents an ideal paradigm for nanoscale systems. Being the fundamental unit of biological systems, their function can be extremely diverse, yet uses only a finite, common set of building blocks. Cells operate under a wide range of environmental conditions with efficiencies unmatched by artificial systems. They can be highly specialized and carry out tens of thousands of chemical reactions in parallel. The dimensional characteristics of cells are well conserved and undoubtedly critical for system function ( Welch, 1992 ; Hess and Mikhailov, 1994 ; Hochachka, 1999 ; Misteli, 2001 ; Harold, 2005 ). Short distances (nm–μm) enable intra- and intercellular communication using simple diffusion-based mechanisms. Also, the small fluid volume of a cell allows for small fluctuations in numbers of specific molecules to result in dramatic changes in cellular state. Higher order, nanoscale structuring ( Welch, 1992 ; Hochachka, 1999 ) and excluded volume effects ( Hall and Minton, 2003 ) are also known to be critical to cellular function. In fact, with regard to heredity, the spatial definition of the cell may be as important as the genetic material ( Harold, 2005 ). Here, we consider the potential for a nano-enabled synthetic biology that may be derived from the confluence of systems biology and nanoscale science and technology. At this confluence, systems biology provides knowledge of the chemical components that comprise the cell and the spatial and temporal interplay between these components. Initial efforts to mimic cells have followed a path of using soft materials that are similar or identical to cellular materials. However, the continued progress of nanoscale science and technology provides hope that many cellular attributes may be transferred to artificial systems through the control of the synthesis and assembly of hard nanoscale materials at the multiple size scales important to cellular function. In the process, advanced tools for understanding basic questions regarding biological function will be provided. Such developments could benefit both technology and science. Cell-like complexity in nanoscale systems may lead to significantly higher levels of function, whereas also forming an experimental system that would allow a much better examination of cellular organizational principles. Here, we highlight efforts to mimic cell-like systems and the emerging tools of nanoscience that may enable an even more synthetic biology."
} | 2,459 |
30050510 | PMC6050453 | pmc | 4,011 | {
"abstract": "Plant rhizospheres encompass a dynamic zone of interactions between microorganisms and their respective plant hosts. For decades, researchers have worked to understand how these complex interactions influence different aspects of plant growth, development, and evolution. Studies of plant-microbial interactions in the root zone have typically focused on the effect of single microbial species or strains on a plant host. These studies, however, provide only a snapshot of the complex interactions that occur in the rhizosphere, leaving researchers with a limited understanding of how the complex microbiome influences the biology of the plant host. To better understand how rhizosphere interactions influence plant growth and development, novel frameworks and research methodologies could be implemented. In this perspective, we propose applying concepts in evolutionary biology to microbiome experiments for improved understanding of group-to-group and community-level microbial interactions influencing soil nutrient cycling. We also put forth simple experimental designs utilizing -omics techniques that can reveal important changes in the rhizosphere impacting the plant host. A greater focus on the components of complexity of the microbiome and how these impact plant host biology could yield more insight into previously unexplored aspects of host-microbe biology relevant to crop production and protection.",
"conclusion": "Concluding Remarks and Future Directions Currently, there is a growing interest in developing a broader understanding of host-microbe biology. Similar to human and other animals, different plant compartments harbor distinct microbiomes, which could evolve and adapt with their host to influence the observed phenotypes. In essence, fitness is both influenced by and shared among multiple levels—the individual plant host and groups comprising its microbiome. Thus, the application of evolutionary frameworks, such as multilevel selection, to plant microbiomes could be useful in developing a more robust understanding of host-microbe interactions. Utilizing –omics techniques is key to uncovering potential mechanisms underlying group-level interactions in the rhizosphere. It is conceivable that cross-kingdom signaling dominates rhizosphere processes, which suggests that the definition of heritability should be inclusive of an individual and its associated microbiome. The plant host may influence the composition and function of the resulting microbiome, but microorganisms have the ability to modify plant traits. An applied outcome of studying group-level dynamics in the rhizosphere is the ability to incorporate concepts of the holobiont into plant breeding. Selection efforts that consider rhizosphere microbiomes as an extended phenotype of a plant could help identify potential mechanisms that enrich for subpopulations of the microbiome. These “plant-cultivated” members of the rhizosphere could play essential roles in supporting the development of specific phenotypes of the plant that improve plant growth under biotic or abiotic stress. However, plant genetics may not play a significant role in influencing the microbiome, but instead the plant may be highly susceptible to microbiome effects on plant traits. A greater understanding of how microbiomes influence the observed phenotype of a plant can help to tease apart the effect of environmental variables from biotic factors. For example, in studies involving genotype by environment interactions (G × E), phenotypic variation is assumed to be a result of plant genetics influenced by varying environmental conditions across field sites. In the near future, we expect that the low cost of microbiome sequencing methods will result in the adoption of rapid microbiome diagnostics revealing the role of microbiome variability across field sites in influencing plasticity of the plant phenotypes. In essence, there will likely be a shift toward analysis of genotype by environment by microbiome interactions (G × E × M) in the coming years. Finally, we believe that the current industry focus on examining single microbial isolate effects on plant traits will be replaced with more emphasis on complex interactions involving multiple players. The recent popularity of examining synthetic communities comprised of multiple microbial strains helps to advance microbiome science forward, but it would be beneficial to move beyond cultivation-dependent methods. Applying selective filters to reduce the diversity of complex microbiomes associated with a plant trait could enable more top-down and bottom-up approaches comprised of cultivation-dependent and –independent multi-player interaction studies. While teasing apart the complexity of the rhizosphere will be incredibly challenging, such research could ultimately help develop a better understanding of how rhizosphere microbiomes influence plant growth, development, and fitness.",
"introduction": "Introduction With growing interest in host-microbe biology, a mixture of new and re-established terms have been developed in recent years to describe complex associations of organisms that are heritable. The concept of the “holobiont” and its “hologenome” (i.e., a host and all of its microbial symbionts, and consequently, the collective genomes of the adaptive unit) ( Rosenberg and Zilber-Rosenberg, 2016 ) signify the potential for natural selection to act, not only on the individual, but also on its suite of associations with its microbial members. While much of the discussion on the holobiont–hologenome theory has focused on animals and their microbiomes, the concept appropriately extends to plants and their associated microbiomes. There is an extensive history of research detailing the co-evolutionary forces dually acting on plants and their microbial symbionts. For example, research on vesicular-arbuscular mycorrhiza (VAM) has suggested that the highly beneficial symbiosis between the plant root and fungal symbiont has driven the diversification of plant root morphology as well as VAM structure and function ( Brundrett, 2002 ). In addition, decades of legume research suggest that interactions, such as plant sanctions against nitrogen-fixing rhizobia, are largely what help stabilize the easily compromised legume-rhizobium mutualism ( Masson-Boivin and Sachs, 2017 ). In more recent years, the advent of next-generation sequencing and other -omics tools has generated interest in better understanding how more complex associations between plants and their microbiome, termed the “phytobiome” ( Leach et al., 2017 ), play a role in plant fitness, as well as plant health, growth, and development. Similar to animal microbiomes, different compartments of a plant can harbor functionally and taxonomically distinct sets of microbiomes—these include the phyllosphere microbiome encompassing the aboveground parts of plants, root, and shoot endophytes (microbiomes colonizing root and shoot tissues), and the rhizosphere microbiome that inhabits soil surrounding plant roots and adhering to root surfaces ( Turner et al., 2013 ). Although the rhizosphere is not a plant organ or a physically intact compartment of the plant, this narrow band of soil surrounding roots harbors a tremendous diversity of microorganisms that are free-living or intricately linked to their plant hosts ( Mendes et al., 2013 ). The root zone is an environment that is heavily enriched in compounds that are secreted by both plants and microorganisms, and play a key role in maintaining plant-microbe interactions ( Badri et al., 2009 ). The exudates include sugars, complex polysaccharides, amino acids, proteins, and a multitude of secondary metabolites ( Badri et al., 2009 ). An important component of these compounds includes signaling of host-microbe and microbe-microbe interactions ( Venturi and Keel, 2016 ). With hundreds of different microbial taxa inhabiting a plant’s rhizosphere, the possibilities of interactions shaping nutrient dynamics impacting plant growth are expansive. In this perspective, we discuss the background research on community evolution and genetics that are applicable to rhizosphere controls on nutrient cycling. We then propose conceptual ideas for experiments that explicitly test group-level dynamics in rhizospheres that can be targeted to alter nutrient capture and utilization processes impacting plant performance."
} | 2,091 |
34552159 | PMC8458526 | pmc | 4,012 | {
"abstract": "Thermal-stress events have changed the structure, biodiversity, and functioning of coral reefs. But how these disturbances affect the dynamics of individual coral colonies remains unclear. By tracking the fate of 1069 individual Acropora and massive Porites coral colonies for up to 5 years, spanning three bleaching events, we reveal striking genus-level differences in their demographic response to bleaching (mortality, growth, and recruitment). Although Acropora colonies were locally extirpated, substantial local recruitment and fast growth revealed a marked capacity for apparent recovery. By contrast, almost all massive Porites colonies survived and the majority grew in area; yet no new colonies were detected over the 5 years. Our results highlight contrasting dynamics of boom-and-bust vs. protracted declines in two major coral groups. These dangerous demographics emphasise the need for caution when documenting the susceptibility and perceived resistance or recovery of corals to disturbances.",
"introduction": "Introduction Climate change is rapidly transforming global ecosystems 1 , 2 . On coral reefs, bleaching-induced coral mortality has led to abrupt changes in their structure, biodiversity, productivity and functioning 3 – 7 . However, the majority of studies examining coral population dynamics have been based on coral cover or colony counts 1 , 6 , 8 – 11 . Only rarely is the fate of individual colonies considered over multiple years, especially during the critical post-bleaching ‘recovery’ period 12 – 15 . Long term evaluations of colony level changes enable the separation of immediate vs. delayed and partial vs. total colony mortality 16 , 17 . Furthermore, if considered across multiple bleaching events, colony-tracking may reveal cumulative impacts and allow the identification of genus and colony-level variation in the response to bleaching impacts. Using an extensive spatial design of fixed photo-quadrat locations (Fig. 1 ), we tracked the fate of 1069 coral colonies (in 362 quadrats spread across 16 km 2 on the Lizard Island reef complex) over 5 years (2016–2021), encompassing three mass bleaching events on the Great Barrier Reef (GBR). Lizard Island was at the epicenter of the first of these bleaching events on the GBR, and represents a critical arena in which to explore long-term responses of corals to bleaching 1 , 18 . We focus on colonies within two dominant coral genera, with contrasting life-histories and differences in bleaching susceptibility: massive Porites , which are slow-growing 19 and resistant to bleaching 20 , and Acropora (all growth forms) , which are fast growing but susceptible to bleaching 19 , 21 , 22 . Our goal was to evaluate the extent, magnitude and variability of colony-level susceptibility to successive bleaching events, as well as the potential demographic consequences and their implications for recovery. Figure 1 Timeline of the study with data collection instances (camera icons) and bleaching events (temperature gauges) with examples of quadrats (1 m 2 ) of the same reef section across repeated sampling periods showing the growth of new Acropora colonies. January 2018, 24 months after first sampling, January 2020, 48 months after first sampling, and February 2021, 60 months after first sampling. All photographs taken at Lizard Island by SB Tebbett.",
"discussion": "Results and discussion There were dramatic differences in the response to successive bleaching between the two coral types investigated (Fig. 2 ). Acropora colonies underwent complete local extirpation (i.e., 100% loss across all quadrats) in the 2 years following the first bleaching episode. Remarkably, however, there was also massive recruitment (i.e., the appearance of previously undetected colonies greater than 3 cm 2 ) of Acropora starting 2 years after the first bleaching, resulting in a 1000% increase in the number of colonies relative to the start of the study (Fig. 2 b). New colonies showed rapid growth, with an average 201% increase in colony size per year by the end of the study period (Fig. 3 ). Despite a tenfold increase in numbers and rapid growth, mean Acropora cover only increased from approximately 1% to 3%. Thus, it still remained low (< 3%) compared to historical levels of Acropora cover (from ~ 15 to 30% between 1995 and 2014 10 , likely reflecting an early ‘recovery’ trajectory (Fig. 2 a). Figure 2 ( a ) Coral cover of Acropora and massive Porites based on 362 quadrats over the 60 month time period. ( b ) Total number of Acropora and massive Porites coral colonies tracked over the 60 month time period spanning three bleaching events at Lizard Island, northern Great Barrier Reef. Photographs: Victor Huertas. Figure 3 Relative live colony area of Acropora and massive Porites colonies over 60 months (each line represents an individual colony). Relative live colony area is the horizontal planar area of living tissue on a colony relative to the value at first detection. The small inner graph represents a zoom showing the standardized live area of Acropora and massive Porites colonies during the first 24 months since first sampling. By contrast, the number of massive Porites colonies remained stable: there was only a 2.3% loss of colonies (2 colonies). But no new colonies were detected over the 5 years (Fig. 2 ). Surviving colonies showed an average increase in colony area of 21%, however, there was extensive among-colony variation in live tissue area changes (Fig. 3 ). Indeed, approximately half of the colonies suffered tissue loss. The extent of tissue loss was relatively well predicted by bleaching severity at the individual level (i.e., relative area of bleached tissue in the April 2016 bleaching event, Fig. 4 ). Thus, Acropora corals appear to be responding with a pronounced boom-and-bust pattern 23 , 24 , while massive Porites colonies exhibit a precarious degree of resilience, increasing in area but with an underlying recruitment deficit and a strong negative response in tissue area to bleaching severity (Fig. 4 b). Figure 4 ( a ) Relative area of live tissue on massive Porites colonies over 60 months. Each line represents a single colony, with line colors representing the proportion of bleaching in each colony (during the 2016 bleaching event). The red dotted line represents the average increase of 21% in colony area of massive Porites . ( b ) Effect of the proportional bleached area (in April-2016) on the subsequent relative change in live tissue area of massive Porites . Line and band show the prediction and 95% confidence intervals of a Gamma GLMM, while dots show raw data points. Modelling was performed in the software R 34 , using the glmmTMB package 35 . The solid horizontal line and arrows indicate where colonies effectively increased or decreased live tissue area. The dotted vertical line represents the minimum bleached area required, on average, to trigger tissue loss. mR 2 = marginal R 2 and cR 2 = conditional R 2 . Our findings agree with previous studies that show a high-susceptibility to thermal stress in Acropora 25 – 27 and a degree of resistance to thermal stress in Porites 25 , 28 . These contrasting responses to disturbances play an important role in structuring coral communities and are now more apparent than ever given the frequency and severity of disturbances impacting coral reefs 24 , 29 . While the devastating effects of climate change on corals have been emphasized numerous times 1 , 6 , 10 , 26 , 30 , the fate of individual coral colonies has rarely been tracked over multiple bleaching events over multiple years, particularly in conjunction with key demographics traits such as recruitment and growth. Quantifying these dynamics is critical to understand future trajectories of coral populations subject to changing disturbance regimes, especially in a scenario of shortening ‘recovery’ windows 31 – 33 . Acropora colony density at the start of the study was relatively low (85 trackable colonies, > 3 cm, across 362 quadrats (521.2 m 2 ) in 2016). This was primarily due to two back-to-back cyclones in 2014 and 2015 10 . Following these disturbances, the severe bleaching events in 2016 and 2017 led to complete loss of Acropora in our censused area. After this widespread mortality period, we documented a > tenfold increase in colony numbers between 2018 and 2021 (relative to the first sampling period), with 897 new colonies by 2021 (1.72 new colonies m −2 ). These seemingly high levels of population replenishment were observed despite large (89%) declines in coral settlement across GBR, especially in Acropora , following the bleaching events in 2016 and 2017 32 . It was anticipated that the GBR-wide decline in settlement would have severely compromised the recovery capacity of these corals, as it was estimated that recovery would take at least a decade, even for faster-growing corals such as Acropora 32 . Although coral replenishment can be highly variable across spatial scales 32 , 36 , the rate of appearance of new colonies in our study, especially following such a sharp decline in coral numbers, offers some hope for the future of coral reefs. Not only did new colonies of Acropora recruit in substantial numbers, but they also rapidly increased in size. Colonies initially detected in January 2018 had grown, on average, by 393% over 24 months. Peak detection of new colonies occurred in January 2020, and new colonies detected in 2020 and 2018 grew, on average, 211% between January 2020 and January 2021 (Fig. 3 ). Such fast growth is likely to underpin the perceived ‘potential recovery’ of Acropora, even as these ‘recovery’ windows between disturbances become shorter and shorter 32 . However, the realized long-term recovery of reef systems will depend on the capacity of these corals to persist in a scenario of increased frequency of extreme thermal events over the coming years 24 , 37 . The growth we observed resulted in a mean Acropora cover of just 3%, far below pre-bleach levels of coral cover. It may represent, therefore, just a short-term boom in a new Anthropocene configuration, where fast-growing corals persist but are unlikely to attain their former abundance due to successive disturbances and suppression of recovery dynamics 6 , 24 , 38 . Nevertheless, the responses we observed over five years highlight the remarkable potential for ‘boom and bust’ dynamics in Acropora , providing evidence that degraded coral reefs may still maintain some potential for apparent Acropora recovery, at least for a limited time and at the colony level. However, our findings also highlight the need for caution. Although massive Porites shows ecosystem-level resistance to bleaching, responses of individual colonies are highly variable 24 , 25 . Indeed, individual bleaching susceptibility (indicated by the maximum proportion of colony area observed to bleach) was able to predict long-term (60 month) individual massive Porites colony tissue loss (Fig. 4 a). Colonies that bleached more intensely also suffered heavier tissue loss, while those that bleached less intensely often grew in tissue area (Fig. 4 b). Nevertheless, even when massive Porites colonies suffered intermediate to high bleaching (in proportion to live colony area), their likelihood of recovery was much higher than Acropora colonies as noted previously 25 . Most importantly, however, despite censusing 521.2 m 2 of reef in extreme detail over 5 years, we did not record a single new massive Porites colony. This lack of apparent recruitment over half a decade suggests that massive Porites could be rare, a pattern supported by the examination of coral recruitment on tiles across large spatial scales post-bleaching 18 . However, the apparent rarity of Porites recruits could also be magnified by the difficulty of detecting Porites recruits in photos. Indeed, due to a combination of cryptic colouration, small size and slow growth, Porites recruits are likely to be harder to detect than Acropora recruits in photographs, potentially leading to an underestimation of relative recruitment in Porites 32 , 39 . Nevertheless, the scarcity of massive Porites recruitment throughout our study highlights the potential for protracted declines and storage effects 40 , 41 . Such protracted declines may be even more concerning than sudden dynamic shifts, as in Acropora abundance, as they may be easier to overlook or ignore, and harder to reverse 42 . Thus, our data has revealed how the colony-level population dynamics of two archetypical coral types, massive Porites and Acropora, have responded in distinctly different manners over multiple disturbances events caused by thermal stress and a short-term ‘recovery’ window. For weedy, fast-growing Acropora colonies, high susceptibility to bleaching and complete mortality was followed by substantial recruitment and fast growth, revealing a marked capacity for apparent ‘recovery’. However, the lifespan of these new colonies is already being tested as a fourth bleaching event began to unfold in January/February 2021, with marked paling of these new Acropora colonies (Supplementary Fig. 1 ). We also demonstrated the well-documented resistance of stress-tolerant colonies of massive Porites , with net positive growth over five years. However, the complete lack of new colonies over this same time frame (despite intensive sampling) suggests that recruitment is rare and, potentially, unpredictable. Without replacement, increasing repetitive bleaching events 30 , 43 , may drive a slow, protracted decline of massive Porites that could be easily overlooked. These markedly different demographic patterns offer grounds for both optimism and concern. Massive Porites are resistant, but potentially compromised in the long-term, while Acropora are vulnerable, but have greater capacity to recover in the aftermath of major disturbances 24 , 31 . In both cases their dangerous demographics require caution when interpreting the susceptibility and perceived resistance of corals to disturbances."
} | 3,533 |
33979170 | null | s2 | 4,013 | {
"abstract": "Microbial life on Earth exists within wide ranges of temperature, pressure, pH, salinity, radiation, and water activity. Extreme thermoacidophiles, in particular, are microbes found in hot, acidic biotopes laden with heavy metals and reduced inorganic sulfur species. As chemolithoautotrophs, they thrive in the absence of organic carbon, instead using sulfur and metal oxidation to fuel their bioenergetic needs, while incorporating CO"
} | 109 |
36574450 | PMC9829172 | pmc | 4,014 | {
"abstract": "Recent observations have revealed that closely related strains of the same microbial species can stably coexist in natural and laboratory settings subject to boom and bust dynamics and serial dilutions, respectively. However, the possible mechanisms enabling the coexistence of only a handful of strains, but not more, have thus far remained unknown. Here, using a consumer-resource model of microbial ecosystems, we propose that by differentiating along Monod parameters characterizing microbial growth rates in high and low nutrient conditions, strains can coexist in patterns similar to those observed. In our model, boom and bust environments create satellite niches due to resource concentrations varying in time. These satellite niches can be occupied by closely related strains, thereby enabling their coexistence. We demonstrate that this result is valid even in complex environments consisting of multiple resources and species. In these complex communities, each species partitions resources differently and creates separate sets of satellite niches for their own strains. While there is no theoretical limit to the number of coexisting strains, in our simulations, we always find between 1 and 3 strains coexisting, consistent with known experiments and observations.",
"introduction": "Introduction Microbial communities in almost all natural settings are characterized by an astonishing diversity, manifesting itself at multiple evolutionary scales [ 1 , 2 ]. These scales range from separate domains (e.g., archaea and bacteria) all the way down to closely-related strains of the same species [ 3 – 7 ], other environments. This wide-ranging diversity can persist even in well-controlled laboratory settings, containing alternating cycles of exponential growth, followed by a transfer to fresh media after dilution by a large factor [ 8 , 9 ]. The coexistence of distantly related community members, such as different species or kingdoms, can be readily explained via niche theory, which suggests that each species can occupy a different niche, e.g., by specializing on a different resource, allowing everyone to coexist [ 10 – 15 ]. Remarkably, it is the coexistence of fine-scale diversity—that is, closely related strains of the same species—that remains puzzling [ 7 , 16 , 17 ]. This is because presumably, such strains haven’t diverged sufficiently to establish and occupy distinct resource niches. Thus, the observation of fine-scale diversity suggests that every resource might contain multiple niches: a primary niche and several “satellite” niches, ready to be occupied by closely related strains, enabling their coexistence. Here, the primary niche is occupied by a strain most competitive at high nutrient concentrations, and each “satellite” niche is occupied by a strain which is more competitive in a specific range of lower nutrient concentrations. Satellite niches are not expected in stable environments, where resources are supplied continuously at a constant rate and reach a fixed concentration, such as in a chemostat. In these conditions, competitive exclusion guarantees that only the strain best adapted to the steady-state concentration will be able to survive [ 13 ]. In contrast, in fluctuating environments where nutrient concentrations change in time, the existence of satellite niches remains a possibility [ 18 – 20 ]. Indeed, in the extreme case of environmental fluctuations, i.e., in boom and bust cycles, where resource concentrations may vary over orders of magnitude, there is ample opportunity for several strains to coexist [ 21 , 22 ]. Furthermore, strains of the same species may rapidly (with just a few mutations [ 23 ]) modify the range of nutrient concentrations optimal for their growth, allowing for rapid colonization of the available satellite niches by closely related strains, rather than by members from distant species. In conclusion, satellite niches may arise as a consequence of boom and bust cycles, and then be occupied by different strains of the same species, allowing their coexistence. Here, we use a consumer-resource model of microbial communities to demonstrate how satellite niches appear and are colonized, over the process of community assembly. We start by considering the case of a single resource, and show that in this case, anywhere between 1 and 3 strains typically coexist. Indeed, the coexistence of even more strains is possible, but has a small likelihood. We then proceed to generalize our results to multiple resources (or niches), colonized by distantly-related species. In this case, each of the species comprises a small number of closely-related strains, which can coexist due to the presence of satellite niches. Our results provide a possible mechanism for the widespread observation of fine-scale diversity in natural as well as laboratory microbial communities.",
"discussion": "Discussion In this paper, we showed that in time-varying environments, the competitive exclusion principle can be broken through the formation of a few satellite niches alongside the primary resource niche. These niches can be occupied by closely related strains belonging to the same species, which rapidly diversify in two key parameters, i.e., their maximum growth rate and resource affinity. Our results add to a substantial body of work investigating how nonlinearities in resource-dependent growth (i.e., Monod growth) can lead to violations of the competitive exclusion principle [ 21 , 22 , 29 ]. As in these studies, in our work satellite niches only appear in time-varying environments, such as the boom and bust cycles we investigated here, and completely disappear in static environments, such as chemostats. In chemostat-like static environments, resource concentrations and microbial abundances reach a fixed value at steady state, resulting in strict competitive exclusion, where only one strain can survive per resource (primary niche). The main property of time-varying environments that create satellite niches is that resource concentrations change with time, creating opportunities for different strains to specialize and be more competitive in different concentration ranges. Specifically, our work provides new mathematical expressions for the coexistence criteria applicable to two strains, connecting several relevant parameters, especially the time period between successive growth-dilution cycles, the dilution factor, as well as the growth parameters of the strains (Eqs (3) – (5) ). Another new aspect of our study relative to prior work in this area, in particular Ref. [ 22 ], is the coexistence of multiple (≥3) strains of each of the species in environments with more than one supplied resource (primary niches). It is reasonable to expect that strains could modify the ratio in which they consume different resources, i.e., change how they allocate their enzyme budgets. Following in the footsteps of Good et al. [ 30 ], we adapted our model and extended it to include the possibility of small variations in resource budget allocation by closely related strains. We found that variation in budget allocation alone rarely (1% of simulations) leads to coexistence of multiple strains, compared with variation in growth parameters alone (11.8% of simulations, Fig B in S1 Text ). Thus, satellite niches created by boom and bust cycles chiefly select for variation in such growth parameters. The existence of organisms which specialize either on rapid growth ( r -strategists) or more complete depletion of the available resources ( K -strategists) is well-established in natural ecosystems [ 24 , 25 , 31 ]. Examples include microbes residing in Earth’s upper ocean, where r -strategists dominate in strongly seasonal temperate oceans, while K -strategists dominate in stable, low-seasonality, equatorial marine environments [ 32 , 33 ]. However, whether such r - and K -strategists can coexist in the same environment has not been fully explored. Our results show that r - and K -strategists may indeed coexist as closely related strains of the same species, both in simple and complex multi-species, multi-resource environments. These predictions also match spatial distributions of strain diversity of microbial populations in Earth’s upper oceans predicted in ref. [ 34 ]. While the strain diversity in highly seasonal environments (up to 8) was somewhat higher than predicted by our model (up to 3), the authors readily admit that their predictions might be somewhat inflated by ocean dynamics, transiently mixing organisms from different habitats. Furthermore, rapid and continuous evolution might also increase the apparent diversity of a community, due to transient strains generated by mutations and ultimately lost due to competitive exclusion. Our model included a fixed pool of strains and provided sufficient time to achieve a steady state as a result of competitive exclusion, and thus ignored the transient diversity due to rapid evolution. Our work intriguingly suggests that a trade-off between Monod growth parameters ( g max and 1/ K ) promotes coexistence, and thus might be observed among coexisting microbial strains in natural communities. Past work [ 35 , 36 ] has indicated similar trade-offs between maximal growth rate and efficiency, or yield (the fraction of environmental carbon converted to biomass), some even suggesting that these trade-offs become more pronounced at lower taxonomic levels [ 35 ]. While the yield or efficiency parameter in these studies does not influence two-strain coexistence in our model ( S1 Text ), a trade-off between maximal growth rate ( g max ) and affinity (1/ K ) in our model has been discussed and reviewed in Ref. [ 37 ], suggesting that they might promote coexistence in natural bacterial and phytoplankton communities. Future work examining such a trade-off and its causal implication for coexistence would be fruitful. Another natural environment in which limited strain diversity may have been detected is the human gut microbiome [ 7 ], with a previous study reporting the coexistence of a few strains (between 1 and 3, termed “oligo-colonization”). In particular, the authors mention that “it is not clear what mechanisms would allow for a second or third strain to reach intermediate frequency, while preventing a large number of other lineages from entering and growing to detectable levels at the same time”. Our work, in quantitative agreement with these observations, suggests that a possible mechanism explaining them might be that closely related strains differ in their growth parameters ( g max and K ) by which they consume resources. “Oligo-colonization” is not limited to natural environments such as ocean and gut microbiomes, but also likely manifests in microbial communities domesticated in the lab [ 16 ]. In these domesticated communities, between 1 and 2 closely related strains of the same species were found to coexist over multiple (∼70) boom and bust (serial dilution) cycles, consistent with the predictions of our model. Thus, taken together, our model explains a possible mechanism by which such “oligo-colonization” of a small number of closely related strains might be widespread in both natural and laboratory-domesticated microbial communities."
} | 2,809 |
39506351 | PMC11540873 | pmc | 4,016 | {
"abstract": "Abstract Microorganisms in large‐scale bioreactors are exposed to heterogeneous environmental conditions due to physical mixing constraints. Nutritional gradients can lead to transient expression of energetically wasteful stress responses and as a result, can reduce the titres, rates and yields of a bioprocess at larger scales. To what extent these process parameters are impacted is often unknown and therefore bioprocess scale‐up comes with major risk. Designing platform strains to account for these intermittent stresses before introducing synthesis pathways is one strategy for de‐risking bioprocess development. For example, Escherichia coli strain RM214 is a derivative of wild‐type MG1655 that has had several genes and whole operons removed from its genome based on their metabolic cost. In this study, we engineered E. coli strain RM214 (referred to as WG02) to produce octanoic acid from glycerol in batch‐flask and fed‐batch bioreactor cultivations and compared it to an octanoic acid‐producing E. coli MG1655 (WG01). In batch flask cultivations, the two strains performed similarly. However, in carbon limited fed‐batch bioreactor cultivations, WG02 provided a greater than 22% boost to biomass compared to WG01 while maintaining similar titres of octanoic acid. Reducing the biomass accumulation of WG02 with nitrogen limited fed‐batch cultivation resulted in a 16% improvement in octanoic acid titre over WG01. Finally, in a scale‐down system consisting of a stirred tank reactor (representing a well‐mixed zone) and plug flow reactor (representing an intermittent carbon starvation zone), WG02 again improved octanoic acid titre by almost 18% while maintaining similar biomass concentrations as WG01.",
"conclusion": "CONCLUSION Within these experiments, we found that the cost or benefit of genome reduction greatly depends on the cultivation mode. Other than a small increase in biomass yield, WG02 provides no substantial benefit when compared to WG01 in batch‐flask cultivations. However, depending on the fed‐batch bioreactor conditions, WG02 may primarily benefit either biomass yield (in a carbon limitation) or octanoic acid yield (in a nitrogen limitation). Furthermore, when exposed to intermittent carbon starvation conditions, WG02 maintained both a higher biomass and octanoic yield compared to WG01. Whether through intermittent carbon starvation stress or nitrogen limitation, we showed that genome reduction can improve heterologous product accumulation on glycerol. It is worth emphasizing however that WG02 is not superior in all cultivation conditions, stressing that future applications of genome reduced strains should always be compared to their parent strains to confirm improvements or shortfalls if any.",
"introduction": "INTRODUCTION A successful bioprocess depends on coordinating strain engineering, feedstock preparation, bioreactor operation and downstream processing. In combination, these unit operations can leverage organisms to create sustainable alternatives to traditional petrochemical processes (Pfleger & Takors, 2023 ). However, to be economically competitive, bioprocesses must be scaled to supply sufficiently large volumes of a product while maintaining high titres, fast rates and maximized yields. Unfortunately, as bioreactor volumes increase, these core process parameters cannot always be maintained. Often, reduced performance can be traced to the physical limitations of mixing large culture volumes. Increased mixing times leads to inhomogeneous distribution of nutrients and a distribution of cellular performance states, many of which are sub‐maximal. For this reason, designing bioprocesses based solely on ideal laboratory bioreactor operation is considered a major risk (Crater & Lievense, 2018 ). To minimize the risk of scale‐up failure, engineers design and evaluate strains in conditions that mimic final bioprocess conditions. This concept can include utilizing the final intended nutrient feed stock in early laboratory cultivations, limiting laboratory cultivations to achievable mixing parameters at scale such as oxygen uptake rate, and evaluating strains in scale‐down systems which mimic the distribution of nutritional environments experienced by cells at large scale. These approaches can help by building strains that are better suited to the stresses at scale and maintain required production parameters throughout the scale‐up process. One approach to reducing the impact of the reported environmental heterogeneities at scale is genome reduction. In this context, genome reduction refers to the removal of unnecessary or costly genes from the host organism to prevent wasteful expenditures during, often transient, stress responses seen at scale. Genome reduced strains may be more efficient, in that the saved energy and carbon could instead be used for either biomass accumulation, expression of heterologous genes or synthesis of more product (Ziegler & Takors, 2020 ). However, the exact interplay of heterologous gene burden, reduced cellular maintenance, and production heterogeneity is not always clear. Genome reduction does not show the same benefits at every scale, production phase or cultivation condition (Cordell et al., 2023 ; Ziegler et al., 2021 ). In one example, Pseudomonas putida strain EM42, a genome‐reduced strain, produced more protein than wild‐type P. putida KT2440 in batch fermentations, but also acquired additional chemical sensitivities compared to wild‐type (Amendola et al., 2024 ; Lieder et al., 2015 ). A similar genome reduced strain, Escherichia coli RM214, was designed based on the transcriptional response of E. coli MG1655 to temporary or transient glucose starvation conditions in a scale‐down reactor. Genes that were upregulated the most during starvation were removed if they were deemed to be unnecessary and unrelated to central metabolism. Deletion targets included flagella and chemotaxis gene clusters; proteins that consumed substantial cellular resources for their synthesis and operation yet were not required to survive transient starvation in a mixed reactor. In these experiments, RM214 maintained a similar maximum growth rate and biomass yield in batch‐flask cultivations when compared to wild‐type. Additionally, RM214 was found to have a lower maintenance energy when grown in a scale‐down reactor with intermittent glucose starvation in a chemostat mode. When expressing eGFP from a rhamnose inducible plasmid during intermittent glucose starvation, RM214 maintained both a greater proportion of high eGFP producing cells and a higher total eGFP yield over 28 h compared to wild‐type (Ziegler et al., 2021 ). While useful for evaluating growth parameters, chemostat cultivations may be less representative of the typical fed batch strategies used in industry. In this study, we explore the impact of the genome reduced strain RM214 on microbial oleochemical production in a fed batch environment with glycerol as a substrate. We reasoned that the more efficient RM214 background may provide excess energy and potentially improve heterologous chemical production in industrially relevant cultivation modes. Glycerol as a byproduct of biodiesel, has already been used to produce microbial lipids, showing its potential as a substrate for fatty acid derived products or oleochemicals (Kosamia et al., 2020 ). Within this oleochemical production space, the demand for medium chain (C8‐C12 acyl chain) species is likely to only increase due to their scarcity in natural and petrochemical sources (Su et al., 2024 ). Microbial production of these oleochemicals, through expression of chain length specific enzymes, may prove more sustainable if scaled to industrial levels. By integrating the eight‐carbon specific thioesterase (CupTE) into the genomes of RM214 and its MG1655 wild‐type parent, we investigated the impacts of genome reduction on octanoic acid production in batch‐flask, carbon limited fed‐batch, nitrogen limited fed‐batch and a carbon starvation scale‐down reactor (Hernández Lozada et al., 2018 ).",
"discussion": "RESULTS AND DISCUSSION Validation of octanoic acid production in batch flask cultivations To build the octanoic acid producing strains, we replaced the fadD locus with an IPTG‐induced thioesterase (CupTE) expression cassette in both E. coli MG1655 and the reduced genome E. coli RM214 (Figure 1B ) (Hernández Lozada et al., 2018 ). The markerless cassette was integrated in using λ‐red recombineering and Cas9‐mediated removal of the fadD locus (see methods) to create strains WG01 (MG1655 background) and WG02 (RM214 background) (Datsenko & Wanner, 2000 ). The removal of fadD and integration of a thioesterase blocks β‐oxidation, allowing accumulation of thioesterase‐generated octanoic acid in culture (Figure 1A ). To confirm octanoic acid production and complete glycerol consumption, cells were cultured in minimal media for 72 h in a shake flask at 30°C. The starting 10 g/L glycerol was completely consumed by both strains, and the final octanoic acid titres were – 478 ± 5 mg/L for WG01 and 426 ± 13 mg/L for WG02 (Figure 1C and Table 3 ). The final biomass titre of WG02, reported as dry cell weight per litre (gDCW/L), was slightly higher (2.69 ± 0.12 g/L) than WG01 (2.42 ± 0.06 g/L) (Figure 1C and Table 3 ). Both strains produced acetate with WG02 accumulating more than four times more acetate than WG01 but with greater variability. With only a final 72‐h point, more subtle changed in acetate production and consumption over the flask experiment may not be captured however these data still speak to the efficiency of strains in a batch cultivation (Figure 1C and Table 3 ). Overall, WG02 maintained slight increase in biomass concentration compared WG01, but as has been seen in previous batch flask studies case (Ziegler et al., 2021 ). The RM214 background did not show any benefit to octanoic acid production and produced more acetate in this case. TABLE 3 Relevant process parameters for experiments conducted in this paper. Strain WG01 WG02 WG01 WG02 WG01 WG02 WG01 WG01 WG02 Cultivation Conditions Batch‐flask Batch‐flask Carbon limited fed‐batch bioreactor Carbon limited fed‐batch bioreactor Nitrogen limited fed‐batch bioreactor Nitrogen limited fed‐batch bioreactor Carbon limited fed‐batch bioreactor Carbon limited fed‐batch bioreactor Carbon limited fed‐batch bioreactor Replicates 3 3 3 3 3 3 2 2 2 Stress NA NA NA NA NA NA NA PFR Carbon Starvation PFR Carbon Starvation Starting volume (mL) 50 50 700 700 700 700 1400 1400 1400 Glycerol Base media (g/L) 10 10 2 2 2 2 2 2 2 Glycerol fed (g) NA NA 9.67 ± 0.20 9.73 ± 0.00 9.14 ± 0.20 9.24 ± 0.01 20.44 ± 0.22 20.45 ± 0.64 20.57 ± 0.32 Octanoate (mg/L) 478 ± 5 425 ± 13 838 ± 28 873 ± 46 846 ± 85 991 ± 125 927 ± 10 1017 ± 9 1238 ± 29 gDCW/L 2.42 ± 0.06 2.69 ± 0.12 3.76 ± 0.09 4.86 ± 0.10 3.62 + 0.10 4.07 + 0.06 3.64 ± 0.24 3.72 ± 0.08 4.02 ± 0.12 Acetate (g/L) 0.06 ± 0.02 0.25 ± 0.18 0.62 ± 0.08 <0.1 0.61 ± 0.1 0.24 ± 0.06 1.47 ± 0.11 1.05 ± 0.14 0.33 ± 0.03 Yps (mol/mol) 0.031 ± 0.000 0.027 ± 0.001 0.039 ± 0.002 0.040 ± 0.002 0.040 ± 0.003 0.048 ± 0.006 0.039 ± 0.001 0.043 ± 0.001 0.052 ± 0.001 Yxs (g/g) 0.24 ± 0.01 0.27 ± 0.01 0.25 + 0.01 0.33 + 0.01 0.24 ± 0 0.00 0.27 + 0.00 0.23 ± 0.00 0.23 ± 0.01 0.25 ± 0.00 \n Note : octanoic acid, gDCW/L, and acetate are endpoint values and yield calculations include base media glycerol in their calculations. Y xs includes a correction for the starting OD 600 of the cultures. Error represents standard deviation for experiments of three replicates and absolute error for experiments with two replicates. See Appendix S1 for raw data. Genome reduction improves biomass yield in carbon limited fed‐batch cultivations To further evaluate RM214 and wild‐type strains in a more industrially relevant scenario, we cultivated each strain in bioreactors while applying a carbon limited exponential feeding strategy (Figure 2A ). Upon complete consumption of the 2 g/L glycerol in the batch phase, an exponential feed was initiated, and the cells were induced by the addition of IPTG. During the fed‐batch phase, WG01 was fed 9.73 ± 0.00 grams of glycerol and WG02 was fed 9.67 ± 0.26 g of glycerol (Table 3 ). After the fed‐batch phase, we observed octanoic acid titres of 873 ± 46 mg/L for WG02 and 838 ± 28 mg/L for WG01 (Figure 2C and Table 3 ). Additionally, WG02 generated ~22% higher biomass titre compared to WG01 (4.86 ± 0.10 vs. 3.76 ± 0.09 gDCW/L) (Figure 2C and Table 3 ). Interestingly, a biomass increase was not noted in previous chemostat experiments comparing eGFP‐producing RM214 and wild‐type strains, however these experiments were completed with glucose as a substrate (Ziegler et al., 2021 ). Finally, WG02 accumulated less acetate (<0.1 g/L) than WG01 (0.62 ± 0.08 g/L) (Figure 2C and Table 3 ). These data indicate that in a carbon limited fed‐batch, the primary benefits of genome reduction are a minor increase in octanoic acid titre, reduced acetate accumulation, and increased biomass yield on glycerol. Genome reduction alters product yield and reduces acetate formation in nitrogen limited fed‐batch cultivations FIGURE 2 (A) Experimental setup for the carbon limited fed‐batch. (B) OD 600 of WG01 and WG02 throughout the cultivation with a dotted line to separate the Batch and Fed‐batch phases. (C) Final octanoic acid, acetate, and biomass (gDCW/L) titre after 24 h of an exponential feed. Error bars represent the standard deviation of 3 biological replicates and statistical significance is marked by an asterisk representing a p ‐value of less than 0.05 for a two‐sided t ‐test with variance considered. See Appendix S1 for raw data. Given WG02 had a higher biomass yield on glycerol, we reasoned that an alternative nutrient limitation, such as nitrogen, could potentially shift carbon and energy flux to octanoic acid or potentially other byproducts rather than biomass (Rajpurohit & Eiteman, 2022 ). Informed by previous nitrogen limitation experiments, we maintained a C:N ratio of approximately 8.5 mol/mol during the cultivation to ensure nitrogen limited growth (Löffler et al., 2017 ). During the fed‐batch phase, WG01 and WG02 strains were fed 9.14 ± 0.20 and 9.24 ± 0.01 g of glycerol respectively. The final octanoic acid titre for WG02 (991 ± 125 mg/L) was higher than WG01 (828 ± 85 mg/L) (Figure 3C and Table 3 ). WG02 acetate titres were again reduced relative to WG01 (Figure 3C and Table 3 ). The final CDW for WG02 (4.07 ± 0.06 gDCW/L) and WG01 (3.62 ± 0.10) was reduced compared to the carbon limited fed‐batch by ~16% and ~4% respectively compared to the carbon limited fed‐batch (Figures 2C and 3B,C and Table 3 ). Overall comparing carbon and nitrogen limited fed‐batch strategies, WG02 had a small benefit to biomass yield, but primarily improved octanoic acid production, although with greater variability under nitrogen limitation. WG01 in contrast, maintained a similar octanoic acid titre (less than 1% difference) and biomass production to the corresponding carbon limited fed‐batch (Figures 2 and 3 ). FIGURE 3 (A) Experimental setup for the nitrogen limited fed batch including a feed and batch phase media with a combined molar C:N ratio of approximately 8.5:1. (B) OD 600 of WG01 and WG02 throughout the cultivation with a dotted line to separate the batch and fed‐batch phase. (C) Final octanoic acid, acetate and biomass (gDCW/L) titre after 24 h of an exponential feed. Error bars represent the standard deviation of 3 biological replicates and statistical significance is marked by an asterisk representing a p ‐value of less than 0.05 for a two‐sided t ‐test with variance considered. See Appendix S1 for raw data. Genome reduction results in a higher biomass and octanoic acid yield during intermittent glycerol starvation In a final experiment, we grew WG01 and WG02 in a scale‐down reactor mimicking an intermittent carbon starvation stress (Figure 4A and Figure S2 ). To first verify the differing reactor cultivation did not significantly alter cultivation outcomes, we first grew WG01 without any PFR stress. Product yields were the same and biomass yields were less than 9% different when comparing WG01 cultivations from the previous carbon limited cultivation described in Figure 2 , suggesting little effect (see Table 3 ). For each condition, approximately the same amount of glycerol was fed to each reactor (Table 3 ). To confirm the scale‐down reactor was sufficiently stressing the cells to illicit a response, we next compared growth of WG01 in both an STR (with no glycerol starvation stress) and an STR‐PFR (with intermittent glycerol starvation). To our surprise after completion of the fed‐batch phase, cultivation in an STR‐PFR led to an improvement in octanoic acid titre, from 927 ± 9 mg/L to 1017 ± 10 mg/L and a reduction in acetate accumulation (Figure 4C and Table 2 ), despite less than a 2% difference in biomass titre. Culturing WG02 in an STR‐PFR resulted in both an increase in the final titre (1238 ± 29 mg/L) and in the gDCW/L (4.02 ± 0.12) and a reduction in acetate (0.33 ± 0.03 g/L) compared to WG01 (Figure 4B,C and Table 3 ). WG02 appears to be significantly limited in its final biomass compared to the unstressed carbon limited fed‐batch (Figure 2C ), and instead maintains a higher octanoic acid titre, like the nitrogen limited conditions shown in Figure 3C . Additional analysis of glycerol and acetate over time is included in Figure S4 showing a very slight accumulation of glycerol (less than 0.25 g/L) for WG01 in the STR and STR‐PFR cultivations. A consequence of this may be that the carbon starvation stress is less strenuous along the PFR for WG01 if it does not completely consume glycerol during the fed‐batch phase in the STR. FIGURE 4 (A) Experimental setup for the carbon limited fed‐batch cultivation including both an STR and PFR reactor to simulate poor mixing conditions. (B) OD 600 of WG01 and WG02 strains throughout the cultivation with a dotted line to separate the batch and fed‐batch phase. (C) Final octanoic acid, acetate and biomass (gDCW/L) titre after 24 h of an exponential feed. Error bars represent the absolute error of biological duplicates. See Appendix S1 for raw data. The overall carbon balance of the STR and STR‐PFR cultivations inform how the scale‐down stress and genome reduction alters cellular expenditures. During carbon starvation, WG01 appears to shift acetate accumulation primarily to CO 2 and octanoic acid production but maintained a similar biomass titre, whereas WG02 accumulated relatively little acetate, and instead produced more biomass, octanoic acid and carbon dioxide compared to wild‐type (Figure 5 ). The relatively lower fraction of biomass and higher fraction of CO 2 may be a result of diverting carbon to the octanoic acid product and additional CO 2 released in the initiation of fatty acid production. Given the unknown fraction of this carbon balance, it is also possible that the extraction methodology used in these experiments underestimates the total octanoic acid produced or that other byproducts were not captured in our analysis. Furthermore, it is unclear to what extent each strain relies on the glyoxylate shunt when consuming glycerol. The increased fraction of carbon dioxide may suggest that RM214 utilizes the full TCA cycle more to support increased octanoic acid production. FIGURE 5 Carbon balance of the STR and STR‐PFR cultivations including glycerol fed in the batch and fed‐batch phase, and octanoic acid, DCW, acetate and total carbon dioxide produced by the end of the cultivation. See Appendix S1 for raw data.\n\nDISCUSSION In comparing RM214 and wild‐type strains for octanoic acid production, we first showed that in batch flask WG02 had a reduced titre but slightly more biomass and acetate in a batch‐flask cultivation after 72‐h (Figure 1C and Table 3 ). When scaled to a carbon limited fed‐batch, WG02 grew faster than its wild‐type counterpart leading to a higher biomass yield and slightly improved octanoic acid titre (Figure 2B,C and Table 3 ). Considering this result occurred in the carbon limited fed‐batch without a carbon starvation condition, likely either the glycerol itself as a carbon source or the carbon limitation induced a stress response in the cell. If true this could lead to expression of chemotaxis and flagellar genes, as has been suggested in previous minimal media experiments (Bhatia et al., 2022 ; Liu et al., 2005 ). Additionally, the cost of continued flagellar motion could also lead to significant energy saving in RM214 (Schavemaker & Lynch, 2022 ). In theory, if these genes are expressed in WG01 and not WG02, the excess energy and carbon could be directed to either product formation, maintenance, or biomass. The results from Figure 2 show that in a carbon limited fed‐batch, WG02 will spend its excess resources primarily on biomass generation. An added benefit of WG02 seen in all fed‐batch cultivations is also reduced acetate accumulation (Figures 2C , 3C and 4C ). Interestingly, while there have been previously reported glycerol‐based fed‐batch cultivations for fatty acid production, acetate was not noted as a major side product (Lu et al., 2008 ). Utilizing a nitrogen limited fed‐batch, we successfully reduced the biomass accumulation seen in Figure 2 , resulting in an increase in octanoic acid titre and yield (Figure 3 , Table 3 ). Comparing the carbon and nitrogen limitations, WG01 approximately maintained both its biomass and product yields, whereas WG02 had a significant reduction (~21%) in biomass yield and a significant increase (~16.7%) in product yield in nitrogen limited conditions, although with increased variability in the latter (Table 3 ). These results suggest that the previously reported maintenance benefits of RM214 are more obvious as growth rates are reduced under nutrient limited conditions. In nitrogen limited conditions, we saw benefits to octanoic acid production and a reduction of acetate accumulation. Finally, we evaluated the effect of an intermediate carbon starvation for WG01 and WG02 strains. Surprisingly, we found that a starvation stress did not affect biomass accumulation but instead led to a modest increase in product titre, reduced acetate accumulation, and a similar OD 600 and final DCW for the WG01 cultivation (Figure 3B,C ). One possible reason for the increase in octanoic acid titre could be that cell growth is halted within the carbon starvation zone, by limiting glycerol backbones for phospholipid biosynthesis but fatty acid biosynthesis continues. Carbon starvation is known to induce the stringent response, leading to an increase ppGpp levels which decreases phospholipid production though the regulation of PlsB (Noga et al., 2020 ). So, fatty acyl‐ACPs may continue to be made, and potentially converted to free fatty acids by CupTE, but ultimately cannot be converted to phospholipids. Comparing WG02 to WG01 in an STR‐PFR cultivation showed a more than 17% improvement octanoic acid titre (Figure 3C ) and a greater than 7% increase in biomass for WG02 (Figure 3B,C ). The result supports that removal of unnecessary genes typically expressed during carbon starvation may provide a surplus of energy for alternative functions in the cell if grown in a carbon stressed condition. Assessing the carbon balance between WG01 and WG02, with approximately 80–85% of the carbon moles accounted for, WG02 appears to produce more carbon dioxide and octanoic acid, whereas WG01 produces relatively more acetate (Figure 5 ). However, it is not immediately clear why acetate is produced as a byproduct, or why WG02 produces less acetate overall when grown on glycerol. Previous analysis suggested glycerol induces an acetate recycling mechanism in which poxB , along with acetate reuptake through increased expression of ACS and pta (Martínez‐Gómez et al., 2012 ). If additional energy is available in WG02, this may allow efficient reuptake of acetate (2 ATP equivalent via ACS or 1 ATP via ackA‐pta), which is then committed to either the TCA cycle or fatty acid production (Wolfe, 2005 ). Alternatively excess energy could reduce the need for acetate recycling, and in combination with increased acetyl CoA demand in fatty acid biosynthesis, less acetate is then produced from acetyl‐CoA or pyruvate. Considering future metabolic engineering efforts, LB glucose batch‐flask cultivations have shown significantly reduced acetate accumulation with the removal of poxB and ackA‐pta . However, removal of these genes has also resulted in reduced fatty acid titre in production strains (Li et al., 2012 ). Whether acetate production or re‐uptake, more research is needed to understand the driving factor for acetate accumulation for WG01 and WG02 during octanoic acid production. While this report focuses on comparing the efficiency of strains in various fed batch cultivations, other considerations for future work could be if genome reduction has any effect on the toxic final titres of fatty acid production. Previous reports suggest a toxic limit of octanoic acid is around 2 g/L and for mixed medium chain fatty acid products is just below 4 g/L in E. coli (Hernández Lozada et al., 2018 ; Wu et al., 2017 ). Future tolerance experiments should also consider previously reported adaptive laboratory evolution mutations and known metabolic engineering strategies in stressed fed‐batch cultivations (Chen et al., 2020 ; Lennen et al., 2023 ; Yan & Pfleger, 2020 ). This strategy will ensure the modifications are beneficial in a strain endogenously producing octanoic acid in industrial‐like scenarios."
} | 6,434 |
29234312 | PMC5712364 | pmc | 4,017 | {
"abstract": "Microbial communities that inhabit environments such as soil can contain thousands of distinct taxa, yet little is known about how this diversity is maintained in response to environmental perturbations such as changes in the availability of carbon. By utilizing aerobic substrate arrays to examine the effect of carbon amendment on microbial communities taken from six distinct environments (soil from a temperate prairie and forest, tropical forest soil, subalpine forest soil, and surface water and soil from a palustrine emergent wetland), we examined how carbon amendment and inoculum source shape the composition of the community in each enrichment. Dilute subsamples from each environment were used to inoculate 96-well microtiter plates containing triplicate wells amended with one of 31 carbon sources from six different classes of organic compounds (phenols, polymers, carbohydrates, carboxylic acids, amines, amino acids). After incubating each well aerobically in the dark for 72 h, we analyzed the composition of the microbial communities on the substrate arrays as well as the initial inocula by sequencing 16S rRNA gene amplicons using the Illumina MiSeq platform. Comparisons of alpha and beta diversity in these systems showed that, while the composition of the communities that grow to inhabit the wells in each substrate array diverges sharply from that of the original community in the inoculum, these enrichment communities are still strongly affected by the inoculum source. We found most enrichments were dominated by one or several OTUs most closely related to aerobes or facultative anaerobes from the Proteobacteria (e.g., Pseudomonas, Burkholderia , and Ralstonia ) or Bacteroidetes (e.g., Chryseobacterium ). Comparisons within each substrate array based on the class of carbon source further show that the communities inhabiting wells amended with a carbohydrate differ significantly from those enriched with a phenolic compound. Selection therefore seems to play a role in shaping the communities in the substrate arrays, although some stochasticity is also seen whereby several replicate wells within a single substrate array display strongly divergent community compositions. Overall, the use of highly parallel substrate arrays offers a promising path forward to study the response of microbial communities to perturbations in a changing environment.",
"introduction": "Introduction From the soil under our feet to the deepest sedimentary basins, microbial life inhabits nearly every environment on Earth (Whitman et al., 1998 ). The abundance and activity of the individual populations that comprise these communities change dynamically in response to changes in their local environment (Nemergut et al., 2013 ). The composition of microbial communities has been linked to specific parameters like water chemistry in environments such as lakes (Youngblut et al., 2014 ), streams (Zeglin, 2015 ), wetlands (Baldwin et al., 2006 ; Peralta et al., 2010 ; Dalcin Martins et al., 2017 ), and aquifers (Flynn et al., 2013 ; Hug et al., 2015 ; Kirk et al., 2015 ). In seawater, for example, the abundance of individual populations of bacteria have been shown to oscillate in sync with changes in light, temperature, and salinity (Eren et al., 2013 ; Ottesen et al., 2014 ). Soil, however, possesses such extreme physical, chemical, and biological heterogeneity that understanding the environmental forces that shape the structure and function of microbial communities there remains an outstanding challenge (Tiedje et al., 1999 ; Roesch et al., 2007 ; O'Brien et al., 2016 ; Bailey et al., 2017 ). As the number of taxonomic groups within a particular soil often exceeds several thousand distinct clades, there is considerable interest in using simplified microbial communities to test hypotheses related to soil ecology. By “minimizing” a native microbial community from soil or elsewhere through enrichment in the laboratory, noise from the myriad co-existing metabolic networks and structural heterogeneities present in the parent environment can be pared down to focus on a particular process of interest, allowing the power of modern omics technology to be brought to bear on specific questions in microbial ecology (Prosser, 2015 ). This microcosm approach is frequently used to examine a subset of a native community such as sulfate reducers (Raskin et al., 1996 ; Kirk et al., 2013 ; Kwon et al., 2014 ), denitrifiers (Laverman et al., 2010 ; Kraft et al., 2014 ), or organisms capable of degrading specific compounds of interest (Brennan et al., 2006 ; Sutton et al., 2013 ; Luo et al., 2014 ; Onesios-Barry et al., 2014 ). Conducting such experiments as high-throughput, parallel replicates across a broad variety of environments has the potential to provide greater insight into how microbial communities respond to changing conditions. Physiological profiling using microtiter plates has been frequently used as a method of examining the functional diversity of mixed microbial communities by monitoring the production of NADH using a redox-active dye (Bochner, 1989 ; Bochner et al., 2001 ). This approach allows the utilization of an array of carbon compounds by microbial communities to be monitored in parallel using 96-well plates. These substrate arrays are frequently used to test the metabolic capabilities of the microbiome inhabiting soil, water, and other environments (Bartscht et al., 1999 ; King, 2003 ; Weber and Legge, 2009 ; Gryta et al., 2014 ; Zhang Y. et al., 2014 ). Given that the composition of the communities that grow from the inocula in these arrays is rarely, if ever, characterized directly, the extent to which the “active” populations utilizing a particular substrate are representative of the community at large remains unclear (Konopka et al., 1998 ; Haack et al., 2004 ). Substrate arrays also offer an opportunity to study in parallel the response of a single inoculum to the addition of a wide array of nutrients. In this study, we employed these substrate arrays as mini-bioreactors to monitor the response of microbial communities from six distinct environments to enrichment on 31 individual carbon compounds. We hypothesize that the fractionation of the complex natural communities will be more influenced by the nature of the carbon source utilized and select for a specific subset of microorganism(s) regardless of source environment. To this end, we selected as inocula soil, water and sediment from a variety of terrestrial environments including a wetland, a grassland, and three types of forest (temperate, subalpine, and tropical). We sought to test (A) the extent to which communities enriched in these substrate arrays are representative of the initial community as a whole, (B) the degree to which the initial structure of a community determines its response to a press disturbance (increase in nutrient levels) for different classes of environmentally-relevant (Hitzl et al., 1997 ) carbon compounds and (C) whether the composition of the communities that grow to inhabit the substrate arrays are more influenced by the composition of the inoculum or the type of carbon source upon which they are enriched.",
"discussion": "Discussion The distinct communities of microorganisms that grow to dominate each enrichment within the substrate arrays bear the strong influence of the initial composition of the soil or water used as inoculum. As can be seen from the NMDS plot in Figure 3 , the source of inoculum is by far the strongest signal in differentiating the microbial communities in these substrate arrays. The statistical significance of this result is confirmed by ANOSIM based on weighted UniFrac 1 , where the resulting R-values recapitulate the trends observed in the NMDS plot (Figure 4 ). Furthermore, these results show that, for the most part, the communities in the substrate arrays from the most divergent inocula [tropical (CRP14) and subalpine (SodaSpr) forest soil] remain divergent from those sourced from temperate soil inocula (AWS, FLP, FLF), which beta diversity comparisons indicate are more similar to each other (Figure S2 ). The exception is the wetland surface water (AWW), which Figure S2 shows has the most divergent community composition of the six inocula prior to enrichment. Following the 72-h incubation, however, the communities that arise in the substrate arrays inoculated with AWW material appear much more similar to the arrays inoculated with temperate soil than to those inoculated with soil from CRP14 or SodaSpr (Figure 3 ). This suggests that the generalists like Pseudomonas , fa. Enterobacteriaceae , and Agrobacterium that grow to dominate the substrate arrays share a similar baseline activity across all the temperate environments and are therefore able to be enriched to a similar degree in the arrays. Still, the smaller but still significant R ANOSIM -values between some of the terrestrial enrichments (e.g., AWW and AWS) indicate the existence of smaller but significant differences between these environments. Despite the strong influence of the initial inoculum, the overall structure of the microbial communities that grow to inhabit these substrate arrays bears little resemblance to that of the parent material, as measured by both alpha (Figure 2 ) and beta diversity (Figure S1 ). In most cases, the enrichments in each substrate array are primarily dominated by one or several OTUs most closely related to aerobic, heterotrophic generalists like Pseudomonas, Burkholderia, Ralstonia , fa. Enterobacteriaceae , and others (Figures 5 , 6 ). Pseudomonas in particular dominated five of the six substrate arrays, although it was nearly absent from enrichments in the array inoculated with soil from site CRP14. Pseudomonas and its relatives are well-known as metabolic generalists and are frequently found in aerobic soil environments. Initially, “pseudomonads” were defined largely by “their most striking and ecologically significant group character… namely, the ability to use a wide variety of organic compounds as carbon and energy sources for aerobic growth” (Stanier et al., 1966 ). Numerous microcosm and enrichment studies from soils under aerobic conditions have found abundant growth of Pseudomonas (Greene et al., 2000 ; Eriksson et al., 2003 ; Ma et al., 2006 ), although these are often limited in scope to a few replicates or the utilization of a particular compound of interest. An exception to this repeated occurrence of Pseudomonas was in the apparent swapping of Pseudomonas for Burkholderia and Ralstonia across the CRP14-inoculated enrichments. Like Pseudomonas, Burkholderia is a metabolic generalist well-distributed in soil environments (Cho and Tiedje, 2000 ; Salles et al., 2004 ; Janssen, 2006 ; Compant et al., 2008 ; Lauber et al., 2009 ; Stopnisek et al., 2014 ). Ralstonia also is a genus commonly found in soil environments (Janssen, 2006 ), although most studies of this genus focus on its role as soil-borne plant pathogen (Castillo and Greenberg, 2007 ; Leonard et al., 2017 ) with a wide distribution in warm and tropical climates (Genin and Boucher, 2004 ). Both Burkholderia and Ralstonia share many characteristics with Pseudomonas ; both were at one time themselves classified as part of that genus (Yabuuchi et al., 1992 , 1995 ) although they are now recognized as Betaproteobacteria while Pseudomonas is classified as a member of the Gammaproteobacteria . The abundance of these two genera in the CRP14-amended substrate array suggests an optimization of the community from the tropical forest system to the set of niches found in the source environment to the exclusion of Pseudomonas . There is likely some consistent factor associated with those niches, however, so that a “distinct generalist” is enriched consistently over time in one environment but not another. When comparing the substrate array enrichments by the chemical class of substrate (amines, amino acids, carbohydrates, polymers, or phenolic compounds) rather than source environment, we found that significant differences in community composition exist primarily between those wells given a carbohydrate as a carbon source and those enriched with a phenolic compound (Figure 8 ). These differences were observed across three of the six environmental inocula: AWW, FLF, and SodaSpr, while none of the other pairwise comparisons between carbon source class showed a significant difference in more than one substrate array. Taken together, these results suggest that the co-occurrence of minimized community members within these three environments and grown on carbohydrates or phenolics are likely non-random associations. Like the most abundant taxa across the substrate arrays, most of the differentially-abundant OTUs (Figure 8 ) between phenolic- and carbohydrate-amended enrichments are most closely related to aerobic heterotrophs. Interestingly, the closest neighbors of several of the OTUs that are differentially abundant in phenolic-amended enrichments are organisms that are specifically known for degrading aromatic compounds. For example, members of the genus Comamonas have previously been isolated and studied based on their ability to degrade polycyclic aromatic hydrocarbons (Goyal and Zylstra, 1996 ) while isolated members of the genus Sphingobium are known for the ability to degrade phenolic compounds such as nonylphenols (Ushiba et al., 2003 ) and chlorophenols (Cai and Xun, 2002 ) as well as other aromatic hydrocarbons (Cunliffe and Kertesz, 2006 ). Carbohydrate-amended enrichments were more enriched with OTUs classified as Luteibacter, Sphingomonas, Pseudomonas, Kaistia, Brevundimonas, Ochrobactrum, Vogesella , and others. Unsurprisingly, known isolates from these groups are primarily aerobic heterotrophs with wide metabolic diversity, including the ability to grow on carbohydrates as an energy source (Lessie and Phibbs, 1984 ; Lebuhn et al., 2000 ; Im et al., 2004 ; de Boer et al., 2007 ) and are commonly found in a variety of terrestrial environments (Fredrickson et al., 1999 ; Cho and Tiedje, 2000 ; Spiers et al., 2000 ; Lauber et al., 2009 ). Despite being more enriched in carbohydrate-amended wells, Sphingomonas spp. have also shown the ability to grow on aromatic compounds (Fredrickson et al., 1995 ). Taken together, these findings provide substantial insight into how microbial communities respond to changes in nutrient conditions. Microbial communities, like all communities of living organisms, are thought to be shaped by two types of ecological factors: those that are more deterministic are dubbed “niche” while those that are more stochastic are “neutral” (Vellend, 2010 ; Stegen et al., 2012 ). Niche factors that influence microbial community dynamics include environmental factors such as temperature or pH, the presence or absence of a particular nutrient (e.g., carbon, nitrogen, phosphorus, etc.) or the physical structure of the environment itself (e.g., the porosity or mineralogy of the soil matrix). Neutral forces, conversely, include random birth/death events, migrations of a particular population from one area to another, and other probabilistic events (Chase and Myers, 2011 ; Stegen et al., 2013 ). Evidence of the significance of both processes in shaping microbial communities has been observed throughout a variety of environments including soil, seawater, and aquifers (Gilbert et al., 2012 ; Shade et al., 2012 ; Handley et al., 2014 ; Graham et al., 2017 ). Understanding the relative importance of these factors is of particular importance in microbial ecosystems, where physiologically-relevant gradients can occur on the scale of micrometers. This heterogeneity at the microscale can be found in biofilms (Battin et al., 2016 ), soil pores (Bailey et al., 2013 , 2017 ), and other sedimentary environments (Jakobsen, 2007 ), potentially imposing both niche and dispersal limitations at scales far smaller than that of the typical environmental sample. This poses a significant challenge to creating phylogenetically-resolved predictive models of microbial activity (Graham et al., 2016 ), particularly considering the breathtaking diversity of natural microbial communities (Howe et al., 2014 ; Hug et al., 2016 ). While these experiments were not designed to explicitly test the extent to which niche and neutral factors lead to the composition of microbial communities within the substrate arrays, we see qualitative evidence of both processes shaping the overall composition of these communities. The degree to which either of these two processes influences the resultant minimized community, however, likely depends on the class of substrate. For example, niche selection clearly determines the overall trajectory of the response of the initial inoculum to changes in environmental conditions, as the organisms that grow to dominate the wells of the substrate arrays are aerobic heterotrophs, matching the oxic and carbon-rich conditions found in the wells. Further, niche selection appears evident in the distinction between carbohydrate- and phenolic-amended enrichments, as specific populations closely related to isolates known for degrading aromatic compounds become significantly more abundant in the presence of phenolic compounds (Figure 8 ). Still, despite the fact that the source of inoculum is a significant determinant of the overall community structure (Figure 3 ), probabilistic events still appear to control some of the finer aspects of the composition of the substrate array communities. The extent to which triplicate wells on the same substrate array ended up with the same community composition varied depending on both the substrate and the population. For example, when populations classified as Burkholderia became abundant in wells inoculated with soil from the SodaSpr site, the abundance was observed uniformly across all three replicates (Figure 6 ). Conversely for some of carbon sources in wells amended with AWS soil, two of the three triplicates contained >90% Pseudomonas while the third well was similarly dominated by sequences classified as either fa. Enterobacteriaceae or Agrobacterium (Figure 6 ). Because the inocula were rigorously diluted, dispersed, and homogenized prior to being added to the substrate arrays, it appears unlikely that this is an artifact of sample preparation. Instead, stochasticity and imperceptible differences in the initial inoculum likely play at least some role in determining the overall trajectory of change in community composition. This has been seen elsewhere, as in Kwon et al.'s ( 2016 ) observation of two distinct mineralogical and microbiological trajectories in replicate microcosms amended with glucose and ferric iron. The extent to which the communities within the substrate arrays represent the environments from which they were enriched depends upon how one looks at the question. In one sense, the communities in the substrate arrays retain components (populations) of the initial community as evidenced by the clustering by environment observed in Figure 3 . However, the composition of these communities bears little resemble to that of the source inoculum when compared by measures of alpha (Figure 2 ) and beta (Figure S1 ) diversity. This is likely primarily due to the differences in the physicochemical makeup within the substrate arrays compared to that of the source environments. Whereas, soil and sedimentary environments display a complex, heterogeneous three-dimensional structure with dynamic changes in temperature, nutrient availability, and other variables, the substrate arrays are relatively homogeneous in comparison. In fact, the substrate arrays that shared the most taxa with their initial inoculum were those inoculated with wetland surface water, where shared taxa comprised 8.0% of the inoculum diversity compared to 1.1–2.5% in the five substrate arrays inoculated with soil suspensions. While still different in many respects, the wetland surface water does most closely resemble the aqueous environment of the substrate array wells. The relative physical homogeneity of the substrate arrays compared to the source environments might be one explanation for the rapid dominance of one or few taxa in most of the substrate arrays over the 72-h incubation period. Previous work has shown that physical structure in laboratory microcosms enhances the stable coexistence of multiple interacting soil bacteria (Kim et al., 2008 ). Other work, however, has found many co-existing microbial populations can exist stably in homogeneous liquid medium (Kraft et al., 2014 ; Sutton et al., 2015 ; Chen et al., 2017 ). For example, recent work has shown that found that co-existence of bacterial isolates could be tied to mortality under different growth conditions within the same media (Friedman et al., 2017 ). While the goal of our experiments was not to replicate natural environments, it is clear from these results and others that both initial community composition and physical structure are likely both substantive controls on the composition of mixed environmental communities, as are intraspecific competition, mutualism, and other forms of organismal interaction (Konopka et al., 2015 ). The parallelized enrichment strategy we employ here provides a framework to capture some of the underlying and potentially novel interactions between microbial community members found in soil and water in a high-throughput manner. This work also has the potential to inform the synthetic design of microbial communities, an area of considerable interest (Shou et al., 2007 ; Mee et al., 2014 ; Stenuit and Agathos, 2015 ). Current work in our laboratory is focused on testing the stability of these “minimal communities” in continuous culture systems with the hope of creating hybrid synthetic communities that are sourced directly from specific environments but streamlined in the laboratory. The isolation of a consistently reoccurring generalist provides an anchor within the community for genetic engineering. A variety of genetic tools are available for Pseudomonas and other taxa seen here, providing a potential platform for customization of minimal communities for industrial and biomedical applications. Moving forward, as desire increases to engineer microbial communities either by strain selection or outright genetic manipulation (Johnson et al., 2012 ; Lindemann et al., 2016 ), the use of highly parallelized microbial enrichments promises to provide novel insights that will allow us to predict with greater accuracy the interactions that contribute to emergent properties of microbial communities, such as community stability."
} | 5,704 |
31890017 | PMC6913021 | pmc | 4,018 | {
"abstract": "Background Anaerobic digestion of easily degradable biowaste can lead to the accumulation of volatile fatty acids, which will cause environmental stress to the sensitive methanogens consequently. The metabolic characteristics of methanogens under acetate stress can affect the overall performance of mixed consortia. Nevertheless, there exist huge gaps in understanding the responses of the dominant methanogens to the stress, e.g., Methanosarcinaceae. Such methanogens are resistant to environmental deterioration and able to utilize multiple carbon sources. In this study, transcriptomic and proteomic analyses were conducted to explore the responses of Methanosarcina barkeri strain MS at different acetate concentrations of 10, 25, and 50 mM. Results The trend of OD600 and the regulation of the specific genes in 50 mM acetate, indicated that high concentration of acetate promoted the acclimation of M. barkeri to acetate stress. Acetate stress hindered the regulation of quorum sensing and thereby eliminated the advantages of cell aggregation, which was beneficial to resist stress. Under acetate stress, M. barkeri allocated more resources to enhance the uptake of iron to maintain the integrities of electron-transport chains and other essential biological processes. Comparing with the initial stages of different acetate concentrations, most of the genes participating in acetoclastic methanogenesis did not show significantly different expressions except hdrB1C1 , an electron-bifurcating heterodisulfide reductase participating in energy conversion and improving thermodynamic efficiency. Meanwhile, vnfDGHK and nifDHK participating in nitrogen fixation pathway were upregulated. Conclusion In this work, transcriptomic and proteomic analyses are combined to reveal the responses of M. barkeri to acetate stress in terms of central metabolic pathways, which provides basic clues for exploring the responses of other specific methanogens under high organics load. Moreover, the results can also be used to gain insights into the complex interactions and geochemical cycles among natural or engineered populations. Furthermore, these findings also provide the potential for designing effective and robust anaerobic digesters with high organic loads.",
"conclusion": "Conclusions The present work describes the gene regulations of M. barkeri in terms of the main metabolism pathways under acetate stress using transcriptomic and proteomic analyses. The findings provide bases to understand responses of other methanogens, and are conductive to explore the complex interactions in mixed consortia. As the sole conductor of methanogenesis, methanogens have multifaceted impacts on mixed consortia. The 50 mM acetate had the most severe inhibition on M. barkeri between the initial sampling points, while the high level of acetate stress (50 mM) promoted the acclimation of M. barkeri to stress. The information exchange by QS system was hindered by insufficient ATP hydrolysis, which offset the advantages of cell aggregations. Enriched iron uptake suggested that M. barkeri could allocate more resources to enhance the uptake of key elements relative to other elements. Therefore, the addition of external iron might be a useful approach to alleviate acetate stress in engineered anaerobic digestors. As the sole pathway to metabolize acetate, the acetoclastic methanogenesis pathway did not show significant regulation of conventional enzymes between the initial sampling points. The high tolerance of acetoclastic methanogenesis to acetate stress made Methanosarcinaceae the dominant methanogens in mixed consortia, where the other microbes in the outer layer of granule sludge could further provide protection. The expressions of hdrABC were complementary mechanisms to keep H 2 cycling and improve thermodynamic efficiency under acetate stress. It was widely considered that Vhx could not function as homologous Vht due to the lack of maturation protease, while the significant regulation of vhx revealed that Vhx might be a complement to Vht, which needs to be further explored. The enriched in methanogenic N 2 fixation pathway revealed that sufficient bioavailable nitrogen sources were essential for sensitive M. barkeri to resist acetate stress. However, the mechanisms where N 2 fixation alleviated acetate stress needed to be further explored. The genes encoding the different subunits of one complex did not show the same regulation trends. On the other hand, the genes encoding the same subunit had distinct regulation trends. Furthermore, a considerable proportion of the DEGs were annotated as hypothetic proteins, and many novel transcripts were assembled by the software. This indicated that comprehensive gene regulations existed in M. barkeri under acetate stress, and some genes were activated, which were not expressed under suitable conditions. Future studies can focus on the functions of the DEGs encoding hypothetic proteins, which may prevent the disorder of physiological activities and adjust pathways dynamically. Meanwhile, the complex interactions in mixed consortia under acetate stress are unclear and need to be further explored.",
"discussion": "Discussion Stress proteins under different levels of acetate stress The genes encoding heat shock proteins (Hsp 60) and DNA double-strand break (Dsb) repair proteins were upregulated in “50-I_25-I” and “50-I_10-I”, respectively. These proteins participated in mitochondrial protein import or macromolecular assembly and restrained cell death or comprehensive genetic variation in cells. The ATP-dependent DNA ligase gene ( lig1 ) was also upregulated in “50-I_10-I” and “50-I_25-I”, which has an active role in DNA replication, recombination and repair [ 31 ]. This indicated that the DNA structure was unstable at the initial sampling point under high level of acetate stress, although M. barkeri was capable of surviving in 50 mM acetate [ 12 , 32 ]. Along with the consumption of acetate, most of the DEGs encoding stress proteins and Lig1 were upregulated in “10-T_10-I”, indicating that M. barkeri still did not acclimatize to the acetate stress. Nevertheless, in “50-T_50-I”, most of the genes encoding stress proteins were downregulated according to the transcriptomic analysis, and proteomic analysis showed that all detected Hsp 60 and Dsb proteins were downregulated. In “50-T_25-I”, the dsb was downregulated. Furthermore, most of the DEGs encoding Hsp, Dsb and universal stress proteins were upregulated in “25-T_10-I”. Considering the OD600 trend in each group (Fig. 1 d) and the regulation trends of DEGs encoding stress proteins, it was revealed that a period of exposure to a high level of acetate stress might promote M. barkeri to acclimatize to acetate stress. This presumption was consistent with the phenomenon in our previous study where the abundance of Methanosarcinaceae started to be detected or increase in the later stages of the reactions [ 5 ]. Signal transduction in cell aggregations The genes encoding cell division proteins (FtsEX complex) which were essential for assembling or stabilizing the septal ring [ 33 ], were downregulated in “10-T_10-I” and “25-T_25-I” (6.41-fold and 13.27-fold, respectively). Nevertheless, these genes showed a slightly decreased fold change in “50-T_50-I” (2.06-fold). These regulation trends roughly coincided with the OD600 trends (Fig. 1 d). ftsH participates not only in cell division and cell control, but also in membrane functions and gene expression, which was upregulated in “50-T_25-I” and downregulated in “25-T_10-I”. Logically speaking, a low level of stress had fewer negative impacts on cells, but the present work indicated that a high level of acetate stress could stimulate the greater “potential” for M. barkeri to resist stress. Cell proliferation could facilitate the formation of cell aggregations. The micrographs and the previous study found that M. barkeri resisted stress by forming multicellular aggregations (Additional file 5 : Fig. S2) [ 34 ]. In the cell aggregations, the gradients of acetate concentrations were formed to alleviate the acetate stress on the inner cells and prevent more H 2 from diffusing [ 35 ]. H 2 cycling was essential for acetoclastic methanogenesis [ 36 ]. Cell aggregations exchanged information of cell densities by quorum sensing (QS) system using peptide signals, such as oligopeptides and dipeptides. In “25-I_10-I”, “50-I_10-I”, and “50-I_25-I”, the genes encoding periplasmic oligopeptide-binding protein (OppA) or oligopeptide/dipeptide transport system permease proteins (OppC and DppB) were upregulated. Nevertheless, the genes encoding ATP-binding proteins (OppD and DppF) were downregulated in “25-I_10-I” and “50-I_10-I”. ATP hydrolysis was essential for the normal functions of ABC transport system [ 37 ], therefore, the downregulation of oppD and dppF indicated that acetate stress could block the information exchange on a community-wide scale. The blocked information exchange offset the advantages of cell aggregations, and M. barkeri might not make proper responses to acetate stress. Because the activation of the Type II secretion system proteins was under the control of QS system [ 38 ], the downregulation of the DEGs encoding Type II secretion system proteins also indicated the blocked information exchange. In other comparisons, opp / dppBCDF were all downregulated, but opp/dppA did not show up- or downregulation. It indicated that opp/dppA was more resistant to acetate stress, which was helpful to maintain the normal functions of the QS system in cell aggregations. Approximately half of the DEGs encoding LSU and SSU ribosomal proteins were upregulated in “50-T_50-I” and “50-T_25-I” (41.4% and 55.6%, respectively), but 88.9% of the DEGs encoding the same proteins were downregulated in “25-T_10-I”. The expression of ribosomal proteins usually represented protein synthesis, which was an energy-consuming process accounting for 75% of energy expenditure in cells [ 39 ]. It was revealed that M. barkeri gradually recovered energy synthesis to support the synthesis of some proteins in the 50-group, which helped M. barkeri acclimatize to acetate stress. Membrane and ABC transporters for translocating elements Transmembrane transfer activities were related to membrane and ABC transporters. Except for the comparisons between the initial sampling points, the fluctuant regulation trends of the DEGs encoding cell surface proteins in other comparisons indicated that the responses of cell membranes were complicated. And in “10-T_10-I”, “25-T_25-I”, “50-T_50-I”, and “50-T_25-I”, the genes encoding mannose-6-phosphate isomerase were upregulated, which was related to polysaccharide biosynthesis and the modification of cell wall carbohydrates. It indicated that M. barkeri modified its cell surface structures according to the levels of acetate stress, which was also observed in the previous study [ 40 ]. The phosphate transport system (Pst) was a more efficient system for Pi translocation in M. barkeri . In “10-T_10-I” and “25-T_25-I”, pstB was downregulated which provided energy to free Pi [ 41 ]. It indicated that acetate stress could result in an insufficient energy supply for translocating elements and thereby cause a series of negative effects on physiological functions. But pstB did not show significant regulation in “50-T_50-I” and “50-T_25-I”, therefore the stable expression of pstB might promote the acclimation of M. barkeri to the acetate stress in 50-group. Iron is essential for maintaining stable methanogenesis [ 42 , 43 ], where iron was a main component in redox enzymes, such as ferredoxin and Hdr. The previous studies demonstrated that iron deficiency hindered nucleotide synthesis and ATP production [ 44 , 45 ]. For more iron uptake, the genes encoding ferrous iron transport protein B, which were essential for iron supply in anaerobic conditions, were upregulated in “50-I_10-I” and “50-I_25-I”. And the proteomic analysis also showed the upregulation of iron complex transport system permease proteins in “50-I_10-I” (Additional file 13 : Dataset S3). Furthermore, the iron complex transport activity was enriched in “50-I_10-I” (Fig. 3 ). It was suggested that the reason why exogenous iron could maintain stable methanogenesis was not only it could enhance the interspecies electron transfer between species and reduce oxidative-reductive potential [ 46 , 47 ], but also it could maintain the integrities of some key enzymatic activities. Compared with the gene regulation related to other elements’ uptake, the upregulation of iron uptake indicated the inhibited M. barkeri would allocate more resources to enhance the uptake of more essential elements, especially under high level of acetate stress. The inappropriate transmembrane ion gradients formed under acetate stress could cause the imbalance of osmotic pressures. The glycine betaine transport system (Pro) could provide osmo-protection [ 48 ]. In “25-I_10-I” and “50-I_10-I”, proV encoding ATP-binding protein was downregulated. The insufficient energy supply would hinder the normal functions of Pro under acetate stress, which thereby induced cell death. The upregulation of proV in “50-T_25-I” also might promote the acclimatization of M. barkeri to the acetate stress in 50-group. As expected, proV was downregulated in “25-T_10-I”, where the M. barkeri did not acclimatize to the acetate stress. Acetoclastic methanogenesis for energy synthesis As the terminal of electron transfer, methane was yielded through acetoclastic methanogenesis with energy synthesis. In “50-I_25-I”, the genes encoding heterodisulfide reductase subunits (HdrB1C1) were upregulated, but the hdrDE did not show significant regulations. HdrA1B1C1 had been speculated to be an electron-bifurcating enzyme in energy conversion as shown in Fig. 7 . One possible explanation for why multitype Hdr expression was that HdrABC could help cells to acclimatize to the fluctuations in substrate concentrations and conserve energy more efficiently [ 23 , 49 ]. The available free energy from acetoclastic methanogenesis under standard condition (Δ G o ʹ = − 36 kJ/CH 4 ) provided only a small amount of energy for growth, because of the endergonic reaction where acetate was activated to acetyl-CoA. The upregulation of hdrB1C1 could be a complementary mechanism for M. barkeri to improve the thermodynamic efficiency under the high level of acetate stress. Fig. 7 The transcriptional changes in genes involved in proposed acetoclastic methanogenesis, nitrogen fixation and ATP synthesis by different comparisons. The values in the heatmaps show the average Log 2 fold changes in transcripts translating the same subunit of each enzyme in different comparisons. Red represents downregulation, blue represents upregulation, and white represents no significant regulation. The solid lines indicate the conventional acetoclastic methanogenesis. The double bond lines indicate the postulated acetoclastic methanogenesis. The dotted lines indicate the overlap of conventional acetoclastic methanogenesis and postulated acetoclastic methanogenesis. The dashed lines indicate the nitrogen fixation pathway. Red solid lines indicate electron flow in each enzyme and blue solid lines indicate H 2 flow in acetoclastic methanogenesis. The question mark represents the enzyme re-oxidizing F 420 H 2 Methanosarcina barkeri was one of the few methanogens that could participate in direct interspecies electron transfer [ 50 ], and it could shift methanogenesis pathways according to stress levels. Furthermore, Methanosarcina could produce H 2 and act as a syntrophic acetate oxidizer during growth on acetate [ 32 ]. On the other hand, HdrA1B1C1 and homologous HdrA2B2C2, which had similar functions [ 49 , 51 ], were suggested to be essential for direct interspecies electron transfer [ 52 ]. These characteristics indicated there might be a preliminary hypothesis that in the cell aggregations formed under high level of acetate stress, some M. barkeri might act as syntrophic acetate oxidizers, and another M. barkeri might perform hydrogenotrophic methanogenesis to yield more energy for cellular activities. Therefore, electron transfer would exist in one species with distinct pathways. Moreover, the DEGs encoding coenzyme F 420 hydrogenase subunit alpha, beta, and gamma (FrhABG), which participated in hydrogenotrophic methanogenesis, were upregulated in “50-I_25-I”. The upregulation of frhABG was part of the evidence for the electron transfer between M. barkeri under high level of acetate stress. And the hypothetical proteins occupying most of the proteome might also participate in this electron transfer. Nevertheless, this hypothesis needs to be further verified. The other key genes participating in acetoclastic methanogenesis did not show significant regulation at the initial sampling points (Fig. 7 ). It indicated that M. barkeri metabolized acetate stably under different levels of acetate stress within its tolerance range. The stable acetate metabolism could help M. barkeri to outcompete other methanogens for acetate and thereby dominating mixed consortia. The gene encoding V-type ATP synthase subunit F (AtpF), which was likely a regulatory subunit for controlling pH homeostasis, was upregulated in “50-I_10-I” and “50-I_25-I” (Fig. 7 ). Therefore, maintaining pH homeostasis was a mechanism of M. barkeri to hold the intracellular environment suitable under acetate stress. In “10-T_10-I”, with the reactions proceeding, hdrA2B2C1 were downregulated (Fig. 7 ). And the genes encoding energy-conserving hydrogenase subunits A and C (EchA and EchC, respectively), which are essential for forming transmembrane proton gradients and keeping H 2 cycling during acetoclastic methanogenesis, were also downregulated (Fig. 7 ). Furthermore, the gene encoding tetrahydromethanopterin S-methyltransferase subunit A (MtrA) was downregulated, which could form a transmembrane sodium gradient for ATP production [ 16 , 21 ]. Meanwhile, atpAECD were downregulated. These results indicated that an insufficient acetate concentration had negative impacts on the energy synthesis of M. barkeri , whose affinity for acetate was low. It might be one of the reasons why M. barkeri were eliminated in low acetate concentrations. Although mtrFG were also downregulated, they appeared to be the nonessential components in mtr operon in terms of transferring methyl [ 53 ]. The same regulation trends of mtrAFG indicated that there might have potential interactions among them. In “25-T_25-I”, methanophenazine-reducing hydrogenase (VhxAG) with unknown functions, showed opposite regulation trends (up- and downregulation, respectively). Furthermore, vhx in “10-T_10-I”, “25-T_25-I”, and “50-T_50-I” showed significant regulation. It was suggested that the deletion of vhxD in vhx operon caused Vhx to have no analogous functions of another methanophenazine-reducing hydrogenase (Vht) [ 20 , 54 ], which was essential for Hdr to conserve energy in acetoclastic methanogenesis [ 36 ]. Nevertheless, vhx operon could encode the main functional subunits homologous to Vht, and VhtD might process Vhx under the controls of the DEGs encoding mobile element proteins or transposons. Combining the gene regulations with the operon structure, it indicated that Vhx might participate in acetoclastic methanogenesis as a hydrogenase. In “50-T_50-I”, the downregulation of ech and atp might be caused by the less acetate concentration at “50-T” point where M. barkeri had acclimatized to the acetate stress as discussed above. Methanogenic N 2 fixation for bioavailable nitrogen resources Methanogenic N 2 fixation is proposed as an essential way to provide bioavailable nitrogen resources [ 55 ], and the methanogens being capable of fixing N 2 such as M. barkeri, Methanobacterium bryantii and so on, distribute in diverse habitats [ 56 – 58 ]. The DEGs encoding nitrogenase (molybdenum–iron) subunits (NifHDK), and alternative nitrogenase (vanadium–iron) subunits (VnfHDK), which has lower catalytic efficiency in Methanosarcina species [ 59 ], were upregulated in “50-I_10-I” and “50-I_25-I” (Fig. 7 ). It indicated that ammonia was indispensable for M. barkeri to resist acetate stress, which could also be confirmed by the upregulation of the DEGs encoding ammonium transporters and nitrogen regulatory protein p II. In “50-I_10-I”, the regulation trends of the nitrogen regulatory proteins, nitrogenases and ammonium transporters, showed positive correlation between the transcriptomic and proteomic analyses (Fig. 6 a). Ammonia can be assimilated into cellular nitrogen by glutamine synthetase (Gs) and glutamate dehydrogenase (Gdh) (Fig. 7 ). Gs was identified as a DEP in “50-I_10-I”, and gs was upregulated in “50-I_25-I”. Ammonia is a biologically useful reduced form incorporated into amino acids and other vital compounds. Therefore, the enhanced nitrogen fixation pathway could help M. barkeri maintain the normal functions of key biological processes in the initial stages of acetate stress. And it could also help the more sensitive M. barkeri to outcompete other methanogens under acetate stress, as observed in the previous studies [ 5 , 34 ]. Although M. barkeri could grow under nitrogen fixation conditions with acetate, the growth rate was considerably slower than with ammonium as nitrogen source [ 60 ]. Therefore, ammonium was used as the nitrogen source in the present work and its concentration was about 9.35 mM as the recommended cultivation condition, which could support the normal growth of M. barkeri . The enhanced nitrogen fixation pathway indicated that more bioavailable nitrogen sources were essential to resist acetate stress. However, as another major problem of anaerobic digestion, ammonia stress is caused by the high concentration of ammonia. Therefore, it is necessary to find a “best of both worlds” ammonia concentration, which still needs further explorations. In addition to maintaining the normal functions of key biological processes, the enriched nitrogen fixation pathway might also keep the proton balance in cells. Under the same pH values, acetate stress produces relatively more free acetic acid, which can diffuse into cells. The intracellular is a near-neutral environment, so free acetic acid will be dissociated and then increase the intracellular proton concentration. The excessive intracellular protons could uncouple proton force on cytomembrane and hinder energy synthesis [ 61 , 62 ]. Nevertheless, the ammonia synthesized by the enriched nitrogen fixation pathway could bind the excessive protons in cytoplasm, and thereby alleviated the imbalance of protons, which was toxic to M. barkeri . Except for “25-I_10-I”, “50-I_10-I”, and “50-I_25-I”, the DEGs encoding nitrogenase subunits were all downregulated in other comparisons. For “10-T_10-I”, “25-T_25-I”, and “25-T_10-I”, the downregulation might be caused by the insufficient energy synthesis as discussed above, because N 2 fixation required abundant reducing power and ATP [ 55 , 63 ]. For “50-T_50-I” and “50-T_25-I”, M. barkeri had acclimatized to the acetate stress at the “50-T” point, indicating more nitrogen sources were not needed. The differences between proteomic and transcriptomic analyses The regulations of some mRNAs and their corresponding proteins showed poor correlation, which was well known and observed in previous studies [ 64 , 65 ]. Proteins could remain stable even beyond the entire cell cycle relative to mRNAs, whose half-lives averaged only a few min in E. coli [ 66 ]. The different temporal scales of transcriptome and proteome could be used to explain the poor correlation between some mRNAs and proteins. In addition to the differences in temporal scales, posttranscriptional or translational regulations were another explanation. The low proportion of coding regions in the genome of M. barkeri (79.2%) indicated that a large number of antisense RNAs and sRNAs existed, which participated in posttranscriptional regulation. The modulation effects of sRNAs played a prominent role in archaea by influencing the evolution and stability of mRNAs and translation efficiency [ 65 , 67 ]. Translation initiation also affected mRNA–protein correlation [ 67 ], therefore the DEGs encoding translation initiation factors in “50-T_50-I” could explain the poor mRNA–protein correlation in part."
} | 6,151 |
30203189 | PMC6131686 | pmc | 4,019 | {
"abstract": "A facial electrospinning method of in situ precise fabricating magnetic fibrous membrane composed of polyurethane (PU) nanofibers decorated with superparamagnetic γ-Fe 2 O 3 nanoparticles with simultaneous heat generation in response to alternating magnetic field (AMF) is reported. In this method, a conical aluminum auxiliary electrode is used to regulate the electrostatic field and affect the process of electrospinning for the in situ rapid and precise deposition of electrospun γ-Fe 2 O 3 /PU fibers. The auxiliary conical electrode can extend the jet stabilization zone of the precursor solution four times longer than that of without auxiliary electrode, which can achieve the precise control of the fiber deposition area. Moreover, the electrospun composite fibrous membranes show a rapid temperature increase from room temperature to 43 °C in 70 s under the AMF, which exhibits faster heating rate and higher heating temperature compared to the samples fabricated without the assist of the auxiliary electrode. The present results demonstrate that the in situ precise electrospinning with the help of an auxiliary conical electrode has the potential as a manipulative method for preparing magnetic composite fibers as well as magnetic hyperthermia of cancer therapy.",
"conclusion": "Conclusions In summary, a magnetic composite nanofiber membrane was fabricated in situ using a portable electrospinning device with the aid of an auxiliary electrode. In the electrospinning process, the addition of the auxiliary electrode prolongs the stable area of the electrospinning and reduces the fiber whipping, thereby reducing the deposition range of the fiber and accelerating the fiber deposition rate. For electrospinning techniques, the application of conical auxiliary electrodes to precisely control the deposition area is suitable for most electrospinning materials. Moreover, the microstructure (diameter, surface morphology) of the electrospinning fiber is not significantly affected. The in situ prepared magnetic composite nanofibrous membranes can convert the AMF energy to the thermal energy to elevate temperature efficiently. With the aid of the auxiliary electrode, the composite fibrous membrane prepared by in situ electrospinning showed efficient heating ability upon the application of AMF, and well-maintained cyclic heating performance under the presence of AMF. These results indicate that the magnetic composite fibrous membrane prepared in situ by the auxiliary electrode is an excellent candidate for the magnetic hyperthermia of cancer therapy.",
"discussion": "Result and Discussion Precise Deposition via the In Situ Electrospinning A comparison in the deposition range between electrospinning with and without an auxiliary electrode was performed. As shown in Fig. 2 , under the same external conditions (temperature, voltage, distance, humidity, spinning speed, spinning precursor fluid, spinning needle diameter, etc.), the deposition range of the fibrous membrane prepared using the auxiliary electrode (diameter of 1.8 cm) was significantly smaller than that of the electrospun fiber without the use of the auxiliary electrode (diameter of 4.6 cm). In the traditional electrospinning process, the spinning precursor fluid splits, whips, and stretches, into micro-/nanoscale fiber in the air, and finally deposits on the collector to form a non-woven fabric membrane [ 21 ]. However, in the unstable region of the spinning jet, the conical spatial distribution of the jet increases the deposition range of the fiber and reduces the accuracy of the fiber deposition. When modified with an auxiliary electrode, the splitting and whipping of the spinning precursor jet are suppressed and the range of the jet stabilization region becomes large and fluctuates in a very narrow lane. As shown in Fig. 2 a, b, without the help of the auxiliary electrode, the jet stabilization zone of the precursor solution was 0.96 cm. And with the aid of the auxiliary electrode, the jet stabilization zone of the precursor solution was extended by 4 cm, which was four times longer than that of without the auxiliary electrode. At the same spinning distance, the extension of the stabilization zone helps to reduce the spinning deposition range and achieve the in situ precise spinning. As shown in Fig. 2 c, d, the deposition ranges of composite fibrous membranes prepared without and with the aid of an auxiliary electrode are circular regions whose diameters are 4.6 and 1.8 cm, respectively. The result demonstrates that the auxiliary electrode can effectively reduce the deposition range during the electrospinning process. Figure 2 e shows the trend of the thickness of the electrospun fiber membrane over time. With the help of the auxiliary electrode, rapid electrospinning can be achieved, and after 30 min, the thickness of the deposited composite membrane is about four times thicker than that prepared by other electrospinning method. It is clear that under the mediation of the auxiliary electrode, the electrospinning jet has a more precise deposition range and a fibrous film having a certain thickness can be formed in a short time, which has great significance in executing the in situ precise spinning and realizing the rapid electrospinning in the following magnetic hyperthermia experiment. Fig. 2 High-speed camera photos of electrospinning jet at steady zone a without and b with the auxiliary electrode. Optical photographs of in situ deposited electrospun fiber membrane c without and d with the auxiliary electrode. e Time-dependent deposition thickness curves for in situ preparation of electrospun fiber membranes Morphological, Structural, and Magnetic Properties The SEM images of PU fibrous membranes and composite membranes prepared with/without an auxiliary electrode are shown in Fig. 3 . As is apparent from Fig. 3 a, e, b, and f, the PU fibrous membranes with sub-micro size, high porosity, and random ordered orientation prepared with and without an auxiliary electrode are both the relatively bead-free and smooth matrixes of interlocking fibers. According to the statistical analyses that are inserted in the upper left corners of the SEM images, the ranges of diameters of PU fibrous membranes which are prepared in two different ways are 700–1900 nm and 1100–2300 nm, respectively, and the mean fiber diameters of them are about 1390 and 1670 nm, respectively. Obviously, the fiber diameters of PU fibrous membranes prepared with an auxiliary electrode are a little thicker than those of the other, which could be attributed to the restriction of electrostatic field by an auxiliary electrode. The addition of the auxiliary electrode constrains the electric field and further limits the whipping and elongation of the spun fibers, so that the spun fibers are relatively thicker than those fabricated in the way where the auxiliary electrodes are not added. As showed in Fig. 3 c, g, d, and h, the addition of γ-Fe 2 O 3 NPs slightly changes the surface morphology and diameter of fibers, but it does not change the geometry and porous structure of the composite fibrous membranes in comparison to PU. After the incorporation of γ-Fe 2 O 3 NPs, the fiber diameter was reduced to 850 nm and the surface of fibers exhibited an increased roughness, which might be due to the dispersion of γ-Fe 2 O 3 NPs in/on the PU fibers because of their high surface-to-volume ratio [ 22 ]. However, the as-prepared composite fibrous membranes using an auxiliary electrode become less smooth (Fig. 3 d). Therefore, in addition to the effects of magnetic particles, the addition of the auxiliary electrode during the electrospinning process inhibits the whipping of the fibers, and the solvent volatilization is incomplete, causing the fiber surface to become rougher. After the addition of γ-Fe 2 O 3 nanoparticles, besides the change in the microscopic morphology of the nanofibers, the color of the composite nanofiber membranes also changed from white to light brown, and the color remained unchanged after several washings. Fig. 3 SEM images of pure PU fiber membranes prepared a , e without and b , f with the use of an auxiliary electrode. γ-Fe 2 O 3 /PU composite fiber membranes prepared c , g without and d , h with the use of an auxiliary electrode (the insets show the diameter distributions of the electrospun fiber membranes) In order to further characterize the dispersion of γ-Fe 2 O 3 NPs incorporated in the magnetic membranes, we have analyzed the TEM image of the composite fiber membrane in detail. As can be observed in Fig. 4 , the γ-Fe 2 O 3 NPs are well dispersed and the majority of them are incapsulated firmly inside the nanofibers, thus preventing their possible leakage and migration when used as the substrate materials for magnetic hyperthermia. The γ-Fe 2 O 3 NPs show good dispersion and no agglomeration in the fiber, which means that the auxiliary electrode does not interfere the uniform distribution of magnetic particles. Fig. 4 TEM images of γ-Fe 2 O 3 /PU composite fiber membranes prepared with the use of an auxiliary electrode Figure 5 A shows the XRD patterns of neat PU fiber membranes, γ-Fe 2 O 3 magnetic nanoparticles, and electrospun γ-Fe 2 O 3 /PU composite fibrous membranes. It is found that the XRD spectra of the electrospun γ-Fe 2 O 3 /PU composite nanofibrous membranes and neat PU fiber membranes display one broad peak, pointing out a typical symbol for low crystalline materials. This result proves that the prepared PU fibrous membrane has low crystallinity. However, the positions and relative intensities of some new peaks of the composite membrane agree well with the standard diffraction card JCPDS 39-1346, which are corresponding to (220), (311), (400), (511), and (440) characteristic peaks of γ-Fe 2 O 3 magnetic nanoparticles. Compared with the γ-Fe 2 O 3 NPs, the significant decrease of the diffraction peak intensity of composite fibrous membranes can be attributed to the physical combination between γ-Fe 2 O 3 NPs and PU fibrous membranes without chemical reaction. Fig. 5 a XRD patterns of PU nanofibers, γ-Fe 2 O 3 /PU composite fiber membranes and γ-Fe 2 O 3 NPs. b FTIR spectra of ( a ) γ-Fe 2 O 3 NPs, ( b ) PU electrospun fiber membranes, and ( c ) magnetic composite fiber membranes To determine the molecular structure of the composite fibrous membranes, Fourier transform infrared (FTIR) spectra of the samples were analyzed in the spectral range of 400–4000 cm −1 (Fig. 5 B). The main band assignments are listed in Table 1 . The curve a in Fig. 5 B presents a weak and broad absorption peak observed around 3347 cm −1 , corresponding to the O-H stretching vibration of H 2 O due to the moisture absorption in γ-Fe 2 O 3 NPs. In addition, a strong band at 557 cm −1 can be assigned to the vibrational frequency of the Fe-O bond. As shown by the curve b in Fig. 5 B, the strong absorption band of electrospun PU membranes at 3328 cm −1 can be attributed to the N-H stretching; the band at 2919 cm −1 is assigned to the stretching vibration of the C-H bond in PU; the bands at 1704, 1729, 1529, 1073, and 771 cm −1 arise from the C-H asymmetrical flexing vibration, >C=H stretching vibrations, amide II band, C-O stretching, and CH 2 rocking, respectively [ 23 – 25 ]. On the other hand, by comparison, the curve c in Fig. 5 B shows the phenomenon that when γ-Fe 2 O 3 NPs were embedded, no evident changes in FTIR spectrum of composite fibrous membranes were observed. For example, the characteristic peak of Fe-O bond also appears at 557 cm −1 without obvious shift in the spectrum. However, we observed a slight shift at 1073 cm −1 in the composite fiber membrane, which means an increase in the hydrogen bond between the PU and γ-Fe 2 O 3 NPs [ 26 ]. Table 1 Major mid-IR vibrational modes and the corresponding wave numbers Description of vibrations Wave numbers (cm −1 ) -O-H stretching vibration of H 2 O 3347 -N-H stretching vibration 3328 -C-H stretching vibration 2919 >C=H stretching vibration 1729 -C-H asymmetrical flexing vibration 1704 AmidII band 1529 -C-O stretching vibration 1073 -(CH 2 ) rocking 771 -Fe-O stretching vibration 557 The magnetization curves of γ-Fe 2 O 3 NPs and composite fibrous membranes prepared with/without an auxiliary electrode, as measured by VSM at 300 K, all revealed a typical superparamagnetic behavior with no distinct hysteresis loop and magnetization values of 58.3, 10.7, and 10.0 emu/g at 15,000 Oe, respectively, which shows that all the samples possess superparamagnetism (Fig. 6 A) [ 5 , 27 ]. The obvious decrease in the magnetization value of the two kinds of composite fibrous membranes in comparison with γ-Fe 2 O 3 NPs at 15,000 Oe can be ascribed to the existence of nonmagnetic PU containing the magnetic nanoparticles and the unhomogeneous distribution of the magnetic nanoparticles in composite fibrous membranes [ 28 , 29 ]. However, the magnetization values of the two kinds of composite fibrous membranes prepared using different electrodes show deviation from the theoretical value calculated by the doping ratio of γ-Fe 2 O 3 NPs. The amount of γ-Fe 2 O 3 NPs incorporated into the composite fibrous membranes can be estimated using the equation: 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}$$ \\mathrm{Doping}\\ \\mathrm{ratio}\\ \\mathrm{of}\\ \\upgamma -{\\mathrm{Fe}}_2{\\mathrm{O}}_3\\ \\mathrm{nanoparticles}=\\kern0.5em \\mathrm{Mb}/\\mathrm{Ma}\\times 100\\% $$\\end{document} Doping ratio of γ − Fe 2 O 3 nanoparticles = Mb / Ma × 100 % Fig. 6 a Field-dependent magnetization curves of ( a ) γ-Fe 2 O 3 NPs and γ-Fe 2 O 3 /PU composite fiber membranes prepared ( b ) with and ( c ) without the use of an auxiliary electrode at room temperature. b Thermogravimetric curves of ( a ) γ-Fe 2 O 3 NPs, γ-Fe 2 O 3 /PU composite fiber membranes prepared ( b ) with and ( c ) without the use of an auxiliary electrode, and ( d ) pure PU electrospun fiber membranes where Ma, Mb are magnetization value of pure γ-Fe 2 O 3 nanoparticles and composite nanofibrous membranes at 15,000 Oe, respectively. According to Eq. ( 1 ), the actual doping ratios are about 18.3% and 17.1% in the composite membranes prepared with/without the auxiliary electrode. Besides the influences of both PU and the distribution of magnetic nanoparticles in composite fibrous membranes, the precipitation of γ-Fe 2 O 3 NPs during electrospinning process also plays a critical role in the magnetization value. The precise measurement of the doping ratio of γ-Fe 2 O 3 NPs can be further performed by the thermogravimetric analysis (TGA). In order to confirm the weight ratio of γ-Fe 2 O 3 NPs and thermal stability of composite fibrous membranes, the TGA was performed (Fig. 6 B). As the curve a in Fig. 6 B shows, the mass of γ-Fe 2 O 3 NPs does not significantly decrease with increasing temperature. The initial thermal decomposition temperature (~ 260 °C) of the composite fibrous membranes is lower than that of the pure PU fibrous membrane (~ 305 °C), which completely satisfies the demanded thermal stability of the composite fibrous membranes for the magnetic heat treatment (curves b, c, and d in Fig. 6 B). Then in the temperature range from 305 to 425 °C, the PU fibrous membranes show a steady degradation (curved in Fig. 6 B). When the temperature reaches up to 500 °C, there is no obviously residual weight for the PU fibrous membrane in comparison to the composite fibrous membranes. It can be inferred from the residual fraction of composite fibrous membranes that the γ-Fe 2 O 3 NPs doping in the composite membranes are 19.1 wt% and 20.4 wt%, which corresponds to the estimated results of VSM. Comparing the residual weight ratios of the composite fibrous membranes prepared with/without an auxiliary electrode, it is obvious that the addition of the auxiliary electrode does not affect the doping amount of the magnetic particles in the composite fibrous membranes. This small deviation of the embedded γ-Fe 2 O 3 NPs can be attributed to the electrospinning process. In Vitro Hyperthermia Measurements Magnetic nanoparticles hyperthermia utilizes the ability of the superparamagnetic γ-Fe 2 O 3 NPs to generate heat under the action of high-frequency AMF [ 30 ]. The loss mechanism of the γ-Fe 2 O 3 NPs under the AMF should be considered, respectively, whether the γ-Fe 2 O 3 NPs are dispersed or aggregated. Although the heat generation of the aggregated γ-Fe 2 O 3 NPs is determined by the hysteresis loss and the intermolecular interaction [ 31 ], the dispersed γ-Fe 2 O 3 NPs are given by the relaxation of Brown and Néel [ 32 ]. And the γ-Fe 2 O 3 NPs are incorporated and fixed inside the fibers, so the free rotation of γ-Fe 2 O 3 NPs can be excluded, and Brown relaxation does not contribute to the magnetic heating that takes place under the AMF. For the embedded magnetic nanoparticles, only the hysteresis losses and Neel relaxation make a critical impact on the magnetic reversal loss heating. The actual AMF-dependent heat generation property of the γ-Fe 2 O 3 NPs doped in polymer fibers is not easy to estimate due to the complex magnetic interaction of the mixed phases and the structure of composite fibrous membranes, the local aggregation, and the partial dispersion of the γ-Fe 2 O 3 NPs [ 33 ]. Thus, the actual AMF-dependent heat generation property of the mixed structure of the dispersed and aggregated γ-Fe 2 O 3 NPs in the fiber mat can be properly evaluated by experimental thermal behavior. Therefore, the magnetic conversion effect was performed by exposing composite fibrous membranes to an AMF. Figure 7 exhibits the time-dependent heating curves of pure PU fibrous membranes and different magnetic composite fibers. As shown in Fig. 7 a, the temperature increase was 10.5 ± 0.4, 16.2 ± 0.3, 19.1 ± 0.5, and 24.4 ± 0.3 °C for γ-Fe 2 O 3 /PU-A5, γ-Fe 2 O 3 /PU-A10, γ-Fe 2 O 3 /PU-A15, and γ-Fe 2 O 3 /PU-A20 composite fibrous membranes, respectively. And in Fig. 7 b, corresponding to the composite membranes prepared without the addition of an auxiliary electrode, the temperature increase was 4.2 ± 0.3, 5.1 ± 0.2, 6.7 ± 0.4, and 9.3 ± 0.2 °C for γ-Fe 2 O 3 /PU-5, γ-Fe 2 O 3 /PU-10, γ-Fe 2 O 3 /PU-15, and γ-Fe 2 O 3 /PU-20 composite membranes, respectively. It was observed that the heating temperature of all magnetic composite fibers increased rapidly with the increase of time and it appeared to eventually arrive at and basically maintain a balance at the end of the examination period. Also, a progressive increase in the heating rate and heating temperature emerged in both the composite fibrous membranes prepared by two different ways, as the time increased for preparing the magnetic composite fibrous membranes, and wherein the existence of γ-Fe 2 O 3 NPs was confirmed by XRD diffraction and morphological analysis. However, at the same preparation time, the heating speed of the composite fibrous membranes prepared with the aid of the auxiliary electrode was faster and the stable temperature was higher than that of the other. For example, the heating rate of the composite fibrous membranes obtained by electrospinning for 15 min with the aid of the auxiliary electrode is 0.42 °C/s, and the equilibrium temperature is 44.3 °C. Moreover, if a fiber membrane having the same heating capacity is desired, a spinning time of 20 min is required with the aid of an auxiliary electrode, which means that the addition of the auxiliary electrode can remarkably improve the spinning efficiency and make full use of the spinning precursor. The results thus clearly indicate that the heating rate and the upper limit of the temperature rise are both remarkably improved compared to the composite membranes obtained without the aid of the auxiliary electrode. In contrast, the pure PU nanofibrous membranes showed slight temperature change under the identical conditions, which could be assigned to the influence of measurement error and the ambient temperature. Fig. 7 Temperature (T)-time (t) profiles for the electrospun fiber membranes prepared by in situ electrospinning a with and b without the use of an auxiliary electrode for 5, 10, 15, and 20 min upon the application of AMF In the case of cancer therapy, the high- and low-temperature cycle of hyperthermia treatment is preferred along with other hyperthermia modes due to the chance of tumor metastasis, which means it is necessary for composite fibrous membranes to possess a uniform cyclic profile with a constant temperature rise during the heating process [ 34 ]. To test the heat stability of γ-Fe 2 O 3 /PU composite fibrous membranes, γ-Fe 2 O 3 /PU-A15 membranes were exposed to AMF for different cycles. As shown in Fig. 8 , no obvious change in the elevated temperature profiles was observed during the three cycles of AMF effect, which indicated that the γ-Fe 2 O 3 /PU composite fibrous membranes could efficiently and rapidly convert AMF energy into thermal energy. More importantly, significant superiority of the composite fibrous membranes for cancer hyperthermia treatment was their capability for repeatable heating without damaging the heating efficiency. Fig. 8 Cyclic heating profile of the electrospun fiber membranes prepared by in situ electrospinning As mentioned above, the portable electrospinning device with the aid of an auxiliary electrode can quickly and precisely deposit the electrospun fiber membrane on the collecting pole in situ, which is in favor of the close contact between the prepared electrospun fiber membrane and the affected area, and improves the heating efficiency of the magnetocaloric therapy. Moreover, the thermotherapy fibers containing chemotherapeutic drugs can also be prepared in situ on the tumor tissue, which is beneficial to the synergistic effect of the drug and hyperthermia. As shown in Fig. 9 , the electrospun fiber membrane can be prepared in situ on the surface of a hand. As can be found in Fig. 9 a, a thin PU composite fibrous membrane is formed on the surface of the hand by a portable electrostatic spinner without an auxiliary electrode. Figure 9 b shows that a tightly bonded, precisely deposited magnetic fibrous membrane is fabricated on the scar of the hand, which just like a second layer of skin due to the electrostatic attraction force. The mark has been completely covered by the magnetic fibrous membrane, while other skin tissue is not affected, which means a good versatility of the in situ preparation of magnetic fiber membranes under the assist of an auxiliary electrode. Fig. 9 Schematic of in situ electrospun magnetic fibrous membrane on the surface of hand a without an auxiliary electrode and b with an auxiliary electrode"
} | 5,747 |
33328348 | PMC7771232 | pmc | 4,020 | {
"abstract": "This first molecular biological study of archaeal immersed liquid biofilms advances our basic biological understanding of the model archaeon Haloferax volcanii . Data gleaned from this study also provide an invaluable foundation for future studies to uncover components required for immersed liquid biofilms in this haloarchaeon and also potentially for liquid biofilm formation in general, which is poorly understood compared to the formation of biofilms on surfaces.",
"introduction": "INTRODUCTION Prokaryotes have evolved a variety of strategies to mitigate the effects of environmental stress, including the establishment of biofilms, which are complex microbial communities surrounded by a matrix of extracellular polymeric substances (EPS). Of the bacteria and archaea found above the subsurface, an estimated 80% in soil and upper oceanic sediment exist in biofilms ( 1 ). It has been suggested that life within a biofilm is the primary way of active life for both bacterial and archaeal species ( 1 ), with other bacterium-specific studies suggesting that life in a biofilm is the default, with planktonic cells merely serving as mediators for the transition from one biofilm to the next ( 2 ). The advantages of being within a biofilm for bacterial cells range from communication and environmental stress protection to improved nutrient acquisition ( 3 ). Similarly, for archaeal species, the demonstrated advantages of living in a biofilm include conferring environmental stress protection, horizontal gene transfer, and syntrophy facilitation as well as mechanical and structural stability provided by EPS ( 4 – 7 ). While some biofilms, such as those that play roles in wastewater treatment or bioremediation ( 8 , 9 ), can provide a variety of important benefits to humans, others can cause serious harm, such as debilitating chronic infections ( 10 – 12 ), as biofilms confer reduced antibiotic and antimicrobial sensitivity ( 13 , 14 ) that can render the embedded bacterial cells up to 1,000 times less susceptible to treatments relative to planktonic cells ( 15 ). Thus, understanding biofilm formation is of significant public health interest. A variety of proteins necessary for biofilm formation have been identified and characterized in an array of bacterial species. Biofilm formation requires type IV pili in organisms such as Pseudomonas aeruginosa and Vibrio cholerae ( 16 – 21 ). Flagella are also sometimes required for biofilms, such as those of Escherichia coli and P. aeruginosa , under certain conditions ( 18 , 19 , 22 , 23 ). Additionally, in P. fluorescens , various surface adhesins are often critical to this process ( 24 – 26 ). While biofilms forming at surfaces have been extensively studied, much less is known about biofilms that form in liquid media. Bacillus subtilis and P. aeruginosa , for example, form pellicles, a type of biofilm that floats at the air-liquid interface (ALI) of a culture, and flagellum-based motility is important for successful pellicle formation in both organisms ( 27 – 29 ). Chemotaxis and oxygen sensing have also been shown to play crucial roles in the formation of pellicles in B. subtilis ( 29 ), and quorum sensing, a form of cell-cell communication, has been shown to be required for proper biofilm formation in species such as V. cholerae through the regulation of EPS biosynthesis ( 30 ). Cellular appendages as well as EPS are also determining factors in shaping the structure of biofilms through cell-cell and cell-surface interactions. The involved physicomechanical forces can range from adsorption/adhesion (coil formation and bridging), often via type IV pili, to repulsion-driven depletion attraction (phase separation), for example, via EPS ( 31 – 34 ). Beyond cellular components, environmental conditions can also play a role in influencing biofilms, such as relative humidity (RH) levels and temperature ( 35 ). Archaea also readily form biofilms in a variety of habitats ( 7 ). The genetically tractable cren- and euryarchaeal species tested thus far form surface-attached biofilms in a type IV pilus-dependent manner, and, in a subset of these species (such as Sulfolobus acidocaldarius and Methanococcus maripaludis ), biofilm formation is also dependent on the archaella, structures analogous to the bacterial flagella, under certain conditions ( 7 , 36 , 37 ). The model haloarchaeon Haloferax volcanii can form biofilms on surfaces at the air-liquid interface of a culture in a type IV pilus-dependent but archaellum-independent manner ( 38 ). Strains lacking the genes encoding the adhesion pilins, the prepilin peptidase, or components of the pilus biosynthesis pathway (Δ pilA1-6 , Δ pibD , and Δ pilB1C1 or Δ pilB3C3 , respectively) are impaired in adhesion to coverslips at the ALI ( 36 , 38 – 41 ). While biofilm formation in H. volcanii presumably also requires the chemotaxis machinery, as transposon insertions between the cheB and cheW1 genes result in a mutant having an adhesion defect, H. volcanii biofilm formation is not impaired in a nonmotile mutant lacking the archaellins arlA1 and arlA2 ( 38 , 42 ). Archaea can also be found in floating liquid biofilms ( 43 , 44 ). Moreover, Chimileski et al. recently described H. volcanii immersed liquid biofilms that form in static-liquid cultures ( 6 ). These biofilms contain polysaccharides, based on concanavalin A staining, and eDNA, based on 4′,6-diamidino-2-phenylindole (DAPI) staining, as major structural components and possibly also include amyloid proteins based on Congo red and thioflavin T staining ( 6 ). Chimileski et al. also reported that after homogenization of the immersed liquid biofilm, aggregation occurred in as little as 3 h, and the biofilm became more concentrated and dense over the course of 48 h ( 6 ). However, the molecular mechanisms required for the formation of these biofilms are not yet known. Here, we report that H. volcanii immersed liquid biofilms form independently of type IV pili along with chemotaxis and archaella machineries, demonstrating that the mechanisms required for the formation of H. volcanii immersed liquid biofilms differ significantly from those required for the formation of an archaeal biofilm on an abiotic surface. We also, for the first time, describe a unique, rapid change in the macroscopic, three-dimensional organization of the biofilm, forming a honeycomb-like pattern in response to reduction in humidity levels, potentially revealing a strategy to disperse from a biofilm. (This article was previously submitted to an online preprint archive [ 45 ].)",
"discussion": "DISCUSSION In this study, we developed an optimized workflow to observe the development of H. volcanii immersed liquid biofilms. Using that workflow, we determined that, for immersed liquid biofilm formation, this model haloarchaeon does not require any of the genes known to affect biofilm formation on abiotic surfaces. Deletion mutants lacking pilA1-6 , which encode type IV pilins, or pilB1C1 and pilB3C3 , which encode proteins required for pilus assembly, all of which exhibit adhesion defects in the ALI assay, could still form immersed liquid biofilms. While the H. volcanii genome encodes two additional PilB and PilC paralogs and 36 additional predicted pilins ( 39 ), which presumably can form distinct type IV pili, it is unlikely that these proteins are involved in immersed liquid biofilm formation, since the absence of pibD , which encodes the only H. volcanii prepilin peptidase ( 46 ) and is required to process prepilins prior to pilus assembly ( 53 ), did not affect immersed liquid biofilm formation. Furthermore, transposon mutants affecting H. volcanii chemotaxis genes, which result in decreased ALI adhesion, still exhibited immersed liquid biofilm formation. However, little is known about the chemotaxis and intracellular signaling of H. volcanii . Thus, it is possible that an alternative signaling pathway is required for the formation of immersed liquid biofilms. Similarly, immersed liquid biofilms formed independently of two major posttranslational modification pathways of cell surface proteins, N -glycosylation (Δ aglB and Δ agl15 ) and ArtA-dependent C-terminal lipid anchoring (Δ pssA and Δ pssD ). These modifications affect the function of various secreted proteins, including the S-layer glycoprotein. However, that does not preclude that other cell surface proteins are involved in the formation of immersed liquid biofilms. It is intriguing that none of the genes known to affect adhesion to abiotic surfaces prevented immersed liquid biofilm formation. The process through which this type of biofilm forms remains to be elucidated. However, during this study, we also observed a previously undescribed phenomenon that could provide further insights into immersed liquid biofilms: the rapid, transient, and reproducible honeycomb pattern formation that occurs in cultures with established immersed liquid biofilms upon removal of the petri dish lid. Chimileski et al. previously noted the dynamic nature of immersed liquid biofilms; however, their work focused on filamentous structures extending and retracting on the edge of the petri dish over the course of hours ( 6 ). While the time frame of these movements is quite different from the rapid formation of honeycomb patterns described here, they were triggered similarly by what was described as physical agitation (tapping or slight lifting of the petri dish lid). In fact, while not discussed in the paper, faint honeycomb-like patterns are visible by slowing down a supplemental video by Chimileski et al. (capturing 90 min in 10-s intervals) ( 6 ). As we describe here, after incubation at 45°C, honeycomb patterns formed on average within 20 ± 4 s after lid removal and dissipated on average 67 ± 13 s after lid removal (corresponding to 29 ± 9 s after peak honeycomb pattern formation). Therefore, it is likely that the social motility discussed by Chimileski et al. represents the subsequent events following the rapid honeycomb pattern formation described here. Since we showed here that honeycomb-like structures formed rapidly even in nonmotile and nonpiliated mutants, together with the short time frame of honeycomb formation, our results strongly suggest that this process is not driven by the active movement of cells. The short time frame of honeycomb pattern formation also indicates that whatever is passively moving the cells must be present within the immersed liquid biofilm before honeycomb patterns form. Therefore, honeycomb pattern formation may reveal the underlying molecular architecture of the immersed liquid biofilm. While the involved structures may not actively move, altered ionic or hydrophobic interactions between the cells and/or with (or within) components of the extracellular matrix could drive the formation of honeycomb patterns. It has been hypothesized that the EPS components of an H. volcanii immersed liquid biofilm include, primarily, polysaccharides, eDNA, and amyloid proteins ( 6 ). These EPS components likely form the underlying structure providing support for the biofilm, and under the conditions tested in this study, this skeletal structure may have played a direct role in the formation of honeycomb patterns. While EPS biosynthesis pathways in H. volcanii remain to be characterized, the pathway of exopolysaccharide biosynthesis in H. mediterranei has been determined ( 54 ). Interestingly, both immersed liquid biofilm formation and honeycomb pattern formation occurred in H. mediterranei ( Fig. S5 ), suggesting that the genes required for both processes are conserved between these species. Although none of the mutant strains analyzed in this study showed macroscopic phenotypes in the formation of immersed liquid biofilms and honeycomb patterns, the microscopic organization of these structures remains to be elucidated and might reveal differences in interactions between cells or with the extracellular matrix. 10.1128/mSphere.00976-20.5 FIG S5 H. mediterranei forms immersed liquid biofilms and honeycomb patterns. Representative images of a wild-type immersed liquid biofilm immediately after petri dish lid removal (A), followed by start of honeycomb formation 14 s after lid removal (B), peak honeycomb pattern formation 26 s after lid removal (C), and dispersal of the honeycomb pattern 71 s after lid removal (D), are shown. Cultures were incubated at 45°C prior to testing. Insets are digitally magnified images (×2.0) of the indicated area. The petri dish diameter is 10 cm. Download FIG S5, PDF file, 0.2 MB . Copyright © 2020 Schiller et al. 2020 Schiller et al. This content is distributed under the terms of the Creative Commons Attribution 4.0 International license . While, to the best of our knowledge, the rapid transition from diffuse immersed liquid biofilms into honeycomb patterns has not been described so far, honeycomb-like structures have been observed in biofilms of other prokaryotes. These honeycomb patterns often appear to serve structural roles within the biofilm and form on a microscopic scale (diameters of 5 to 50 μm compared to 1 to 5 mm of H. volcanii honeycomb-like structures described in this study) over the course of hours to days (i.e., multiple generation times). For example, a honeycomb-like meshwork generated by interconnected eDNA strands bound to cells through positively charged proteins has been reported for Staphylococcus aureus biofilms ( 55 ), and membrane-bound lipoproteins that can bind DNA have been implicated in maintaining the structure of S. aureus biofilms ( 56 ). Furthermore, in P. aeruginosa PAO1 biofilms, interactions between eDNA and exopolysaccharide Psl fibers result in web-like patterns observed in pellicles and flow cells ( 57 , 58 ). The web pattern might function as a supportive scaffold that allows bacterial attachment and subsequent growth within the biofilm ( 58 ). Furthermore, it might play a role in bacterial migration to facilitate nutrient uptake, since the web-like pattern is most pronounced in nutrient-starved areas within the biofilm ( 57 ). This is in line with studies in Listeria monocytogenes biofilms, which, under conditions of constant liquid flow, form honeycomb-like (“knitted”) structures in diluted, nutrient-poor medium but not in rich medium ( 59 ); under static conditions, honeycomb hollows were shown to contain planktonic cells, suggesting a transition to biofilm dispersal ( 60 ). A variety of benefits from honeycomb-like structures is also supported by Schaudinn et al., who hypothesize that for cells undergoing stress from fluid forces, honeycombs could provide flexibility and distribution of forces over the six vertices ( 61 ). Moreover, the increased surface area of honeycomb-like structures could aid cells faced with limited nutrients and could also serve as “communication roadways” for intercellular signaling ( 61 ). Computer models of honeycomb patterns with a larger diameter (several hundred micrometers) observed in Thiovulum majus biofilms suggest that these structures cause water advection that would result in improved distribution of oxygen within the biofilm ( 62 ). While the microscopic dimensions of these bacterial honeycomb patterns are substantially different from the macroscopic scale of the honeycomb patterns we described here for H. volcanii , these examples illustrate that honeycomb-like structures may serve important biological roles. Upon honeycomb pattern formation, an upward motion (toward the ALI) of cells was observed, followed by the dissipation of the pattern ( Movie S2 ). Since an active movement of cells is unlikely due to the lack of flagella and type IV pili in the respective mutants, which still formed honeycomb patterns, the honeycomb-like structures might contribute to increased floating properties of the biofilm. Based on the rapid formation of honeycomb patterns in H. volcanii , which is unparalleled in other prokaryotes, it is also tempting to speculate that this process results in turbulences in the liquid culture that could facilitate improved distribution of minerals and other nutrients from the surrounding media to the cells within the biofilm. The DPG experiments with constant airflow indicate that the rapid transition to honeycomb-like structures was not induced by changes in the concentration of volatiles synthesized by H. volcanii . Instead, decreasing the humidity level within the headspace of the immersed liquid biofilm triggered honeycomb pattern formation. Biofilm formation has previously been shown to be influenced by RH levels ( 35 ). Moreover, in B. subtilis , expansion of biofilm coverage area was observed with increases from low (20 to 30%) to high (80 to 90%) RH levels ( 63 ). Others have shown via simulation models that phase separation can occur within a biofilm due to aggregation of bacterial cells to provide ample volume for produced EPS ( 31 ) or as a result of cell-cell and cell-surface interactions ( 32 ). While these models focused on microscopic pattern formations, it is nevertheless tempting to speculate that in H. volcanii , the reduction in humidity led to phase separation, resulting in honeycomb pattern formation. It is challenging to determine whether the observed honeycomb-like structures are the result of an active biological response or a physicochemical effect. However, the immersed liquid biofilm, as a prerequisite, was previously shown to be formed only by living cells ( 6 ). Furthermore, a physicochemical process that involves biologically active structures, even if it is not driven by an active biological response, does not exclude the possibility of providing a fitness benefit to the organism. Honeycomb patterns may protect against increased evaporation at lower humidity levels; in general, pattern formation has been suggested to confer cells within biofilms increased protection against environmental flux ( 64 ), potentially extending to changes in humidity. EPS has also been suggested to be a protective measure against changing external conditions, such as humidity ( 65 ). Alternatively, in the natural environment of H. volcanii , humidity dispersed by wind could signal a beneficial change in environmental conditions, e.g., the mixing of water or an influx of oxygen, and honeycomb pattern formation may aid in the dispersal of immersed liquid biofilms. This hypothesis is supported by the outward and upward movement of cells following honeycomb pattern formation. Similar to the formation of immersed liquid biofilms, the molecular mechanism and genes required to form honeycomb-like structures in H. volcanii remain to be elucidated. This could provide further insights into the biological role of these structures as well. In conclusion, this study showed that H. volcanii immersed liquid biofilms form through an unknown mechanism that is independent of many of the genes required for biofilm formation at the ALI. Moreover, this study supports the notion that pattern formation within biofilms is a common phenomenon, but in contrast to previously described pattern formations in bacteria, honeycomb-like structures in H. volcanii can form on a macroscopic scale and within seconds, triggered by a reduction in humidity levels."
} | 4,831 |
39639996 | PMC7616896 | pmc | 4,022 | {
"abstract": "Bacterial communication via quorum sensing (QS) molecules, as well as toxin-antitoxin (TA) gene modules located on bacterial chromosomes are well-studied mechanisms. Escherichia coli mazEF is a stress-induced TA system mediating cell death requiring a QS extracellular death factor (EDF), the pentapeptide NNWNN. MazF is an endoribonuclease specific for ACA sites. During adverse conditions, the activated MazF generates a stress induced translation machinery, composed of MazF-processed mRNAs and selective ribosomes that specifically translate these processed mRNAs. Moreover, we identified the molecular mechanism underlying the formation of EDF from the zwf mRNA that involves distinct steps comprising the activity of MazF, the trans-translation system as well as the protease ClpPX. Bacterial trans-translation is generally known as a quality control process that rescues stalled translation complexes at the 3’-terminus of non-stop mRNAs. Our results indicate that trans-translation has a similar role in EDF generation from zwf mRNA. However, our data reveal that the trans-translation system may also provide a regulatory mechanism to attenuate EDF generation in the single cells. Thereby, the required threshold of EDF molecules is only achieved by the entire bacterial population, as expected for a genuine QS process."
} | 333 |
39639996 | PMC7616896 | pmc | 4,022 | {
"abstract": "Bacterial communication via quorum sensing (QS) molecules, as well as toxin-antitoxin (TA) gene modules located on bacterial chromosomes are well-studied mechanisms. Escherichia coli mazEF is a stress-induced TA system mediating cell death requiring a QS extracellular death factor (EDF), the pentapeptide NNWNN. MazF is an endoribonuclease specific for ACA sites. During adverse conditions, the activated MazF generates a stress induced translation machinery, composed of MazF-processed mRNAs and selective ribosomes that specifically translate these processed mRNAs. Moreover, we identified the molecular mechanism underlying the formation of EDF from the zwf mRNA that involves distinct steps comprising the activity of MazF, the trans-translation system as well as the protease ClpPX. Bacterial trans-translation is generally known as a quality control process that rescues stalled translation complexes at the 3’-terminus of non-stop mRNAs. Our results indicate that trans-translation has a similar role in EDF generation from zwf mRNA. However, our data reveal that the trans-translation system may also provide a regulatory mechanism to attenuate EDF generation in the single cells. Thereby, the required threshold of EDF molecules is only achieved by the entire bacterial population, as expected for a genuine QS process."
} | 333 |
39639996 | PMC7616896 | pmc | 4,023 | {
"abstract": "Bacterial communication via quorum sensing (QS) molecules, as well as toxin-antitoxin (TA) gene modules located on bacterial chromosomes are well-studied mechanisms. Escherichia coli mazEF is a stress-induced TA system mediating cell death requiring a QS extracellular death factor (EDF), the pentapeptide NNWNN. MazF is an endoribonuclease specific for ACA sites. During adverse conditions, the activated MazF generates a stress induced translation machinery, composed of MazF-processed mRNAs and selective ribosomes that specifically translate these processed mRNAs. Moreover, we identified the molecular mechanism underlying the formation of EDF from the zwf mRNA that involves distinct steps comprising the activity of MazF, the trans-translation system as well as the protease ClpPX. Bacterial trans-translation is generally known as a quality control process that rescues stalled translation complexes at the 3’-terminus of non-stop mRNAs. Our results indicate that trans-translation has a similar role in EDF generation from zwf mRNA. However, our data reveal that the trans-translation system may also provide a regulatory mechanism to attenuate EDF generation in the single cells. Thereby, the required threshold of EDF molecules is only achieved by the entire bacterial population, as expected for a genuine QS process."
} | 333 |
39639996 | PMC7616896 | pmc | 4,023 | {
"abstract": "Bacterial communication via quorum sensing (QS) molecules, as well as toxin-antitoxin (TA) gene modules located on bacterial chromosomes are well-studied mechanisms. Escherichia coli mazEF is a stress-induced TA system mediating cell death requiring a QS extracellular death factor (EDF), the pentapeptide NNWNN. MazF is an endoribonuclease specific for ACA sites. During adverse conditions, the activated MazF generates a stress induced translation machinery, composed of MazF-processed mRNAs and selective ribosomes that specifically translate these processed mRNAs. Moreover, we identified the molecular mechanism underlying the formation of EDF from the zwf mRNA that involves distinct steps comprising the activity of MazF, the trans-translation system as well as the protease ClpPX. Bacterial trans-translation is generally known as a quality control process that rescues stalled translation complexes at the 3’-terminus of non-stop mRNAs. Our results indicate that trans-translation has a similar role in EDF generation from zwf mRNA. However, our data reveal that the trans-translation system may also provide a regulatory mechanism to attenuate EDF generation in the single cells. Thereby, the required threshold of EDF molecules is only achieved by the entire bacterial population, as expected for a genuine QS process."
} | 333 |
35174616 | PMC9544924 | pmc | 4,024 | {
"abstract": "ABSTRACT Network theory offers innovative tools to explore the complex ecological mechanisms regulating species associations and interactions. Although interest in ecological networks has grown steadily during the last two decades, the application of network approaches has been unequally distributed across different study systems: while some kinds of interactions (e.g. plant–pollinator and host–parasite) have been extensively investigated, others remain relatively unexplored. Among the latter, aquatic macrophyte–animal associations in coastal environments have been largely neglected, despite their major role in littoral ecosystems. The ubiquity of macrophyte systems, their accessibility and multi‐faceted ecological, economical and societal importance make macrophyte–animal systems an ideal subject for ecological network science. In fact, macrophyte–animal networks offer an aquatic counterpart to terrestrial plant–animal networks. In this review, we show how the application of network analysis to aquatic macrophyte–animal associations has the potential to broaden our understanding of how coastal ecosystems function. Network analysis can also provide a key to understanding how such ecosystems will respond to on‐going and future threats from anthropogenic disturbance and environmental change. For this, we: ( i ) identify key issues that have limited the application of network theory and modelling to aquatic animal–macrophyte associations; ( ii ) illustrate through examples based on empirical data how network analysis can offer new insights on the complexity and functioning of coastal ecosystems; and ( iii ) provide suggestions for how to design future studies and establish this new research line into network ecology.",
"conclusion": "VIII. CONCLUSIONS \n We propose bipartite ecological networks as a novel analytical framework to investigate the ecological associations between marine macrophytes (i.e. macroalgae and seagrasses) and animals, on the grounds that: ( i ) human impacts and global environmental change are driving rapid, profound changes in macrophyte communities worldwide, with far‐reaching and currently unpredictable consequences on coastal biodiversity and ecosystem functioning. ( ii ) In a food‐web framework, basal macrophyte–animal links are generally represented with low resolution and based only on trophic interactions. Conversely, bipartite macrophyte–animal networks provide higher detail and account for the suite of interactions through which macrophytes sustain animal diversity, increasing our ability to model processes at the macrophyte–animal interface and their potential effects on coastal ecosystems as a whole. Through examples based on literature data, we provide guidance on how to assemble bipartite macrophyte–animal networks, explore their structure and model the effects of disturbance on network properties. We also discuss the range of ecological information obtainable with this approach. We suggest potential future directions, built on representing the multiple types of ecological interactions at play in macrophyte–animal systems in a multi‐layer framework, and on integrating macrophyte–animal networks into coastal food‐webs.",
"introduction": "I. INTRODUCTION Network science offers innovative tools to explore the complex ecological mechanisms regulating species associations and interactions (Delmas et al ., 2019 ). Rapid theoretical developments from multiple domains have recently provided researchers with new analytical and modelling tools, which allow us to venture beyond species‐specific processes and to achieve a more realistic characterisation of the mechanisms regulating natural communities (Dunne, 2006 ; Landi et al ., 2018 ; Delmas et al ., 2019 ). This development has led to an increasing recognition that ecological interactions play a fundamental role in determining how ecological systems respond to environmental change (Woodward et al ., 2010 ; Valiente‐Banuet et al ., 2015 ; Bruder et al ., 2019 ). Several studies have revealed that the effects of direct drivers of species loss – such as global climate change or human overexploitation – can propagate through the many paths connecting species into complex ecological networks, causing secondary extinctions and even driving entire systems to collapse (Dunne & Williams, 2009 ; Strona & Lafferty, 2016 ; Strona & Bradshaw, 2018 ). This insight calls for increasing efforts to improve our understanding of the mechanisms controlling network dynamics and responses to perturbations which, in turn, requires the collection of proper data. Although the availability of information on the quality and intensity of ecological interactions is growing steadily (Poelen, Simons & Mungall, 2014 ), study effort is unequally distributed, hindering our ability to generalise and compare knowledge across different ecosystems. Aside from food webs, which form an independent, long‐standing research field studied through specific theoretical and computational tools (Dunne, 2006 ), there is a disproportionately large (and still growing) number of studies addressing plant–pollinator networks compared to other kinds of interaction networks (Fig. 1 ). Other ecological interactions that have been investigated using network analysis (Fig. 1 ) include those between hosts and parasites (Runghen et al ., 2021 ), bacteria and phages (Weitz et al ., 2013 ), plants and seed dispersers (Donatti et al ., 2011 ), plants and herbivores (Araújo, 2016 ), plants and epiphytes (Naranjo et al ., 2019 ), plants/animals and their microbiota (Bennett, Evans & Powell, 2019 ), ants and their partner organisms (Cagnolo & Tavella, 2015 ), and cleaners and their clients (Quimbayo et al ., 2018 ). Such studies have provided important insights into the mechanisms regulating natural systems and advanced our understanding of the relationship between network structure and ecological stability (Bascompte & Jordano, 2007 ; Fontaine & Thébault, 2015 ; Welti, Helzer & Joern, 2017 ; Vizentin‐Bugoni et al ., 2018 ). However, to the best of our knowledge, no study has explicitly focused on the complexity of aquatic macrophyte–animal interaction networks. Here and throughout the text we refer to ‘macrophyte’ as a general term including both macroalgae and aquatic rooted vascular plants. Fig. 1 Number of peer‐reviewed publications per network type as retrieved from Google Scholar (on 23/12/2021; see Table S1 for a complete list of Google Scholar queries per network type). While different types of ecological interactions have been addressed using ecological network analysis in both terrestrial and aquatic habitats, no study has yet focused on aquatic macrophyte–animal networks. In this review, we investigate the reasons why macrophyte–animal systems have so far been largely neglected by network scientists. We then illustrate, aided by examples based on literature data, how networks analysis and modelling offer a powerful and flexible framework to explore a broad suite of fundamental ecological questions. Finally, we discuss practical ways to promote the establishment of this new field of research and its integration into coastal ecology. While our analysis mainly focuses on macrophyte–animal associations in the marine environment, we believe the approach proposed herein could provide novel insights into the functioning and ecological structure of freshwater and brackish ecosystems as well."
} | 1,861 |
37973866 | PMC10686836 | pmc | 4,025 | {
"abstract": "Development of microbial communities is a complex multiscale phenomenon with wide-ranging biomedical and ecological implications. How biological and physical processes determine emergent spatial structures in microbial communities remains poorly understood due to a lack of simultaneous measurements of gene expression and cellular behaviour in space and time. Here we combined live-cell microscopy with a robotic arm for spatiotemporal sampling, which enabled us to simultaneously acquire phenotypic imaging data and spatiotemporal transcriptomes during Bacillus subtilis swarm development. Quantitative characterization of the spatiotemporal gene expression patterns revealed correlations with cellular and collective properties, and phenotypic subpopulations. By integrating these data with spatiotemporal metabolome measurements, we discovered a spatiotemporal cross-feeding mechanism fuelling swarm development: during their migration, earlier generations deposit metabolites which are consumed by later generations that swarm across the same location. These results highlight the importance of spatiotemporal effects during the emergence of phenotypic subpopulations and their interactions in bacterial communities.",
"discussion": "Discussion and Conclusions Our analysis revealed all spatiotemporally regulated genes in Bacillus subtilis swarm development. We identified three major regions of the swarm with qualitatively different gene expression profiles and phenotypes: the region just behind the swarm front, the late swarm centre, and the intermediate spatiotemporal region between the front and the late swarm centre. At the swarm front, cells consume their preferred carbon sources, which are succinate and then malate in LB medium. At the swarm front, the cells also secrete pyruvate and fumarate, which are left in the agar across which the cells migrate. Our microscopy videos show that although the cells at the very edge of the swarm front are usually stuck or non-motile, the cells directly behind the leading edge are highly motile and frequently form rafts. Further inwards, motile cells coexist with non-motile elongated cells. In this intermediate region, biofilm matrix genes are beginning to be expressed, surfactin and fatty acids are synthesized, and the PBSX prophage is induced. In the late swarm centre, the preferred carbon sources have been depleted and cells consume pyruvate and fumarate, which were left behind in the agar by the preceding generations. As described previously 22 , 23 , cells in the late swarm centre form long threads that are present in multiple layers, resulting in a 3D biofilm. In previous work it was shown that these threads are cell chains 22 . Cell chain formation is associated with a low expression of the autolysin gene lytF 44 , which is consistent with the low expression levels of lytF we observed in the biofilm region (Supplementary Fig. 16 ). Between the gaps in the biofilm, a few short and motile cells are present. The three major regions of the swarm with distinct physiology and cellular behaviour display gradual transitions between each other and no sharp boundaries. We therefore do not expect that higher spatiotemporal resolution of transcriptomes would reveal further distinct regions of major consequence for the swarm development. However, it is possible that phenotypic subpopulations that coexist within the same spatiotemporal locations 23 , 35 are important for driving the swarm expansion. For example, in the late swarm centre, the long cell chains coexist with small motile cells, which are not distinguished by our transcriptome measurements. Furthermore, there are probably phenotypic differences of coexisting cells within the 3D biofilm due to resource gradients 6 , 45 – 47 . Similarly, in the intermediate region, long non-motile cells that sometimes form stationary clusters coexist with highly motile cells, yet again our transcriptome measurements do not distinguish these subpopulations. Potentially, these subpopulations can be distinguished by single-cell RNA-seq techniques that have emerged for bacteria, albeit with low genome coverage in their current versions 17 , 43 , 48 , 49 . In summary, we reported simultaneous measurements of densely sampled spatiotemporal transcriptomes and microscopy-based biophysical properties in a developing microbial community. Comparing gene expression patterns and phenotype patterns, we observed a surprising disconnection between motility gene expression and cell speed, indicating the substantial influence of mechanisms beyond transcriptional regulation. By combining our spatiotemporal gene expression dataset with spatiotemporal metabolite measurements, we further discovered a spatiotemporally organized cross-feeding of pyruvate and fumarate, which are secreted by cells at the swarm front that perform substrate-level phosphorylation for energy generation. The secreted pyruvate and fumarate are left behind in the agar across which the cells migrate and are then consumed by a later generation of cells to run the TCA cycle. Due to the widespread conservation of the metabolic pathways involved in this spatiotemporal cross-feeding process, we expect this process to be ubiquitous for expanding microbial communities. More generally, the multilevel spatiotemporal datasets made available through this study provide the basis for the development of detailed spatiotemporal models that will connect gene expression, cellular phenotypes and biophysical dynamics within bacterial communities."
} | 1,382 |
24622509 | null | s2 | 4,026 | {
"abstract": "Pseudomonas aeruginosa is a monoflagellated bacterium that can use its single polar flagellum to swim through liquids and move collectively over semisolid surfaces, a behavior called swarming. Previous studies have shown that experimental evolution in swarming colonies leads to the selection of hyperswarming bacteria with multiple flagella. Here we show that the advantage of such hyperswarmer mutants cannot be explained simply by an increase in the raw swimming speed of individual bacteria in liquids. Cell tracking of time-lapse microscopy to quantify single-cell swimming patterns reveals that both wild-type and hyperswarmers alternate between forward and backward runs, rather than doing the run-and-tumble characteristic of enteric bacteria such as E. coli. High-throughput measurement of swimming speeds reveals that hyperswarmers do not swim faster than wild-type in liquid. Wild-type reverses swimming direction in sharp turns without a significant impact on its speed, whereas multiflagellated hyperswarmers tend to alternate fast and slow runs and have wider turning angles. Nonetheless, macroscopic measurement of swimming and swarming speed in colonies shows that hyperswarmers expand faster than wild-type on surfaces and through soft agar matrices. A mathematical model explains how wider turning angles lead to faster spreading when swimming through agar. Our study describes for the first time the swimming patterns in multiflagellated P. aeruginosa mutants and reveals that collective and individual motility in bacteria are not necessarily correlated. Understanding bacterial adaptations to surface motility, such as hyperswarming, requires a collective behavior approach."
} | 423 |
33510173 | PMC7844223 | pmc | 4,027 | {
"abstract": "Biological organic-inorganic materials remain a popular source of inspiration for bioinspired materials design and engineering. Inspired by the self-assembling metal-reinforced mussel holdfast threads, we tested if metal-coordinate polymer networks can be utilized as simple composite scaffolds for direct in situ crosslink mineralization. Starting with aqueous solutions of polymers end-functionalized with metal-coordinating ligands of catechol or histidine, here we show that inter-molecular metal-ion coordination complexes can serve as mineral nucleation sites, whereby significant mechanical reinforcement is achieved upon nanoscale particle growth directly at the metal-coordinate network crosslink sites.",
"introduction": "Introduction From abalone shells to tendons, nature displays a wide array of organic–inorganic composites with a broad spectrum of mechanical properties spanning from hard and fracture resistant to soft and tough 1 . This remarkable variety is in large part thanks to the evolution of cell-orchestrated material assembly processes, in which cascades of catalytic proteins and ion transport mechanisms coordinate the templated mineralization of macromolecular scaffolds 2 – 5 . In the absence of successful mimicry of such active cellular material assembly, various biomacromolecular hydrogel networks have been employed in attempts to gain some control over material mineralization processes, and different biomolecular functionalities have been utilized to bind metal ions, upon which metal oxide minerals can nucleate and grow 6 – 9 . In an attempt to gain deeper insights on the coupling between early stage mineral growth dynamics and polymer network mechanics, we sought to nucleate metal oxide particle growth directly at chain-end inter-molecular crosslinking sites in a model hydrogel scaffold. To assemble such a system, we took inspiration from the incorporation of Fe-catechol coordinate crosslinks in mussel holdfast threads, a material design principle, which have been widely utilized in the integration of tunable stimuli-responsive motifs in advanced hydrogel engineering 10 – 12 . Since catechol ligands have also been shown to bind strongly to iron oxide nanoparticle surfaces 13 – 18 , we hypothesized that a catechol-polymer network could be utilized as a simple mineralization scaffold, wherein in situ iron oxide mineral nucleation is targeted directly to the network crosslink sites by strong coordination bonding, thereby avoiding the compromise in network elasticity normally observed upon particle incorporation 15 , 19 – 22 . While the Fe-catechol system serves as an ideal platform to test our proof of concept of metal-coordinate crosslink mineralization 15 , 23 – 25 , we further examined if this approach could be extended to different metal-ligand coordination systems using histidine-modified polymers, which bind ions and minerals of nickel or copper. Here, we introduce our findings supporting that metal-ion coordination complexes can indeed serve as direct mineral nucleation sites, whereby significant mechanical reinforcement is achieved upon nanoscale particle growth directly at the metal-coordinate network crosslink sites.",
"discussion": "Discussion Mineralization in macromolecular hydrogel networks is a broad field of study, which have focused on various important topics such as mineral morphogenesis control 45 – 49 , mineral incorporation of macromolecules 41 , 50 , 51 , as well as the influence of mineralization on mechanical properties, for example of solid nacre-like nanocomposites 52 , 53 . Here, we have shown that metal-coordinate crosslinked macromolecular hydrogel networks appear to offer new opportunities to direct the growth of nanoparticles through in situ gel mineralization. By nucleating minerals directly at the coordinate complex crosslinking sites, we were able to better control mineralization spatially, while mechanically reinforcing the hydrogel network using only a small amount of minerals and minimizing network defect formation typically associated with a more conventional incorporation of particles such as mixing. This approach was shown to be generally applicable to different types of metal-coordinate crosslinking systems. Furthermore, through repeated mineralization cycles, we demonstrated the ability to increase mineral content and hydrogel magnetization without sacrificing gel stiffness and strength. We thereby achieved a significant increase in stiffness using only a small amount of minerals compared with conventional nanoparticle composite gels. We note that the scope of this paper was not to mimic hard-condensed biological composite materials such as nacre 52 , 53 or chiton teeth 3 , 54 . Rather we focused on a fundamental exploration of a new bioinspired approach to reinforcement of organic–inorganic soft-condensed matter that could prove advantageous and efficient compared to conventional routes. Nonetheless, our work suggests that we can simultaneously reinforce and functionalize hydrogels with magnetic properties for potential use in soft actuation, drug delivery, and tissue engineering applications 6 – 9 , 55 , 56 . More broadly, the bioinspired approach to material solidification through targeted crosslink mineralization of aqueous metal-coordinate polymer networks presented here, could offer both resource- and cost-efficient processing pathways required to meet the future demands of sustainable manufacturing of organic–inorganic composite materials."
} | 1,366 |
40221492 | PMC11993693 | pmc | 4,028 | {
"abstract": "In this study, a novel tunable dopingless band-to-band tunneling mechanism based Leaky Integrate and Fire (LIF) neuron is proposed with a notable improvement in integration density and energy consumption. The forward transfer characteristics of Tunnel FET with sharp sub-threshold swing have been utilised to simulate the neural activity. The simulations performed using Atlas 2D software confirm that the proposed TFET can effectively replicate the spiking behavior of a biological neuron, eliminating the need for additional circuitry, in addition to offering tunable features. The proposed LIF neuron demonstrates significantly lower energy consumption, operating at just 144 aJ per spike. This energy efficiency is at least \\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}$$10^6$$\\end{document} times lower than the single MOSFET-based neuron 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}$$10^3$$\\end{document} times lower than TFET-based 1-transistor neurons reported in prior literature. This remarkable improvement is attributed to the underlying mechanism, which leverages tunneling and material engineering techniques. The proposed neuron has also been successfully investigated for the implementation of adaptable threshold logic functions (NOT, OR and AND). This offers a solution for the design of highly scalable and energy efficient threshold logic circuits for future neuromorphic computing systems. Lastly, we implement a multilayer SNN that confirms the image recognition ability of the proposed neuron with 92.1 \\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}$$\\%$$\\end{document} accuracy.",
"conclusion": "Conclusion In this article, a novel structure of a dopingless floating gate material-engineered TFET (Dl-FG-ME-TFET) is utilized to design a Leaky Integrate-and-Fire (LIF) neuron without the need for any external circuitry. The proposed neuron architecture employs a single transistor and consumes only 144 aJ per spike, which is six and three orders of magnitude lower than previously reported silicon-based MOSFET and TFET LIF neurons, respectively. The proposed LIF neuron demonstrates exceptional performance in terms of simplicity, scalability, adaptability, and energy efficiency. The Dl-FG-ME-TFET exhibits a steep subthreshold swing (SS) and a reduced threshold voltage ( \\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}$$V_{th}$$\\end{document} ), which contribute to the design of an energy-efficient LIF neuron. To evaluate the applicability of the proposed neuron in logic design, threshold logic circuits were developed, and their functionality as linearly separable logic gates was confirmed. Additionally, a multilayer SNN was constructed, achieving a 92.1% accuracy in image recognition, thereby validating the neuron’s effectiveness. The proposed neuron holds significant potential for highly scalable logical designs in the field of neuromorphic computing. Furthermore, the dopingless nature of the device eliminates doping-related issues, offering additional advantages in design and performance.",
"introduction": "Introduction Neuromorphic computing uses the human brain as a model to develop energy-efficient information processing technology that can do extremely complex jobs. By emulating the brain’s distributed topology, systems constructed using common electronics can enhance speed and energy efficiency. Significant hardware technical advancements are needed to scale up such systems and improve their speed, energy consumption, and performance by several orders of magnitude. Artificial neural network (ANN) has emerged as the potential choice to minimize the effect of Von Neumann bottlenecks paradigms in computing systems 1 – 6 . Inspired by high-parallelism biological brain networks, the bio-inspired computing architecture has emerged as a practical way to manage challenging artificial intelligence tasks without requiring frequent data shuttles in the von Neumann design. For intelligence tasks, bio-mimetic spiking neural networks (SNNs) exhibit a great deal of promise for excellent energy efficiency 7 . The third generation of ANNs, known as SNNs, were first created with inspiration from the brain 8 . The research community has been drawn to the efficiency of computers in resolving categorization and recognition issues as well as the laws guiding how the human brain functions. In order to create a neuromorphic computing system-a viable choice for a quicker and more energy-efficient computer system-researchers are working to create hardware with computational capabilities like to those of the human brain. The neuronal cell is a key component of a neural network and is necessary for its correct operation. The leaky-integrate-and-fire (LIF) model 9 – 13 is an effective method of formalizing a neuron’s dynamics and closely resembles the behavior of biological neurons. Using the outputs of other neurons, the synapses assist in activating a neuron. Through the use of ion channels, the neurotransmitter chemical compounds transfer the stored charged carrier in the potential well of the neuron cell. Ion channels are activated to produce an action potential once the accumulated charge carriers in the cell potential well reach their critical value. This causes an axon to spike and the neuron to return to its resting posture. A major problem for large-scale integrated neuromorphic computing systems is that artificial neurons are still primarily CMOS-implemented and still have high energy consumption and high hardware costs. In contrast, SNN has used a variety of emerging memory devices, to develop the artificial synapses for significantly improved energy and area efficiency 14 , 15 . Compact and energy-efficient neurons will always play a part in large-scale neuromorphic computing. Consequently, a great deal of research has been conducted to design and implement such devices. In this regard, two terminal structures include NIPIN diodes 16 and biristors 17 . However, since these devices lack a control terminal, neuron inhibition is not possible. Field effect transistor (FET) based neurons have been described in the literature as a solution to these issues. Utilizing innovative beyond-CMOS devices is one potential remedy 18 , 19 . Tunnel FET (TFET), has emerged as a promising promising energy-efficient device having steep subthreshold swing which is beneficial for low-power neuromorphic computing applications 20 – 24 . A significant obstacle that TFETs must overcome is their low ON current value, which results from the inefficiency of their ambipolar current, doping realted issues and band-to-band tunneling (BTBT) functioning. The use of strain, high-k gate insulators, low bandgap materials, and heterostructures fully addresses these issues 25 – 27 . Based on literature, FET based neurons are broadly classified as: (1) impact ionization based devices and (2) tunneling based devices. Partially depleted silicon on insulator (PDSOI) 9 and 1-T neurons 28 are examples of impact ionization-based devices. However, because of their slow body charging behaviour, these devices are energy inefficient and behave sluggishly 29 . It should be noted that impact ionization is a high current process, and that the creation of electron-hole pairs (EHPs) uses a very small portion of the drain current (0.1%), leading to energy-inefficient devices. Additionally, one of the biggest problems with impact ionization-based devices is their hot carrier dependability issue 30 . However, tunneling-based devices 31 , 32 use less energy because the charge carriers in these devices integrate into the body to raise the body potential by tunneling through drain-channel junctions. These devices use more external circuitry, which increases the circuit’s complexity and energy consumption even while they use less energy when used alone. Recently, spiking neurons have been implemented in hardware using heterojunction TFETs based on direct bandgap III-V materials 33 , 34 . The steep subthreshold swing of TFETs can lower the supply voltage for neurons, but they have a high-static-energy-consumption problem because of the high OFF-state leakage current of III-V heterojunction TFETs. This problem can be even more severe for event-driven brain-inspired neuromorphic systems. Since the circuit topology remains the same as with a traditional MOSFET-based neuron, the hardware cost for implementing a III-V-TFET-based neuron is still significant. Fig. 1 Dl-FG-ME-TFET ( a ) proposed device structure, ( b ) energy band diagram (ON, OFF state and with gate2(G2) connected to \\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}$$-0.5$$\\end{document} V), ( c ) calibrated transfer characteristics, ( d ) proposed devices transfer characteristics, ( e ) impact of floating gate (FG) length, ( f ) impact of floating gate (FG) workfunction. In this work, a spiking neuron based on novel TFET is proposed, achieving higher energy efficiency, tunability and lower hardware cost than CMOS implementation. The proposed device consists of dual semiconductor material (InGaAs and Silicon), Floating gates and does not require the conventional doping for the realization of Source and Drain regions, as these regions are created using metal work-function engineering: a charge plasma concept (CP) 35 . Due to the utilization of CP, material and oxide engineering, the proposed device is named the Dopingless Material-Engineered Floating Gate Tunnel FET (Dl-FG-ME-TFET). To obtain the neuron LIF behavior, the TFET transfer characteristics have been utilised. The main reason for employing Dl-ME-FG-TFET structure for LIF neuron design is its lower supply voltage, steep sub-threshold swing (SS), desidred threshold voltage and improved driving capability. The rest of the manuscript is arranged as follows: The description of the device parameters and schematics is presented in “Structural description and simulation parameters”. The analysis of the results is detailed in “Results”. Lastly, “Conclusion” describes the conclusion of the paper. Fig. 2 Neuron ( a ) biological, ( b ) circuit design, ( c ) input current to neuron circuit, ( d ) voltage and current spiking characteristics. Fig. 3 Electron CP device profile with tunneling rate and respective energy band diagrams of Dl-FG-ME-TFET ( a ) \\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}$$t_0$$\\end{document} without input, ( b ) \\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}$$t_1$$\\end{document} with first pulse, ( c ) \\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}$$t_2$$\\end{document} with second pulse, ( d ) \\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}$$t_3$$\\end{document} with third pulse."
} | 3,150 |
30014573 | PMC6116752 | pmc | 4,029 | {
"abstract": "Summary Microbial consortia are capable of surviving diverse conditions through the formation of synergistic population‐level structures, such as stromatolites, microbial mats and biofilms. Biotechnological applications are poised to capitalize on these unique interactions. However, current artificial co‐cultures constructed for societal benefits, including biosynthesis, agriculture and bioremediation, face many challenges to perform as well as natural consortia. Interkingdom microbial consortia tend to be more robust and have higher productivity compared with monocultures and intrakingdom consortia, but the control and design of these diverse artificial consortia have received limited attention. Further, feasible research techniques and instrumentation for comprehensive mechanistic insights have only recently been established for interkingdom microbial communities. Here, we review these recent advances in technology and our current understanding of microbial interaction mechanisms involved in sustaining or developing interkingdom consortia for biotechnological applications. Some of the interactions among members from different kingdoms follow similar mechanisms observed for intrakingdom microbial consortia. However, unique interactions in interkingdom consortia, including endosymbiosis or interkingdom‐specific cell–cell interactions, provide improved mitigation to external stresses and inhibitory compounds. Furthermore, antagonistic interactions among interkingdom species can promote fitness, diversification and adaptation, along with the production of beneficial metabolites and enzymes for society. Lastly, we shed light on future research directions to develop study methods at the level of metabolites, genes and meta‐omics. These potential research methods could lead to the control and utilization of highly diverse microbial communities.",
"conclusion": "Concluding remarks Interkingdom microbial interactions between archaea, bacteria, fungi and algae provide societal benefits in natural and engineered systems that are unlikely to be achieved in monocultures or intrakingdom consortia due to a lack of promoting symbiotic or competitive functions. Biotechnological advances allow for the development of consortia from different natural environments without the need for genetic engineering or optimization of nutrients and cell ratios (Hom and Murray, 2014 ). Similarly, emerging analytical tools targeting specific metabolites and genes can be used to manipulate synthetic microbial consortia by taking advantage of the microbial mechanisms discussed in this review. Further identification of new microorganisms, special microbial communication patterns and novel metabolites will promote interkingdom consortia construction for cost‐effective design and enhanced microbial applications, including bioremediation, bioenergy and biomedical. Importantly, understanding microbial communication and interactions within interkingdom consortia will provide references to study interactions between microorganisms and higher‐level species (Oh et al ., 2014 ), such as humans, animals and plants, and could even extend to their pathogenicity and/or immune defences."
} | 794 |
31105372 | null | s2 | 4,030 | {
"abstract": "To help mitigate future problems in the supply of platinum group metals (PGM) due to their scarcity and high demand, new recovery processes must be developed. Microbial processes are a great alternative for the recovery of PGM from waste since they are clean and environmentally friendly techniques. This research studied the microbial reduction of Pt(II) using an anaerobic granular sludge under different physiological conditions. The anaerobic granular sludge was able to reduce Pt(II) to Pt(0) nanoparticles that were deposited intracellularly as well as extracellularly as confirmed by X-ray diffraction (XRD) and transmission electron microscopy (TEM) analyses. Hydrogen (H This study reported for the first time the reduction of Pt(II) using anaerobic granular sludge and provided insights that could help develop biorecovery techniques to alleviate future problems in the supply of PGMs."
} | 223 |
21234345 | PMC3017947 | pmc | 4,033 | {
"abstract": "Methanohalophilus mahii is the type species of the genus\n Methanohalophilus , which currently comprises three distinct species with validly published names.\n Mhp. mahii represents moderately halophilic methanogenic archaea with a strictly methylotrophic metabolism.\nThe type strain SLP T was isolated from hypersaline sediments collected from the southern arm of Great Salt\nLake, Utah. Here we describe the features of this organism, together with the complete genome sequence and annotation. The 2,012,424 bp\ngenome is a single replicon with 2032 protein-coding and 63 RNA genes and part of the Genomic Encyclopedia of Bacteria\nand Archaea project. A comparison of the reconstructed energy metabolism in the halophilic species Mhp. mahii \nwith other representatives of the Methanosarcinaceae reveals some interesting differences to freshwater species.",
"conclusion": "3.4. Conclusions Anderson et al. proposed the classification of methanogens in three different classes based on a phylogenetic analysis of conserved genes and the distribution of signature proteins [ 44 ]. Based upon these criteria, Mhp. mahii is affiliated to class III methanogens except that no gene for the phage shock protein A was detected, which has been found so far in all members of the Methanosarcinales . An interesting outcome of this study is that Mhp. mahii and other halophilic species of the Methanosarcinaceae use different energy-conserving electron routes during methylotrophic methanogenesis compared to freshwater species. Msc. mazei and Msc. barkeri rely on a hydrogen cycle with molecular H 2 as intermediate whereas species adapted to saline environments prefer reduced cofactors for the intracellular transfer of reducing power. Obviously, the type of energy metabolism in Methanosarcinaceae does not correlate with the inherited halotolerance or the phylogenetic position, but seems to be the result of an adaptation to the occupied habitat, which explains why only Msc. acetivorans has omitted an H-cycle, but not the halotolerant freshwater species Msc. mazei and Msc. barkeri . It is tempting to speculate that the advantage of installing an H-cycle is the achievement of faster growth rates. Redox reactions of the rapidly diffusing H 2 molecule can proceed very fast, because they do not rely on membrane-bound redox carriers that have to interact with large enzyme complexes, which is likely to slow down electron transfer. This would offer a possible explanation for the observation that methanogens without methanophenazines can have doubling times as low as one hour whereas methanogens with a membrane-bound eletron transport chain have generally doubling times above ten hours [ 41 ]. On the other hand, utilization of H 2 as redox carrier could lead to the loss of reducing power from the cell, if freely diffusing H 2 is scavenged by competing microorganisms. The abandonment of molecular hydrogen as intermediate substrate for methanogenesis in halophilic representatives of the Methanosarcinaceae can thus be explained by a competition with sulfate reducing microorganisms, which are usually only highly abundant in sulfate-rich saline environments and consume hydrogen more efficiently than methanogens [ 53 , 72 ]. The observed effect of habitat salinity on the energy metabolism of methanogens seems to be restricted to members of the Methanosarcinaceae . This is probably based on the approximately tenfold lower hydrogen affinity of cytochrome-containing methanogens compared to methanogens of class I and class II, which are able to thrive by hydrogenotrophic methanogenesis in saline environments [ 41 ]. In summary, the obtained genome data allow the conclusion that the revealed abundance of Mhp. mahii in microbial mats of saline and hypersaline environments is based on a successful competition with other anaerobes, maybe by omitting molecular hydrogen as redox carrier, and by acquiring an oxidative stress protection system that is fully comparable to the system of microaerotolerant sulfate-reducing bacteria [ 73 ].",
"introduction": "1. Introduction Halophilic methanogens contribute significantly to carbon mineralization in marine and hypersaline environments. The preferred substrates for methanogenesis in these habitats are C-1 methylated compounds, for example, methylamines that are constantly provided by the degradation of osmolytes like glycine betaine or membrane compounds such as choline. The preference of methylated C-1 compounds over hydrogen by methanogens thriving in saline environments reflects a competition with sulfate-reducing bacteria that are able to utilize hydrogen more efficiently than methanogens, but usually cannot use methanol or methylamines as substrates [ 1 ]. Strain SLP T (= DSM 5219 T = ATCC 35705 T ) is the type strain of the moderately halophilic methanogen Methanohalophilus mahii [ 2 ]. SLP T (Salt Lake Paterek) is the only strain of this species available from culture collections and was isolated from anoxic sediments of Great Salt Lake in Utah (USA) [ 3 ]. Although SLP T represents the only described strain of this species, cultivation independent studies indicate that methanogens that are closely related to Mhp. mahii are quite common in anoxic saline environments. The 16S rRNA gene sequence of the nearest neighbor, Methanohalophilus portucalensis strain FDF-1, shares 99.8% sequence identity with SLP T whereas the type strains of all other species in the Methanosarcinales share less than 94.7% with SLP T [ 4 ]. Numerous cloned 16S rRNA genes more than 99% identical to the sequence of SLP T were retrieved from hypersaline microbial mats of solar salterns in Guerrero Negro (Baja California Sur, Mexico) [ 5 ] and Eilat (Israel) [ 6 ], an endorheic hypersaline lake in La Macha, Spain (EF031086, unpublished), the deep-sea anoxic brine lake Urania, Eastern Mediterranean Sea (AM268272, unpublished) and an oilfield in Qinghai, China (EF190085, unpublished). In addition, clones of the methyl coenzyme M reductase alpha subunit (McrA) gene were obtained from hypersaline microbial mats in Guerrero Negro ponds (EU585971-EU585973, unpublished) that display high-sequence similarities (>97%) at the amino acid level with the McrA protein gene of Mhp. mahii (Mmah_0612). \n Mhp. mahii strain SLP T is the first genome sequenced member of the genus Methanohalophilus representing moderately halophilic, methylotrophic methanogens. The comparison with the genomes of other freshwater and halophilic species belonging to the family Methanosarcinaceae provides novel insights into the genomic adaptations of methanogens to their environments.",
"discussion": "3. Results and Discussion 3.1. Biology and Evolution of Mhp. mahii 3.1.1. Phenotypic Characteristics Cells of Mhp. mahii SLP T are irregular cocci with a diameter of 0.8 to 1.8 μ m that occur singly or in small clumps ( Figure 1 ). Cells stain Gram-negative and are nonmotile [ 2 ]. Suitable salinities for growth of this moderately halophilic strain are in the range between 0.5 and 3.5 M NaCl. The highest growth rates are achieved in medium containing 2.0 M of sodium chloride, but the highest culture density was found at a salinity of 1.2 M NaCl [ 2 ]. Besides sodium, the metal ions Mg 2+ , K + , Ca 2+ , and Fe 2+ are essential for methanogenesis and growth. The pH range for growth is 6.5 to 8.2 with an optimum at pH 7.5 [ 3 ]. \n Mhp. mahii SLP T is strictly anaerobic and grows heterotrophically using methanol or methylamines as substrates for methanogenesis. No growth occurs lithotrophically with hydrogen and carbon dioxide or with the organic carbon sources acetate, formate, methionine, choline, or betaine [ 2 ]. Biotin stimulates growth of this strain in mineral medium with trimethylamine as substrate [ 33 ]. The polar lipid composition of Mhp. mahii strain SLP T was analyzed by Koga et al. [ 34 ]. They identified the following lipid components: β -hydroxyarchaeol as core lipid, glucose as glycolipid sugar and myo -inositol, ethanolamine and glycerol as phospholipid-polar head groups. The deduced structure of the polar lipid diethers is in agreement with the current taxonomy that places the genus Methanohalophilus in the family Methanosarcinaceae [ 35 ]. Further data about chemotaxonomical traits in the genus Methanohalophilus , including the determination of cytochromes or methanophenazine are currently not available. The classification and general features of Mhp. mahii strain SLP T in accordance with the MIGS recommendations [ 36 ] are summarized in Supplementary Table 2. 3.1.2. Phylogeny and Taxonomy According to current taxonomy halophilic methanogens are mainly affiliated to several genera within the family Methanosarcinaceae. Most representatives of this clade of halophilic archaea have a coccoid morphology and are methylotrophic and neutrophilic or alkaliphilic. Moderately halophilic methylotrophic species belong to the genera Methanohalophilus and Methanosalsum , slightly halophilic methanogens to the genera Methanolobus and Methanococcoides and extreme halophiles are classified in the genus Methanohalobium . In addition, the slightly halophilic species Methanolobus siciliae was described [ 37 ], but it was later transferred to the genus Methanosarcina [ 38 ]. At present the genus Methanohalophilus comprises three species with validly published names: Mhp. mahii (type species), Mhp. halophilus and Mhp. portucalensis . A fourth species, “ Mhp. euhalobius ”, was described by Obraztsova et al. [ 39 ] and Davidova et al. [ 40 ], but the species epithet has not been validated. The 16S rRNA-based tree in Figure 2 shows the phylogenetic position of Mhp. mahii strain SLP T among members of the order Methanosarcinales . The genome of strain SLP T contains three copies of the 16S rRNA gene that differ by up to one nucleotide from the previously published 16S rRNA gene sequence generated from the same strain (M59133), which contains 23 ambiguous base calls. The difference between the genome data and the herereported 16S rRNA gene sequence is most likely due to sequencing errors in the previously reported sequence. In order to obtain a more accurate view on the evolution of halophilic members of the Methanosarcinaceae a phylogenetic reconstruction based on whole-genome data of sequenced representatives of the class “ Methanomicrobia” [ 18 ] was performed. The number of aligned and filtered OrthoMCL clusters containing at least four entries (i.e., genes from distinct genomes) was 2344 and their length ranging from 27 to 1732 amino acids (267.45 on average). The concatenated supermatrix thus comprised 626,903 columns, including 577,297 variable and 291,638 parsimony-informative characters. The ML phylogeny inferred from the concatenated gene alignments is shown in Figure 3 together with ML and MP bootstrap support values. The final highest log likelihood obtained was −10,355,411.023, whereas the single best MP tree had a score of 1,907,449 (excluding uninformative sites). ML and MP topologies were identical except for a sister-group relationship between Methanoculleus marisnigri and Methanosphaerula palustris , which was preferred by MP (data not shown). Support was maximum (100%) for all branches under ML, and maximum for all but two branches under MP. The taxonomy was well recovered, and the tree showing the monophyly of all families and orders was included in the sample. However, the branching order within the family Methanosarcinaceae differed between the 16S rRNA- and whole-genome-based tree. Interestingly, the halophilic species Methanococcoides burtonii , Methanosalsum zhilinae and Mhp. mahii , which depend on NaCl for growth ( Table 3 ), form a monophyletic branch in the whole-genome tree, whereas in the reconstructed 16S rRNA tree Methanosalsum zhilinae forms a separate line of descent together with the extremely halophilic species Methanohalobium evestigatum . Thus, it is likely that the tree based on genome-scale data is more accurate than the 16S rRNA tree and for this reason it is in higher agreement with the phenotype. In addition, the whole-genome-based tree indicates that in the evolution of methanogens production of cytochromes originated in the common ancestor of Methanocellales and Methanosarcinales . Originally, it was thought that the presence of cytochromes is restricted to the order Methanosarcinales , but recently genes encoding cytochromes were detected in methanogens from rice rhizosphere representing the newly proposed order Methanocellales [ 41 ]. 3.2. Genome Structure and Content The genome consists of a 2,012,424 bp long chromosome with a 42.6% GC content ( Table 1 and Figure 4 ). Of the 2095 genes predicted, 2032 were protein-coding genes, and 63 RNAs; forty five pseudogenes were also identified. The majority of the protein-coding genes (69.7%) were assigned a putative function while the remaining ones were annotated as hypothetical proteins. The distribution of genes into COGs functional categories is presented in Table 2 . 3.3. Comparative Genome Analysis Three different types of methanogens that can be mainly distinguished by the phylogenetic analyses of housekeeping genes and by some phenotypic traits have been proposed by Anderson et al. [ 44 ]. Class I methanogens belong to the orders Methanobacteriales , Methanococcales and Methanopyrales , class II methanogens are represented by the order Methanomicrobiales and class III methanogens by Methanosarcinales . The species Mhp. mahii belongs to the family Methanosarcinaceae and hence to the class III. Postulated hallmark traits shared by all class III methanogens include the utilization of methyl compounds as sole substrate for methanogenesis, expression of cytochromes and the presence of genes encoding the following proteins: A, K, and N subunits of reduced coenzyme F 420 (F 420 H 2 ) dehydrogenase, a bacterial-type phosphoglycerate mutase, a bacterial adenylate kinase, phage shock protein A, the nonhistone chromosomal protein MC1 and an elongated variant of the condensin subunit ScpB [ 44 ]. The available genomic data set on representatives of the order Methanosarcinales is extended by presenting the complete genome of Mhp. mahii SLP T , thereby allowing a further evaluation of the postulated distribution of signature proteins in class III methanogens. Furthermore, the adaptation of methanogenic pathways to increasing environmental salt concentration in members of the Methanosarcinaceae can be reconstructed by comparison of the genomes of the saltwater-adapted species Mhp. mahii , Mco. burtonii [ 45 ] and Methanosarcina acetivorans [ 46 ] with the genetic inventory of the freshwater preferring species Msc. mazei [ 47 ] and Msc. barkeri [ 48 ]. 3.3.1. Substrate Utilization and Methanogenesis Strain SLP T is reported to grow exclusively on the C-1 compounds methanol and methyl amines whereas alternative substrates for methanogenesis like hydrogen, formate, and acetate are not utilized as substrates for growth [ 2 ]. A schematic drawing of the pathway of methanogenesis in Mhp. mahii is shown in Figure 5 . The first step in methylotrophic methanogenesis is the transfer of a methyl group to coenzyme M (CoM). Then, the coenzyme M bound methyl group is reduced with coenzyme B (CoB) to methane, thereby leading to the formation of the CoM-S-S-CoB heterodisulfide. Methyltransferase systems of methanogens generally consist of the following three components that are localized in the cytoplasm: a methyl-accepting corrinoid protein (protein C), a substrate specific methyltransferase that catalyzes methylation of the corrinoid protein (protein B) and a methyltransferase that catalyzes methyl transfer from the methylated corrinoid protein to coenzyme M (MtbA). Methylation of the corrinoid protein requires reduction of the Co(II) corrinoid to the Co(I) state. The ATP-dependent reductive activation of the corrinoid protein is catalyzed in methylotrophic methanogens by the iron-sulfur protein RamA (Mmah_1683) [ 49 ]. In Methanosarcina species it was demonstrated that the corrinoid protein and the substrate specific methyltransferase form a tight complex and that the corresponding genes are transcribed in a single operon, whereas the MtbA genes are localized somewhere else in the genome and transcribed separately [ 50 ]. This seems also to be the case in the genome of Mhp. mahii strain SLP T , where methyltransferase systems for the following substrates were identified: methanol (Mmah_0975/Mmah_0976), monomethylamine (Mmah_1136/Mmah_1137 and Mmah_1154/Mmah_1155), dimethylamine (Mmah_0498/Mmah_0499 and Mmah_1674/Mmah_1675), and trimethylamine (Mmah_1680/1682). Genes encoding permeases for the uptake of methylamines could be identified in close proximity to the methyltransferase systems: Mmah_1133/1134 (monomethylamine transporter), Mmah_0500 (dimethylamine transporter) and Mmah_1679 (trimethylamine transporter). In addition, six different isozymes of methylcobalamin:coenzyme M methyltransferases (MtbA) could be detected: Mmah_0008, Mmah_0279, Mmah_0518, Mmah_0901, Mmah_0970, and Mmah_1478. In Mhp. mahii as in several other studied Methanosarcina species and Mco. burtonii genes encoding methylamine methyltransferases contain an amber codon (UAG), which causes normally a translation stop, but in this case can be recognized by a specific suppressor tRNA that carries the modified amino acid pyrrolysine [ 51 ]. It was shown that this amino acid plays an important role in the catalysis of the methyl transfer to the cognate corrinoid protein. Pyrrolysine is ligated to the amber decoding tRNA Pyl by the pyrrolysyl-tRNA synthetase PylS (Mmah_0283). The reduction of the CoM-bound methyl group to methane is catalyzed by the enzyme methyl-coenzyme M reductase (Mcr) that is exclusively found in methanogens. It is composed of the three subunits: McrA (Mmah_0612), McrB (Mmah_0616), and McrG (Mmah_0613) and contains the nickel porphinoid F 430 as coenzyme. The reducing equivalents required for the reduction of the methyl group to methane are generated in strictly methylotrophic methanogens by the oxidation of the methyl group to carbon dioxide. Stoichiometrically, the oxidation of one methyl group to CO 2 provides, electrons for the generation of three molecules of methane. The first step in the oxidative branch of methylotrophic methanogenesis is the transfer of the methyl group from CoM to tetrahydromethanopterin (H 4 MPT), which is catalyzed by the membrane-bound enzyme complex tetrahydromethanopterin S-methyltransferase (MtrA-H). It has been shown that this multisubunit enzyme couples the exergonic transfer of the methylgroup from tetrahydromethanopterin to coenzyme M with the translocation of two sodium ions [ 52 ]. Thus, during methylotrophic methanogenesis this complex requires a sodium motive force to enable the endergonic transfer of the methylgroup from CoM to H 4 MPT. In Mhp. mahii all subunits of this enzyme are encoded in a single putative operon (Mmah_1776-1783), however, additional paralogs of some genes are found at several sites of the genome. Subsequently, the enzymes methylene-H 4 MPT reductase (Mmah_1513) and methylene-H 4 MPT dehydrogenase (Mmah_0679) oxidize the methyl to a methenylgroup using the deazaflavin cofactor F 420 as electron acceptor. The enzyme methenyl-H 4 MPT cyclohydrolase (Mmah_1138) then catalyzes the hydrolysis of methenyl-H 4 MPT to formyl-H 4 MPT. A further oxidation of the formyl group requires the transfer to the cofactor methanofuran (MF) by formyl-MF:H 4 MPT formyltransferase (Mmah_2027). Finally, the large enzyme complex formyl-MF dehydrogenase oxidizes the formyl group to CO 2 using a ferredoxin as a putative electron acceptor. It was previously shown that two different types of formyl-MF dehydrogenases are encoded in the genomes of Methanosarcina species, which is also observed in Mhp. mahii . Genes for a putative molybdate containing enzyme are arranged in a single unit (Mmah_1266–1271) whereas the presumably tungstate containing enzyme is encoded by genes that are localized at different sites or transcribed in different directions (Mmah_0590, Mmah_0950–952, Mmah_0956, and Mmah_1821). However, no gene encoding the subunit A of the tungstate containing formyl-MF dehydrogenase ( fwdA ) was identified, which may indicate that this enzyme is not functional in Mhp. mahii . Alternatively, the missing subunit could be replaced by the homologous subunit of the molybdate containing enzyme (FmdA). Genes encoding enzymes for the utilization of alternative substrates for methanogenesis, like formate dehydrogenase ( fdhAB ), F 420 -dependent alcohol dehydrogenases ( adf ), or energy-conserving [NiFe] hydrogenases ( ech ) for the uptake of H 2 were not detected in the annotated genome sequence, thus confirming the strict methylotrophy of this species. For the activation of acetate for methanogenesis Methanosarcina species use either acetate kinase ( ack ) and phosphotransacetylase ( pta ) or an ADP-forming acetyl-coenzyme A synthetase ( acdAB ). However, none of these genes were identified in the Mhp. mahii genome. 3.3.2. Energy Metabolism The generation of metabolically useful energy in methylotrophic methanogens strictly depends on the buildup of a chemiosmotic gradient that can be utilized to form ATP by a membrane localized ATP synthase complex. The establishment of an ion-motive force usually requires membrane-bound protein complexes that convert the free energy change of electron transport processes in the translocation of protons or sodium ions outside of the cell. In methanogenic archaea, the energy-conserving electron transfer route is terminated by reduction of the heterodisulfide CoM-S-S-CoB to the corresponding thiol derivates CoM-SH and CoB-SH [ 41 ]. Possible electron donors for the electron transport chain in members of the Methanosarcinaceae depend on the substrate and can be molecular hydrogen, F 420 H 2 or reduced ferredoxin [ 53 ]. A detailed description of the potential electron transfer routes and membrane-bound complexes involved in Mhp. mahii , including a comparison with the proposed pathways in Methanosarcina species, follows below and is illustrated in Figure 6 . \n Hydrogenases and Hydrogen Cycling Recently, a hydrogen-cycling mechanism was postulated for the major mechanism of reducing the heterodisulfide reductase in Msc. barkeri [ 54 ] and Msc. mazei [ 55 ]. In these freshwater species the reduced cofactors ferredoxin (Fd red ) and F 420 (F 420 H 2 ) are probably oxidized by the membrane-bound Ech hydrogenase and the cytoplasmic Frh F 420 -hydrogenase, respectively. The produced H 2 is in turn oxidized by a membrane-bound methanophenazine-reducing hydrogenase (Vht/Vho). Finally, the reduced methanophenazine (MPH 2 ) is used by the membrane-bound heterodisulfide reductase HdrED for reduction of CoM-S-S-CoB and concomitant proton translocation across the membrane [ 59 ] ( Figure 6(a) ). Interestingly, no genes encoding functional hydrogenases were identified in the Mhp. mahii genome. This would imply that H 2 cannot be used for heterodisulfide reduction during methylotrophic growth. In Table 3 it is shown that genes encoding subunits of [NiFe] hydrogenase are also absent in Mco. burtonii, another halophilic species belonging to the Methanosarcinaceae . Although several types of hydrogenases are encoded in the halotolerant marine species Msc. acetivorans , experimental data have shown that no significant hydrogenase activity is present, so that H 2 probably does not play a role as intermediate in methanogenic pathways of this species [ 56 ]. Thus, it is possible that the detected hydrogenase genes are silent or have an unknown function [ 42 ]. It is obvious from the above mentioned data that Mhp. mahii as well as Msc. acetivorans and Mco. burtonii must have evolved different strategies for the regeneration of reduced cofactors that do not rely on the generation of H 2 as intermediate. \n \n Regeneration of F 420 \n In Msc. mazei and Msc. barkeri, an alternative route for the regeneration of F 420 is possible that depends on the F 420 H 2 dehydrogenase complex (Fpo) and indicates a branched electron transfer chain in these species. Fpo is a multimeric membrane-bound complex with proton translocation activity and has some similarities with the canonical NADH dehydrogenase I (Nuo) of aerobic bacteria [ 60 ]. In Mhp. mahii and other methanogens, this enzyme complex is encoded in a large putative operon (Mmah_1589–1601) with the conserved gene arrangement fpoABCDHIJJKLMNO . Only the gene of subunit FpoF (Mmah_1512) that contains the catalytic active site for F 420 H 2 oxidation is encoded elsewhere. Interestingly, in the case of Mhp. mahii, it is adjacent to the gene of the methylene-H 4 MPT reductase (Mmah_1513), which represents one of the two enzymes in the oxidative branch of methylotrophic methanogenesis that reduce F 420 . Like the bacterial NADH dehydrogenase the Fpo F 420 H 2 dehydrogenase of methanogens reduces a lipophilic redox carrier that is localized in the cytoplasmic membrane. Methanophenazine was identified in all hitherto studied species of the Methanosarcinaceae [ 41 ] as a functional analogue of the respiratory lipoquinones that are reduced by the bacterial NADH dehydrogenase. Thus, in Mhp. mahii, the Fpo dehydrogenase is probably responsible for the regeneration of the oxidized F 420 cofactor using methanophenazine as electron acceptor. Mhp. mahii encodes also the membrane-bound heterodisulfide reductase HdrED (Mmah_0632/0633) that catalyzes the reduction of the heterodisulfide of CoM-S-S-CoB with MPH 2 as reductant. \n \n Regeneration of Oxidized Ferredoxin Several mechanisms for the regeneration of oxidized ferredoxin without the generation of hydrogen have been recently proposed. A possible pathway involves a membrane-bound protein complex that was shown to be highly expressed in Msc. acetivorans and resembles the Rnf complex of bacteria [ 42 ]. It is assumed that in Rhodobacter capsulatus, this complex employs a chemiosmotic gradient to enable the endergonic reduction of ferredoxins with NADH [ 61 ]. In Msc. acetivorans electron transfer probably takes place in the reverse direction leading to the exergonic oxidation of ferredoxin with methanophenazine as electron acceptor and concomitant proton or sodium ion translocation [ 57 ]. Notably, freshwater species of Methanosarcina that encode an Ech hydrogenase catalyzing ferredoxin oxidation do not contain genes for a Rnf complex whereas in the genomes of Mhp. mahii (Mmah_1689–1696) and Mco. burtonii a putative Rnf operon was detected ( Table 3 ), suggesting that this way of ferredoxin regeneration is the preferred option in halophilic and saltwater-inhabiting species of Methanosarcinaceae ( Figure 6(b) ). An alternative route for ferredoxin oxidation was postulated by Buan and Metcalf [ 58 ]. Based on their findings obtained with gene-deletion mutants of Msc. acetivorans, they postulate that a cytoplasmic HdrABC complex uses reduced ferredoxin for the direct reduction of the CoM-S-S-CoB heterodisulfide. A possible advantage of this reaction would be that methanophenazine would not be required as an intermediate thereby allowing faster turnover rates for ferredoxin regeneration. Moreover, a possible growth-inhibiting overreduction of the methanophenazine pool by the Rnf complex is avoided. This assumption is supported by the finding that the cytoplasmic heterodisulfide reductase is especially important under conditions allowing fast growth of Msc. acetivorans in which regeneration of CoM-SH with reduced methanophenazine could represent a rate-limiting step [ 58 ]. In Mhp. mahii two sets of genes encoding cytoplasmic heterodisulfide reductases were found. One set is organized in a putative transcriptional unit (Mmah_0415–0417) whereas the other set encodes HdrA (Mmah_0955) and HdrBC (Mmah_1786/1787) separately. \n \n ATP Synthase Complex and Ion Motive Force A common genetic trait of halophilic representatives of Methanosarcinaceae seems to be the presence of genes encoding a multisubunit sodium/proton antiporter ( Table 3 ). Antiporters of this type are encoded by six to seven different genes and were first described in bacteria as multiple-resistance/pH regulation (Mrp) complexes [ 62 ]. In Mhp. mahii, the Mrp complex is encoded in a single putative operon (Mmah_0736–0742). It has been proposed that these membrane-associated complexes function as proton-driven pumps for the efflux of sodium ions to achieve cellular homeostasis of pH and sodium [ 62 ]. Typically, genes encoding Mrp complexes are arranged as cassettes and often found in combination with distinct enzymes of the electron-transport chain, like formate dehydrogenases or energy converting hydrogenases that are supposed to translocate proton or sodium ions [ 63 ]. What could be the reason for the restricted distribution of the Mrp complex in halophilic species of the Methanosarcinaceae ? One idea is that the Mrp complex plays a role in energy metabolism when chemiosmotic gradients of Na + instead of protons are used for ATP synthesis. There is no direct evidence for this assumption, but it was shown by gene expression analyses that utilization of acetate in Msc. acetivorans stimulated production of the ATP synthase complex and the Mrp antiporter [ 42 , 57 ], which might indicate that the Mrp complex is essential for the proper functioning of the ATP synthase. A tight coupling of electron transport with ATP synthesis is most important during the growth of methanogens on acetate, because the energy yield of this substrate is very small (ΔG 0′ = −36 kJ/mol CH 4 ) and close to the limit allowing cell growth [ 55 ]. A possible explanation for the absence of the Mrp complex in freshwater species of Methanosarcina is that their ATP synthases translocate protons instead of Na + ,and hence are less dependent on sodium homeostasis compared to marine Methanosarcina species exposed to varying salinities and pH values. In contrast to several Methanosarcina species that contain two different types of ATP synthases, Mhp. mahii contains only an ATP synthase of the archaeal A 1 A 0 -type that is encoded in a single putative operon (Mmah_1442–1450). Bioinformatic analyses of the ion-translocating proteolipid c-subunit of ATP synthases would indicate that Na + translocation is used by all Methanosarcina species for the synthesis of ATP [ 42 ]. However, laboratory experiments of Pisa et al. [ 64 ] have shown that the ATP synthase of the freshwater species Msc. mazei depends on proton translocation, thus either bioinformatic predictions of the coupling ion are unreliable or ATP synthases of Methanosarcina species can depend on both, protons and sodium ions, depending on the growth conditions. \n 3.3.3. Biosynthetic Metabolism \n Carbon Assimilation \n Mhp. mahii is able to grow in minimal media with methanol as sole carbon source, which indicates that all biosynthetic precursors can be synthesized from C-1 compounds. The first step of carbon assimilation is catalyzed by the cytoplasmic acetyl-CoA synthase/CO dehydrogenase complex (Mmah_1166–1172) that synthesizes acetyl-CoA from CO 2 , CoA, and methyl-H 4 MPT in a reaction that depends on reduced ferredoxin. Alternatively, external acetate may be transported into the cell and then activated via an adenosine 5′-monophosphate (AMP) and pyrophosphate forming acetyl-CoA synthase (Mmah_1375). The gene for a membrane-bound proton-translocating pyrophosphatase (Mmah_1380) is located in close proximity on the genome and may convert the chemical energy of the pyrophosphate bond into a chemiosmotic gradient that could be used for ATP synthesis, thereby regaining some of the energy invested for the activation of acetate. Carbon assimilation further proceeds by the reductive carboxylation of acetyl-CoA to pyruvate that is catalyzed by pyruvate:ferredoxin oxidoreductase (Mmah_0351/0354). The reduced ferredoxin required for carbon assimilation is probably provided by the formyl-MF dehydrogenase complex. \n \n Central Carbon Metabolism Starting from pyruvate, further carbon skeletons for biosynthesis can be either produced by the citric acid cycle or by gluconeogenesis. In Mhp. Mahii, the enzymes phosphoenolpyruvate synthase (Mmah_0997) and pyruvate phosphate dikinase (Mmah_0650) convert pyruvate into phosphoenolpyruvate (PEP) that can enter the gluconeogenic Embden-Meyerhof-Parnas (EMP) pathway by enolase (Mmah_1993) and phosphoglycerate mutase, which is present in an archaeal (Mmah_0223) and bacterial version (Mmah_1844), as in all studied members of the Methanosarcinales [ 44 ]. In Mhp. mahii, all necessary genes are present to operate the EMP pathway also in the glycolytic direction, which indicates that glycogen or starch is probably used as reserve material in this species and degraded under starvation conditions. On the other hand, pyruvate can be directed to the citric acid cycle by the enzyme pyruvate carboxylase (Mmah_0621/0622) that produces oxaloacetate. The important precursor metabolite succinyl-CoA is probably synthesized from oxaloacetate through the reductive branch of the citric acid cycle. Annotated genes representing enzymes of the reductive fork of the citric acid cycle include malate dehydrogenase (Mmah_1107), fumarase (Mmah_0724 and Mmah_1279/1280) and fumarate reductase (Mmah_0725/0726 and Mmah_1949/1950). Although genes for a canonical succinyl-CoA synthetase were not identified, it is possible that such an enzyme is encoded by the genes Mmah_1653 (potential ATPase) and Mmh_1654 (acyl-CoA synthetase), resulting in a complete set of enzymes for the partial reductive citric acid cycle. In Mhp. mahii , as in other members of the Methanosarcinaceae studied so far, 2-oxoglutarate is synthesized from oxaloacetate through the oxidative branch of the citric acid cycle using the enzymes citrate synthase (Mmah_0479), aconitase (Mmah_0478), and isocitrate dehydrogenase (Mmah_0582). It has to be considered that the citrate synthase gene of Mhp. mahii contains an amber stop codon at position 177 of the coding nucleotide sequence, so that it is currently designated as a pseudogene. On the other hand, 2-oxoglutarate is an indispensable precursor for the synthesis of glutamate and other essential amino acids, which leads to the assumption that the UAG stop codon could encode the noncanonical amino acid pyrrolysine as in the case of the methylamine methyltransferases discussed above. \n \n Cofactor Biosynthesis The enzymology of biochemical pathways for the synthesis of methanogenesis-specific cofactors has only recently begun to unveil. However, detailed studies on the synthesis of methanofuran and coenzyme F 430 are still missing [ 65 ]. Coenzyme M biosynthesis was studied in Methanocaldococcus jannaschii, and a complete pathway including the involved genes was described [ 66 ]. Of the four enzymes catalyzing CoM synthesis in Methanocaldococcus jannaschii only the genes for sulfopyruvate decarboxylase ( comDE ; Mmah_1754/1755) were identified in the Mhp. mahii genome, which could indicate the existence of multiple pathways for sulfopyruvate production in methanogens. In contrast, several genes could be detected that probably encode enzymes participating in 2-oxoacid elongation steps required for synthesis of the 7-mercaptoheptanoyl chain of coenzyme B, that is, aksA (Mmah_1938), aksD (Mmah_0418), aksE (Mmah_0127), and aksF (Mmah_0129). Likewise, a complete set of genes ( cofC , cofD , cofE , and cofH ) involved in synthesis of the coenzyme F 420 was identified in the Mhp. mahii genome. All members of Methanosarcinaceae analyzed so far contain methanophenazine and cytochromes as part of their electron transport chains, so that genes encoding enzymes for their synthesis should be also present in Mhp. mahii . Only recently, Ogawa et al. [ 67 ] identified an enzyme in Msc. mazei that is specifically involved in the synthesis of methanophenazine. Methanophenazine contains a C-25 polyprenyl side-chain as lipophilic membrane anchor and an ether-linked redox-active phenazine moiety. It is thought that a specific step in the pathway of methanophenazine biosynthesis is the production of a C-25 prenyl group [(all- E ) geranylfarnesyl diphosphate] that is subsequently combined with 2-hydroxyphenazine or its precursor. In Msc. mazei the synthesis of all - E geranylfarnesyl diphosphate is catalyzed by an (all- E ) prenyl diphosphate synthase encoded by the gene MM_0789 whereas a homologous enzyme producing the C-20 (all- E ) geranylgeranyl diphosphate is probably encoded by MM_1767 [ 67 ]. C-20 polyprenyl hydrocarbons are generally used in methanogenic archaea for the synthesis of membrane lipids, indicating that the distribution of this enzyme is not restricted to methanogens-producing methanophenazine. Indeed, it was found that highly similar sequences ( E values <1 e − 50) of the gene MM_0789 were found only in the genomes of Mhp. mahii (Mmah_1452) and other members of the Methanosarcinales whereas a similarly restricted distribution was not evident for the gene MM_1767. Interestingly, in the genome of Mhp. mahii, a cluster of genes required for heme biosynthesis (Mmah_1457–1461) and the ATP synthase operon are located in close proximity to the tentative (all- E ) geranylfarnesyl diphosphate synthase gene (Mmah_1452), which could indicate a coordinated regulation of genes involved in electron transport phosphorylation. \n 3.3.4. Protection against Osmotic and Oxidative Stress \n Halotolerance Halophilic or halotolerant microbes adapt to low water activity or varying salt concentrations by accumulating compatible solutes that balance the cell turgor under conditions of osmotic stress. The composition of osmolytes in Mhp. mahii is currently unknown but it was investigated in the phylogenetically related species Mhp. portucalensis . In this species the principal osmotic solutes are glycine betaine, N \n ε -acetyl- β -lysine, β -glutamine and α -glucosylglycerate [ 68 ]. For energetic reasons the uptake of organic compatible solutes is preferred to de novo synthesis, hence transporters of common osmotic solutes should be encoded in the Mhp. mahii genome. Indeed, genes for an ABC-type transporter for glycine betaine (Mmah_0337–0340) were found. In addition, genes for alternative BetT-type choline transporters (Mmah_0372 and Mmah_1398) could be involved in the uptake of betaine or its precursors. In Methanosarcina species transient osmotic stress is usually compensated by the intracellular potassium (K + ) concentration [ 69 ]. Accordingly, in Mhp. mahii a K + uptake system encoded by the genes trkA (Mmah_1614), trkI (Mmah_0056) and trkH (Mmah_2022) was identified and could play a role in a salinity-dependent increase of the cytoplasmic K + concentration. Under conditions of hypoosmolarity efflux of K + and Na + ions could be catalyzed by KefC-type potassium/proton antiporters (Mmah_1757/Mmah_2010) and an NhaP-type sodium/proton antiporter (Mmah_1674), respectively. In addition, it is thought that mechanosensitive ion channels ( mscS1-3: Mmah_0364, Mmah_0563, and Mmah_0666) that are gated by membrane tension play a role in the nonspecific efflux of solutes in response to hypoosmotic stress [ 70 ]. The immediate adaptation of cells to an increase of external salt concentrations by the rapid uptake of solutes is usually complemented by the cellular synthesis of organic osmolytes. In Mhp. mahii, the synthesis of N \n ε -acetyl- β -lysine is catalyzed by lysine-2,3-aminomutase ( ablA , Mmah_1439) and β -lysine acetyltransferase ( ablB , Mmah_1438) whereas glycine betaine synthesis in methanogens relies on the genes for glycine sarcosine N-methyltransferase (Mmah_0524) and sarcosine dimethylglycine N-methyltransferase (Mmah_0525) [ 71 ]. \n \n Oxygen Tolerance Cultivation-independent studies have revealed that methanogens closely related to the type strain of Mhp. mahii are abundant in the upper layers of photosynthetically active oxygenic microbial mats of solar salterns [ 5 ]. It is likely that these microbial mats are frequently exposed to UV light and oxygen, which lead to the generation of reactive oxygen species (ROS) being extremely toxic for obligately anaerobic cells. Consequently, members of this species must have acquired highly developed mechanisms to cope with oxidative stress. An analysis of the annotated genome sequence of Mhp. mahii indicates that the oxidative stress protection system in this species comprises multiple lines of defense characterized by enzymes reacting directly with oxygen and its derivatives or are involved in the repair of damaged cellular compounds. A whole array of enzymes is putatively involved in primary oxygen detoxification: Molecular oxygen entering the cell is reduced by a predicted F 420 H 2 oxidase ( fprA, Mmah_1537). The highly reactive superoxide radical (o 2 \n − ) generated by auto-oxidation of thiols or flavins can be detoxified by two distinct desulfoferrodoxin-type superoxide reductases (Mmah_0553 and Mmah_1131) that reduce superoxide to hydrogen peroxide (H 2 O 2 ). In turn, H 2 O 2 is reduced to water by several types of peroxidases, including rubrerythrin or rubredoxin peroxidase ( rbr , Mmah_0444), a ferritin-like Dps protein ( dps , Mmah_0552), and a bacterial-type bifunctional catalase/peroxidase ( katG , Mmah_1997). On the other hand, an effective damage-repair mechanisms is installed that reacts with cellular compounds after they have become oxidized by ROS. Mhp. mahii encodes three different isozymes of 3-Cys thioredoxin peroxidases or peroxiredoxins (Mmah_0555, Mmah_1055, and Mmah_1299) that probably function as alkyl hydroperoxide reductases and repair oxidized lipids of the cytoplasmic membrane. Besides membrane lipids methionine residues of cytoplasmic proteins represent another prime target of ROS. The generation of methionine sulfoxide can lead to an alteration of the protein structure and other deleterious effects, so that it is necessary to reduce the sulfoxide moiety. In Mhp. mahii, the two different epimeric forms of methionine sulfoxide are reduced by the enzymes methionine-R-sulfoxide reductase ( msrB , Mmah_0636) and methionine-S-sulfoxide reductase ( msrA , Mmah_0990). The electron transfer chain to desulfoferrodoxins, rubrerythrin, and peroxiredoxins is probably initiated by NADPH:thioredoxin reductase (Mmah_1201) or ferredoxin:thioredoxin reductase (Mmah_0953). \n 3.4. Conclusions Anderson et al. proposed the classification of methanogens in three different classes based on a phylogenetic analysis of conserved genes and the distribution of signature proteins [ 44 ]. Based upon these criteria, Mhp. mahii is affiliated to class III methanogens except that no gene for the phage shock protein A was detected, which has been found so far in all members of the Methanosarcinales . An interesting outcome of this study is that Mhp. mahii and other halophilic species of the Methanosarcinaceae use different energy-conserving electron routes during methylotrophic methanogenesis compared to freshwater species. Msc. mazei and Msc. barkeri rely on a hydrogen cycle with molecular H 2 as intermediate whereas species adapted to saline environments prefer reduced cofactors for the intracellular transfer of reducing power. Obviously, the type of energy metabolism in Methanosarcinaceae does not correlate with the inherited halotolerance or the phylogenetic position, but seems to be the result of an adaptation to the occupied habitat, which explains why only Msc. acetivorans has omitted an H-cycle, but not the halotolerant freshwater species Msc. mazei and Msc. barkeri . It is tempting to speculate that the advantage of installing an H-cycle is the achievement of faster growth rates. Redox reactions of the rapidly diffusing H 2 molecule can proceed very fast, because they do not rely on membrane-bound redox carriers that have to interact with large enzyme complexes, which is likely to slow down electron transfer. This would offer a possible explanation for the observation that methanogens without methanophenazines can have doubling times as low as one hour whereas methanogens with a membrane-bound eletron transport chain have generally doubling times above ten hours [ 41 ]. On the other hand, utilization of H 2 as redox carrier could lead to the loss of reducing power from the cell, if freely diffusing H 2 is scavenged by competing microorganisms. The abandonment of molecular hydrogen as intermediate substrate for methanogenesis in halophilic representatives of the Methanosarcinaceae can thus be explained by a competition with sulfate reducing microorganisms, which are usually only highly abundant in sulfate-rich saline environments and consume hydrogen more efficiently than methanogens [ 53 , 72 ]. The observed effect of habitat salinity on the energy metabolism of methanogens seems to be restricted to members of the Methanosarcinaceae . This is probably based on the approximately tenfold lower hydrogen affinity of cytochrome-containing methanogens compared to methanogens of class I and class II, which are able to thrive by hydrogenotrophic methanogenesis in saline environments [ 41 ]. In summary, the obtained genome data allow the conclusion that the revealed abundance of Mhp. mahii in microbial mats of saline and hypersaline environments is based on a successful competition with other anaerobes, maybe by omitting molecular hydrogen as redox carrier, and by acquiring an oxidative stress protection system that is fully comparable to the system of microaerotolerant sulfate-reducing bacteria [ 73 ]."
} | 11,504 |
29062947 | PMC5625725 | pmc | 4,036 | {
"abstract": "Natural products (NPs) continue to play a pivotal role in drug discovery programs. The rapid development of synthetic biology has conferred the strategies of NPs production. Synthetic biology is a new engineering discipline that aims to produce desirable products by rationally programming the biological parts and manipulating the pathways. However, there is still a challenge for integrating a heterologous pathway in chassis cells for overproduction purpose due to the limited characterized parts, modules incompatibility, and cell tolerance towards product. Enormous endeavors have been taken for mentioned issues. Herein, in this review, the progresses in naturally discovering novel biological parts and rational design of synthetic biological parts are reviewed, combining with the advanced assembly technologies, pathway engineering, and pathway optimization in global network guidance. The future perspectives are also presented.",
"introduction": "1 Introduction Natural products, produced by bacteria, fungi, and plants, play a highly significant role in the drug discovery and development process [1] .Many of them, such as paclitaxel [2] ,digitalis [3] ,codeine [4] ,and erythromycin [5] are highly concerned with astonishing biological activities and are used for diverse purposes such as anticancer, congestive heart failure treatment, alleviating pains, and antibacterial, respectively. Unfortunately, these desired products are commonly isolated from native organism in low yield or synthesized with inefficient or unfeasible because of their complex structures [2] , [5] . Synthetic biology provides an alternative approach to produce these valuable products for industry application [6] , [7] .It aims to reduce the complex biosynthetic systems in originated organism to a simplified, reliable, quality-controlled heterologously artificial biological network to achieve our special goals. The biological parts, devices, or modules related to the targeting biosynthetic pathway are assembled and transplanted from the natural host into a genetically tractable host system such as Escherichia coli , Saccharomyces cerevisiae . The classical engineering strategies have been widely provided for our purposes in this approach. For example, overexpress enzymes responsible for putative bottleneck steps in biosynthetic pathway [8] , delete competing steps [9] , transfer biosynthetic machinery to an amenable heterologous host [10] ,re-regulate regulatory circuits to awaken unknown natural compounds [11] ,or even create enzyme variations by domain shuffling [12] .Nevertheless, there is still a challenge when integrating a heterologous pathway for complex natural products in chassis cells for overproduction purpose due to the limited characterized parts, modules incompatibility, and cell tolerance towards product. Thus in this review, we will discuss the strategies to deal with the problems mentioned above for products production."
} | 736 |
36311477 | PMC9597109 | pmc | 4,041 | {
"abstract": "Hemicellulose is the second most abundant carbohydrate in lignocellulosic biomass and has extensive applications. In conventional biomass refinery, hemicellulose is easily converted to unwanted by-products in pretreatment and therefore can't be fully utilized. The present study aims to summarize the most recent development of lignocellulosic polysaccharide degradation and fully convert it to value-added bioproducts through microbial and enzymatic catalysis. Firstly, bioprocess and microbial metabolic engineering for enhanced utilization of lignocellulosic carbohydrates were discussed. The bioprocess for degradation and conversion of natural lignocellulose to monosaccharides and organic acids using anaerobic thermophilic bacteria and thermostable glycoside hydrolases were summarized. Xylose transmembrane transporting systems in natural microorganisms and the latest strategies for promoting the transporting capacity by metabolic engineering were summarized. The carbon catabolite repression effect restricting xylose utilization in microorganisms, and metabolic engineering strategies developed for co-utilization of glucose and xylose were discussed. Secondly, the metabolic pathways of xylose catabolism in microorganisms were comparatively analyzed. Microbial metabolic engineering for converting xylose to value-added bioproducts based on redox pathways, non-redox pathways, pentose phosphate pathway, and improving inhibitors resistance were summarized. Thirdly, strategies for degrading lignocellulosic polysaccharides and fully converting hemicellulose to value-added bioproducts through microbial metabolic engineering were proposed.",
"introduction": "1 Introduction The extensive use of fossil fuels has brought challenges such as environmental pollution and carbon dioxide emission to the world today ( Jeffries, 2006 ). Lignocellulose is the most abundant renewable resource on earth, and converting it to value-added products offers a potential solution to the challenges ( Lin and Tanaka, 2006 ; Brat and Boles, 2013 ; Jia and Han, 2019 ; Winkelhausen and Kuzmanova, 1998 ; Chun et al., 2006 ). Lignocellulose is mainly composed of cellulose, hemicellulose, and lignin, the polysaccharides can be degraded into hexose (glucose) and pentose (xylose, arabinose) through chemical or biological processes ( Cardona and Sanchez, 2007 ; Zhao et al., 2016 ; Galbe and Zacchi, 2012 ). Xylose is the main component of hemicellulose and the second most abundant sugar in nature after glucose ( Zhao et al., 2020 ; Kawaguchi et al., 2006 ). Xylose is widely used in food ( Sasanam et al., 2021 ; Corim Marim and Gabardo, 2021 ), medicine ( Zhou and Murphy, 2010 ; Cheudjeu, 2020 ; Chen et al., 2020 ), and chemical industry ( Zhang et al., 2022a ; Wang et al., 2022 ) as food additive ( Sasanam et al., 2021 ; Corim Marim and Gabardo, 2021 ), drug excipients ( Cheudjeu, 2020 ), and feedstock ( Zhou and Murphy, 2010 ; Chen et al., 2020 ; Zhang et al., 2022a ; Wang et al., 2022 ). In addition, xylose can also be used as carbon and energy for microbial metabolism and growth. However, hemicellulose of biomass has not been fully converted to value-added products due to insufficient pretreatment of lignocellulose, carbon catabolic repression (CCR) effect and incomplete understanding of pentose metabolic process. Due to the complexity and recalcitrance structure of natural lignocellulose, it can’t be degraded directly by most microorganisms. Therefore, lignocellulose is usually pretreated by chemical or physicochemical methods in biomass refinery process ( Qasim et al., 2021 ; Yan et al., 2022 ). While in the pretreatment process, hemicellulose will inevitably be converted to unwanted chemicals (such as furfural, phenol, formic acid etc.) ( Guo et al., 2022 ; Zhang et al., 2022b ). It not only causes a waste of resources but also affects the subsequent microbial fermentation and bioproducts synthesis ( Hou et al., 2019 ). Therefore, it’s necessary to develop green and efficient processes to fully convert hemicellulose to monosaccharides and desired bioproducts. A wide variety of microorganisms in nature can grow with hemicellulose through different metabolic pathways ( Jia et al., 2018 ). Xylose typically coexists with glucose in lignocellulosic hydrolysate, so the CCR effect affects xylose utilization in microbial fermentation. Transmembrane transport is the first and critical step in xylose assimilation in microorganisms, while some of them lack efficient transmembrane transport systems, thus hindering their utilization. Metabolic engineering has been conducted to convert xylose to value-added bioproducts through microbial and enzymatic catalysis ( Kim et al., 2010 ; Singh et al., 2008a ; Jia et al., 2017 ; Ostergaard et al., 2000 ). The present review aims to discuss the latest research progress in bioprocess and metabolic engineering to convert hemicellulose to value-added bioproducts. Firstly, microbial metabolic engineering and bioprocess for utilization of lignocellulosic carbohydrates were discussed. Secondly, the metabolism, regulatory, transmembrane transport, CCR mechanism for xylose utilization in microorganisms, and microbial metabolic engineering for converting xylose to value-added bioproducts were summarized. Thirdly, bioprocess for biodegrading biomass polysaccharides and converting hemicellulose to value-added bioproducts through metabolic engineering were proposed."
} | 1,360 |
34638728 | PMC8508622 | pmc | 4,042 | {
"abstract": "Soil health and fertility issues are constantly addressed in the agricultural industry. Through the continuous and prolonged use of chemical heavy agricultural systems, most agricultural lands have been impacted, resulting in plateaued or reduced productivity. As such, to invigorate the agricultural industry, we would have to resort to alternative practices that will restore soil health and fertility. Therefore, in recent decades, studies have been directed towards taking a Magellan voyage of the soil rhizosphere region, to identify the diversity, density, and microbial population structure of the soil, and predict possible ways to restore soil health. Microbes that inhabit this region possess niche functions, such as the stimulation or promotion of plant growth, disease suppression, management of toxicity, and the cycling and utilization of nutrients. Therefore, studies should be conducted to identify microbes or groups of organisms that have assigned niche functions. Based on the above, this article reviews the aboveground and below-ground microbiomes, their roles in plant immunity, physiological functions, and challenges and tools available in studying these organisms. The information collected over the years may contribute toward future applications, and in designing sustainable agriculture.",
"introduction": "1. Introduction Plants are colonized aboveground and belowground by mutualistic and parasitic organisms. These organisms can be categorized into groups based on areas of colonization; for instance, microorganisms that colonize the external parts of the plant are generally known as epiphytes, while those that colonize the inside of the plants are endophytes. Furthermore, there are phyllosphere organisms that colonize the leaf surface; and the most abundant group of them would be the rhizosphere inhabitants, which colonize regions closest to the root system [ 1 , 2 , 3 ]. This region is teaming with microbes, which are attracted to the root systems due to their exudates. The exudates depend on the developmental stages and physiological statuses of the plants [ 4 , 5 ]. Although the recruitment of microbes to the root region may be a consequence of plant exudation, the microorganisms that colonize this region have diverse roles in supporting plant growth, development, and inhibition of host pathogens. This implies interdependency between the host and microbes in the aboveground and belowground interactions [ 6 , 7 ]. The microbial diversification, speciation, structural complexity, and interactions that surround the root systems make it essential to understand the microbial population as well as the root architecture, to have a clear view on how these interactome associate [ 8 ]. Due to the high levels of interaction between the plant and microbes, these components are observed as holobionts or metaorganisms [ 9 , 10 ]. In addition to the intertwining plant and microbe associations (plant-microbe–plant), there is the microbe–microbe and microbe–soil association. The complexity of the microbes in soil is not just circumnavigated by the plant, but by the environment and other constituents in the soil. The physicochemical and biological components of the soil largely influence the microbiome. For instance, climate change and its effect on agriculture, such as drought and flooding, severely impact soil microbiomes. Furthermore, physical changes in temperature, pH, oxygen level, and soil structure also affect its inhabitants [ 11 ]. In addition, the chemical compounds derived through the cycling of materials in the soil or from agricultural practices also affects soil biology. Microbes that adapt to a particular stress condition might be beneficial to plants, since beneficial microbes are shown to increase soil health and fertility. This is not inclusive of the role played by macro- and microorganisms belowground and aboveground in influencing the plant-microbe interaction (such as animal grazing, etc.) [ 5 ]. Beneficial microorganisms can be inoculated in soil or used as input to improve agricultural practices. Microbial inoculants are administered to the plant or the soil to boost crop productivity and health, and mitigate the negative effects of agrochemicals. It is a viable alternative to chemical treatment and is capable of promoting plant development, controlling pests and diseases, and stabilizing soil structure. These inputs may be employed as biocontrol agents, biopesticides, bioherbicides, and biofertilizers. Over the last few decades, significant developments have been made in manufacturing, marketing, and use of inoculants [ 12 ]. Nowadays, the use of inoculants is more widespread, owing to the availability of excellent and multifunctional strains in the market, improving yield at a lower cost than synthetic fertilizers. Rhizobia are the most extensively utilized microbes as inoculants [ 13 ]. The legume–rhizobia symbiosis influences the mechanism of biological nitrogen fixation (BNF), which satisfies the plant’s N needs [ 12 ]. Plant growth-promoting bacteria (PGPB) can support a plant in a range of areas on its own or in combination with other factors. PGPB influences plants through phytohormones and siderophores synthesis, phosphate solubilization, and elicitation of a plant’s internal defense against biotic and abiotic stressors [ 14 , 15 ]. Various microorganisms are increasingly being employed in agriculture for ecological pest and disease management [ 16 ]. The recent surge in new technologies in genome studies has enabled us to further characterize the microbial diversity, genome, and proteome of microorganisms living in association in soil or on plants. DNA/RNA, genome analysis, transcriptome, proteome, metagenome, and all other omics-based technologies have provided a means to dissect beneficial and non-beneficial plant-microbe interactions at depths and speeds that were not possible decades ago. These technologies enable us to understand the dynamics belowground and aboveground, to further utilize this information to improve growth, yield, and disease reduction [ 17 ]. If we are able to decipher the factors responsible for the establishment of the microbial communities in the rhizosphere, we will be able to utilize this information in designing sustainable ecosystems that are beneficial, stable, and productive for the long haul [ 18 , 19 ]. Despite the fact that the ecosystem was sustainable prior to interference, this approach restores the environment to its original state before human intervention. Hence, given the above background, this current review focuses on the aboveground and belowground microbial interactions, the development of diseases and emerging threats, the beneficial uses of microbes, and the available new tools to study them at greater depth (see Supplementary Figure S1 for the methodology of Systematic Review for Plant Microbe Interactions)."
} | 1,724 |
40143247 | PMC11945551 | pmc | 4,043 | {
"abstract": "Phages, the most abundant and diverse lifeforms on Earth, require strict parasitism for survival. During infection, temperate phages integrate both intracellular and extracellular host information to decide between lysis and lysogeny for replication. While various environmental and physiological factors influence the lysis–lysogeny decision, recent insights into phage–bacterium interactions reveal phages’ ability to communicate with and influence bacteria, leveraging the host’s quorum sensing system or small molecular signals. This article provides a succinct overview of current research advancements in this field, enhancing our understanding of phage–host dynamics and providing insights into bacteria’s multicellular behavior in antiviral defense.",
"conclusion": "3. Conclusions The burgeoning study of QS in phages sparks several intriguing inquiries: Can phages discern different QS signals to selectively infect bacteria equipped with those systems? Might phages evolve to harness additional QS or QQ homologs, thereby manipulating bacterial communications to their advantage? Are there other unique communication systems, akin to the arbitration system, employed by phages [ 112 ]? Furthermore, with multiple signal molecules at play, it remains to be clarified how these can act as either promoters or inhibitors of phage replication and whether various communication mechanisms might be activated concurrently or interactively [ 112 , 113 , 114 ], fostering competition or cooperation. While the QS dynamics within bacterial communities are relatively well-elucidated [ 115 , 116 ], understanding how phages interact with these systems is still an emerging area of research [ 91 ]. Recent studies have highlighted how phages can detect bacterial QS signals and modulate their infection strategies accordingly [ 48 , 59 , 78 ]. The current study adds to this body of work by investigating how phages utilize QS systems to control their decision between lytic and lysogenic cycles. While previous research has confirmed that QS-regulated prophage induction is a widespread phenomenon [ 59 ], current research provides new insights into the specific molecular interactions between QS signals and phage regulators, revealing potential mechanisms that remain underexplored. For example, the role of AHLs in regulating the prophage λ induction in E. coli via SdiA receptors is consistent with earlier work by Ghosh et al. [ 59 ]. But adds a novel layer by linking extracellular polysaccharide synthesis to phage induction. Furthermore, this study highlights the potential of bioinformatics approaches to predict QS-controlled mechanisms in phage–host interactions, an area that has received limited attention in previous studies. By leveraging computational tools to identify QS signatures and their interaction with phage genomic elements, we open new avenues for exploring the co-evolutionary dynamics between phages and bacteria. Overall, while the foundational concepts of QS in phage–host communication are well-supported by prior studies, the current findings provide new insights into the specific mechanisms at play and offer a refined understanding of microbial ecosystem dynamics and diversity [ 116 ]. The exploration of communication mechanisms between phages and bacteria is crucial for leveraging these interactions in environmental and medical contexts. By manipulating signal molecules and phages, it is possible to control the populations of detrimental bacteria, aiding in pollution mitigation and ecosystem management [ 111 , 117 ]. Moreover, in an era of escalating antibiotic resistance, phage therapy emerges as a promising alternative, potentially circumventing the challenges posed by resistant bacterial strains [ 118 , 119 ]. A nuanced comprehension of phage–bacterial communication can enhance the predictability, efficacy, and safety of phage therapy. For example, stimulation of the quorum sensing system in P. aeruginosa upregulates the expression of genes associated with phage receptors, thereby enhancing phage adsorption and infectivity. Additionally, the lasR gene promotes the synthesis of lipopolysaccharides (LPS) and type IV pili, which further increases the infectivity of phage vB_Pae_PLY. Moreover, the phage-encoded quorum sensing system can be modulated by natural and synthetic inhibitors, offering promising avenues for the development of novel antibacterial strategies [ 81 , 120 ]. Strategically combining signal molecules with phages might not only counteract bacterial defenses but also amplify the therapeutic potential of phages against pathogenic bacteria, offering innovative solutions to combat antibiotic-resistant infections. QS provides a comprehensive framework for understanding the intricate interactions between phages and bacteria, influencing their behaviors and physiological responses. Recent advancements in QS research hold the potential to significantly enhance our understanding of phage–host dynamics, offering deeper insights into the complexity of microbial ecosystems. This regulatory mechanism is crucial for optimizing phage survival and replication while reducing the risk of host extinction. However, the significance of these findings extends far beyond phage–host interactions. Understanding the role of quorum sensing in phage decision-making provides deeper insights into microbial ecosystem dynamics. In particular, it offers a valuable perspective on how microbial populations—including phages, bacteria, and other microorganisms—maintain stability, resilience, and diversity under fluctuating environmental conditions [ 93 ]. The QS mechanisms discovered in temperate phages have profound implications for understanding microbial ecosystem dynamics and diversity. QS enables phages to “sense” the density and behavior of their bacterial hosts and adjust their life cycle accordingly, switching between lysis and lysogeny. This process not only influences individual phage–host interactions but also shapes broader ecological equilibria within microbial communities. By regulating phage replication, QS helps control bacterial population size, preventing the overgrowth of certain strains while allowing others to thrive, thereby promoting biodiversity. This regulation is particularly critical for maintaining the stability of microbial ecosystems, where different populations interact and depend on each other for survival in natural environments [ 39 ]. In the context of environmental changes, such as nutrient availability or the presence of antimicrobial agents, QS-mediated decision-making can enhance microbial resilience. By opting for lysogeny under unfavorable conditions, phages can remain dormant, safeguarding their genetic material until conditions improve. This mechanism not only supports phage survival but also influences the evolutionary trajectory of their bacterial hosts, fostering genetic diversity and the potential for adaptive traits. Studies by Avelino Alvarez-Ordóñez et al. and Diana P. Pires et al. on QS in phage–host interactions have highlighted how these molecular signaling networks contribute to microbial community structure and resilience, underscoring the intricate balance that governs microbial ecosystems [ 121 , 122 ]. The interplay between QS, phage infection cycles, and microbial diversity presents an exciting avenue for further exploration of ecological dynamics, with implications not only for natural ecosystems but also for biotechnological applications such as phage therapy. This expanded understanding enriches our knowledge of microbial ecology, revealing that interactions between viruses and their hosts are not merely competitive but rather part of a finely tuned regulatory system that sustains microbial diversity across various habitats [ 123 ]. Such knowledge could facilitate the development of novel preventive and therapeutic strategies against bacterial infections. By unraveling how phages exploit or disrupt bacterial QS, researchers can create innovative methods to modulate bacterial behavior, combat antibiotic resistance, and improve the effectiveness of phage therapy. Future studies in this area are expected to unveil transformative applications in microbiology, infectious disease management, and other related fields.",
"introduction": "1. Introduction The evolutionary arms race between bacteria and phages has led to the development of sophisticated defense mechanisms in bacteria, such as restriction–modification (R–M) systems [ 1 ], CRISPR-Cas [ 2 ], toxin–antitoxin systems [ 3 ], and surface barriers [ 4 ]. These mechanisms not only highlight the survival strategies of these microorganisms but also provide valuable insights into microbial immunity. However, these interactions are further complicated by the ability of phages to sense and respond to bacterial population density through quorum sensing (QS). QS allows phages to adapt their infection strategy, switching between lytic and lysogenic cycles based on the density and behavior of bacterial hosts. This novel dimension of phage–bacteria interaction underscores the complexity of microbial defense and offers new avenues for therapeutic applications. Recent studies have illuminated the role of QS in modulating phage–host interactions. For instance, research on the phage VP882 revealed that it utilizes a QS system to influence its lysis–lysogeny decision, thereby affecting its replication strategy and potential to spread within the host population [ 5 ]. Additionally, a study on the lambda phage demonstrated that the CII protein, a key regulator in the phage’s life cycle, is influenced by environmental factors, including those affecting QS, which in turn impacts the phage’s decision to enter either the lytic or lysogenic pathway [ 6 ]. Understanding the interplay between QS and phage infection cycles is crucial for developing more effective phage therapies. By integrating QS mechanisms into phage therapy, we can potentially enhance phage efficacy, control bacterial populations more precisely, and mitigate the development of bacterial resistance. This approach not only deepens our knowledge of microbial immunity but also opens the door to more refined and effective strategies for managing bacterial infections, particularly in the face of rising antimicrobial resistance [ 7 ]. The R–M system acts by recognizing and cleaving foreign DNA while protecting the bacterial genome through methylation [ 8 ]. The CRISPR–Cas system, on the other hand, provides adaptive immunity by capturing and storing phage genetic material, enabling precise defense against subsequent infections with the same phage [ 9 ]. Toxin–antitoxin systems regulate the release of cellular toxins, aiding in the inhibition of phage replication, while defense islands, with their unique gene clusters, offer additional protection [ 10 ]. Additionally, bacteria can alter surface structures or induce self-destruction of infected cells to prevent phage adsorption and propagation [ 11 ]. With the advancement of research on phage–bacterial interactions, it has become evident that phages exploit host bacterial quorum sensing systems or small molecule signals to communicate with bacteria and influence their behavior. Recent studies have utilized a range of experimental techniques to detect and manipulate these quorum-sensing signals. For example, acyl-homoserine lactones (AHLs), a major class of signaling molecules in Gram-negative bacteria, are commonly quantified using high-performance liquid chromatography (HPLC) or mass spectrometry (MS) to assess their concentration in bacterial cultures. These methods enable researchers to measure the accumulation of AHLs in real time, providing insight into how phages may respond to bacterial population density. Additionally, genetic analyses, such as the use of reporter constructs with luxR or other QS receptor genes, have been employed to identify specific signaling molecules and their interactions with phage receptors. These genetic tools allow for precise manipulation of bacterial quorum sensing pathways, offering a way to dissect the role of QS in modulating phage decision-making between lytic and lysogenic cycles. For instance, studies have shown that introducing QS inhibitors or disrupting QS pathways in bacterial strains can significantly alter the behavior of infecting phages, supporting the notion that QS is a key regulator of phage–host dynamics. Research by Liu et al. and Gutiérrez et al. further illustrate the use of AHL quantification and genetic tools to explore phage responses to quorum sensing and to identify how these molecules impact the efficiency and timing of phage infection [ 12 ]. This review will explore these interactions from the perspective of QS, providing insights into the mechanisms by which phages may manipulate bacterial communication and behavior. It is hoped that this discussion will contribute to a deeper understanding of these complex interactions and guide future research in this area. 1.1. Definition and Classification of Phages Phages, viruses that specifically infect bacteria, are estimated to number over 10 31 in the biosphere [ 13 ]. They account for 20–40% of bacterial mortality daily [ 14 ], significantly influencing Earth’s biogeochemical cycles. This vast interaction underscores their role in shaping microbial populations and the planet’s ecological balance [ 14 , 15 , 16 ]. Phages are commonly classified into two categories based on their reproductive strategies: (1) lytic phages, which hijack the host bacterial machinery to replicate their genomes and produce capsid proteins, subsequently releasing progeny by inducing host cell lysis via the action of holins and endolysins; and (2) temperate phages, which integrate their genetic material into the bacterial genome and replicate alongside the host cell as a prophage. This integration confers resistance to subsequent infections by similar phages and may also impart new physiological traits to the host, establishing a symbiotic relationship. While a single infection typically triggers a lytic cycle, multiple infections often result in lysogeny [ 17 ]. Notably, the lytic and lysogenic cycles are interconnected, with temperate phages capable of switching between these two states in response to environmental cues or changes in host bacterial density, which are detected through quorum-sensing molecules [ 18 ]. Upon infection, the fate of a bacterial cell is determined by the interplay between viral decision-making and the bacterial defense system. In most cases, the phage’s decision predominates, dictating whether the cell undergoes lysis or is maintained as a host. Under these circumstances, the bacterial cell has little control over its fate. However, in certain bacteria that have evolved specialized defense mechanisms, infection can be actively halted upon detection. For instance, bacterial cells equipped with the abortive infection (Abi) system can terminate their own viability, thereby preventing further phage propagation and protecting the surrounding bacterial population [ 19 ] ( Figure 1 ). The lysis–lysogeny decision in phages is regulated by specific molecular mechanisms, exemplified by the temperate phage λ in Escherichia coli. This system has long been used as a model for understanding phage decision-making because of its well-characterized genetic framework and the ability to switch between lytic and lysogenic cycles in response to environmental cues [ 21 ]. The choice of E. coli and phage λ is not only based on their simplicity and tractability in laboratory settings but also on their ecological and clinical relevance. E. coli is a key component of the human gut microbiota and is often associated with pathogenic strains that cause a wide range of infections, from urinary tract infections to sepsis [ 22 ]. The ability of phage λ to regulate its lifecycle in response to environmental conditions is ecologically significant, as lysogeny can facilitate phage persistence in bacterial populations, potentially leading to horizontal gene transfer and the spread of virulence factors. Moreover, phage therapy, particularly targeting E. coli in clinical settings, has gained attention as an alternative to antibiotics in the face of rising antibiotic resistance [ 23 ]. This makes the E. coli –phage λ system particularly relevant for both basic research and therapeutic applications. The lysis–lysogeny decision is primarily influenced by the expression of regulatory genes during the early stages of infection. In the λ phage system, environmental factors such as low temperature, high multiplicity of infection (MOI), reduced cell size, and nutrient scarcity promote lysogeny. Conversely, conditions that favor optimal viral replication tend to bias the decision toward lysis [ 24 , 25 , 26 ]. In the lysis–lysogeny decision of bacteriophage λ, several key regulators, including CI, CII, CIII, N, Cro, Q, PL, PR, and the integrase (Int) enzyme, play crucial roles in determining whether the phage enters the lytic or lysogenic cycle. When CI protein levels are high, CI binds to the lysogenic promoters (PL and PR), repressing the expression of lytic genes and thereby directing the phage toward the lysogenic cycle, where it stably maintains its genome within the host. CII is a critical activator that promotes the maintenance of lysogeny by enhancing CI expression, facilitating entry into the lysogenic cycle [ 27 ]. CIII further stabilizes CII by protecting it from degradation by host proteases, ensuring that CII can effectively activate CI expression and support lysogenic commitment. Without the protective function of CIII, CII would be rapidly degraded, shifting the decision in favor of the lytic cycle. N is an antitermination factor that plays a pivotal role in early phage gene expression by preventing premature transcription termination, allowing the continuation of gene expression. N is essential for initiating the lytic cycle by enhancing transcriptional efficiency and supporting the synthesis of lytic proteins. Similarly, Q functions as another antitermination factor but primarily acts in the late stages of the lytic cycle. It prevents transcription termination signals from halting gene expression, ensuring the full activation of lytic genes necessary for phage replication and host cell lysis. Cro acts as an antagonist to CI, promoting the lytic cycle by inhibiting CI expression. When Cro levels are high, it competitively binds to the lysogenic promoters, repressing CI synthesis and ultimately triggering the lytic cycle. PL and PR are two major phage promoters that regulate early gene transcription. PL drives the expression of lytic genes, while PR is responsible for the transcription of lysogeny-associated genes. CI maintains the lysogenic state by binding to PL and PR, suppressing their activity and preventing lytic gene expression. The Int enzyme is a key factor in the lysogenic cycle, facilitating the integration of the phage genome into the host bacterial chromosome. This integration ensures the stable maintenance of the prophage within the bacterial genome, allowing the phage to persist in the lysogenic state [ 12 ]. At the early stage of infection, the concentrations of CII and CIII are low, allowing Cro to competitively inhibit CI and activate the expression of lytic genes. N and Q further enhance the transcription of lytic genes, promoting the progression of the lytic cycle. As the infection progresses, the concentrations of CII and CIII gradually increase. Once a critical threshold is reached, CI is activated, which in turn represses the activity of PL and PR, thereby maintaining the lysogenic state and preventing the expression of lytic genes. CII and CIII collectively support lysogeny by promoting CI expression and inhibiting the function of Cro. The molecular basis of this decision lies in the interplay between the CII protein, N anti-terminator protein, and Q anti-terminator protein. This interaction subsequently regulates the expression of the CI protein and the Int gene, which are critical for determining the phage’s fate between lysis and lysogeny [ 24 ]. Increased levels of CII promote lysogeny by inhibiting the expression of the lysis gene Cro and facilitating the activation of Int, which enables the integration of phage DNA into the bacterial genome. Conversely, reduced CII levels lead to the activation of Cro expression, which is repressed by the CI repressor protein, thereby favoring the lytic cycle [ 28 ]. Subsequently, the function of the Q anti-terminator facilitates the expression of structural and lysis genes. The expressed proteins will then assemble new phage particles and lyse the host cell, thereby initiating the lytic cycle through the activation of lysis genes mediated by the Q anti-terminator [ 29 ]. Elevated levels of CII promote lysogeny by inhibiting the expression of the lytic gene Cro and facilitating the activation of Int, which drives the integration of phage DNA into the bacterial genome. In contrast, reduced CII levels result in the derepression of Cro expression, which is normally inhibited by the CI repressor protein, thereby tipping the balance towards the lytic cycle [ 30 ]. Additionally, various environmental and physiological factors can influence the phage’s decision to enter either the lytic or lysogenic cycle. These factors include fluctuations in salinity, aeration, nutrient availability, temperature, pH, and exposure to antibiotics, as well as external stimuli such as ultraviolet light, hydrogen peroxide, pollutants, and changes in bacterial or phage density. Furthermore, interactions with other prophages may also play a role in modulating this decision [ 24 , 31 , 32 , 33 , 34 , 35 , 36 , 37 , 38 , 39 , 40 ]. In nature, phages employ additional infection strategies beyond the conventional lytic and lysogenic cycles, including pseudolysogeny and chronic infection. Pseudolysogeny, a less common phenomenon induced by nutrient deprivation, involves the phage genome persisting as a dormant, non-integrated entity within the host. This state is maintained until conditions improve, at which point the phage may either enter the lytic cycle or establish lysogeny [ 24 ]. In contrast, during chronic infection, phages replicate continuously within the host and are released gradually without inducing cell lysis. This process allows for the sustained release of viral particles over an extended period [ 41 ] ( Figure 2 ). It should be noted that not all phages are capable of pseudolysogeny—indeed, pseudolysogeny is a variant form of lysogeny—whereas the strictly virulent phages we discuss are lytic by nature, a trait determined by the phage’s own genetic makeup and mechanisms. 1.2. Introduction of Quorum Sensing Recent decades of research have significantly broadened our understanding of communication, extending it beyond multicellular organisms to encompass microorganisms. Bacteria, for example, utilize small molecules to communicate both with each other and with eukaryotic hosts, thereby influencing a range of physiological processes, from gene expression to cell interactions. A key example of microbial communication is QS, in which bacteria assess their population density through the secretion of autoinducers (AIs) and use this information to coordinate collective behaviors such as biofilm formation, antibiotic resistance, and host interactions. Although QS systems and their specific responses can vary across species, the fundamental principles underlying these systems are highly conserved. At low cell densities, AI concentrations are insufficient to activate QS; however, as bacterial populations increase, the accumulation of AIs triggers coordinated actions that benefit the community, such as bioluminescence or the expression of virulence factors [ 44 , 45 , 46 ]. Additionally, QS is counterbalanced by quorum quenching (QQ), which disrupts these communications [ 47 ]. Intriguingly, recent research shows that phages can employ a similar arbitration system to gauge their densities, influencing their decision between lytic and lysogenic cycles [ 48 , 49 , 50 ]. This review highlights significant advances in understanding how quorum sensing mediates phage–host interactions.\n\n1.2. Introduction of Quorum Sensing Recent decades of research have significantly broadened our understanding of communication, extending it beyond multicellular organisms to encompass microorganisms. Bacteria, for example, utilize small molecules to communicate both with each other and with eukaryotic hosts, thereby influencing a range of physiological processes, from gene expression to cell interactions. A key example of microbial communication is QS, in which bacteria assess their population density through the secretion of autoinducers (AIs) and use this information to coordinate collective behaviors such as biofilm formation, antibiotic resistance, and host interactions. Although QS systems and their specific responses can vary across species, the fundamental principles underlying these systems are highly conserved. At low cell densities, AI concentrations are insufficient to activate QS; however, as bacterial populations increase, the accumulation of AIs triggers coordinated actions that benefit the community, such as bioluminescence or the expression of virulence factors [ 44 , 45 , 46 ]. Additionally, QS is counterbalanced by quorum quenching (QQ), which disrupts these communications [ 47 ]. Intriguingly, recent research shows that phages can employ a similar arbitration system to gauge their densities, influencing their decision between lytic and lysogenic cycles [ 48 , 49 , 50 ]. This review highlights significant advances in understanding how quorum sensing mediates phage–host interactions."
} | 6,456 |
28899031 | PMC5812533 | pmc | 4,044 | {
"abstract": "Abstract The recent start-up of several full-scale ‘second generation’ ethanol plants marks a\nmajor milestone in the development of Saccharomyces cerevisiae strains\nfor fermentation of lignocellulosic hydrolysates of agricultural residues and energy\ncrops. After a discussion of the challenges that these novel industrial contexts impose on\nyeast strains, this minireview describes key metabolic engineering strategies that have\nbeen developed to address these challenges. Additionally, it outlines how proof-of-concept\nstudies, often developed in academic settings, can be used for the development of robust\nstrain platforms that meet the requirements for industrial application. Fermentation\nperformance of current engineered industrial S. cerevisiae strains is no\nlonger a bottleneck in efforts to achieve the projected outputs of the first large-scale\nsecond-generation ethanol plants. Academic and industrial yeast research will continue to\nstrengthen the economic value position of second-generation ethanol production by further\nimproving fermentation kinetics, product yield and cellular robustness under process\nconditions.",
"introduction": "INTRODUCTION Alcoholic fermentation is a key catabolic process in most yeasts and in many fermentative\nbacteria that concentrates the heat of combustion of carbohydrates into two-thirds of their\ncarbon atoms \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym} \n\\usepackage{amsfonts} \n\\usepackage{amssymb} \n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n}{}$({\\rm (CH_2O)}_n \\rightarrow \\frac13n\\ {\\rm C_2H_6O} + \\frac13n\\ {\\rm CO_2)}$\\end{document} .\nIts product, ethanol, has been used as an automotive fuel for over a century (Bernton,\nKovarik and Sklar 1982 ). With an estimated global\nproduction of 100 Mton (Renewable Fuels Association 2016 ), ethanol is the largest-volume product in industrial biotechnology. Its\nproduction is, currently, mainly based on fermentation of cane sugar or hydrolysed corn\nstarch with the yeast Saccharomyces cerevisiae. Such ‘first generation’\nbioethanol processes are characterized by high ethanol yields on fermentable sugars (>90%\nof the theoretical maximum yield of 0.51 g ethanol·(g hexose sugar) −1 ), ethanol\ntiters of up to 21% (w/w), and volumetric productivities of 2–3\nkg·m −3 ·h −1 (Thomas and Ingledew 1992 ; Della-Bianca et al. 2013 ; Lopes et al. 2016 ). Over the past two decades, a large international effort, involving researchers in academia,\nresearch institutes and industry, has aimed to access abundantly available agricultural and\nforestry residues, as well as fast-growing energy crops, as alternative feedstocks for fuel\nethanol production (Rude and Schirmer 2009 ).\nIncentives for this effort, whose relative impact depends on geographical location and\nvaries over time, include reduction of the carbon footprint of ethanol production (Otero,\nPanagiotou and Olsson 2007 ), prevention of\ncompetition with food production for arable land (Nordhoff 2007 ; Tenenbaum 2008 ),\nenergy security in fossil-fuel importing countries (Farrell et al. 2006 ) and development of rural economies (Kleinschmidt\n 2007 ). Techno-economic forecasts of low-carbon\nscenarios for global energy supply almost invariably include liquid biofuels as a\nsignificant contributor (Yan, Inderwildi and King 2010 ). Moreover, successful implementation of economically and environmentally\nsustainable ‘second generation’ bioethanol processes can pave the way for similar processes\nto produce other biofuels and commodity chemicals (Pereira et al. 2015 ). In contrast to starch, a plant storage carbohydrate that can be easily hydrolysed, the\nmajor carbohydrate polymers in lignocellulosic plant biomass (cellulose, hemicellulose and,\nin some cases, pectin) contribute to the structure and durability of stalks, leaves and\nroots (Hahn-Hägerdal et al. 2006 ).\nConsistent with these natural functions and with their chemical diversity and complexity,\nmobilization of these polymers by naturally occurring cellulose-degrading microorganisms\nrequires complex arrays of hydrolytic enzymes (Lynd et al. 2002 ; Van den Brink and de Vries 2011 ). The second-generation ethanol processes that are now coming on line at demonstration- and\nfull commercial scale (Table 1 ) are mostly based on\nfermentation of lignocellulosic biomass hydrolysates by engineered strains of S.\ncerevisiae . While this yeast has a strong track record in first-generation\nbioethanol production and its amenability to genetic modifications is excellent, S.\ncerevisiae cannot hydrolyse cellulose or hemicellulose. Therefore, in\nconventional process configurations for second-generation bioethanol production, the\nfermentation step is preceded by chemical/physical pretreatment and enzyme-catalysed\nhydrolysis by cocktails of fungal hydrolases, which can either be produced on- or off-site\n(Fig. 1 ; Sims-Borre 2010 ). Alternative process configurations, including simultaneous\nsaccharification and fermentation and consolidated bioprocessing by yeast cells expressing\nheterologous hydrolases are intensively investigated (Olson et al. 2012 ; Den Haan et al. 2015 ). However, the high temperature optima of fungal\nenzymes and low productivity of heterologously expressed hydrolases in S.\ncerevisiae have so far precluded large-scale implementation of these alternative\nstrategies for lignocellulosic ethanol production (Vohra et al. 2014 ; Den Haan et al. 2015 ). This minireview will, therefore, focus on the\ndevelopment of yeast strains for conventional process designs. Figure 1. Schematic process-flow diagram for ethanol production from lignocellulose, based on\nphysically separated processes for pre-treatment, hydrolysis and fermentation, combined\nwith on-site cultivation of filamentous fungi for production of cellulolytic enzymes and\non-site propagation of engineered pentose-fermenting yeast strains. Table 1. Overview of operational commercial-scale (demonstration) plants for second-generation\nbioethanol production. Data for USA and Canada reflect status in May 2017 (source:\nEthanol Producer Magazine 2017 ); data for other\ncountries (source: UNCTAD 2016 ) reflect status\nin 2016. Company/plant Country (state) Feedstock Capacity ML·year −1 DuPont Cellulosic Ethanol LLC—Nevada USA (IA) Corn stover 113.6 Poet-DSM Advanced Biofuels LLC—Project Liberty a USA (IA) Corn cobs/corn stover 75.7 Quad County Cellulosic Ethanol Plant USA (IA) Corn fiber 7.6 Fiberight Demonstration Plant USA (VA) Waste stream 1.9 ICM Inc. Pilot integrated Cellulosic Biorefinery USA (MO) Biomass crops 1.2 American Process Inc.—Thomaston Biorefinery USA (GA) Other 1.1 ZeaChem Inc.—demonstration plant USA (OR) Biomass crops 1.0 Enerkem Alberta Biofuels LP Canada (AB) Sorted municipal solid waste 38.0 Enerkem Inc.—Westbury Canada (QC) Woody biomass 5.0 Iogen Corporation Canada (ON) Crop residue 2.0 Woodlands Biofuels Inc.—demonstration plant Canada (ON) Woody biomass 2.0 GranBio Brazil Bagasse 82.4 Raizen Brazil Sugarcane bagasse/straw 40.3 Longlive Bio-technology Co. Ltd—commercial demo China Corn cobs 63.4 Mussi Chemtex/Beta Renewables Italy \n Arundo donax , rice straw, wheat straw 75.0 Borregaard Industries AS—ChemCell Ethanol Norway Wood pulping residues 20.0 a With expansion of capacity to 94.6 ML per year. Over the past decade, the authors have collaborated in developing metabolic engineering\nconcepts for fermentation of lignocellulosic hydrolysates with engineered S.\ncerevisiae strains and in implementing these in advanced industrial strain\nplatforms. Based on their joint academic–industrial vantage point, this paper reviews key\nconceptual developments and challenges in the development and industrial implementation of\n S. cerevisiae strains for second generation bioethanol production\nprocesses."
} | 1,966 |
26769929 | PMC4714111 | pmc | 4,046 | {
"abstract": "We report here the complete sequence and fully manually curated annotation of the genome of strain Ch5, a new member of the piezophilic hyperthermophilic species Thermococcus barophilus ."
} | 47 |
38633354 | PMC11021937 | pmc | 4,049 | {
"abstract": "Cable bacteria are long, filamentous bacteria with a unique metabolism involving centimetre-scale electron transport. They are widespread in the sediment of seasonally hypoxic systems and their metabolic activity stimulates the dissolution of iron sulfides (FeS), releasing large quantities of ferrous iron (Fe 2+ ) into the pore water. Upon contact with oxygen, Fe 2+ oxidation forms a layer of iron(oxyhydr)oxides (FeO x ), which in its turn can oxidize free sulfide (H 2 S) and trap phosphorus (P) diffusing upward. The metabolism of cable bacteria could thus prevent the release of H 2 S from the sediment and reduce the risk of euxinia, while at the same time modulating P release over seasonal timescales. However, experimental support for this so-called ‘iron firewall hypothesis’ is scarce. Here, we collected natural sediment in a seasonally hypoxic basin in three different seasons. Undisturbed sediment cores were incubated under anoxic conditions and the effluxes of H 2 S, dissolved iron (dFe) and phosphate (PO 4 \n 3− ) were monitored for up to 140 days. Cores with recent cable bacterial activity revealed a high stock of sedimentary FeO x , which delayed the efflux of H 2 S for up to 102 days. Our results demonstrate that the iron firewall mechanism could exert an important control on the prevalence of euxinia and regulate the P release in coastal oceans.",
"introduction": "1 . \n Introduction Oxygen concentrations in coastal waters are decreasing as a result of global change (IPCC report [ 1 ]). An increased nutrient run-off from land in combination with warming waters leads to an increase in the spatial extent, temporal extent and frequency of bottom-water oxygen depletion [ 2 – 4 ]. The development of bottom-water hypoxia ([O 2 ] < 63 µmol l −1 ) is typically a seasonal phenomenon linked to the stratification of the water column in spring and summer, which reduces the replenishment of the bottom water with oxygen-rich surface water [ 3 ]. Bottom-water hypoxia substantially impacts the seafloor ecosystem functions related to macrofauna such as bioirrigation and bioturbation (e.g. [ 5 , 6 ]). This impact can be particularly aggravated when anoxia develops and eventually free sulfide escapes from the sediment and accumulates at the bottom of the water, a condition referred to as euxinia. Under fully oxygenated bottom waters, free sulfide (H 2 S) is efficiently oxidized in the top layer of the sediment and hence, it does not escape to the overlying water. However, when bottom waters become anoxic, the sediment releases H 2 S and euxinia develops. The latter condition can have important ecological and economic consequences, as H 2 S is highly toxic to fauna [ 7 ]. While seasonal hypoxia is observed more frequently and for longer time periods in coastal waters [ 8 ], the reports of euxinia are relatively rare (except for permanently stratified systems such as the Baltic and Black Sea). So why is euxinia not more prominent in coastal environments? And will the prevalence of euxinia increase with the ongoing global change? A study by Seitaj et al . [ 9 ] proposes that the relative infrequency of euxinia in coastal bottom waters can partly be explained by an ‘iron firewall’ mechanism. This mechanism implies strong seasonal switches in the iron and sulfur geochemistry of the sediment, which are induced by the metabolic activity of a specific type of sulfide-oxidizing bacteria, called cable bacteria [ 9 ]. Cable bacteria form long filaments that can spatially separate two redox half-reactions of aerobic sulfide oxidation by inducing electric currents over centimetre-scale distances [ 10 – 13 ]. The bottom cells of the cable bacterium filaments oxidize free sulfide in deeper sediment layers and then transport the electrons from cell to cell to the top cells, which reduce the oxygen near the sediment–water interface. This spatial separation of two redox half-reactions also implies a spatial separation of proton production and proton consumption in the sediment. Electrogenic sulfur oxidation (e-SO x ) causes the acidification of the deeper anoxic zone, while oxygen reduction entails an alkalization of the shallow oxic zone, thus leading to significant pH excursions with depth [ 12 , 14 , 15 ]. The acidification of deeper sediment layers (>2 pH units, e.g. [ 16 , 17 ]) also leads to the dissolution of particulate iron monosulfides (FeS), which releases ferrous iron (Fe 2+ ) and free sulfide (H 2 S) into the pore water [ 15 , 18 ]. The free sulfide is immediately scavenged by cable bacteria, which have a high affinity for free sulfide and use it as an electron donor [ 14 ]. The ferrous iron accumulates in the pore water and diffuses to the top layer of the sediment, where iron(oxyhydr)oxides (FeO x ) are formed upon contact with oxygen [ 9 , 18 , 19 ]. FeO x accumulation near the sediment surface also occurs without the activity of cable bacteria, through the sedimentation of FeO x from the water column [ 20 , 21 ]. Still, the oxidation of FeS by cable bacteria has the potential to substantially increase this FeO x pool within the surface sediment [ 9 ]. A five-year survey of a seasonally hypoxic lake (Lake Grevelingen, The Netherlands) uncovered that cable bacteria are abundant and active in the sediment in winter and spring, prior to the onset of hypoxic conditions. In this period, the cable bacterial activity correlated with the formation of a large enrichment of FeO x in the top sediment layer. In late spring and summer, this FeO x reservoir gradually disappeared, likely by reduction with H 2 S diffusing from below, thus preventing an efflux of H 2 S from the sediment. Seitaj et al . hypothesized that by generating this ‘iron firewall’ before the onset of anoxia, cable bacteria could delay or even avoid the occurrence of euxinia in seasonally hypoxic basins [ 9 ]. The formation and dissolution of an FeO x layer at the sediment surface also affect the cycling of phosphorus (P) [ 22 , 23 ]. The degradation of organic matter and reduction of FeO x onto which inorganic phosphate is adsorbed in the sediment provide the source of P to the pore water [ 24 ]. FeO x strongly bind to P and so the formation of FeO x can efficiently trap P released by organic matter mineralization [ 23 ]. Consequently, the large pool of FeOx created by cable bacteria in spring has the potential to retain P in the sediment [ 25 ]. Field studies from Lake Grevelingen have indeed demonstrated a zero efflux of P from the sediment in the spring period, when high rates of FeO x formation occur, stimulated by the e-SOx activity of cable bacteria [ 25 ]. Cable bacteria seem to thrive particularly well in seasonally hypoxic basins [ 9 , 16 , 17 , 26 – 28 ], so the iron firewall mechanism could be potentially widespread in stratified coastal basins. To date, however, no experimental verification has been provided that cable bacterial activity can indeed prevent H 2 S effluxes from sediments and hence delay euxinia. As a result, various aspects remain unclear such as How long can the iron firewall mechanism delay euxinia? How does it modulate P effluxes from the sediment? And does the firewall strength change when the sediment has been exposed for a longer time to hypoxic conditions? Here, we report on a detailed experimental investigation of the iron firewall mechanism and its impact on sulfur and phosphorus effluxes from the coastal sediment. To this end, intact sediment cores were collected from Lake Grevelingen at key time points within the seasonal hypoxia cycle and these cores were subsequently exposed to anoxia during laboratory sediment incubations. Fluxes were documented at weekly resolutions, to verify the timing and strength of the iron firewall and to examine how the sediment geochemistry evolves ‘en route’ towards the state of euxinia.",
"discussion": "4 . \n Discussion 4.1 . \n Seasonality in sedimentary biogeochemical cycling in Lake Grevelingen The seasonal depletion of oxygen in the bottom water imposes a pronounced seasonality on the population dynamics of the sediment infauna and microbial communities which profoundly affect the sedimentary geochemical cycling of sulfur in Lake Grevelingen. Seitaj et al . [ 9 , 19 , 25 ] proposed a model for the seasonal iron and sulfur cycling in the sediments of Lake Grevelingen, which distinguishes four consecutive biogeochemical regimes throughout the seasonal cycle: (i) electrogenic sulfur oxidation by cable bacteria occurs from winter to spring, (ii) bioturbation-induced metal cycling becomes prominent in late spring and early summer, (iii) anoxic conditions dominate throughout summer ( figure 7 ) and (iv) sulfur oxidation by Beggiatoaceae rises in fall right after bottom water ventilation. Figure 7 . \n Schematic of the seasonal cycle in the seasonal hypoxic Lake Grevelingen. In winter/early spring, cable bacteria promote the build-up of FeOOH in the oxic zone and deplete FeS in the suboxic zone. Afterwards, bioturbation-induced mixing leads to down-mixing of FeOOH (which is transformed in FeS). In summer, hypoxia/anoxia occurs and H 2 S will further deplete FeOOH. Finally, after the first reoxygenation, Beggiatoa recolonizes the sediment. Overall, the dataset collected here fully aligns with the seasonal Fe and S cycling model reported by Seitaj et al . [ 9 ]. In March, the pore water chemistry revealed a clear imprint of electrogenic sulfur oxidation by cable bacteria ( figure 2 ) [ 12 – 14 ], as indicated by alkaline pH peaks in the oxic zone and acidic pore waters in the suboxic zone ( figure 2 ) and the associated dissolution of FeS (as indicated by strong dFe accumulation; figure 4 a \n ) and CaCO 3 (as indicated by strong Ca 2+ accumulation; figure 4 c \n ). Overall, the metabolic activity of cable bacteria drives the dissolution of FeS and stimulates the subsequent reoxidation of dFe to FeO x in the oxic zone [ 15 ], which accumulates near the sediment surface ( figure 5 ). In contrast, in May, the pore water chemistry showed the features of bioturbation-driven iron cycling, as indicated by the acidic pH minimum ( figure 2 ) at the base of the oxic zone indicating iron re-oxidation [ 9 , 37 ], recovery to higher pH values below (indicative of iron reduction [ 37 ]; figure 2 ) and less pronounced FeO x in the surface sediment ( figure 5 ). Note that the alignment between the O 2 decrease and the pH minimum is not perfect in May, which is likely caused by the uneven surface of the cores (see the core picture in figure 2 ). Since we set the surface for each individual profile and profiles of O 2 and pH are taken at separate locations, it is not surprising to have mismatches in the depth between individual microprofiles. In August, no oxygen was present in the overlying water ( figure 2 ) suggesting that the sediment geochemistry is governed by anoxic biogeochemical processes. Mineralization is dominated by sulfate reduction, while FeO x is reduced back to FeS using the available H 2 S. The pH profile stays constant with depth, as is expected for sediment dominated by sulfate reduction and without significant iron cycling [ 9 ]. As a result, the stock of FeO x is depleted to its background value throughout the depth in the solid phase of the sediment ( figure 5 ). At the end of the incubation, all measured parameters showed near-identical down-core profiles, demonstrating that cores incubated in different seasons eventually all converged to the same type of geochemical cycling, i.e. organic matter mineralization dominated by sulfate reduction ( figures 3 and 4 ) in combination with a small amount of calcium carbonate dissolution. 4.2 . \n Strength of the microbial-induced firewall The so-called ‘iron firewall’ hypothesis predicts that the build-up of FeO x as a consequence of the metabolic activity of cable bacteria in spring in seasonally hypoxic systems imposes an oxidative barrier for sulfide, which hence prevents the efflux of ΣH 2 S when the oxygen in the bottom water becomes depleted in summer. Our experiments support the firewall hypothesis: sulfide fluxes are substantially delayed in the March cores (103 ± 25 days) when a large FeO x stock is present in the top layer of the sediment ( figure 5 ), while sulfide release is immediate in the cores sampled in late August when this FeO x stock is depleted. The FeO x stock in the sediment surface can originate from two processes; (i) external, via delivery of FeO x from the water column through sedimentation and (ii) internal, via upward diffusion of reduced ferrous iron and subsequent reoxidation in the oxic zone [ 20 , 21 ]. The external source of FeO x can be estimated from the surface concentration of FeO x in August (the season when there is no active iron cycling in the sediment [ 9 , 19 ]) ([FeO x ] = 50 µmol g −1 ) and the sediment accumulation rate (1.6 g cm −2 yr −1 [ 17 ]), which gives us an annually averaged external delivery of FeO x of 2.1 mmol m −2 d −1 . The internal source, which is the part of the FeO x layer due to cable bacterial activity, equals the upward diffusing ferrous iron flux (1.2–1.5 mmol m −2 d −1 ). Hence, the supply of FeO x to the surface sediment is 57–71% higher due to the activity of cable bacteria. The recorded iron fluxes support the idea that FeO x accumulated in the top layer prevents the efflux of sulfide. In all incubations, the start of the H 2 S efflux coincides with the end of the dFe flux. The reaction of FeO x with free sulfide (sulfide-mediated iron dissolution) is a chemical process, where Fe 2+ is formed (note that we write this two-step process as one reaction for simplicity; in reality, elemental sulfur is formed as an intermediate) [ 38 – 40 ]. \n H S − + 8 F e O O H + 15 H + → S O 4 2 − + 8 F e 2 + + 12 H 2 O . \n Subsequently, Fe 2+ reacts with H 2 S to form FeS. \n F e 2 + + H S − → F e S + H + . \n During the first step, Fe 2+ is released into the pore water and as a consequence, part of the Fe 2+ released can diffuse out of the sediment, rather than being trapped as FeS. This explains the observed efflux of Fe 2+ out of the sediment. Note that the oxidation of organic matter can also reduce iron, yet sulfide-mediated iron dissolution is likely the dominant iron-reducing process in the non-bioturbated sediments investigated here [ 41 , 42 ]. dMn fluxes peak just before dFe fluxes ( figure 5 ), which suggests that, as long as there are manganese oxides (MnO 2 ) present, a fraction of the produced Fe 2+ is initially reoxidized to FeOOH by MnO 2 reduction [ 19 ]. \n 2 F e 2 + + M n O 2 + 2 H 2 O → 2 F e O O H + M n 2 + + 2 H + . \n At the field site, manganese oxides are present in concentrations that are <5% of the iron oxide concentrations [ 19 ], which is indicated by low dMn fluxes (4 times lower than dFe) and the rapid decrease to quasi-zero ( figure 5 ). Hence, the impact of manganese on the eventual sulfide delay can be considered minor compared to the iron oxide firewall. How strong is the firewall induced by the cable bacteria? In the March cores, we observe an inventory change of ~850 mmol m −2 of FeO x between the start and the end of incubation (change in top 1 cm, figure 5 ). During incubation, the cumulative flux of dFe out of the sediment is 100 mmol m −2 . If we suppose that dFe is only released from iron oxides, 750 mmol m −2 of dFe from FeO x must be captured as FeS in the sediment (i.e. a trapping efficiency of 750/850 * 100 = 88%). Carbon mineralization is ~15 mmol m −2 d −1 in the cores over the course of incubation (as derived from the mean DIC flux a–c). Note that the DIC efflux is not solely the effect of organic mineralization, but can also increase due to carbonate dissolution. As a result, we can consider the DIC effluxes as an upper bound on the mineralization rate. Since anoxic carbon mineralization in Lake Grevelingen is dominated by sulfate reduction [ 9 ], one expects sulfate reduction rates in the range of ~7.5 mmol m −2 d −1 (based on the estimated organic matter mineralization rate and a stoichiometric S:C ratio of 1:2). Assuming that the total FeO x inventory change was caused by sulfide-mediated iron dissolution, the consumption of free sulfide by FeO x reduction amounts to (1/8) * 850 = 106 mmol S m −2 , while the ensuing FeS precipitation removes another 750 mmol S m −2 . Therefore, the accumulated FeO x would be able to delay the sulfide release for at least 856 mmol m −2 / 7.5 mmol m −2 d −1 = 114 days in March. This estimate is highly congruent with the euxinia delay of 103 ± 25 days as observed in the incubation experiment. A similar sulfur budget calculation can be made for May incubation. This provides a theoretical delay of the sulfide release of 45 days, which is again comparable to the flux results from the incubations (the observed delay of the free sulfide release in the three incubated cores ranged between 40 and 60 days). Note that in situ temperatures during summer become higher and sulfide production would increase accordingly. The delay in sulfide release would thus be shorter than in our incubated cores. In May, we observed small polychaetes at the sediment surface, consistent with the previous observations of sediment recolonization by juvenile macrofauna in late spring [ 9 ]. We hence contend that macrofaunal activity could induce the down-mixing of FeO x through bioturbation [ 43 , 44 ]. A fraction of FeO x in the top layer will be mixed down which will be reduced in deeper layers, thus accelerating the conversion of FeO x into FeS ( figure 7 ) and hence partially weakening the strength of the iron firewall. In August 2015, the iron firewall appeared to be completely exhausted and a sulfide efflux was detectable from the first week in the incubations ( figure 6 f \n ). Because H 2 S was not detectable in the bottom water, it appears that our August sampling occurred at a moment when the iron firewall was exhausted by previous weeks of anoxia, but the bottom water did not have the chance yet to accumulate H 2 S in large concentrations. Alternatively, more turbulence created by a stochastic event (e.g. by strong winds) prior to our sampling in August could have led to the transient ventilation of the bottom water [ 45 ]. In either case, the bottom water of Lake Grevelingen was on the brink of developing euxinia. If we take the conservative estimate that the bottom 10 m of the water column is well-mixed and adopt a flux of 12 mmol m −2 d −1 of H 2 S (as measured in August, figure 6 f \n ), about 17 days of efflux are needed to reach 20 µmol l −1 H 2 S, a threshold above which eukaryotic mitochondria become poisoned [ 7 ]. Therefore, an increase in the hypoxia length of a few weeks as a result of climate change (e.g. caused by an earlier onset of stratification in spring and/or increased bottom waters temperatures and higher mineralization rates in summer) would hence increase the risk of developing euxinia in Lake Grevelingen. 4.3 . \n Effect on phosphorus cycling Phosphorus (P) is an essential nutrient (in combination with nitrogen) for primary production in coastal systems and is intimately linked to the iron cycle [ 23 ]. In Lake Grevelingen, the formation of FeO x , stimulated by electrogenic sulfur oxidation, was proposed to prevent the efflux of P from the sediment during spring, while the dissolution of the FeO x layer during summer led to a higher release of P from the sediment [ 25 ]. The flux pattern in our incubations fully aligns with this model proposed by Sulu-Gambari et al . [ 25 ]. In March, the PO 4 \n 3− effluxes only started 14 days after the start of the incubation and reached a maximum of 0.9 mmol m −2 d −1 . In May, the fluxes of P immediately started and reached a much higher rate in a shorter period of time. In spring, the newly formed FeO x layer had a large capacity to bind phosphorus, but due to the cable bacterial activity and the formation of FeO x , the binding capacity for P was not yet fully exhausted. This could explain the two-week lag in P effluxes in March. Later in the season, when cable bacterial activity had ceased and the formation of the FeO x had stopped, the FeO x pool likely became saturated with PO 4 \n 3− , explaining why P effluxes are higher in May compared to March and why they immediately start right after the induction of anoxia. In Lake Grevelingen, the benthic–pelagic coupling of P is consequently heavily regulated by the activity of the cable bacteria ([ 25 ]; this study). In spring, a large pool of FeOx was formed, which can keep most P in the sediment or even promote the capture of additional P into the sediment. As such, the presence of cable bacteria can induce a large retention of P within the sediment which leads to amplified P efflux once hypoxia sets in. 4.4 . \n Outlook: cable bacteria as ecosystem engineers The metabolic activity of cable bacteria appears to have a large impact on the biogeochemical cycling of Fe, Mn, P, S and trace elements in Lake Grevelingen [ 9 , 19 , 25 , 46 , 47 ]. The build-up of FeO x in the spring is an immediate consequence of the acidifying metabolism of cable bacteria and our experiments demonstrate that this large FeO x pool forms an effective barrier against sulfide release from the sediment later in the hypoxia season. Moreover, this FeO x pool efficiently retains P in the sediment. As a result, cable bacteria can be thought of as microbial ecosystem engineers. Given the toxicity of sulfide for organisms and the large detrimental impact of sulfide on coastal ecosystems, the capability of delaying or even preventing euxinia emerges as a major structuring factor in coastal ecosystems. The occurrence of cable bacteria in other seasonal hypoxic environments [ 16 , 27 , 28 ] hints towards a similar function and thus suggests that the iron firewall mechanism could be more widespread. Moreover, in order to determine the future prevalence of euxinia, it is appropriate to investigate how cable bacteria and their iron firewall mechanism will respond to a warming coastal ocean. In 2015, the strength of the iron firewall appeared to match the length of the hypoxia regime in Lake Grevelingen, preventing the development of euxinia in late summer. Still, the system appears right on the brink of developing euxinia and in the near future, our results suggest that H 2 S-rich bottom waters may form in warmer years with prolonged stratification periods."
} | 5,618 |
29028004 | PMC5739016 | pmc | 4,050 | {
"abstract": "Oxygen-dependent microbial oxidation of sulfur compounds leads to the acidification of natural waters. How acidophiles and their acidic habitats evolved, however, is largely unknown. Using 16S rRNA gene abundance and composition data from 72 hot springs in Yellowstone National Park, Wyoming, we show that hyperacidic (pH<3.0) hydrothermal ecosystems are dominated by a limited number of archaeal lineages with an inferred ability to respire O 2 . Phylogenomic analyses of 584 existing archaeal genomes revealed that hyperacidophiles evolved independently multiple times within the Archaea, each coincident with the emergence of the ability to respire O 2 , and that these events likely occurred in the recent evolutionary past. Comparative genomic analyses indicated that archaeal thermoacidophiles from independent lineages are enriched in similar protein-coding genes, consistent with convergent evolution aided by horizontal gene transfer. Because the generation of acidic environments and their successful habitation characteristically require O 2 , these results suggest that thermoacidophilic Archaea and the acidity of their habitats co-evolved after the evolution of oxygenic photosynthesis. Moreover, it is likely that dissolved O 2 concentrations in thermal waters likely did not reach levels capable of sustaining aerobic thermoacidophiles and their acidifying activity until ~0.8 Ga, when present day atmospheric levels were reached, a time period that is supported by our estimation of divergence times for archaeal thermoacidophilic clades.",
"conclusion": "Conclusions Acidic hydrothermal ecosystems in YNP are dominated by Archaea, which is consistent with data from other globally distributed hydrothermal systems ( Xie et al. , 2014 ; Ward et al. , 2017 ). Physiological inference suggests that the transition to archaeal-dominated acidic hydrothermal habitats is accompanied by an increase in the ability to integrate O 2 into respiration, likely due, in part, to meet the bioenergetic demands associated with mitigating oxidative stress ( McCarthy et al. , 2016 ). This observation, coupled to data indicating that the generation of acidic environments typically requires the O 2 -dependent oxidation of sulfur compounds, suggests that thermoacidophilic Archaea and the acidity of their habitats co-evolved after the emergence of oxygenic photosynthesis. Further, we hypothesize that these events may have taken place through a series of geological–biological feedbacks in a process that is similar to what has been described as niche construction ( Odling-Smee et al. , 1996 ). Although the process of niche construction may be little explored in microbial ecology, it is likely a widespread phenomenon in microbial evolution considering how quickly microorganisms can influence the geochemical composition of their local environments, the apparent ease by which they can acquire new traits via HGT, and their relatively fast rates of reproduction. Phylogenomic analyses support these conclusions and suggest that the evolution of acidophily in Archaea has occurred independently in divergent lineages relatively recently and was potentially aided by HGT. Taken together, these results expand our understanding of the ecological prevalence of Archaea in hot springs and provide physiological and evolutionary context for their current dominance in these environments. Moreover, these observations point toward a hypothesis of biological modification of natural environments in shaping the diversification of an organism’s progeny (that is, niche construction), local co-inhabitants or downstream inhabitants (that is, facilitation). Further laboratory experimentation of aerobic thermoacidophiles is needed to assess how adaptation toward increased acidophily affects ecological fitness in the adapted and ancestral pH niches as well as the potential impacts on incipient species divergence.",
"introduction": "Introduction Hyperacidic environments (pH<3) are pervasive landscape features, albeit isolated, and are commonly associated with volcanic systems or sulfide ore deposits. These environments define the lower pH limit for life, are major sources of economically important metals and have the potential to contribute to the pollution of natural waters ( Johnson and Quatrini, 2016 ). As such, hyperacidic environments are of substantial interest to microbiologists, geochemists, geologists and planetary scientists, and have been subject to extensive research to understand the processes that contribute to their formation and the adaptations that allow for their habitation. Considerable research has been conducted on the role of microbial activity in the formation of hyperacidic waters ( Johnson et al. , 1993 ; Baker and Banfield, 2003 ). However, the events that led to the evolution of acidophiles and their role in the generation of acidic habitats are underexplored. Two dominant processes are involved in the formation of hyperacidic natural waters: magmatic degassing that contributes hydrochloric, hydrofluoric and sulfuric acid (from disproportionation of sulfur dioxide and subsequent oxidation of hydrogen sulfide or elemental sulfur) and the oxidation of mineral sulfides that produces sulfuric acid ( Nordstrom et al. , 2000 ). Common to both processes are the oxidation of sulfur compounds, including free sulfide (H 2 S), mineral sulfides (for example, FeS 2 ) or elemental sulfur (S 0 ), and the concomitant production of sulfate and protons. High-potential oxidants capable of driving sulfide/S 0 oxidation include nitrate (NO 3 − ), ferric iron ions (Fe III ) and O 2 ( Falkowski et al. , 2008 ). Mechanisms of generating NO 3 − include lightning-catalyzed oxidation of atmospheric dinitrogen and precipitation of nitrogen oxides as NO 3 − , a process that has been decreasing in importance since 3.8 Ga ( Navarro-Gonzalez et al. , 2001 ), and biological oxidation of ammonia, which requires O 2 ( Godfrey and Falkowski, 2009 ). Likewise, the generation of Fe III requires either abiological photo-oxidation of ferrous iron (Fe II ; Braterman et al. , 1983 ), which has been of negligible importance after the onset of an ozonated atmosphere following the Great Oxidation Event (GOE) ~2.5 Ga ( Kim et al. , 2013 ), or one of several biological oxidative processes ( Emerson et al. , 2010 ). Biological oxidation of Fe II requires O 2 or NO 3 − as an oxidant ( Emerson et al. , 2010 ) or Fe II -oxidizing phototrophic organisms ( Widdel et al. , 1993 ). The involvement of phototrophic organisms in Fe III generation in acidic environments is of putative importance only in environments with temperatures <56 °C—the upper temperature limit for phototrophs in acidic (pH<4.0) environments ( Boyd et al. , 2012 ). Thus, the remaining and most likely oxidant capable of driving H 2 S/S 0 oxidation and the development of hyperacidic hydrothermal ecosystems is atmospheric O 2 rather than local O 2 , given temperature constraints on photosynthesis. Previous studies indicate that abiotic oxidation of H 2 S with O 2 can be extremely slow in aqueous solutions with pH⩽6 ( Chen and Morris, 1972 ; Zhang and Millero, 1993 ; D’Imperio et al. , 2008 ). Further, at elevated pH (that is, in marine waters) where abiotic oxidation of sulfide is quicker, rates can be several orders of magnitude slower than biotic oxidation ( Luther et al. , 2011 ), although biotic oxidation is not always necessary to explain observed rates ( Millero, 2001 ). Further, the rate of abiotic oxidation of S 0 with O 2 is extremely slow ( Nordstrom et al. , 2005 ). Finally, the growth of several sulfur-oxidizing, aerobic thermoacidophiles results in the acidification of the cultivation medium ( Shivvers and Brock, 1973 ; Giaveno et al. , 2013 ). These observations, coupled with evidence for the widespread distribution of aerobic organisms capable of oxidizing both H 2 S and S 0 in acidic hot springs ( Zillig et al. , 1994 ; Inskeep et al. , 2013 ; Xie et al. , 2014 ; Huber and Stetter, 2015 ) and the capability of sulfur-oxidizing organisms to acidify their environments, strongly suggest that biological activity is involved in the generation of many low-pH (<3.0) hydrothermal ecosystems ( Nordstrom et al. , 2005 ; Nordstrom et al. , 2009 ; Johnson and Quatrini, 2016 ). Here, we hypothesize that O 2 -dependent biological oxidation of sulfur compounds in hydrothermal ecosystems is dependent on a non-point source of O 2 and that the widespread development of low-pH (<3.0) hot spring ecosystems could only have occurred after O 2 began to accumulate in the atmosphere to levels capable of supporting and sustaining aerobic biological activity ~0.8 Ga. As such, we further hypothesized that the microorganisms that dominate and are presumptively responsible for forming acidic hot springs belong to recently evolved lineages that incorporate aerobic metabolism to meet energetic demands associated with their acidophilic lifestyles. To begin to assess these hypotheses, we measured microbial community abundances and composition among geochemically diverse hot springs in Yellowstone National Park (YNP), Wyoming, USA, to determine the abundance of taxonomic lineages found in thermal acidic springs. We then investigated the evolutionary history of thermoacidophiles using phylogenomic analyses of publicly available genomes from cultured and uncultured taxa. To better understand the adaptations that led to increased acid tolerance, we used comparative genomics to determine the protein complements that differentiate thermoacidophiles from other members of their higher-order lineages. Finally, we present these results in context of changes in atmospheric O 2 over geologic time to evaluate the hypothesis that both thermoacidophiles and the habitats that they are putatively responsible for generating are recent evolutionary and geologic innovations, respectively.",
"discussion": "Results and discussion The diversity, distribution and inferred physiological characteristics of microbial populations inhabiting 72 representative hot spring environments in YNP that span a pH range of 2.1–9.6 and a temperature range of 32.7–92.5 °C were determined ( Figure 1a and Supplementary Table S4 ). Quantitative PCR of archaeal and bacterial 16 S rRNA genes (as proxies for population sizes) revealed a transition toward archaeal dominance in low-pH springs ( Figure 1b ). Regression analyses of the log-transformed ratio of archaeal to bacterial 16S rRNA gene copies indicated a highly significant and inverse relationship with pH ( β =−0.22, adjusted R 2 =0.29, P =6.42 x 10 −7 ; Supplementary Figure S1 ) but no significant correlation with temperature ( β =0.00, adjusted R 2 =−0.01, P =0.83). A multiple linear regression model incorporating both pH and temperature reiterated that pH was primarily responsible for the observed population ratios, whereas temperature was of negligible influence (data not shown). It should, however, be noted that many of the springs sampled here (57/72) have temperatures >50 °C and thus the lack of an apparent effect of temperature on archaeal dominance is likely related to the generally limited sampling of low-temperature hot springs. Analysis of variance tests of archaeal/bacterial 16S rRNA gene copy quantitative PCR ratios in relation to pH while parsing samples into low/high-pH groups at thresholds ranging from pH 3.0 to 7.0 indicated that a pH 4.0 threshold best segregated the data and supports the observation that archaeal dominance is pronounced in springs with pH<4.0 ( Figure 1b , Supplementary Table S5 and Supplementary Figure S2 ). Although the number of 16S rRNA gene operons present in a genome can vary and thus complicate the estimation of population sizes via quantification of their copy numbers ( Acinas et al. , 2004 ), 16S rRNA gene copy numbers in archaeal genomes are generally much lower than that of Bacteria ( Acinas et al. , 2004 ). Moreover, a survey of 16S rRNA gene operon copy numbers within the rrn DB operon database ( Stoddard et al. , 2015 ) revealed that the archaeal orders Sulfolobales, Desulfurococcales and Thermoproteales (which are among the predominant taxa reported in these springs; discussed below; Supplementary Table S1 ) do not contain multiple 16S rRNA gene copies, whereas the predominant bacterial orders (Aquificales, Thermales, Firmicutes and Proteobacteria) all consist of genera with multiple 16S rRNA gene operons. Consequently, our estimates of bacterial population sizes via quantification of 16S rRNA genes are likely to overestimate true population sizes. Thus, qualitatively, our estimates of archaeal predominance in low-pH springs (as archaeal/bacterial population ratios) are likely to underestimate true community dominance. Archaeal population dominance over Bacteria has also been observed in an acidic (pH ~2.5) New Zealand hot spring when temperatures exceed ~65 °C ( Ward et al. , 2017 ) and in the hottest and most acidic of 20 YNP hot spring metagenomes ( Inskeep et al. , 2013 ). The major transition toward archaeal dominance in springs with pH<4.0 is consistent with cultivar-based inferences from globally distributed environments, which suggest that Archaea have an ecological advantage over Bacteria in acidic thermal habitats ( Valentine, 2007 ). Pyrotag sequencing of archaeal 16S rRNA genes recovered from the springs analyzed here and physiological inference based on taxonomic identities suggest that the transition to archaeal dominance in acidic hot spring ecosystems is accompanied by an increased ability to integrate O 2 respiration into energy metabolism ( Figure 1c ). Linear regression analyses indicated a significantly negative correlation between the percent of the archaeal community inferred to be aerobic and pH ( β =−9.15, adjusted R 2 =0.36, P =1.82 × 10 −5 ), but no significant correlation with temperature ( β =−0.53, adjusted R 2 =0.05, P =0.09). Parsing samples into low/high-pH groups at thresholds from pH 3.0 to 7.0 indicated that pH 4.0 best segregated the communities based on inferred aerobic capacity and supports the observation that communities in springs with pH<4.0 are dominated by Archaea with aerobic respiratory physiologies ( Supplementary Table S6 and Supplementary Figure S3 ). This trend is driven by an increased prevalence of sequences with affiliation to organisms in the Thermoplasmatales and Crenarchaeal-associated lineages in the lowest pH springs, the majority of which are capable of using O 2 in energy metabolism ( Supplementary Table S1 ). In contrast to lower-temperature acidic environments (that is, acid mine drainages; Tyson et al. , 2004 ), Bacteria did not represent significant fractions of the acidophilic microbial communities analyzed here. Although acidophilic Bacteria can inhabit high-temperature acidic springs (primarily aerobic Hydrogenobaculum spp. of the Aquificales order), they are not dominant where temperatures exceed ~75 °C ( Supplementary Table S1 ; Inskeep et al. , 2013 ). These results are consistent with the ubiquitous distribution and dominance of largely aerobic Thermoplasmatales and Crenarchaeota (particularly the Sulfolobales order) in high-temperature acidic hot springs in YNP and elsewhere ( Inskeep et al. , 2013 ; Xie et al. , 2014 ; Ward et al. , 2017 ). It has been previously suggested that Archaea dominate the hottest and most acidic environments because of key adaptations that allow them to cope with chronic energy stress ( Valentine, 2007 ). Our data suggest an alternative, but not mutually exclusive, explanation for archaeal dominance in acidic geothermal systems. Here, the development of acidic thermal waters is driven largely by microbially mediated O 2 -dependent oxidation of S 0 or H 2 S ( Nordstrom et al. , 2005 ; Nordstrom et al. , 2009 ) by members of acidophilic lineages such as the Sulfolobales, due in part to meet energetic demands associated with habitation of these environments. It follows that the dominance of these lineages in acidic environments may result from the modification of their local environment (that is, niche) in the form of sulfuric acid production, thereby excluding less well-adapted populations in a process of geological–biological feedbacks like what has been described as niche construction ( Odling-Smee et al. , 1996 ). The process of niche construction allows for the modification of an environment by the activity of an organism, with the modified environment favoring the fitness or selectivity of the modifying organism and their progeny. In the case of extant thermoacidophiles, it is possible that the biological production of acidity may have resulted in the development of slightly more acidic, high-temperature niche space that promoted the radiation of those organisms responsible for acidification, and their respective lineages. Over time and through successive generations, this process could have manifested in divergence of acidophilic lineages away from neutrophilic ancestors in a unidirectional manner. To examine further the role of O 2 in the evolution of acidophilic Archaea, we compiled publicly available archaeal genomes ( Supplementary Table S2 ), corresponding pH optima (or culture conditions, for cultivars) or environmental pH (for uncultured organisms), and O 2 usage data (for cultivars). Phylogenomic reconstructions using single-copy phylogenetic marker genes reveal that acidophily (pH optima/environmental pH⩽3) is present in multiple archaeal lineages and is particularly enriched in the Thermoplasmatales and Sulfolobales ( Figure 2 ). Notably, all acidophilic lineages, including the Thermoplasmatales and Sulfolobales, are nested among higher-order neutrophilic and alkaliphilic lineages. This indicates that acidophily is a derived physiological trait that has evolved independently and multiple times from neutrophilic or moderately acidophilic ancestors. Although environmental surveys have detected additional uncultivated Archaea (for example, Micrarchaeota, Parvarchaeota, Thaumarchaeota-related and Geoarchaeota) in acidic environments ( Baker et al. , 2010 ; Kozubal et al. , 2013 ; Beam et al. , 2014 ), they are all nested among largely uncultured lineages that are also prevalent in circumneutral or alkaline environments, suggesting that acidophily is a derived trait in these lineages as well. In addition, devolution of acidophilic lineages to moderately acidophilic or neutrophilic sublineages is not observed in our phylogenomic reconstruction, suggesting that evolution toward an increased acidophily has largely been a unidirectional evolutionary process. Together, these observations suggest relatively recent, multiple origins of acidophilic Archaea ( Figure 2 ). Mapping of O 2 use among available cultivars on the archaeal phylogeny reveals predominance in the Sulfolobales and Thermoplasmatales, pointing to the importance of high-energy-yielding metabolisms in adapting to and inhabiting acidic environments ( Figure 2 ). Indeed, analysis of temperature and pH optima along with O 2 usage of available archaeal cultivars reveal that taxa with growth optima of pH 3.0 or less consistently exhibit the ability to respire O 2 ( Figure 3 ). As oxygenic phototrophs are excluded from acidic hot springs in YNP with temperatures >56 °C ( Boyd et al. , 2012 ), the O 2 that supports thermoacidophiles and most likely supported their ancestors would have only been available through diffusion from atmospheric sources (or as dissolved O 2 transported via groundwater). Although all characterized acidophilic bacteria isolated to date also exhibit aerobic metabolic capacity, only one sulfur-oxidizing genus within the Aquificae ( Hydrogenobaculum ) and another methanotrophic genus ( Methylacidiphilum ) within the Verrucomicrobia are known to grow optimally at ⩾60 °C, but neither are known to grow optimally above 65 °C ( Dopson, 2016 ). This suggests that Bacteria are of marginal importance in the formation of high-temperature acidic environments today and, by extension, the geologic past. Comparative genomics was used to identify assemblages of protein-encoding genes that may contribute to successful habitation of hyperacidic habitats. Ordination of a dissimilatory matrix of protein homolog distances encoded among archaeal genomes revealed clustering of acidophile genomes ( Figure 4a and Supplementary Figure S4 ). This indicates that the proteins encoded in acidophile genomes are similar despite belonging to disparate phylogenetic lineages. In addition, the proteins encoded by Sulfolobales and Thermoplasmatales genomes are, themselves, distinct from other groups of the TACK and Euryarchaeota superphyla, respectively ( Figures 4b and c ). These observations suggest that phylogenetically distinct taxa may have converged on similar protein-coding gene complements during their diversification into acidic habitats. To identify those protein complements that contributed to the differentiation of acidophiles from their higher-order lineages, protein bins were identified that demarcated the Thermoplasmatales and Sulfolobales from the Euryarchaeota and TACK groups, respectively. Predicted membrane-associated permeases or transporters comprised ~25% of the protein bins that distinguished the Thermoplasmatales from other euryarchaeotes ( Figure 5 and Supplementary Table S7 ). Of the 138 Thermoplasmatales-enriched bins, 32 were also present in >50% of Sulfolobales genomes ( Figure 5 and Supplementary Table S7 ), which is consistent with observations that genomes from the Thermoplasmatales species Picrophilus torridus and Thermoplasma acidiphilum share significant homology with Sulfolobus genomes ( Ruepp et al. , 2000 ; Futterer et al. , 2004 ). Many of the shared proteins are permease- or membrane transport-related, including amino acid and solute transporters/permeases ( Supplementary Table S7 ), which supports the assertion that these protein functions are essential for intracellular pH homeostasis and thus, habitation of acidic environments ( Baker-Austin and Dopson, 2007 ). In contrast, the enrichment of Thermoplasmatales-like proteins in Sulfolobales members is not observed ( Supplementary Figure S5 ). These results suggest that the differentiation of Thermoplasmatales from the Euryarchaeota may be due, in part, to the acquisition of genes from a Sulfolobales-like ancestor, but that the converse is not supported. Phylogenetic analysis of the Thermoplasmatales-enriched bins indicates a nesting of Thermoplasmatales homologs within crenarchaeal outgroups in most (65.6%) of the protein phylogenies (data not shown). These data support the hypothesis that the Thermoplasmatales, which are found in lower-temperature springs when compared with Sulfolobales, diverged from other Euryarchaeota due, at least in part, to horizontal acquisition of genes from an acidophilic crenarchaeal-like ancestor. This scenario is consistent with the hypothesis that aerobic sulfur-oxidizing Sulfolobales are responsible for the formation of high-temperature acidic niche space (for example, >65 °C), which may then facilitate the generation of lower-temperature acidic niche space for later diverging, less thermophilic acidophile lineages, such as the Thermoplasmatales. The downstream physical location of Thermoplasmatales (lower-temperature transects) relative to the upstream physical location of the Sulfolobales (higher-temperature transects) in hydrothermal systems may have contributed to the apparent unidirectional transfer of genes from the Sulfolobales to the Thermoplasmatales. Extensive horizontal gene transfer (HGT; at the inter- and intra-specific levels) has been documented in acidophiles ( Whitaker et al. , 2005 ; Simmons et al. , 2008 ; Schonknecht et al. , 2013 ) and may be a general mechanism by which lineages acquire traits that allow for successful adaptation to acidophilic environments. Experimental evolution of Sulfolobus solfataricus toward increased acidophily supports the hypothesis that adaptation to a progressively more acidic environment necessitates increased metabolic energy yield, in part, to meet the increased biosynthetic demands associated with oxidative stress ( McCarthy et al. , 2016 ). Serial passage of S. solfataricus over 3 years into progressively more acidic culture conditions resulted in a substantial decrease in the minimum pH that supported growth (pH 0.60 for evolved strain; pH 1.64 for parental strain). Transcriptomic analyses of the derived and parental strains showed that increased acid tolerance in derived strains was accompanied with increased expression of catabolic functions (for example, TCA cycle genes) and anabolic functions (membrane biosynthesis genes). Comparative analysis of the genome of the derived and parental strain, however, revealed only several point mutations in membrane-related and transporter-associated genes ( McCarthy et al. , 2016 ), suggesting that evolved acidophilic strains differed primarily at the level of gene regulation rather than at the level of acquisition of new traits or trait variants. Adaptation toward increased acidophily in the natural environment, however, might be expected to be influenced more by HGT rather than by single point mutations. For example, in open natural systems it is possible that environmental DNA from lysed cells, exogenous sources and viruses—the latter of which are common in acidic hydrothermal environments ( Bolduc et al. , 2015 ; Gudbergsdottir et al. , 2016 ) and in cultures of known acidophiles ( Hochstein et al. , 2016 )—may accelerate HGT and diversification toward more acidic habitats. Indeed, comparative genomic analyses performed here and elsewhere ( Ruepp et al. , 2000 ; Futterer et al. , 2004 ; Schonknecht et al. , 2013 ) underscore the importance of HGT in the evolution of acidophilic lineages. These collective observations prompt the intriguing question as to when thermoacidophiles and their acidic habitats emerged. Aerobic organisms within the Sulfolobales, such as S. solfataricus, grow optimally at O 2 concentrations between ~1.5% and 24% v/v corresponding to 0.87 and 13.9 mM O 2 at 80 °C, respectively, whereas no growth is observed in the absence of O 2 ( Simon et al. , 2009 ). Oxygenation of Earth’s atmosphere did not begin until after the evolution of oxygenic photosynthesis, and oxygen concentrations did not reach appreciable levels until after the GOE between ~2.4 and 2.1 Ga. The timing of the GOE is widely supported by paleosol evidence indicating a substantial change in readily oxidized, redox-sensitive compounds such as pyrite (FeS 2 ) and uraninite (UO 2 ) in addition to the disappearance of mass-independent sulfur-isotope fractionations from the sedimentary rock record after this time ( Farquhar et al. , 2000 ; Canfield, 2005 ). However, the availability of atmospheric oxygen following the GOE has only recently come into focus. Accepted models have bounded atmospheric O 2 somewhere between ~1% and 40% of present atmospheric levels during the mid-Proterozoic (1.8–0.8 Ga) based on sulfur-isotope evidence for anoxic deep oceans and paleosol chemical profiles, and particularly those of Fe 3+ ( Rye and Holland, 1998 ; Canfield, 1998 ; Canfield, 2005 ; Lyons et al. , 2014 ). Emerging data arising from chromium (Cr) isotopic records (documenting decreased Cr redox cycling, which is a highly oxygen-sensitive process) indicate that atmospheric oxygen levels likely decreased after the GOE to levels that did not exceed >~0.1% present atmospheric level during the mid-Proterozoic ( Frei et al. , 2009 ; Planavsky et al. , 2014 ; Lyons et al. , 2014 ; Cole et al. , 2016 ). A final increase in atmospheric oxygen to near present atmospheric level during the late Proterozoic (0.8–0.55 Ga) is evinced by multiple lines of geochemical observations including carbon isotopic analyses indicating high organic carbon burial rates in ocean sediments ( Knoll et al. , 1986 ), and increased Cr redox cycling ( Frei et al. , 2009 ; Cole et al. , 2016 ) among other observations ( Canfield, 2005 ; Holland, 2006 ; Lyons et al. , 2014 ). Thus, given the above evidence, the nonlinear decrease in O 2 solubility with increasing water temperature ( Shock et al. , 2010 ), and the necessity for a non-point source of oxygen availability in high-temperature acidic springs (discussed above), it follows that aerobic thermoacidophiles did not likely emerge until at the earliest, the most recent rise of atmospheric O 2 to present atmospheric level in the latter period of the mid-Proterozoic ~0.8 Ga. An alternative hypothesis is that aerobic thermoacidophiles emerged before or during the GOE but lost niche space during the intervening ~1.5 billion years when atmospheric O 2 plummeted and were confined to refugia, only to re-emerge and radiate ~0.8 Ga. Others have hypothesized that the spike in the abundance of Cr in sedimentary iron deposits dated to the GOE or just after the GOE, along with a lack of Cr redox cycling, could be explained by the release of reduced Cr (III) from acid weathering of a global terrestrial pyrite reservoir. It was hypothesized that this weathering was driven by the activity of low-temperature aerobic pyrite-oxidizing acidophiles that could hypothetically have been present during this time frame ( Konhauser et al. , 2011 ). The above evidence for extremely low mid-Proterozoic oxygen levels and the return of Cr abundances to pre-GOE levels in multiple sedimentary records during the mid-Proterozoic ( Frei et al. , 2009 ; Konhauser et al. , 2011 ; Cole et al. , 2016 ) potentially supports the aerobic acidophile niche-collapse hypothesis. To assess whether one of the two above hypotheses is supported via molecular dating of the archaeal phylogeny, we constructed a bacterial-rooted time tree using a subset of archaeal taxa ( n =100) from our phylogenomic data set. Using maximum and minimum age estimates for the divergence of all Archaea as 3.83 Ga (the age of the earliest potential evidence for life based on isotopically light graphite inclusions; Mojzsis et al. , 1996 ; McKeegan et al. , 2007 ) and 3.46 Ga (the earliest isotopic evidence for microbially produced methane; Ueno et al. , 2006 ), the Most Recent Common Ancestor (MRCA) of the Sulfolobales was estimated to diverge at 1.053 Ga (95% confidence interval (CI): 1.601–0.656 Ga), whereas the divergence date of the MRCA of the Thermoplasmatales was estimated as 0.843 Ga (95% CI: 1.301–0.505 Ga; Supplementary Figure S6 ). These dates are broadly consistent with earlier estimates using smaller genomic data sets ( Battistuzzi et al. , 2004 ) and provide further support that aerobic thermoacidophiles radiated late in Earth history and are coincident with estimates for the timing of the mid-Proterozoic atmospheric rise in oxygen at ~0.8 Ga. Moreover, the estimated radiation of the Sulfolobales before that of the Thermoplasmatales provides additional support for the hypothesis that the Thermoplasmatales may have adapted to thermoacidophilic lifestyles, in part, because of HGT from Sulfolobales-like ancestors that predominate at higher-temperature hydrothermal settings (that is, HGT occurring down temperature gradients, rather than up gradient). However, it should be noted that dating phylogenies, and particularly those of Archaea, is problematic because of the lack of available calibration points for lineages. Thus, divergence estimates that are based on a single calibration point should be treated tentatively. Intriguingly, previous analyses have provided evidence for the divergence of chemotrophic sulfur-oxidizing Proteobacteria involved in the oxidation of sulfides in marine sediments at a similar time frame (0.64–1.05 Ga; Canfield and Teske, 1996 ). The late Proterozoic divergence of these mesophiles is coincident with the late Proterozoic rise in oxygen and large-scale changes in the isotopic fractionation of sedimentary sulfides that can be best explained by the emergence of an oxidative sulfur cycle driven by sulfide and sulfur-oxidizing non-photosynthetic Bacteria ( Canfield and Teske, 1996 ). Whether the consilience between our date estimates for the origin of sulfur-oxidizing thermoacidophilic Archaea and those for mesophilic marine sulfide and sulfur-oxidizing Bacteria are coincidental, or rather, are linked via HGT between Archaea and Bacteria is a topic that is of interest for better understanding the origins of both sulfur-oxidizing microbial lineages and their role in the sulfur cycle. Despite the suggestion that low-temperature mesophiles may have been involved in the generation of acidic environments following the GOE ( Konhauser et al. , 2011 ), the likelihood that discretely distributed, highly oxygenated and high-temperature refugia would have existed throughout the mid-Proterozoic that could continuously support aerobic thermoacidophiles certainly is low. Thus, our data support the hypothesis for a Neoproterozoic origin for archaeal thermoacidophiles. Taking into account the role of biology in accelerating the kinetics of reactions that lead to the acidification of hydrothermal waters, we contend that it is unlikely that thermal acidic ecosystems, such as those found in the YNP geothermal system, were widespread before the emergence of aerobic sulfur-oxidizing thermoacidophiles. Rather, these observations more likely suggest a recent emergence of thermoacidophiles and their habitats, which may have arisen and evolved in concert through a process of geological–biological feedbacks over the past ~0.8 Ga. Finally, confirmation of the emergence of thermoacidophilic Archaea during the mid to late Proterozoic, either through geological data or biological data, would provide a much-needed calibration point for archaeal phylogenies, allowing for more accurate molecular clock simulations to be conducted."
} | 8,502 |
35650244 | PMC9159989 | pmc | 4,053 | {
"abstract": "Understanding the stability of ecosystem multifunctionality is imperative for maintaining ecosystem health and sustainability under augmented global change. However it remains unknown whether and how biological communities mediate multifunctional stability in response to biodiversity loss and disturbances. Here, we conducted a 3-year experiment by exposing 270 plant communities of four plant richness levels, i.e., 1, 2, 4, or 8 species, to drought and exotic plant invasion disturbances. Then, the direct effects of plant richness, drought and invasion, and their indirect effects mediated by the stability of plant, litter-faunal, and soil-faunal communities on multifunctional stability were disentangled. We found that plant richness increased, while drought and invasion decreased ecosystem multifunctional stability, which were mediated by plant or faunal community stability. By incorporating the stability of communities into the complex ecological mechanisms, the completeness and goodness of ecological models for explaining and maintaining the stability of ecosystem multifunctionality will be improved.",
"introduction": "Introduction Terrestrial ecosystems comprise multiple components that interact rapidly and systematically to drive the dynamics of multiple ecosystem functions (ecosystem multifunctionality), such as, biomass production, nutrient cycling, carbon stock, and litter decomposition 1 , 2 . Ecological stability is the key concept describing the responses of these components to disturbances, e.g., stochastic environmental fluctuations, drought, and exotic biotic invasion, especially in the face of augmented global change, laying the basis for understanding and predicting ecosystem dynamics, and maintaining ecosystem sustainability under a changing environment 3 , 4 . Previous research of ecosystem stability has simply focused on the stability (such as invariability in time and space, and resistance and resilience against disturbances and fluctuations) of individual functions, e.g., productivity stability, but only a few has tried to understand the overall stability of multiple ecosystem functions as a whole, i.e., ecosystem multifunctional stability 5 , 6 (the specific stability aspect assessed in this study, refers to the invariability (or its similar term reliability 7 ) against environmental stochasticity, and the resistance to drought/invasion disturbance), despite the fact that most ecosystems perform multiple functions simultaneously 2 , 4 , 8 . Understanding and predicting the ecosystem multifunctional stability in a noisy world, calls for clear awareness of its multidimensional nature (accounting for its multiple function components, and the different aspects of stability against multiple types of disturbances), and requires keen insights into not only the direct biotic/abiotic (e.g., biodiversity and disturbances) controls, but also the indirect cascading effects on multifunctional stability via biological communities across the food web 3 , 8 , 9 . Fortunately, pioneering work has already been done to test the effects of biotic/abiotic factors, through the mediating roles of multiple biotas, on multiple types of ecosystem functions 10 – 14 . However, such knowledge on the regulation of ecosystem multifunctional stability is still lacking 3 , especially when the ecosystem is under the control of multiple factors (e.g., plant diversity, drought, and exotic plant invasion) simultaneously. This knowledge gap constrains our understanding of the direct and indirect effects of biodiversity and disturbances on ecosystem multifunctional stability, and thus limits our ability to predict or maintain ecological sustainability under global change 10 . Biodiversity’s (e.g., aboveground plant richness) control on ecosystem dynamics has long been a core focus of ecological studies aimed at maintaining or increasing the ecosystem (multi)functionality in the face of global change 2 , 15 – 17 . Previous studies suggest that high plant diversity stabilizes the composition of communities of multiple biotas 18 – 20 , as well as individual ecosystem functions (mainly biomass production) 17 , 21 , 22 . However, it is still only theoretical whether, and how, plant richness stabilizes ecosystem multifunctionality 5 directly or indirectly by affecting the compositional stability of communities 3 , 23 . Global change disturbances’ (e.g., drought and exotic invasion) regulation on the composition of communities and the fate of ecosystem multifunctionality has also become a central topic of ecological research 15 , 24 – 27 . Despite a large body of studies discussing this topic, few have directly looked into the effects of disturbances on the stability of communities or the stability of ecosystem multifunctionality 28 , 29 . It is also still unclear whether and how disturbances, especially the multiple and entangled ones, affect community compositional stability (e.g., effects of drought/invasion on the invariability, or the resistance to invasion/drought of communities), and what cascading consequences this will have for ecosystem multifunctional stability 30 . Thus, knowledge of, and the mechanisms (e.g., the mediating roles of plant and faunal communities) underlying, the relationship between biodiversity/disturbance and ecosystem multifunctional stability are imperative, particularly in circumstances where multiple factors control and entangle ecosystem dynamics simultaneously. Plant and faunal communities, both, play key roles in ecosystems 31 , linking the dynamics of various ecosystem functions 32 , 33 . This is due to the plant community’s strong ability to shape habitat conditions for communities at higher trophic levels 31 , and that faunal communities can act as links between above- and belowground biotas by simultaneously interacting with plants and exerting influences on fungal or bacterial communities 33 – 35 . Numerous empirical studies have already shown that the dynamics of multiple ecosystem functions, and the effects of biotic/abiotic factors (e.g., plant richness, drought, and exotic plant invasion) on them, largely rely on the communities of multiple biotas, especially those of plants and fauna 10 , 26 , 36 – 38 . Despite, the mediating role of plant or faunal communities, it has rarely been considered in the diversity- or disturbance-ecosystem multifunctional stability relationship models, such that our ability is limited, to understand, predict, or cope with the fate of ecosystem multifunctional stability in the face of climate change. Filling these knowledge gaps requires explicitness about the general patterns of, and mechanisms underlying, richness/disturbance-multifunctional stability relationships. To test whether, and how, plant richness, drought, and exotic plant invasion will affect ecosystem multifunctional stability by modulating community compositional stability, a 3-year experiment was performed by exposing 270 plant communities, with four levels of plant richness (i.e., 16 monocultures, 10 two-species mixtures, 10 four-species mixtures, 9 eight-species mixtures with 6 replicates in each), to drought (non-, moderate-, and intensive-drought; treated numerically as 0, 1, and 2 during data analyses) and exotic plant invasion (non-invasion and invasion; 0 and 1). We calculated the compositional stability of plants, litter-faunal, and soil-faunal communities based on both their species abundances and phylogenetic traits, and also evaluated the stability of ecosystem multifunctionality based on 14 function-related variables that relate to biomass production (aboveground and belowground plant biomass, light interception efficiency, and litter- and soil-fauna abundances), soil properties (soil carbon, nitrogen, phosphorus, and glomalin related soil protein (GRSP)), or processes (litter decomposition rate, and activities of β-glucosidase, protease, nitrate reductase, and dehydrogenase). Then, we assessed three aspects of stability, i.e., invariability (reliability 7 ) against environmental stochasticity, drought resistance, and invasion resistance, for both community stability and multifunctional stability. Finally, the direct and indirect effects of plant richness, drought, and invasion on ecosystem multifunctional stability (all aspects), were assessed using structural equation modelings (SEMs). The overall setup and analyses allowed us to test the following hypotheses: (1) Plant richness increases ecosystem multifunctional stability (Fig. 1a ); (2) Drought/invasion decreases multifunctional stability (invariability, and resistance to invasion/drought) (Fig. 1b ); (3) Plant, litter-, and soil-faunal community stability mediate the effects of plant richness, drought, and invasion on multifunctional stability (Fig. 1c ). Fig. 1 Hypotheses and experimental design. \n a Plant richness increases ecosystem multifunctional stability (Hypothesis 1). b Drought/invasion decrease multifunctional stability (invariability and resistance to invasion/drought) (Hypothesis 2). c Plant, litter-, and soil-faunal communities mediate the effects of plant species, drought and invasion on ecosystem multifunctional stability (Hypothesis 3). d With the species pool consisting of 16 plant species, the monoculture of each species, and the random mixtures of 2, 4, and 8 species (with 10, 10, and 9 distinct assemblages, respectively) were designed, creating a complete set of 45 distinct plant assemblages. e Each plant assemblage was replicated 6 times, for a total of 270 assemblages (pots). After 1-year of growth the assemblages were manipulated with three levels of drought intensities (non-, moderate-, and intensive-drought). Nine months after the introduction of drought stress, 2 complete sets (45 pots) of each drought treatment we randomly exposed (invasion) or not exposed (non-invasion) to the invasive species Symphyotrichum subulatum . f Experiment schedules. # Litter sampling for litter-fauna extraction. ## Plant sampling for collecting aboveground/belowground plant biomass, and plant community data; Soil sampling for extracting soil-fauna, determining contents of soil organic carbon, nitrogen, phosphorus, and glomalin related soil protein (GRSP), or measuring activities of soil enzymes including β-glucosidase, protease, nitrate reductase, and dehydrogenase; Light interception efficiency was determined monthly from May to August. ### Litterbags sampling for litter decomposition rate evaluation.",
"discussion": "Discussion Evaluation of ecosystem multifunctional stability. Traditional studies on ecosystem multifunctional stability normally analyze the multidimensional data in a univariate manner, by either reducing data dimensionality (e.g., mean of z -scores or first principal component) or calculating similarity in a strict one-to-one correspondence manner. This may tease away undesired noise, but will also simultaneously discard a substantial fraction of information (e.g., the overlap of functional traits among totally different plant species compositions can also drive similar ecosystem functioning, especially for the case of mix-plant stands), leading to a reduction in statistical strength, thus requiring larger sample sizes to generate convincing conclusions on ecological stability. In this study, we analyzed the community and multifunctionality data in a multivariate manner, evaluating the cascading effects of the manipulated factors (plant richness, drought, and invasion) on different aspects (i.e., invariability, drought resistance, and invasion resistance) of community stability or multifunctional stability, using SEMs (Fig. 2 ) based on the specific aspect of stability extracted from the corresponding subset of a similarity matrix (Supplementary Fig. 1 ). With these analyses, we were able to assess the links between community stability and multifunctional stability, and the direct/indirect effects of multiple factors on community stability and multifunctional stability, on aspects of invariability, drought resistance, and invasion resistance. To evaluate the strengths of the multivariate-based SEMs (Fig. 2 ) over that of the univariate-based ones (Supplementary Fig. 2 ), we also build the same SEMs by calculating similarity in a strict one-to-one correspondence manner according to Baert et al. 39 . The multivariate-based SEMs (Fig. 2b, c ) showed generally comparable levels of statistical significances of effects but higher explained variances of multifunctional resistance to invasion (41.5% versus 30.0%) or drought (42.9% versus 37.2%) compared to the univariate-based ones (Supplementary Fig. 2b, c ), suggesting higher strengths of the multivariate-based SEMs over that of the univariate-based ones. Another evidence, that support the higher strengths of the multivariate-based SEMs over the univariate-based ones, is that the former can account for the contribution of the functional overlap between totally different plant species compositions to multifunctional stability especially for the case of high-diversity communities, as evidenced by the higher effects of plant richness on plant community stability showed by the result derived from the former method (Fig. 2 and Supplementary Fig. 2 ). Though, both manners also showed similar results, i.e., both a positive plant richness-multifunctional stability relationship and negative disturbance-multifunctional stability relationship can be mediated by the stability of faunal communities (Figs. 2 a–c and 3 , and Supplementary Fig. 2 ). Community stability matters for regulating multifunctional stability. It has been recognized that the composition of communities across the food web play determining roles in regulating the dynamics of various ecosystem functions 38 , 40 , 41 . Deeper insights have also been given into the common linkage between ecosystem multifunctional stability and the composition, or more specifically, the compositional stability of communities 3 , 38 , 42 . Our results suggested that ecosystem multifunctional stability (invariability, drought resistance, and invasion resistance) was positively linked to the stability of plant, litter-, and soil-faunal communities ( p < 0.05; Fig. 2a–c ), and this result was further supported by the generally positive links between the stability of individual functions and the stability of the three communities (Supplementary Table 1 ), suggesting that the stability of communities is critical for mediating ecosystem multifunctional stability. Understanding the biotic and abiotic controls on ecosystem stability, requires us to be clear about the cascading link between community stability and multifunctional stability 3 , 5 , 9 , which are crucial for maintaining and increasing the robustness of ecosystem multifunctionality in the face of global change. To further address which plant or fauna groups are important to stability of ecosystem multifunctionality, we estimated the relative contributions of plant species (or faunal taxa at the Order level) to the relationship between community stability and ecosystem multifunctional stability (invariability, drought resistance, or invasion resistance) (see supplementary method for detailed estimation procedure). We found that the positive relationship between the stability (all aspects) of community (plant, soil fauna, and litter fauna) and multifunctionality decreased with the remove of plants species (or faunal Orders) from the original community, and the level of such decrease increased with the number of plants species (or faunal Orders) removed (Supplementary Fig. 3 ), demonstrating that the co-working and interaction among multiple plants (or fauna) are important for the maintenance of multifunctional stability, despite that some dominant plant species ( Patrinia scabiosifolia, Artemisia stolonifera , and their combinations with others) or faunal Orders (soil fauna: Posuromorpha and Trombidiformes ; litter fauna: Trombidiformes and Araneae ) accounted for relatively high level of contributions (Supplementary Fig. 4 ). We also found that the higher the mean abundances of the plant species or faunal taxa that drive the ecosystem functions, the greater their contribution to multifunctional stability (Supplementary Fig. 5a–c ). In addition, the contribution of plant species (or their combinations) to the community-multifunctional stability decreased with the mean coefficient of variance (CV) of biomass, while those of soil and litter-faunal Orders (or their combinations) increased with the mean CV of faunal abundance (Supplementary Fig. 5d–f ), suggesting that the stable biomass production of dominant plant species while the asynchronous dynamics of faunal taxon that drive the dynamic of ecosystem functions were also key to shaping the community-multifunctional stability relationship in the face of disturbances (spatial stochasticity, drought and invasion). Plant richness and disturbances modulate community stability. Our results showed that higher plant richness supported higher plant and faunal community stability, for the aspects of invariability, drought resistance, and invasion resistance (Figs. 2 a–c and 3a ). This result is supported by the diversity-stability hypothesis that community stability increases with species richness 43 , and is consistent with the ample empirical evidence present in the literature that shows plant richness stabilizes communities across trophic levels 18 , 20 . Several mechanisms, notably asynchronous performance associated with mix-species plant communities and compensatory dynamics generated by negative species covariance and selection for stable dominant species populations, may underlie the positive richness-community stability relationship 44 . Moreover, the bottom-up regulation of a plant community on soil organisms has also been suggested to be the indirect mechanism driving the stabilizing effects of plant richness on communities 10 , because plant communities can strongly shape the habitat for communities of higher trophic levels 45 , 46 as evidenced by the positive relationship between the communities of plant and soil-fauna ( p < 0.001; Table 2 ). Both drought and plant invasion had neutral effects on the stability of the aboveground plant community, but significantly decreased that of both litter- and soil-faunal communities, for different aspects of stability (Fig. 2a–c ). This suggests that drought and exotic plant invasion may have a more prominent direct effect on litter- and soil-faunal communities than on aboveground plant communities, which may imply a top-down governance on the effects of drought or invasion on communities 46 . The destabilizing effects of disturbances, e.g., drought and exotic invasion, on community stability may be governed by multiple mechanisms relating to the increase of environmental heterogeneity 47 , the impairment of local asynchrony and insurance effect 48 , the decrease of belowground competition 49 , the reduction of species movement and dispersion 26 , and the decoupling of multitrophic interactions 30 , 46 . In addition, faunal communities occupy a key position within the soil food web, as they interact intensively with the plant assemblage and influence the fungal and bacterial communities simultaneously 26 , 34 , 45 , thereby linking the dynamics of ecosystem functions 32 , 36 , 50 . Thus, the indirect role of faunal communities in modulating multifunctional stability should be considered to gain a holistic understanding of the ecosystem multifunctional stability under climate change 10 , 26 . Plant richness increases multifunctional stability by increasing community stability. There was a significantly positive effect of plant richness on multifunctional stability, for different stability aspects ( p < 0.01; Figs. 2 a–c and 3a ). Plant richness effect on the ecosystem stability highly depends on the dynamics of the composition and functional traits of plant community 51 , as well as multitrophic interactions 52 . Several mechanisms, including insurance effect, portfolio effect, and compensatory interactions, have been proposed to underpin the effect of plant richness on ecosystem stability 53 – 56 . These mechanisms highlight the higher probability to include more disturbance-tolerant species 30 , diversified ecological traits and niches, and the intensified interspecific interactions within mix-plant stands, which allow compensatory performances to buffer community compositional and functional variation against disturbances or fluctuations 52 . Community composition has been suggested to play an even more important role than biodiversity per se in driving the dynamics of multiple ecosystem functions 40 , 41 , 57 , 58 , and this lays the basis for the logic that models of plant richness-multifunctional stability relationship may be improved by incorporating the compositional traits (e.g., stability) of communities across the food web. Our results based on SEMs showed the positive indirect effects of plant richness on multifunctional stability by increasing the stability of plant, litter-, and soil-faunal communities (Figs. 2 a–c and 3 ), with the indirect effects accounting for 42–51% of the total plant richness effects ( p < 0.01; Fig. 3a ). This suggests the significant role of community stability in mediating the plant richness-multifunctional stability relationship. Since only a small fraction of the biotas (i.e., plant and faunal communities) across the food web were included in this study, substantial parts of plant richness effects still cannot be explained by stability of the communities (reflected as the direct plant richness effects; Figs. 2 a–c and 3a ). Thus, we propose that, by exploring the stability of adequate communities across multiple trophic levels with the plant richness-multifunctional stability models, the completeness and goodness of ecological models for explaining, maintaining, and predicting plant richness-multifunctional stability relationship would be improved. Drought and invasion decrease multifunctional stability by decreasing the stability of litter- and soil-faunal communities. Our results also showed a negative disturbance-multifunctional stability relationship (Fig. 3a ). Among the large body of studies on ecosystems under global change disturbances, only a few have looked into the effects of disturbances on ecosystem functional stability, e.g., drought and invasion reducing productivity stability and ecosystem resistance 28 , 29 . Thus, knowledge on the general ecological pattern of disturbance-multifunctional stability relationship and the underlying mechanisms is imperative, particularly in cases where compounded disturbances occur simultaneously. However, the cascading links from disturbances—through multitrophic communities—to numerous ecosystem functions, for example, the faunal community compositional change induced by plant invasion was associated with soil nitrogen cycling 59 , may help us to take a snapshot of potential general pattern of disturbance-multifunctional stability relationship. Drought and invasion significantly decreased multifunctional stability by decreasing litter- and soil-faunal community stability ( p < 0.05; Figs. 2 a–c and 3a, b ), and the indirect effects accounted for more than 20% of the total effects ( p < 0.01; Fig. 3a ), suggesting significant roles for faunal communities in mediating the disturbance-multifunctional stability relationship. Similarly, the direct disturbance effects (Figs. 2 a–c and 3a ) may be further explained by the stability of biological communities that were not assessed in this study. More insights into the stability of multitrophic communities mediating the disturbance-multifunctional stability models are imperative, for understanding and predicting ecosystem multifunctional stability in the face of intensified global change under circumstances where multiple disturbances stress ecosystems. Our results showed a significantly positive plant richness-multifunctional stability relationship and a significantly negative disturbance-multifunctional stability relationship. To the best of our knowledge, this is the first study that treated and incorporated plant richness, drought, and invasion as influencing factors into a single ecological model to assess the indirect mechanism(s), by modulating community stability, underlying the ecological patterns of the plant richness- and disturbance-ecosystem multifunctional stability relationships, and newly evidenced that both relationships can be mediated by the stability of plant or faunal communities. Our results might be strengthened by including the temporal aspects of stability (e.g., temporal stability and recovery of community and multifunctionality) 5 , 6 ; however, constrained by the non-time-series dataset, the temporal aspects of stability can’t be assessed in this study. Further studies should incorporate more aspects of stability to build a more general framework for understanding and predicting the diversity- and disturbance-multifunctional stability relationships. Nevertheless, on the aspects of invariability, resistance of both community and ecosystem multifunctionality, the loss of plant diversity, and the drought and invasion distrubances would likely reduce the sustainability of ecosystem multifunctionality in the face of global change."
} | 6,356 |
29180366 | PMC5772236 | pmc | 4,055 | {
"abstract": "ABSTRACT New environmentally sound technologies are needed to derive valuable compounds from renewable resources. Lignin, an abundant polymer in terrestrial plants comprised predominantly of guaiacyl and syringyl monoaromatic phenylpropanoid units, is a potential natural source of aromatic compounds. In addition, the plant secondary metabolite tricin is a recently discovered and moderately abundant flavonoid in grasses. The most prevalent interunit linkage between guaiacyl, syringyl, and tricin units is the β-ether linkage. Previous studies have shown that bacterial β-etherase pathway enzymes catalyze glutathione-dependent cleavage of β-ether bonds in dimeric β-ether lignin model compounds. To date, however, it remains unclear whether the known β-etherase enzymes are active on lignin polymers. Here we report on enzymes that catalyze β-ether cleavage from bona fide lignin, under conditions that recycle the cosubstrates NAD + and glutathione. Guaiacyl, syringyl, and tricin derivatives were identified as reaction products when different model compounds or lignin fractions were used as substrates. These results demonstrate an in vitro enzymatic system that can recycle cosubstrates while releasing aromatic monomers from model compounds as well as natural and engineered lignin oligomers. These findings can improve the ability to produce valuable aromatic compounds from a renewable resource like lignin. IMPORTANCE Many bacteria are predicted to contain enzymes that could convert renewable carbon sources into substitutes for compounds that are derived from petroleum. The β-etherase pathway present in sphingomonad bacteria could cleave the abundant β–O–4-aryl ether bonds in plant lignin, releasing a biobased source of aromatic compounds for the chemical industry. However, the activity of these enzymes on the complex aromatic oligomers found in plant lignin is unknown. Here we demonstrate biodegradation of lignin polymers using a minimal set of β-etherase pathway enzymes, the ability to recycle needed cofactors (glutathione and NAD + ) in vitro , and the release of guaiacyl, syringyl, and tricin as depolymerized products from lignin. These observations provide critical evidence for the use and future optimization of these bacterial β-etherase pathway enzymes for industrial-level biotechnological applications designed to derive high-value monomeric aromatic compounds from lignin.",
"introduction": "INTRODUCTION There is economic and environmental interest in using renewable resources as raw materials for production of chemicals that are currently derived from fossil fuels. Lignin, a renewable resource that accounts for ∼15 to 30% (dry weight) of vascular plant cell walls ( 1 , 2 ), is comprised of aromatic compounds that may be valuable commodities for the biofuel, chemical, cosmetic, food, and pharmaceutical industries ( 3 ). Consequently, intensive efforts are currently aimed at developing chemical, enzymatic, and hybrid methods for deriving simpler and lower-molecular-weight (lower-MW) products from lignin ( 4 ). The lignin backbone is predominantly composed of guaiacyl (G) and syringyl (S) phenylpropanoid units ( Fig. 1A ) that derive from the monomers coniferyl alcohol and sinapyl alcohol, which become covalently linked during lignification via radical coupling reactions, primarily by endwise addition of a monomer (radical) to the phenolic end of the growing polymer (radical). G and S units are interlinked by a variety of chemical bonds by which the units are characterized: resinols (β–β), 4–O–5-diaryl ethers, phenylcoumarans (β–5), and β–O–4-aryl ethers (termed β-ethers here) ( 5 – 7 ). In grasses, the flavone tricin (T unit [ Fig. 1A ]) begins a chain and is covalently linked to the next unit via a 4–O–β-ether bond ( 8 – 10 ). Given that approximately 50 to 70% of all interunit linkages in lignin are β-ethers ( 5 – 7 ), cleavage of these bonds is crucial for processes aiming to derive valuable low-molecular-weight compounds from lignin in high yields. The formation of β-ether linkages during lignification generates a racemic lignin product containing both β( R )- and β( S )-carbons that, after rearomatization of the quinone methide intermediate by proton-assisted water addition, are adjacent to either α( R )- or α( S )-configured benzylic alcohols ( 11 – 13 ). Each unit therefore has 4 optical isomers and two “real” isomers—the so-designated threo and erythro (or syn and anti ) isomers. Lignin depolymerization via β-ether bond cleavage has been demonstrated with chemical catalysis ( 14 , 15 ). In addition, cytoplasmic enzymes in a sphingomonad β-etherase pathway have been identified that oxidize and cleave model β-ether-linked aromatic dimers ( 16 ). FIG 1 Aromatic monomers and the β-etherase pathway. Panel A shows the structures of predominant monomeric phenylpropanoids found in lignin, guaiacyl (G, in blue), syringyl (S, in red), and tricin (T, in green) units. Arrows indicate where interunit linkages are formed during radical coupling reactions. Dashed lines indicate positions that may form additional covalent bonds during postcoupling reaction mechanisms. Panel B shows β-etherase pathway-mediated degradation of the diaromatic β-ether-linked model compound GGE via NAD + -dependent dehydrogenases LigD and LigN to form GGE-ketone and NADH. GGE-ketone undergoes GSH-dependent β-ether cleavage by β-etherase enzymes LigE and LigF to yield guaiacol and GS-HPV as monoaromatic derivative products. GS-HPV undergoes GSH-dependent thioether cleavage by NaGST NU or LigG, producing GSSG and monoaromatic product HPV. As indicated by the dashed arrows, AvGR recycles cosubstrates GSH and NAD + via NADH-dependent reduction of GSSG. For reactions involving an R - or S -configured epimer as the substrate, the isomer toward which each enzyme exhibits activity is shown in gray text. Panel C shows how β-etherase pathway enzymes degrade GTE through intermediate GTE-ketone to yield tricin and HPV. The β-etherase pathway is present in Sphingobium sp. strain SYK-6 and other sphingomonads (e.g., Novosphingobium spp.) ( 16 , 17 ). The diaromatic β-ether-linked guaiacylglycerol-β-guaiacyl ether (GGE [ Fig. 1B ]) lignin model compound has been used as a substrate to identify the following three enzymatic steps in cleavage of β-ether linkages in vitro ( 17 – 21 ): (i) a set of dehydrogenases catalyze NAD (NAD + )-dependent α-oxidation of GGE to GGE-ketone, also referred to as α-(2-methoxyphenoxy)-β-hydroxypropiovanillone (MPHPV), and NADH ( 19 , 22 ); (ii) β-etherases, members of the glutathione S -transferase (GST) superfamily, carry out glutathione (GSH)-dependent cleavage of GGE-ketone, releasing guaiacol and β-S-glutathionyl-γ-hydroxypropiovanillone (GS-HPV) ( 18 , 21 , 23 ); and (iii) one or more glutathione lyases catalyze GSH-dependent cleavage of GS-HPV, yielding glutathione disulfide (GSSG) and γ-hydroxypropiovanillone (HPV) ( 18 , 21 , 24 ; W. S. Kontur, C. Bingman, C. Olmstead, D. Wassarman, A. Ulbrich, D. L. Gall, R. W. Smith, L. M. Yusko, B. G. Fox, D. R. Noguera, J. J. Coon, and T. J. Donohue, submitted for publication). The use of multiple enzymes for some of the pathway's steps is attributable to the existence of both R - and S -configured chiral centers in lignin ( 11 – 13 ). The known NAD + -dependent dehydrogenases (LigD, LigL, LigN, and LigO) exhibit strict stereospecificity at the α position, with indifference to the configuration at the β position ( 19 ). With model diaromatic substrates, LigD and LigO are active on the R -configured α-epimers, whereas LigL and LigN are active on the S -configured α-epimers. Because the combined activity of these dehydrogenases eliminates the chiral center at α, GGE-ketone exists as two β-enantiomers that are cleaved by stereospecific β-etherases LigE, LigP, and LigF, each of which catalyzes the release of guaiacol with chiral inversion at the β position, and one of two β-epimers of GS-HPV [LigE and LigP convert β( R )-GGE-ketone to β( S )-GS-HPV, and LigF converts β( S )-GGE-ketone to β( R )-GS-HPV] ( 21 ). The final step is the GSH-dependent cleavage of the GS-HPV epimers, yielding GSSG and HPV as coproducts. LigG has been shown to cleave both β( R )-GS-HPV and β( S )-GS-HPV ( 24 ), although it appears to have a strong preference for the former ( 18 , 21 ). Recently, a GSH transferase from Novosphingobium aromaticivorans DSM12444 (NaGST NU ; Saro_2595 in GenBank assembly GCA_000013325.1 ) (Kontur et al., submitted) has been shown to have high activity with β( R )-GS-HPV and β( S )-GS-HPV both in vivo and in vitro , producing HPV and GSSG as products ( Fig. 1B ). Despite what is known about the activity of individual β-etherase pathway enzymes with model diaromatic compounds, there is little information on their function with lignin oligomers. In vivo activity may be limited to aromatic dimers or small lignin oligomers due to restrictions in transporting large polymers into the bacterial cytoplasm, where the β-etherase pathway enzymes are found. Recently, modest recovery of low-molecular-mass aromatic compounds from lignin from a multistep enzymatic process that used a laccase mediator system, two β-etherases, and a glutathione lyase was reported ( 25 ). However, the size of lignin fragments that were subject to enzymatic cleavage was not determined, and it therefore remains unknown whether the β-etherases were active on only small or also large lignin oligomers. To better understand the function of β-etherase pathway enzymes, we sought to use a minimal set of enzymes to develop a coupled in vitro assay capable of releasing G, S, and T aromatic monomers and recycling the cosubstrates NAD + and GSH. Here we demonstrate complete conversion of GGE to guaiacol and HPV in a reaction including LigD, LigN, LigE, LigF, NaGST NU , and the Allochromatium vinosum DSM180 GSH reductase (AvGR), which catalyzes NADH-dependent reduction of GSSG and recycles the cofactors needed in the reaction ( Fig. 1B ) ( 26 ). We also show that this combination of enzymes releases tricin from the model compound guaiacylglycerol-β-tricin ether (GTE [ Fig. 1C ]). In addition, we show that the same combination of enzymes releases G, S, and T units from bona fide lignin oligomers. We discuss new insights gained from this study and its implications for the future production of these and possibly other valuable products from lignin.",
"discussion": "DISCUSSION In order to use a polymer like lignin as a source of valuable aromatics and other chemicals, it is necessary to develop new or improve on existing depolymerization strategies. Recently developed oxidative and hydrogenolytic depolymerization approaches are showing some promise for producing low-molecular-weight aromatics in near-theoretical yields ( 15 , 30 ), but there has also been considerable interest in exploring the biological production of aromatics from this renewable plant polymer ( 25 ). The use of the bacterial β-etherase pathway for biological depolymerization involves milder conditions that could result in the release of monomers, such as HPS and HPV, that are useful in their own right or extractable low-MW mixtures that could be further valorized ( 25 , 31 ). There is now a large amount of information on the types of model diaromatic substrates recognized by individual β-etherase enzymes in vitro , the products of their activity, and their structural or functional relationships to other known enzymes ( 27 , 32 ). Despite this, information on their activity with lignin oligomers is lacking. In addition, as these are cytoplasmic enzymes, it is plausible that they evolved to break down β-ether links only in the smaller lignin oligomers that could be transported inside the cells. A recent study described an in vitro enzymatic treatment of lignin yielding 12% (by weight) of low-molecular-mass aromatic products, although it remains unknown whether these aromatics were released from only small or also large oligomers ( 25 ). In this work, we sought to develop a coupled in vitro system containing a set of β-etherase pathway enzymes that was capable of releasing monoaromatic compounds when incubated with different substrates. We reasoned that such a system would provide additional information on the β-etherase enzymes and aid in studies aimed at determining the requirements for release of valuable aromatics from bona fide lignin oligomers. We identified a minimum set of enzymes (LigD, LigN, LigE, LigF, NaGST NU , and AvGR) that, in a single procedure, cleaves β-ether linkages and completely converts model diaromatic compounds to aromatic monomers. We further showed that this coupled in vitro assay system is capable of stoichiometric production of monoaromatic products from model diaromatics in the presence of limiting amounts of the cosubstrates NAD + and GSH. The ability to recycle NAD + and GSH allows the use of small quantities of these expensive cofactors and increases the future utility of a coupled enzyme system for processing lignin oligomers in vitro . Finally, we showed that this coupled enzyme system has activity with fractionated lignin oligomers. Below we summarize the new information gained from using this assay with widely used or new model β-ether linked substrates as well as lignin oligomers of different sizes. Insights gained from using the coupled assay with diaromatic compounds. Using GGE as a substrate, we demonstrated that the GSH reductase AvGR is capable of recycling the cosubstrates NAD + and GSH, enabling the β-etherase enzymes to completely cleave GGE in the presence of substoichiometric amounts of these cofactors ( Fig. 2A to C ). The A. vinosum DSM180 AvGR is well suited for this purpose, as most glutathione reductases described in the literature use NADPH instead of NADH as an electron donor ( 33 ). When AvGR was not present in an assay in which GGE concentrations were greater than those of NAD + and GSH, there was incomplete hydrolysis of this diaromatic substrate, accumulation of β-etherase pathway intermediates, and depletion of NAD + , as expected if the reaction was cofactor limited. We were also able to detect the release of tricin when GTE was used as a substrate in this assay, showing that β-etherase pathway enzymes are capable of β-ether bond cleavage in a substrate bearing a large flavonoid moiety. This further shows that the β-etherase pathway enzymes are not limited to substrates containing only G and S monoaromatic units. In prior research, we had demonstrated the ability of LigE and LigF to cleave G–G, G–S, S–G, and S–S dimer models ( 17 , 21 ), so this result extends the knowledge of the diversity of substrates for these enzymes to the G–T dimers. Thus, although the β-etherase pathway enzymes are thought to be highly stereospecific, they are also capable of recognizing the many different configurations of β-ether-linked aromatics potentially present in lignin. With the results of these and previous findings combined ( 17 , 21 ), we conclude that the minimal set of enzymes used in this study is sufficient to enable the β-etherase pathway in vitro to release G, S, and T units from compounds modeling β-ether units in lignin. This coupled assay also allowed us to directly compare the abilities of LigG and NaGST NU to function in the β-etherase pathway. We found that the presence of NaGST NU and AvGR, along with LigD, LigN, LigE, and LigF, was sufficient to allow complete conversion of GGE to HPV and guaiacol ( Fig. 2A to C ). This is consistent with our prediction that NaGST NU can accommodate both GS-HPV epimers in its active site (Kontur et al., submitted) and the ability of this enzyme to produce stoichiometric amounts of HPV from GGE when added to this coupled assay. In contrast, when LigG replaced NaGST NU under otherwise identical assay conditions, there was incomplete hydrolysis of GGE to HPV and guaiacol, with significant accumulation of GGE-ketone and smaller amounts of GS-HPV ( Fig. 2A , D , and E ). Thus, although it has been suggested that LigG can hydrolyze both β-epimers of GS-HPV ( 24 ), this result, along with those published previously ( 21 ), supports the hypothesis that LigG has a strong preference for β( R )-GS-HPV. This direct comparison of substrate conversion to products in assays that differ only in the addition of LigG or NaGST NU allows us to conclude that use of the latter enzyme has advantages owing to its greater ability to release HPV from both GS-HPV epimers under comparable conditions in vitro . Release of aromatic monomers from lignin oligomers in vitro . The features of this coupled β-etherase assay allowed us to begin testing the ability to remove monomer aromatics from bona fide lignin. Lignin is a heterogeneous, high-molecular-weight polymer, with only limited solubility under the aqueous buffer conditions used for this assay. Consequently, to increase our chances of observing aromatic products under the conditions used for the coupled assay, we used several different lignin oligomers. We also fractionated these materials to test for release of aromatics from different-size lignin oligomers. This has provided several important new insights into the activity of β-etherase enzymes with lignin oligomers and identified opportunities for increasing our understanding of this pathway. We tested the ability of this enzyme mixture to cleave lignin oligomers that were derived from HP lignin, an engineered poplar line comprised of as much as 97.5% S units ( 29 ). HPS was detected as a product when high-molecular-weight fractions of the HP lignin were used as the substrate. This provides direct proof that the enzyme mixture cleaves aromatic oligomers containing S units and that this set of β-etherase pathway enzymes is active with lignin oligomers. Given that the vast majority of the aromatic units in HP lignin are S units ( 29 ), we estimate that the oligomers used in the enzymatic assay had between 40 and 50 aromatic units ( Table 1 ). With the concentration of lignin oligomer used in this assay (∼2.2 mg ml −1 ), complete substrate degradation would yield ∼8 mM HPS. The measured HPS concentration in this assay was 1.0 mM, resulting in a 12.5% yield of HPS from HP lignin. Thus, it appears that the mixture of enzymes used in this study, while sufficient for complete cleavage of model diaromatic compounds and of some β-ether links in HP lignin, is not capable of complete cleavage of all the β-ether linkages in the HP lignin oligomers. It is possible that a heretofore-undescribed protein is required to further process these lignin oligomers or that inhibition of enzyme activity was caused by the presence of some of the high-MW oligomers. Although our findings with the model dimers, and previous research, indicate that LigD and LigN are sufficient for complete oxidation of diaromatic compounds ( Fig. 2 ) ( 19 , 34 ), it is possible that the seemingly redundant dehydrogenases LigO and LigL have a higher affinity for higher-MW lignin oligomers. Similarly, LigP, a GSH-S-transferase with apparent redundant activity with LigE ( 20 ), may be of interest for the optimization of in vitro lignin depolymerization. In the assays using HP lignin as a substrate, we did not detect syringaresinol as a product, even though this dimer is found in moderate abundance in this polymer ( 29 ). Existing models for the composition of HP lignin predict that syringaresinol is primarily internal to the polymer ( 29 ). Thus, it is possible that the failure to detect syringaresinol as a reaction product reflects the inability of the tested β-etherase enzymes to access and cleave β-ether bonds that are adjacent to a syringaresinol moiety or, perhaps, that the enzymes exhibited only limited exolytic activity, thus preventing the enzymes from ever reaching syringaresinol units in the polymer. Having established that the coupled enzymatic assay exhibited β-etherase catalytic activity with high-MW fractions of the HP lignin oligomers, we tested a more complex lignin sample from corn stover as a substrate (MCS lignin). This lignin has been thoroughly characterized and shown to contain only tricin, which is covalently bonded to the lignin oligomers ( 9 ). Fractionation of this lignin was carried out and experiments with a wider array of lignin fractions were conducted to test for the release of the major aromatic monomers present in this material (G, S, and T units). Unfortunately, background absorbance was observed in the chromatograms, for all lignin fractions analyzed, at retention times that overlapped with tricin's. Although this background absorbance was present in all lignin fractions, fortunately, tricin was detectable as a defined absorbance peak with a retention time identical to that from the pure standard. The detection of HPV, HPS, and tricin from different MCS lignin fractions confirms the observations with the β-ether-linked models that the enzyme set used was active in the release of G, S, and T units from lignin. However, tricin was observed only with the lignin fraction having an average MW of 460 ( Fig. 7 ). Using a crude assumption that the average aromatic unit in lignin has an MW of 210 and the known MW of tricin (330), this fraction represents mostly lignin dimers or a T unit with at most one or two other S or G units. Thus, the ability of the enzymes to cleave the β-ether linkage next to a flavonoid moiety appears to be restricted to lower-MW oligomers. In contrast, HPS and HPV were released from MCS lignin in assays using all of the fractions tested ( Fig. 8 ), which we estimate to encompass a range of oligomers from dimers to 50-unit oligomers ( Table 2 ). The highest measured concentration of HPS and HPV corresponded to the lignin fraction with an average MW of 1,390, or ∼7 aromatic units ( Table 2 ). Using the same assumption of 210 as the average MW of an aromatic unit in lignin, and the mass of lignin used in the assay (2.2 mg ml −1 ), we estimate a yield of HPS plus HPV of ∼5%, which is lower than the estimated HPS yield from HP lignin. This lower release of substrates from MCS than HP lignin likely reflects the more heterogeneous and complex structure of the MCS lignin sample and potential inability of the β-etherase pathway enzymes to access and cleave all β-ether bonds in the polymer. The low yield of low-MW aromatics in the multistep enzymatic study ( 25 ) is in agreement with the low release of HPS and HPV observed in this study, supporting the hypothesis that the currently known β-etherase enzymes are not sufficient for complete breakdown of β-ether bonds in polymeric lignins. Taken together, the findings presented here reveal new and exciting features of the β-etherase pathway enzymes. We identified tricin as a valuable flavonoid that can be enzymatically cleaved from β-ether-linked models and from low-MW lignin fractions. We also demonstrated β-etherase activity with intact lignin oligomers of various sizes, some of which might even be too large to be transported into cells. These findings therefore provide a demonstration that partial in vitro depolymerization of lignin is possible with β-etherase enzymes, an important step toward the development of biotechnological applications designed to derive high-value monomeric compounds from bona fide lignin polymers. Improving in vitro lignin depolymerization may depend on future discoveries of novel enzymes active on β-ether bonds, such as the newly characterized NaGST NU (Kontur et al., submitted) used in this study, or the engineering of existing β-etherase enzymes to improve the range of β-ether-containing substrates they can utilize. Ultimately, the activity of the studied enzymes on oligomeric substrates provides an opportunity to develop and optimize conditions for aromatic release from lignin fractions derived from biomass deconstruction chemistries that are or will be used by industry."
} | 5,991 |
37016494 | PMC10116646 | pmc | 4,056 | {
"abstract": "Galvanized steel surfaces are widely used in industry\nas a solution\nto prevent corrosion of steel tools that operate in outdoor or corrosive\nand oxidative environments. These objects are coated with a zinc protective\nlayer deposited by hot dip galvanization. Turning the surface of galvanized\nsteel tools into superhydrophobic may lead to very useful functionalities,\nalthough it may be a difficult task, because the preservation of the\nthin zinc layer is a claim. We propose herein the use of a bottom-up\napproach based on sandblasting, followed by sintering of zinc nanoparticles\non the galvanized steel substrate, which allowed us to produce a zinc-made\nhierarchical structure required for superhydrophobicity. These samples\nacquired a double-scale structure that led to superhydrophobicity\nwhen they were later hydrophobized with a thin fluoropolymer layer.\nWe found that sandblasting might be useful but not mandatory, unlike\nthe sintering process, which was essential to reach superhydrophobicity.\nWe found that, under certain experimental conditions, the surfaces\nshowed outstanding water-repellent properties. We observed that the\nsandblasting on galvanized steel caused more damage than the sintering\nprocess. Sintering of low-melting-point metal nanoparticles was revealed\nas a promising strategy to fabricate functional metallic surfaces.",
"conclusion": "4 Conclusions The sandblasting process\nincreases the surface roughness remarkably\nat the microscale. However, we observed that this texture is not enough\nto reach extreme water repellency. An additional treatment aimed at\nadding nanosized surface asperities is also required. This finding\nagrees with a previous study on GS surfaces as well. 12 In that work, the nanoasperities were created by a soft\nacid etching. In this study, we changed it by a less aggressive method\nbased on the sintering of zinc NP. The NP sintering process\nmodified the surface structure in two\nways: the thermal treatment needed to melt the Zn NPs altered the\nroughness at the microscale. However, we observed that, like sandblasting,\nthe roughening induced by heating was not enough for the second level\nof roughness incorporated by the Zn NPs that is essential for superhydrophobicity.\nSandblasting allowed us to find out the experimental conditions required\nfor superhydrophobicity during the optimization of the sintering process.\nHowever, we found that sandblasting damaged the GS surface at the\nmicroscale. The treatment based on NP sintering seems to be more convenient\nbecause of its excellent water-repellent performance and minor changes\nin the original chemical composition of GS. NP sintering to\nproduce water-repellent surfaces has been proposed\nin other works, specifically those aimed at fabricating durable and\nsuperhydrophobic silica surfaces. 16 , 24 However, scarce\nworks 24 use this strategy to create a specific\nnanostructure on metal surfaces since most metal particles have high\nmelting points. NP sintering is a promising strategy to create hierarchical\nstructures on surfaces with relatively low melting points. This\nwork proposes the use of sintered metal nanoparticles to incorporate\na hierarchical texture on metal surfaces. This strategy was not used\nearlier and opens up new possibilities for fabricating robust functional\nsurfaces, such as lotus-like or petal like surfaces. We chose a fluoropolymer\ndeposition as the hydrophobization method, although it can be replaced\nby any other hydrophilization method capable of creating a uniform\nand thin low-energy coating. 18 In fact,\nthe use of fluorinated compounds should be avoided due to their toxic\nnature. In addition, the durability tests confirm that the life of\nthe coating might be increased by using a hydrophobic compound which\nis more strongly adhered to the substrate. However, the focus of this\nwork is on the texturization method rather than the hydrophobization\nmethod.",
"introduction": "1 Introduction Turning metal-based surfaces\ninto nonwetting surfaces is challenging\nbecause metals are high-surface-energy materials. There are many applications\nfor low-adhesion metal surfaces. Lotus-like or superhydrophobic (SH)\nsurfaces have been often proposed as anti-icing, 1 , 2 antibiofouling, 3 antibacterial, 4 or\nnoncorrosive solutions. 3 , 5 − 7 Water-repellent\nsurfaces are obtained when specific surface texture and low-surface\nenergy compounds are incorporated on the surface. However, most manufactured\nmetallic surfaces are smooth and hydrophilic. Producing SH surfaces\non those materials requires the use of bottom-up approaches, such\nas surface coatings. 8 − 10 Unfortunately, most of the commercially available\nSH coatings are not durable 11 or may mask\nother interesting surface functionalities of the material. For this\nreason, an alternative strategy is the use of top-down approaches.\nThey are based on a surface modification aimed to incorporate topographic\nfeatures, followed by an increase of the intrinsic contact angle through\nthe deposition of a thin low-surface energy layer. 12 , 13 The physical and chemical modification of the metal surface may\nbe achieved by one-step or two-step strategies. Galvanized steel\n(GS) surfaces are zinc-coated steel/iron surfaces,\ntypically fabricated by hot-dip galvanization. Depending on the galvanization\nprocess, the thickness of the zinc coating may vary from microns to\nmillimeters. 14 The main purpose of the\nincorporation of the zinc coating on steel is the corrosion or oxidation\nprevention of the bulk steel. This process is less expensive than\nthe fabrication of stainless steel. For this reason, GS is used in\nmany industrial applications that require large steel tools: 14 building structures, roofs, gratings, sheets,\nand wires. These elements operate in wet/humid conditions, and the\nincorporation of nonwetting properties might be particularly beneficial. However, GS is a coated material, and the preservation of the zinc\ncoating is a must. This is an issue if the SH surfaces are prepared\nby using top-down approaches because these strategies require the\nmaterial removal intended to create a specific surface texture. Some of us proposed a protocol to fabricate water-repellent GS\nfollowing a top-down route based on sandblasting and soft acid etching. 12 New bottom-up approaches have been reported\nto produce SH surfaces on GS. 1 , 8 The incorporation of\nsurface composites is still one of the most recurrent strategies. 10 Other options are based on the incorporation\nof enhanced zinc-based coatings on steel. These coatings are created\nby electrodeposition followed by chemical modification of steel surfaces. 1 However, there is still a gap in the state-of-the-art\napproaches. Surface treatments that directly incorporate the SH properties\non GS are challenging. In this work, we propose a scalable bottom-up\nstrategy to fabricate\nSH surfaces on GS. The strategy is based on a combination of two different\ntexturization methods: sandblasting and nanoparticle (NP) sintering,\nboth aimed to create the hierarchical surface structure on GS. With\nthese two roughening methods, a double-scale surface texture is produced\nwith minor damage to the zinc layer. Sintering of micro-/nanoparticles\nhas been used in other studies to fabricate SH surfaces. 15 Ling et al. 16 fabricated\ntransparent SH films by sintering silica NP onto glass surfaces. Their\nroute to create the nanoscale structure was divided into two steps:\na deposition process in which silica NPs are spontaneously adsorbed\non the surface by electrostatic interactions and a second process\nin which the particle–substrate bonding is enhanced with a\nsintering process at temperatures close to the melting point of silica.\nOur study is inspired by that work. We found that the incorporation\nof zinc NP on the GS surface led to superhydrophobicity, once it was\nfurther coated with a thin fluoropolymer layer. We followed\ntwo different routes to create direct surface roughness:\n(a) sandblasting followed by the sintering process of zinc NPs and\n(b) direct sintering on the GS surface. Sintering was used since,\nin a previous study, 12 we found that this\nroughening method was determining to produce SH samples on GS. The\nfabricated samples are robust, as revealed by several durability tests\nconducted on them. These tests are presented in a separate section\nwithin the Supporting Information .",
"discussion": "3 Results and Discussion 3.1 Effect of the Heating Treatment The\nheating treatment was used to incorporate zinc NPs onto the GS by\nsintering. However, in preliminary experiments, we observed that this\nprocess (without any particle deposition) induced changes in the surface\ntexture of GS. For this reason, we first investigated the role of\nthe heating treatment in the final surface roughness and wettability\nof the surfaces (once they were hydrophobized). With this analysis,\nwe validated if the heating itself was able to reach the surface texture\nthat is required to produce SH surfaces on GS. We prepared 10\ndifferent GS samples by heating for 5 min the previously cleaned as-received\nsamples at temperatures ranging from 350 to 600 °C. Once the\nsamples were cooled down, they were hydrophobized. For comparison,\nwe included in the same graph the results that were obtained for an\nuntreated (not heated) but hydrophobized sample. We focused on the\nRa values and compared them with the CTA values obtained for each\ntemperature. Results are plotted in Figure 2 . Figure 2 Critical tilting angle and average roughness\nfactor (Ra) in terms\nof the heating temperature. In this graph, we also included the results\nfor the unheated sample for comparison. Lines are guides to the eye. Above a certain temperature value, close to the\nzinc melting point\n(around 415 °C), the heating process was able to increase the\nsurface roughness. A more detailed analysis of the surface structure\ninduced by heating will be discussed below. When the heat treatment\nis conducted at temperatures lower than 400 °C, no significant\nchanges in the surface structure and wettability properties of the\nsamples are observed. However, above 450 °C, we did not notice\nany clear dependence of temperature on the final roughness. This was\nalso found with the wetting results. Besides, above a certain temperature,\nthe critical tilting angle was higher than the one measured for the\nsmooth (unheated) samples. This reveals that the heating process,\neven though it increased the surface roughness, was still unable to\ncreate the specific surface structure, leading to superhydrophobicity.\nSimilar conclusions related to sandblasting were drawn in a previous\nwork; 12 in Figure 3 , we show images of the surface structure\nanalyzed by ESEM at two different scales. We also plot the surface\ntopographies captured by confocal microscopy. The structure of an\nuntreated sample ( Figure 3 a) is very different from that of a heated (at 420 °C)\nsurface ( Figure 3 b).\nThe influence of the thermal treatment on the roughness and surface\nmorphology of the GS samples is noticeable, as discussed above. Figure 3 SEM images\n(left) and confocal topographies (right) obtained for\n(a) untreated sample and (b) heated sample at 420 °C. A proper sintering process requires the use of\nsintering temperatures\nvery close to the melting point of the NP material. According to the\nresults of the study reported in this section, we fixed the sintering\ntemperature to 420 °C. Higher temperatures did not influence\nthe final roughness of the samples. As reported in similar studies\naimed at producing SH surfaces by sintering NPs, 16 temperatures higher than the melting point of the material\nmay induce a total melt of the NP, which might reduce the surface\nroughness at the nanoscale. 3.2 Effect of the Sintering Process In\nthis section, we explored the wettability properties of all the samples\nproduced by sintering Zn NPs. The analysis was conducted for two set\nof samples: smooth and sandblasted samples. As discussed above, sandblasting\nand thermal heating, despite being able to change noticeably the surface\nroughness and wetting properties of the GS samples, were insufficient\nto generate the specific texture that is required for superhydrophobicity.\nThe samples used in this work were all hydrophobized. This further\nfunctionalization is mandatory because the sintered samples were extremely\nwettable. The goal of the study presented in this section is to find\nthe optimal particle concentration needed to enhance the water repellency\nfor each type of treatment. For this purpose, we used different colloidal\nsuspensions of Zn NPs at concentrations varied up to 10 g/L. We explored\nthe degree of superhydrophobicity using tilting plate experiments\nand bouncing drop experiments. The use of both techniques was aimed\nat characterizing both the shear and tensile drop adhesion. In Figure 4 a, we show the results\nfor those samples that were previously sandblasted, while in Figure 4 b, we show the results\nfor the smooth samples. Figure 4 Wetting properties of the modified GS surfaces\nused in this work,\ncharacterized by bouncing drop (squares) and tilting plate experiments\n(circles). (a) results for the sandblasted + sintered GS samples and\n(b) smooth + sintered GS samples. The results are shown in terms of\nthe nanoparticle (NP) concentration of the 5 mL solution used to cover\nthe surface prior to heating it. Dash lines are guides to the eye. Comparing Figure 4 a with Figure 4 b,\nwe concluded that the sandblasting promotes the water repellency since,\nfor the entire range of NP concentration, the critical tilting angle\nwas always lower than 10°. However, for the smooth samples (no\nprevious sandblasting), the critical tilting angle may reach values\nhigher than 20° for some particle concentrations. In contrast,\nthe best results, in terms of superhydrophobicity for all the prepared\nsamples, were found for the sintered smooth sample using a solution\nof zinc nanopowder at 1 g/L. This was confirmed by the high number\nof bounces (26 ± 2) and the low critical tilting angle (0.6 ±\n0.3°). The sintered sandblasted sample that showed the best performance\nwas fabricated using a concentration of zinc nanopowder of 2 g/L.\nIn this case, the measured number of bounces was 23 ± 2 and the\ncritical tilting angle was 0.6 ± 0.5°. The differences are\nnot significant, and both samples revealed excellent water repellency\nproperties. To confirm their superhydrophobicity, the wettability\nof these two selected samples was also analyzed by drop shape analysis\n(ADSA-P) with growing-shrinking experiments. These experiments provide\nthe contact angle values collected in Table 1 . Table 1 ACA, RCA, Critical Tilting Angle,\nand Number of Bounces Measured for the Samples That Revealed the Best\nResults in Terms of Water Repellency among All the Samples Analyzed\nUsing Each Procedure sample ACA (°) RCA\n(°) critical tilting angle (°) # bounces sandblasting + sintering NPs (2 g/L) 158 ± 3 154 ± 2 0.6 ± 0.5 23 ± 2 sintering NPs (1 g/L) 164 ± 2 161 ± 2 0.6 ± 0.3 26 ± 2 We found that the range of optimal nanopowder concentration\nis\nshorter for the smooth surfaces than for the sandblasted ones, but\nsandblasting is not essential to reproduce water-repellent properties. It is worth mentioning that the surface roughness at the microscale\nwas not much influenced by the particle concentration. In Table 2 , we show the Ra values\nfor the most representative samples of this study. In this table,\nwe also included the measured Ra values for nonheated samples as well\nfor comparison. Our first conclusion is that the thermal heating increases\nthe roughness, regardless of the Zn NPs. As illustrated in the previous\nsection, this increase is especially clear for smooth samples since\nthe roughness increased by a factor of 5 after heating the sample.\nConcerning the role of NP concentration, we observed that for low\nconcentrations, the roughness scales with the NP concentration, but\nit decreases again at high concentration values. This might be expected\nsince the addition of a roughening agent does not always lead to higher\nroughness. 18 Above a certain degree of\nroughness, a roughening agent may no longer be considered as such.\nSimilar conclusions were drawn in our previous work related to the\netching time used to create nanoasperities: at short acid exposure,\nthe roughness increased with etching time, but the opposite trend\nwas observed for longer acid etching. 12 , 18 Table 2 Average Roughness Values (Ra) for\nthe Most Representative Samples Used in This Work sandblasted samples smooth samples nanopowder concentration Ra (μm) Ra (μm) 0 g/L (not heated) 5.3 ± 0.3 0.69 ± 0.11 0 g/L 8.9 ± 1.3 3.3 ± 0.3 1 g/L 10.2 ± 1.2 3.6 ± 0.4 2 g/L 9.1 ± 1.1 2.9 ± 0.2 5 g/L 4.4 ± 0.4 4.5 ± 0.3 3.3 Surface Morphology and Chemical Composition The morphology of the samples was studied by ESEM. The goal is\nto analyze the micro-/nanostructure incorporated on the GS surfaces\nafter roughening with the most efficient treatments. In Figure 5 , the ESEM images of four representative\nsamples are shown: (a) A smooth sample (untreated), (b) a smooth sample\nfurther heated to sinter Zn NPs (1 g/L colloidal suspension), (c)\na sandblasted sample, and (d) a previously sandblasted sample treated\nby sintering Zn NPs on it (2 g/L colloidal suspension). The effect\nof surface heating on GS was analyzed in detail in Section 3.1 . In Figure 5 , it is clear how the heating and sintering\nprocesses incorporate a hierarchical structure based on micro- and\nnanosized defects. These structures validate the excellent water repellency\nproperties of the samples referred to in Table 1 . Figure 5 ESEM images of four representative samples:\n(a) untreated sample,\n(b) a smooth surface that was subsequently sintered, prior deposition\nof a 1 g/L solution of zinc NPs, (c) a sandblasted surface, and (d)\nsandblasted + sintered surface, prior deposition of a 2 g/L solution\nof zinc NPs. The samples in (b,d) were those that showed the best\nresults in terms of water repellency. The next step was to study how each surface roughening\nmethod affected\nthe chemical composition. The analysis was conducted through a chemical\nmapping focused on the presence of three different elements dominant\non the GS surfaces: Fe, Al, and Zn. This analysis points out to the\ndamage that each surface treatment caused on the samples. In Figure 6 , we show the chemical\nmappings of the same samples used in Figure 5 . The smooth (untreated) sample reveals a\nvery homogenous distribution of the three elements. The lower contrast\nobserved for the untreated sample may be explained in terms of a lower\nsurface roughness since the picture is a superposition of the ESEM\nimage and the chemical mapping. A very similar elemental chemical\ndistribution was observed for the smooth + sintered sample ( Figure 6 b). Here, the blue\nsignal is more pronounced due to a higher Zn concentration. This is\nexpected due to the presence of sintered nanopowder. Otherwise, the\nhomogeneous chemical distribution was no longer observed for the rest\nof the samples in Figure 6 . The inhomogeneity is particularly relevant to the sandblasted\nsample ( Figure 6 c).\nSome microsized corundum alumina particles embedded in the sample\nare clearly distinguishable. These particles are surrounded by material\nrich in iron (confirmed by a red corona around the particle). This\nis an indication of a possible removal of the native Zn coating caused\nby the particle impact. Once the sample is subjected to the sintering\ntreatment ( Figure 6 d), the chemical homogeneity is partially restored. However, we can\nstill observe the presence of alumina particles and a higher presence\nof iron on the surface if we compare it with the untreated GS ( Figure 6 a) or the smooth\n+ sintered surface ( Figure 6 b). These results indicate that sandblasting does not ensure\nthat GS surfaces remain unaltered. Surface texturization by single\nsintering (without any prior sandblasting) is the most convenient\nstrategy because it is equally effective in terms of wetting response\nbut less harmful than combining it with sandblasting. The chemical\ncomposition of the studied samples was further analyzed by XPS, comparing\nit with an untreated GS surface. The aim is to demonstrate that the\nstructured sample maintains a very similar composition to the original\none. In particular, the presence of Fe on both the untreated and smooth\n+ sintered samples is negligible, which suggests that the protective\nzinc layer remains unaltered in both cases. The results are shown\nin the Supporting Information (see Supporting\nInformation for more details). Figure 6 Mapping obtained by ESEM-EDX: (a) an untreated\nsample, (b) a smooth\n+ sintered sample, (c) a sandblasted sample, and (d) a sandblasted\n+ sintered sample. The green signal corresponds to Al, the red signal\nto Fe, and the blue signal to Zn. In this work, we showed two different routes to\nfabricate water-repellent\nsurfaces on GS. Both routes are focused on the incorporation of double-scale\nroughness and a further hydrophilization by fluoropolymer deposition.\nThe difference between both strategies was the treatment used to create\nroughness on the surface: the first one consisted of a combination\nof sandblasting + sintering Zn NPs, while the second one was only\nbased on sintering Zn NPs. Although we observed that the heating during\nthe sintering process modified the surface roughness (higher roughness\nparameter and greater drop adhesion), the incorporation of the nanopowder\nwas essential. Unlike our previous study with similar purposes, 12 here, we concluded that sandblasting is unnecessary,\nalthough it allows us to find the experimental conditions that ensures\nwater repellency. In contrast, no sintering is needed because both\nthe sandblasting and the thermal heating by themselves, were not able\nto create the proper surface texture. Besides, we also observed that\nsandblasting was harmful when the chemical composition of the surface\nwas analyzed in detail. The thermal heating was less aggressive and\nled to the same degree of water repellency. On the other hand, NP\nsintering is postulated as a nonaggressive bottom-up approach to fabricating\nSH surfaces on GS."
} | 5,542 |
22134863 | null | s2 | 4,057 | {
"abstract": "Episodic resource inputs (i.e., pulses) can affect food web properties and community dynamics, but detailed mechanistic understanding of such effects remain elusive. Natural aquatic microsystems (e.g., tree holes, human-made containers) are colonized by invertebrates that form complex food webs dependent on episodic and sometimes sizeable inputs of allochthonous detritus from adjacent terrestrial environments. We investigated how variation in pulse frequency, amount, and resource type interacted to affect richness, abundance, composition, and population sizes of colonizing invertebrates in water-filled tires and tree hole analogs in a forest habitat. Different container types were used to assess the generality of effects across two environmental contexts. Containers received large infrequent or small frequent pulses of animal or leaf detritus of different cumulative amounts distributed over the same period. Invertebrates were sampled in June and September when cumulative detritus input was equal for the two pulse frequencies. Pulse frequency and detritus type interacted to affect the responses of richness and abundance in both months; pulse frequency alone in June affected the relationship between richness and abundance. Richness and abundance were also greater with more detritus regardless of detritus type. One group, the filter feeders, were most important in driving the response of abundance and richness to pulses, especially in June. This work highlights the potential complex nature of responses of communities and populations to resource pulses and implicates the ability of certain groups to exploit pulses of detrital resources as a key to understanding community-level responses to pulses."
} | 430 |
38485722 | PMC10940724 | pmc | 4,058 | {
"abstract": "The ability to scale two-dimensional (2D) material thickness down to a single monolayer presents a promising opportunity to realize high-speed energy-efficient memristors. Here, we report an ultra-fast memristor fabricated using atomically thin sheets of 2D hexagonal Boron Nitride, exhibiting the shortest observed switching speed (120 ps) among 2D memristors and low switching energy (2pJ). Furthermore, we study the switching dynamics of these memristors using ultra-short (120ps-3ns) voltage pulses, a frequency range that is highly relevant in the context of modern complementary metal oxide semiconductor (CMOS) circuits. We employ statistical analysis of transient characteristics to gain insights into the memristor switching mechanism. Cycling endurance data confirms the ultra-fast switching capability of these memristors, making them attractive for next generation computing, storage, and Radio-Frequency (RF) circuit applications.",
"introduction": "Introduction In today’s digital era, the role of memory technology has become integral, particularly in the context of artificial intelligence (AI) applications. Several AI tasks, such as classification, recognition, natural language processing, prediction etc., heavily rely on large-scale memory storage and processing capability of the underlying hardware 1 – 3 . Conventional memory technologies like Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM) are energy-inefficient for implementing these data-intensive applications due to their volatile nature, resulting in dynamic as well as static power dissipation. These energy requirements are even more stringent for battery-operated mobile, wearable electronics, and Internet of Things (IoT) edge devices 4 , 5 . Although flash memory is non-volatile, the slow programming speed (>10us) makes it impractical for these applications 6 , 7 . To effectively harness and maximize the potential of AI and other emerging applications, an ultra-fast non-volatile memory is necessary. Memristors are promising devices in the emerging non-volatile memory landscape that have shown great potential owing to their small footprint (4F 2 ), fast operation, and low power consumption 8 – 13 . Several studies explored the use case of memristors for storage, memory-centric computing 14 – 17 , and high-frequency RF applications 18 – 20 . In the past decade, memristors fabricated using a variety of materials such as Transition Metal Oxides (TMO) 21 – 24 , chalcogenides 25 , 26 , and organic materials 27 – 29 have been extensively studied. TEM studies have conclusively established that the resistive switching in memristors can be attributed to the presence of conductive nanofilaments 30 , 31 . Based on the experimental observations, the switching dynamics in memristors have been captured using different modeling techniques 32 – 34 . The commercially available memristors typically switch in ~50 ns–100 μs range, making them slower than state-of-the-art DRAM 35 – 37 . Although a few studies have reported faster-switching memristors ( T SWITCH < 5 ns) 38 – 47 , the fast-switching dynamics have not been thoroughly studied. Here, we present an ultra-fast memristor fabricated using a two-dimensional (2D) material, i.e., hexagonal Boron Nitride (hBN) as the switching layer 48 – 50 . The atomically thin nature of the 2D material facilitates rapid filament dynamics enabling an ultra-fast and energy-efficient memristor. We study these memristors using ultra-short pulses ( T PULSE < 2.7 ns) in a custom-built RF test setup. Moreover, since the filament formation/dissolution in memristors is a stochastic process 51 – 53 , we employ statistical analysis of the transient switching characteristics to study these memristors. Statistical data provided critical insights into the switching mechanism and the inherent stochasticity of the filament dynamics. To the best of our knowledge, this is the first study of this kind not just in 2D memristors but among the plethora of scientific reports based on TMO memristors. In addition, by leveraging cues from statistical data, we model the fast-switching dynamics using a combination of finite element-based physics solver, empirical, and analytical equations.",
"discussion": "Discussion In summary, we fabricated Ti/hBN/Au memristors that exhibit ultra-fast switching characteristics when characterized using short voltage pulses ( T PULSE < 3 ns). Unlike other ultra-fast memristors, our devices with thicker hBN (7–8 layers) exhibit high cycling endurance (~600 cycles) using short 2.7 ns voltage pulses with a mean switching time of 1.43 ns. On the other hand, thin hBN (3–4 layers) devices switch under ultra-short pulses of 120 ps, which is the fastest reported switching speed among 2D material-based memristors. Finite-element-analysis-based thermal simulations provided key insights which help explain the fundamental reason responsible for the observed ultra-fast switching in 2D memristors. Statistical data collected from several devices revealed useful correlations between switching time-resistance ratio and switching energy-resistance ratio, providing a practical knob to tune device characteristics. Furthermore, the unique experimental methodology employed in this work allowed us to study the dynamic evolution of resistance (during the pulse) as well as the change in resistance (before and after the pulse). To the best of our knowledge, this is the first instance where such an approach has been adopted. Correlating these data points revealed a significant presence of joule heating-induced filament narrowing in our devices. The impact of Joule heating on filament stability was studied using a combination of statistical analysis, retention testing, and electrothermal simulations. Moreover, an electro-thermal model was developed which accurately captures the transient switching characteristics including secondary effects such as Joule heating. Overall, this study unveils the true potential of 2D material memristors for future high-speed computing, storage, and RF applications."
} | 1,513 |
35138660 | PMC9307002 | pmc | 4,060 | {
"abstract": "Abstract Carboxyl methyltransferase (CMT) enzymes catalyse the biomethylation of carboxylic acids under aqueous conditions and have potential for use in synthetic enzyme cascades. Herein we report that the enzyme FtpM from Aspergillus fumigatus can methylate a broad range of aromatic mono‐ and dicarboxylic acids in good to excellent conversions. The enzyme shows high regioselectivity on its natural substrate fumaryl‐ l ‐tyrosine, trans , trans ‐muconic acid and a number of the dicarboxylic acids tested. Dicarboxylic acids are generally better substrates than monocarboxylic acids, although some substituents are able to compensate for the absence of a second acid group. For dicarboxylic acids, the second methylation shows strong pH dependency with an optimum at pH 5.5–6. Potential for application in industrial biotechnology was demonstrated in a cascade for the production of a bioplastics precursor (FDME) from bioderived 5‐hydroxymethylfurfural (HMF).",
"conclusion": "Conclusion In conclusion we have shown that FtpM is a promising carboxyl methyltransferase with the greatest substrate range reported to date for any CMT. FtpM was able to catalyse the formation of diesters and regioselective formation of monoesters from diacids. It also showed substrate specificity with a range of substituted benzoic acids. Our substrate survey suggests that aromatic acids are preferred over aliphatic, and this may reflect a requirement for conjugated carboxylate groups, as shown with trans,trans ‐muconic acid. An AlphFold2 model shows strongly electropositive characteristics in the active site, in good agreement with the preference for diacids over monoesters. The enzyme shows great promise for application in synthetic multienzyme cascades in industrial biotechnology as demonstrated by the one‐pot HMF to FDME conversion. As with most methyltransferases FtpM has relatively low activity. We therefore used a relatively high enzyme loading in order to observe dimethylation. Current work is focused on creating mutants with improved kinetics for both mono‐ and dimethylation guided by the AlphaFold 2 model and further structural studies.",
"introduction": "Introduction With increases in population growth and energy use there are compelling reasons to develop sustainable solutions to chemical synthesis and biofuels. This presents significant challenges and opportunities for industrial biotechnology to find alternatives to the use of petrochemicals as feedstocks. New approaches need to provide alternatives to conventional chemical process that are scalable. Methylation of carboxylic acids is a simple but important reaction and is used for activation of carboxylic acids or as the final synthetic step. Simple acids can be esterified under the classical conditions (MeOH, H + , heat) or by prior activation as the acid chloride/anhydride, in which case the acid needs to be pre‐dried. Other methylation methods utilise diazomethane, dimethyl sulphate or methyl iodide but carry significant safety risks. Methyltransferase enzymes (MTs) have long been known to catalyse the methylation of heteroatoms such as N, C, S, O, Se, As or halide atoms. The majority of these enzymes use the cofactor S ‐adenosyl methionine (SAM) as a methyl donor and catalyse the methyl transfer to substrates such as proteins, nucleic acids and small organic molecules. Several reviews have summarised recent advances in the use of MT enzymes, their substrate specificity, use of alternative cofactor analogues and application in biotechnology.[ \n 1 \n , \n 2 \n , \n 3 \n , \n 4 \n ] One of the attractive features of enzymatic methylation is the ability to carry out the reactions in aqueous solution, thus making methylation compatible with other enzymatic processes. We became interested in an unexploited sub‐group of enzymes known as carboxyl methyltransferases (CMTs) that transfer a methyl group from SAM to carboxylic acids. \n [3] \n Many bioprocesses that produce carboxylic acids require addition of stoichiometric base to maintain neutral pH for optimal activity of the whole‐cell biocatalyst or enzyme. \n [5] \n In situ enzymatic methylation of the acid would remove this requirement and lower the environmental impact of bioprocesses. This would facilitate product recovery or allow coupling with additional enzymes for multistep synthesis. For example, acyltransferases have recently been used to catalyse acyl transfer from methyl esters to amines in buffer where there is a kinetic preference for acyl transfer over hydrolysis.[ \n 6 \n , \n 7 \n , \n 8 \n ] The ability to methylate carboxylic acids in situ would therefore enable one‐pot conversion of acids into amides. This approach compares favourably with methods that involve use of expensive coupling reagents or existing enzymes that require ATP activation of the carboxylic acid by the enzymes. \n [9] \n \n Many of the small molecule CMTs studied to date are involved in plant secondary metabolism, for example in the generation of volatile esters as plant chemo‐attractants.[ \n 10 \n , \n 11 \n ] The best studied group of enzymes was named SABATH, named after their ability to methylate salicylic acid, benzoic acid and theobromine, among other substrates. \n [12] \n The activities of these and MT enzymes are generally quite low ( K \n cat <1 s −1 ) and have a limited substrate range.[ \n 13 \n , \n 14 \n , \n 15 \n ] Other CMT enzymes work on more complex substrates such as gibberellic acid and loganic acid (a key intermediate for indole alkaloids such as vincristine), terpenes and fatty acids.[ \n 16 \n , \n 17 \n , \n 18 \n , \n 19 \n ] We started our search for a CMT that could catalyse dimethylation since we have an interest in activating and reacting 2,5‐furandicarboxylic acid (FDCA) 2 , which we made using an enzyme cascade starting from bioderived 5‐hydroxymethylfufural (HMF) 1 .[ \n 20 \n , \n 21 \n ] Dimethylation of FDCA to make the dimethyl ester FDME 3 would allow in situ conversion to higher order bioplastics precursors such as BisBDO diester 4 , as we have previously demonstrated using the plastic degrading enzyme PETase (Scheme 1 ). \n [22] \n \n Scheme 1 The development of a CMT for dimethylation of bioderived FDCA 2 would allow an enzymatic cascade under aqueous conditions from HMF 1 to bioplastics precursor 4 . The enzyme known as FtpM is a CMT from Aspergillus fumigatus and was reported to dimethylate fumaryl‐ l ‐tyrosine 5 (Scheme 2 ) and also fumaryl‐ l ‐phenylalanine as part of the aromatic fumaric amide biosynthesis pathway. \n [23] \n This is a unique enzyme in that it is able to iteratively methylate both carboxylic acid groups of the substrate. Here we show that FtpM can di‐ and monomethylate a wide range of aromatic dicarboxylic acids, benzoic acids and acyclic acids. The enzyme also demonstrates regioselectivity, allowing for selective monoesterification. FtpM is the first example of a CMT that shows excellent potential for application in industrial biotechnology and for use in combination with other enzymes in cascade sequences. Scheme 2 Conversion of the natural substrate 5 and synthetic monoesters 6 and 7 by FtpM. Reactions consisted of substrate (1 mM), FtpM (500 μM), SAM (2 mM) and SAH‐nucleosidase (4 μM) in 50 mM MES buffer (pH 6) shaken for 16 h at 25 °C. Products were detected by RP‐HPLC and confirmed using authentic standards (see Supporting Information).",
"discussion": "Results and Discussion Our attempts to express the previously reported N‐terminal His‐tagged FtpM resulted in a truncated form of the enzyme in addition to the full‐length protein. We cloned the gene (UniProt accession number Q4WZ45) into a C‐terminal His‐tagged vector (see Supporting Informtion) and found that FtpM expressed well and had greater activity on several of our test substrates. We determined optimum conditions for FtpM production and were able to isolate >60 mg L −1 of recombinant protein (see Supporting Informtion). With access to reasonable quantities of the C‐terminally His‐tagged FtpM enzyme we were able to explore reaction conditions and the substrate specificity of this enzyme. For the natural substrate 5 we observed only monomethylation, exclusively forming the monoester 6 (Scheme 2 ). This is in contrast to the previously reported exclusive dimethylation, with no observation of any monoester as an intermediate. \n [23] \n In order to confirm the identity of 6 , we synthesised both monoesters 6 and 7 (see Supporting Information) and monoester 6 was identical by HPLC to the biotransformation product. We then tested both monoesters as enzyme substrates under the same reaction conditions. Interestingly, the tyrosyl ester 7 was converted to the diester 8 , whereas the fumaryl ester 6 gave only a trace of diester (1 %). These results show that with the C‐terminally His‐tagged FtpM, the enzyme is unable to access the tyrosyl group for methylation and thus dimethylation of this substrate would not be possible. This was confirmed by a time course reaction for 5 in which no diester was detected at any stage in the reaction (Figure S12). We used an AlphaFold 2 \n [25] \n model of the FtpM dimer in order to visualize the locations of the protein termini and consider possible implications of alternative His‐tag locations (Figures S10 and S11). The pTM score of the top‐ranking model as 0.89 strongly suggests a confident prediction. \n [25] \n In the model both termini are fully solvent‐exposed and distant to the predicted interface suggesting that the position of the His‐tag should not impact dimerisation so that a structural explanation for the differences in activity on the natural substrate 5 for differently tagged proteins remains elusive. However, the Webina docking of the natural substrate 5 revealed the likely basis for the selectivity for the fumaryl over the tyrosyl carboxylate (Figure 1 ). The second ranked pose for 5 places the fumaryl carboxylate close (3.0 Å) to the methyl group of the SAM cofactor (Figure 1 ). The top‐ranked pose (scoring slightly better: predicted affinity −7.1 kcal mol −1 vs. −7.0 kcal mol −1 for the productive pose) places neither carboxylate suitably for reaction and in none of the Webina poses is the tyrosyl carboxylate closer than 5 Å to the SAM cofactor.\n Figure 1 Docking of the natural substrate 5 into the FtpM AlphaFold 2 monomer model. The top‐ranked (yellow carbon) and second‐placed (white carbon) poses are shown as sticks. The protein is shown as purple ribbon and surface coloured according to the APBS \n [24] \n electrostatic calculations (blue positive, red negative; see scale). The unit of the scale is k \n B \n T / e \n c where k B \n is the Boltzmann constant, T is the temperature, and e \n c is the charge of the electron. In contrast to the natural substrate, we were pleased to find that the new substrates FDCA 2 and terephthalic acid (TA) 9 both afforded mono‐ and diester products (Figure 2 ). Whilst monomethylation could be achieved with 10 μM or 100 μM final enzyme concentration, it was observed that dimethylation required higher amounts of enzyme, so 500 μM was used in subsequent reactions (Table S3). The dimethylation of FDCA 2 and TA 9 showed a pronounced pH dependence with pH 6 being optimum (Figure 2 A and B). FDCA 2 gave 46 % of the dimethyl ester FDME 3 and 53 % monoester 10 whilst TA 9 gave 36 % diester DMT 12 and 63 % monoester 11 (see Table 1 ). The effect of temperature was also assessed, and conversions showed little variation between 25 and 37 °C, although the second methylation of FDCA was notably slower at 20 °C (Figure S13). The pH dependence of methylating the monoesters 10 and 11 was also assessed and conversions to the diesters were much higher at pH 5.5 and 6 (Figure S14A and B).\n Figure 2 pH Dependence of methylation and dimethylation of A) FDCA 2 ; B) TA 9 , 50 mM MES Buffer (pH 5.5–6.5), 100 mM KPi Buffer (pH 7). C), D) Time course reaction for methylation of FDCA 2 (C) and TA 9 (D) with FtpM. Reaction conditions as for Scheme 2 but duration shortened to 8 h for ( C) and (D). Red: diacid; blue: monoester; green: diester. Table 1 Diacid substrates for FtpM. Reaction conditions as for Scheme 2 . Products were detected by RP‐HPLC and confirmed using authentic standards or LC‐MS (see Supporting Information). \n Diacid substrate \n \n Diacid [%] \n \n Monomethyl ester [% conv.] \n \n Dimethyl ester [% conv.] \n \n \n 2 \n \n \n \n \n \n \n \n 2 (1) \n \n \n 10 ( 53) \n \n \n 3 (46) \n \n \n \n \n \n \n \n \n \n \n \n \n 9 \n \n \n \n \n \n \n \n 9 (0) \n \n \n 11 (63) \n \n \n 12 (36) \n \n \n \n \n \n \n \n \n \n \n \n \n 13 \n \n \n \n \n \n \n \n 13 (2) \n \n \n 14 (94) \n \n \n 15 (4) \n \n \n \n \n \n \n \n \n \n \n \n \n 16 \n \n \n \n \n \n \n \n 16 (0) \n \n 2‐Me ester 17 (17) 5‐Me ester 18 (65) \n \n \n 19 (17) \n \n \n \n \n \n \n \n \n \n \n \n \n 20 \n \n \n \n \n \n \n \n 20 (0) \n \n 1‐Me ester 21 (9) 4‐Me ester 22 (69) \n \n \n 23 (22) \n \n \n \n \n \n \n \n \n \n \n \n \n 24 \n \n \n \n \n \n \n \n 24 (0) \n \n 1‐Me ester 25 (5) 4‐Me ester 26 (95) \n \n (0) \n \n \n \n \n \n \n \n \n \n \n \n \n 27 \n \n \n \n \n \n \n \n 27 (0) \n \n 4‐Me ester 28 (100) \n \n (0) \n \n \n \n \n \n \n \n \n \n \n \n \n 29 \n \n \n \n \n \n \n \n 29 (22) \n \n \n 30 (78) \n \n (0) \n \n \n \n \n \n \n \n \n \n \n \n \n 31 \n \n \n \n \n \n \n \n 31 (27) \n \n 1‐Me ester 32 (73) \n \n (0) \n \n \n \n \n \n \n \n \n \n \n \n \n 33 \n \n \n \n \n \n \n \n 33 (0) \n \n \n 34 (45) \n \n \n 35 (55) \n \n \n \n \n \n \n \n \n \n \n \n \n 36 \n \n \n \n \n \n \n \n 36 (2) \n \n \n 37 (75) \n \n \n 38 (23) \n \n \n \n \n \n \n \n \n \n \n \n \n 39 \n \n \n \n \n \n \n \n 39 (36) \n \n \n 40 (64) \n \n (0) \n Wiley‐VCH GmbH FDME stability was investigated at pH 6, 25 °C to confirm that the presence of the monomethyl ester 10 was not a result of FDME hydrolysis and after 16 h only a small percentage of monoester 10 (5 %) was present. Therefore pH 6 and 25 °C were chosen for all remaining reactions. The increased conversion to the dimethyl ester products when starting from FDCA and TA at pH 6 vs. 7 may not necessarily be as a result of increased enzyme activity, but due to the increase in stability of SAM. SAM is most stable in the pH range 3.5–5.5 and also at lower temperatures. \n [26] \n At pH 5.5, the conversion to the diesters from both TA and FDCA was lower than that at pH 6, despite the expected increased stability of SAM and the higher conversion to diesters when starting with the monoesters. Thus, pH 6 is potentially a compromise between methyl donor stability and FtpM activity for iterative double methylation, where two equivalents of SAM are required and SAM needs to remain stable for the duration of the reaction. \n [27] \n The initial monomethylation activity may have a broader optimum pH range that allows a high monomethylation activity between pH 5.5 and 7. It may also be that the required optimum protonation state of the key catalytic residues of FtpM is different for the monomethylated ester and the diacid substrates. In addition to the AlphaFold 2 model, a crystal structure of FtpM with and without substrates/products would aid further understanding and improvement of activity by mutagenesis. A time course for FDCA 2 showed fast conversion to the monoester 10 , followed by much slower conversion to FDME 3 (Figure 2 C). TA 9 showed a very rapid conversion to the monoester 11 , followed by slow conversion to DMT 12 (Figure 2 D). However, in the case of TA 9 , no DMT 12 formation was observed until all of the TA had been consumed, suggesting a large kinetic preference for the diacid over the monoester 11 . Kinetic parameters for TA 9 were k \n cat =0.89 min −1 , K \n m =0.072 mM ( k \n cat / K \n m =12.3 mM −1 min −1 ) (Table S4) which is commensurate with some other CMT enzymes (Table S5), also known to have low k \n cat values, although the K \n m value for TA with FtpM appears to show comparatively good affinity. The values for FDCA 2 were K \n cat =0.02 min −1 and K \n m =0.52 mM ( k \n cat / K \n m =0.04 mM −1 min −1 ). Catalytic efficiencies for the corresponding monoesters 10 ( k \n cat / K \n m =0.004 mM −1 min −1 ) and 11 ( k \n cat / K \n m =0.003 mM −1 min −1 ) were much lower, as expected. Interestingly the kinetics for the natural substrate 5 ( k \n cat / K \n m =0.093 mM −1 min −1 ) were less efficient than for TA 9 . We used our AlphaFold 2 model of FtpM in conjunction with Webina \n [24] \n docking in order to seek a structural explanation for the kinetic data. Pleasingly, with each of the substrates FDCA 2 and TA 9 the top‐ranked pose placed one of the carboxylate groups ideally for methyl transfer (Figure 3 ). The distance from the closer carboxylate group to the methyl group of SAM is 2.9 Å and the proper positioning is ensured by a hydrogen bond to Gln31 and an electrostatic interaction with Arg27. The substrate binding pocket as a whole bears strongly positive electrostatic characteristics in good agreement with the observed preference for diacids over monoesters.\n Figure 3 Top‐ranked poses for FDCA 2 (sticks;white carbon) and TA 9 (pink carbon) in the FtpM AlphaFold 2 monomer model. The protein is shown as purple ribbon and surface coloured according to the APBS 24 electrostatic calculations (blue positive, red negative; see scale). The unit of the scale is k \n B \n T / e \n c where k \n B is the Boltzmann constant, T is the temperature, and e c \n is the charge of the electron. Also shown are interactions with Arg27 and Gln31 that position the reactive carboxylic acid group (yellow dashes) and Arg residues numbered 166, 192 and 274 which define the strong positive charge on the substrate binding pocket. Encouraged by the results we explored several substrates related to the natural substrate and then a series of aromatic diacids (Table 1 ). Trans,trans ‐muconic acid 13 resembles the left (fumaryl) side of the natural substrates 5 and also (after rotation around the central bond) represents a fragment of TA 9 . \n Cis,cis‐ muconic acid can be produced by fermentation in engineered E. coli \n \n [28] \n and other microbial strains and can be readily isomerized to the trans,trans ‐isomer 13 . \n [29] \n We were intrigued to find that 13 was an excellent substrate for mono‐methylation giving high conversion to 14 (94 %), with a trace of the dimethylation product 15 . In contrast, N ‐acetyl l ‐phenylalanine, which resembles the right‐hand portion of 5 , was not a substrate. This result fits with the lack of reactivity for the tyrosyl carboxylate found for the natural substrate 5 . 2,5‐Pyridine dicarboxylic acid 16 can be produced from lignin biomass using engineered whole cells of Rhodococcus jostii RHA1 and simple esters have been used as bioplastic precursors.[ \n 30 \n , \n 31 \n , \n 32 \n ] The ability to esterify this substrate would activate it for polymerization, in a similar manner to FDCA. Both monoester isomers 17 and 18 and the diester 19 were obtained with the 5‐monoester 18 predominating. Separate incubations with the monoester substrates 17 and 18 confirmed a clear preference for esterification of the 5‐carboxylate in the 2‐Me ester 17 to give diester 19 in 75 %, whereas as the 5‐Me ester 18 ester gave only 10 % conversion to 19 . A similar regioselectivity was observed for 2‐aminoterephthalic acid 20 which gave ester 22 , resulting from a preference for the less hindered acid. The regioselectivity was much more pronounced for 2‐nitroterephthalate 24 and 2‐hydroxyterephthalate 27 that were monomethylated regiospecifically or with very high selectivity in the 4‐position. In all these cases, complete conversion of starting material was observed, suggesting that the SAM cofactor may have been limiting where mixtures of mono‐ and diesters were obtained. 2,5‐Dihydroxyterephthalate 29 also gave exclusively the monomethyl ester 30 , with incomplete conversion of the starting diacid (22 %). Substrate 31 demonstrated the preference of FtpM for an aromatic acid forming exclusively the benzoate ester 32 . The ortho analogue of 31 and also 1,2‐ and 1,3‐phenylendiacetic acids were tested and found not to be substrates. As observed for terephthalic acid, isophthalic acid 33 gave a good conversion to both monoester 34 and diester 35 . However, phthalic acid was not a substrate. Introduction of a 5‐amino or 5‐nitro group into isophthalic acid in 36 and 39 slowed or stopped the second methylation reaction leading in the case of 39 exclusively to the monoester 40 . The ability to regioselectively monomethylate dicarboxylic acids is synthetically attractive. In addition, the nucleophilic amine groups in substrates 16, 20 and 36 notably remain unmethylated by the FtpM enzyme and so would not require protection as would be the case when using chemical methylating reagents. Given the unexpected regioselectivity observed with the natural substrate and some of the aromatic diacids, we then decided to assess a range of aromatic monocarboxylic acids (Figure 4 ). We were particularly interested in whether the enzyme requires a carboxylic acid group or acidic/polar group in the para/meta position as suggested by some of the previously tested substrates and non‐substrates (e.g. phthalic acid). 2‐ and 3‐substituted furoic acids were esterified although in lower conversions than for FDCA 2 and methyl benzoate was formed in lower conversion than the terephthalate esters 11 and 12 . This supports the previous findings that the second methylation of a diacid is slower and that although a second carboxylate group is not an absolute requirement for activity, diacids are better substrates. Interestingly, conversion of 3‐ and 4‐hydroxybenzoic acid to give esters 52 and 54 was much higher than for benzoic acid, suggesting that the presence of the acidic phenolic hydroxyl group may mimic a carboxylate group upon binding in the enzyme active site. Interestingly however, 2‐hydroxybenzoic acid (salicylic acid) was not a substrate and here an analogy can again be made with the corresponding phthalic acid, also a non‐substrate. Thus, FtpM provides a complementary enzyme to the previously studied salicylic acid methyltransferase (SAMT), which otherwise has a very limited substrate range. \n [33] \n The outcome for 2‐ versus 3‐hydroxybenzoic acids may be mapped on to the result for the 2‐hydroxy diacid 27 which was only esterified in the 4‐position, suggesting that a 3‐hydroxyl group is accepted but not a 2‐hydroxyl group. Substrate 29 however, further contradicts this in that both acid groups could be seen as having both a 2‐ and a 3‐hydroxyl substituent, although the overall conversion for 29 was lower than for 27 . Results for the methoxy‐substituted benzoic acids gave a slightly different pattern in that the 3‐methoxybenzoic acid was the preferred substrate, giving almost quantitative conversion to the ester 58 , although again the 2‐methoxy substrate was not methylated. Only the 4‐aminobenzoic acid gave appreciable conversion (43 %) but there was no activity for the 2‐amino analogue. Comparison of the outcome for 5‐amino isophthalic acid 36 which afforded monoester 37 (75 %) and diester 38 (23 %) with the 3‐amino benzoate ester 64 (8 %), shows that the second acid group in the diacid substrate 36 is more effective than the amino group in terms of activating the acid for esterification. Since the para diacid substitution appeared beneficial in terephthalic acid, we also tested two other types of carbonyl groups in the 4‐position, a ketone and an amide.\n Figure 4 Monoester products from monoacids catalysed by FtpM. Reaction conditions as for Scheme 2 . Products were detected by RP‐HPLC and confirmed using authentic standards or LC‐MS (see Supporting Information). Whilst the methyl ketone was a relatively poor substrate giving 68 (22 %), the amide was converted well to give 70 (65 %). Nitrobenzoic acids were also tested but gave low conversions (3‐nitro 16 % and 4‐nitro 5 %) and the 2‐nitro acid was not a substrate. The low conversion to 3‐nitro benzoate ester contrasts sharply with the result for 2‐nitroterephthalate 24 (95 % conversion to the 4‐monoester 26 ) and also 5‐nitroisophthalate 39 (64 % conv. to monoester 40 ), demonstrating the pronounced difference in activity with a second acid group present in the substrate. Finally, the hydroxypyridyl ester 72 was formed in modest yield (38 %), although lower than for 4‐hydroxybenzoate 54 (83 %) and in notably less overall conversion than the pyridine diacid 16 . In order to demonstrate the potential to use FtpM in a multienzyme cascade we carried out the multienzyme synthesis of the bioplastics precursor FDME 3 from HMF in a one‐pot, two stage process (Scheme 3 ). Initially, HMF 1 was oxidized using the four‐enzyme combination GOase M 3‐5 /PaoABC/catalase/HRP. \n [20] \n After 2 h, conversion to FDCA 2 was complete and the pH was adjusted to pH 6 prior to addition of FtpM/SAM/SAH‐nuc. The reaction was allowed to stir for 16 h prior to quenching and precipitation of the proteins. We were delighted to find that levels of conversion of the FDCA to the diester FDME 3 and monoester FMME 10 were similar with those obtained for the FtpM reaction alone (Table 1 ), showing that FtpM is compatible with the presence of the other enzymes. Scheme 3 Cascade process for the conversion of HMF 1 to FDME 3 (For reaction conditions see Supporting Information). Products were detected by RP‐HPLC and confirmed using authentic standards (see Supporting Information). FtpM has low sequence similarity with the SABATH enzymes and appears to have a much broader substrate range. For example, SAMT has low activity on 3‐ and 4‐hydroxybenzoate and on other substrates in the SABATH series. \n [33] \n Within the SABATH group of enzymes, it has been shown that the SAM binding site is conserved whilst small changes in the substrate binding site can modulate substrate specificity.[ \n 34 \n , \n 35 \n , \n 36 \n ] FtpM is active on 3‐ and 4‐substituted benzoic acids and also 2‐substituted terephthalates (for methylation of the 4‐carboxylate) whereas 2‐substituted benzoic acids are not substrates. This may reflect the inability of FtpM enzyme to methylate an internally H‐bonded acid (e.g., salicylic acid) or tolerate steric hindrance by an adjacent group. Given that FtpM already demonstrates activity on a significant substrate range we envisage that the enzyme will be readily modulated by directed evolution approaches to extend substrate scope and create a suite of enzymes for regioselective methylation and dimethylation. Most methyltransferases are subject to feedback inhibition by S ‐adenosyl homocysteine (SAH), potentially limiting their application in synthesis. \n [37] \n However, an iterative MT catalyzing successive methylations is less likely to be subject to such control, since the first product (monoester) must be further methylated by the enzyme. \n [38] \n As a precaution against possible inhibition of FtpM by SAH, SAH‐nucleosidase was included in the reactions to hydrolyse the SAH. For larger scale reactions with MTs, the SAM cofactor needs to be recycled either in vitro for isolated enzymes or within whole cells. In vitro recycling can be achieved using an auxiliary enzyme such as halide methyltransferase (HMT) to directly convert SAH back into SAM. \n [39] \n Alternatively a multienzyme biomimetic cascade system using polyphosphate, methionine and catalytic AMP was developed. \n [40] \n Stable synthetic SAM analogues such as 7dzAdotMet have shown to be competent methyl donors and therefore show promise for use, if they can be recycled. \n [41] \n \n In cells, SAM upregulation can be used to improve the yield of target methyl ester products. For example, E. coli was engineered to boost methionine levels by introduction of a single copy of the methionine synthase Mat1A gene into the host genome under inducible control. This in turn resulted in a 3‐fold increase of SAM levels, leading to a 19 % increase in fatty acid methyl ester production catalyzed by a recombinant CMT.[ \n 42 \n , \n 43 \n ] More recently improvements in methylated product yields were obtained using an E. coli strain in which the MetJ gene, which encodes a transcriptional regulator of methionine/SAM biosynthesis, was disrupted. \n [44] \n In situ SAM regeneration within whole cells currently appears to be the most promising approach for scale‐up of methyltransferase reactions. Uptake of diacids across the cell membrane at neutral pH could be impeded by the fact they are doubly charged. This has been addressed using whole cells of an engineered E. coli strain for conversion of TA to vanillin, where pH 5.5 was found to provide an optimal balance between TA uptake and minimizing acid stress to the cells. The pathway involved an O ‐methyltransferase and the uncharged vanillin product could be isolated by in situ ‐ product removal (ISPR) using an oleyl alcohol overlay, minimizing any product toxicity. \n [45] \n Thus, a similar approach could be envisioned for whole cell bioconversions using FtpM."
} | 7,277 |
36079585 | PMC9459794 | pmc | 4,061 | {
"abstract": "Plants interact with diverse microbial communities and share complex relationships with each other. The intimate association between microbes and their host mutually benefit each other and provide stability against various biotic and abiotic stresses to plants. Endophytes are heterogeneous groups of microbes that live inside the host tissue without showing any apparent sign of infection. However, their functional attributes such as nutrient acquisition, phytohormone modulation, synthesis of bioactive compounds, and antioxidant enzymes of endophytes are similar to the other rhizospheric microorganisms. Nevertheless, their higher colonization efficacy and stability against abiotic stress make them superior to other microorganisms. In recent studies, the potential role of endophytes in bioprospecting has been broadly reported. However, the molecular aspect of host–endophyte interactions is still unclear. In this study, we have briefly discussed the endophyte biology, colonization efficacy and diversity pattern of endophytes. In addition, it also summarizes the molecular aspect of plant–endophyte interaction in biotic stress management.",
"conclusion": "6. Conclusion and Future Perspective In the last two decades, significant progress has been made in endophytic microbiome research on the utilization of biocontrol agents and biofertilizers. It is known that a mutual and fine tuning of molecular signaling and interactions modulates the colonization of plant tissues by the endophytes. However, a significant fraction of endophytes communities and their functional attributes remain hidden due to unable to culture in the laboratory conditions/culture and not understanding of their molecular mechanism of action. Nowadays, continuous effort has been made to explore the novel biocontrol agent as an alternative to chemical pesticides that not only affect the texture and nutrient quality of fruits and crops, but also adversely affect the health of consumers. Better colonization efficacy and stability against the environmental fluctuations make the endophytes a suitable biocontrol agent compared to another microorganisms. However, the competition for nutrients and space, mycoparasitism, and synthesis of volatiles compounds are the most common mechanisms of biocontrol action. Nevertheless, a significant fraction of endophytes’ functional attributes has been hidden, which can be explored by a deep study of complex plant endophyte interactions. Furthermore, the molecular mechanism of host- endophytes’ pathogen interactions can provide a broad understanding for biocontrol screening and its successful application.",
"introduction": "1. Introduction The biology of endophytic microorganisms has been gaining momentum in the last few years due to better colonization efficacy and acclimatization potential against biotic and abiotic stress. In the last few years, endophytes, bacteria, or fungi have been frequently applied in sustainable agricultural practices as biofertilizers to meet nutrient requirements. Biocontrol agents have been used to prevent pathogen invasion or disease control and to mitigate various abiotic stresses, including salinity, drought, etc. The prospect of an endophytic microbiome has been reported in various review papers, which have been published recently [ 1 , 2 ], while molecular aspects of plant–endophyte interactions have been not covered extensively [ 3 ]. Plant-microbe interaction is a complex process in which the plant system interacts with diverse heterotrophic microorganisms and can share an intimate relationship from symbiotism to parasitism [ 4 , 5 , 6 ]. The intimate association of microbes with plants has a long history, and it is assumed that both have co-evolved together since the time of plants’ origin [ 7 ]. This inseparable relationship is also referred to as second genomes or holobionts, which play a significant role in maintaining plant health and fitness [ 8 ]. The term holobionts is also used as collective term for the microbiome associated with the host and referred as a single entity, which provides genomic reflection and stability to plants under various biotic and abiotic stresses [ 9 ]. The functional attributes of a plant as it secretes a range of sugars, metabolites organic or volatiles compounds are also dependent on the associated microorganism. Still, their exact mechanism is unclear at the community level. However, the study of synthetic communities and their outcome can be used to explore the colonization and assembly pattern of microorganism, which can be used to control pathogen invasion and biotic stress management [ 10 , 11 ]. The interaction of plants with microbes is mediated through various organic metabolites or signalling molecules. Their secretions include organic compounds such as amino acids, lipids, polysaccharides, flavonoids etc., that attract the microbial strains for colonization. For example, Steinkellner et al. [ 12 ] reported the functional role of root exudates, flavonoids, and strigolactones in the root colonization and hyphal growth differentiation of various Fusarium species and also their role as signaling molecules during symbiotic and pathogenic plant-fungus interactions. Similarly, Oku et al. [ 13 ] reported the role of amino acids in the root colonization of Pseudomonas fluorescens Pf0-1 to tomato plants. The plant’s rhizosphere is a hot spot of microbial communities and is considered as the favourable site of plant-microbe interaction due to its abundantly present root exudates. Their composition depends upon plant genotypes, development stages, and the surrounding environmental conditions of the rhizospheric microbiota [ 14 ]. However, some of the rhizospheric microbes enter the host tissue through natural openings such as stomata, pores, wounds, and hydathodes, acting as endophytes. The entry and establishment of endophytes is a complex process accomplished by various signalling molecules and colonization processes. In this review article we have briefly discussed the endophyte biology, colonization efficacy and diversity pattern of endophytes. In addition, we also summarize the molecular aspect of plant–endophyte interaction during biotic stress management."
} | 1,550 |
35118426 | PMC8792420 | pmc | 4,063 | {
"abstract": "Summary Electroactive microorganisms (EAMs) are a group of microbes that can access solid extracellular electron donors or acceptors via extracellular electron transfer processes. EAMs are useful in developing various microbial electrochemical technologies. This protocol describes the use of bioelectrochemical systems (BESs) to enrich EAMs at the cathode from an extreme haloalkaline habitat. It also provides information for a detailed characterization of enriched cathodic biofilms via various cross-disciplinary techniques, including electrochemical, analytical, microscopic, and gene sequencing techniques. For complete details on the use and execution of this protocol, please refer to Chaudhary et al. (2021) ."
} | 179 |
40109114 | PMC11923619 | pmc | 4,064 | {
"abstract": "An important advantage to sociality is division of labour, which is often associated with specialization of group members, such as the polymorphic subcastes of ant workers. Given this advantage, it is puzzling that many social groups do not show clear specialization. Among ants, workers of closely related species have one, two or even three polymorphisms. The degree of specialism of asocial animals depends on environmental variability because specialists will perform poorly in some conditions. Here, we use a numeric model to consider whether the magnitude and type of environmental variability can help to explain the diversity of specialism in cooperative groups. By finding the optimal distribution of group members along a single dimension of specialization for two tasks, we predict when groups should be composed of specialists, generalists, both of these (trimodal) or moderate specialists. Generalism is predicted more when environments are unstable and when task importance—rather than demand—varies but depends on the likelihood that the group can complete all tasks in the range of experienced conditions. The benefit of sociality is strongest in invariable environments and there is selection for redundancy in the workforce, which may explain the widely observed inactivity in social insects. This article is part of the theme issue ‘Division of labour as key driver of social evolution’.",
"introduction": "1 . Introduction Social animals that form cooperative groups dominate many ecosystems, and specialization of members for different tasks is common [ 1 – 3 ]. Because reproductive success in social animals is often highly correlated with group-level performance, such specialization is often based on the share of the tasks and resources within the group. Such cooperative task sharing in social animals is known as ‘division of labour’ [ 4 ]. Division of labour has evolved in many taxa where related individuals live in groups, such as social amoebae [ 5 ], algae [ 6 ], sea anemones [ 7 ], social insects [ 8 , 9 ], birds [ 10 , 11 ], mammals [ 12 , 13 ] and even viruses [ 14 ]. In empirical studies, division of labour is often quantified by the variation in body size as a form of phenotypic polymorphism. The clearest example may be large body size variation within the workers of some species of leaf-cutting ants [ 15 ] and fire ants [ 16 , 17 ]. The distribution of body sizes is often continuous and may be unimodal, bi- or even trimodal, and the modes may be specialized to different worker roles [ 18 ]. In some species of ant, the distribution of body size differs between colonies or habitats [ 9 , 15 , 19 , 20 ] but is often multimodal. In other eusocial animals, such as bumblebees, size variation is striking but unimodal [ 21 ]. Different body sizes are for specialization for specific tasks and improve the performance of a particular task to the detriment of the performance of other tasks [ 18 ]. Nevertheless, size variation is not always the best indicator for division of labour. For instance, honeybee and bumblebees divide labour according to the age of the workers [ 22 ]. Past theories on division of labour have identified several influential factors: food size distribution, number of resource types, group size and resource availability [ 9 , 15 , 19 ]. A dominant theoretical focus is on the emergence of reproductive specialists, which leads to the evolution of multicellularity, eusociality or cooperative breeding (e.g. [ 23 , 24 ]), but these studies do not consider the variation among non-reproductive units. Oster & Wilson [ 18 ] focused on the situation in which a continuous trait value (e.g. body size) determines the handling ability of different sized foods and predicted that the optimal distribution of workers’ traits can be either unimodal or multimodal depending on the distribution of food size, although the maximum number of worker classes is equal to the number of resource types. In other words, the balance between the usability of various food and the cost of producing multiple workers classes determines the emergence of specialists or generalists. Wahl [ 14 ], Tannenbaum [ 25 ] and D’Orazio & Waite [ 26 ] considered cooperation among non-kin that must carry out two tasks and showed that the coexistence of specialists and generalists can occur, depending on group size and the relative performance of specialists compared with generalists. In these cases, the advantage of generalists compared with the specialists is that generalists can flexibly switch tasks depending on the types and tasks of other group members. Variability in environmental conditions, on the other hand, has not been considered despite increasing awareness of its importance in the behaviour of cooperating groups (e.g. [ 27 ]). Organisms usually face temporal–spatial variability in environmental conditions [ 28 – 30 ]. In asocial animals, adaptive strategies for coping with variable environments can divided into two types: specialize for a limited range of conditions or generalize for a wide range of conditions with the cost of lower maximum performance. The evolution of specialists and generalists has been widely observed in various taxonomic groups [ 31 ] and has been theoretically investigated [ 28 , 32 – 34 ]. Previous theoretical studies predicted that adaptative strategies for variable environments should be influenced by the particulars of the trade-off between the adaptations for different environments and the statistical patterns of environmental fluctuation (e.g. spatial/temporal variation or interval of the fluctuation [ 34 ]). In sum, past theory on other types of biological adaptation has predicted that generalism is selected when the trade-off between the performance in different conditions has a convex shape or the environmental variation is temporal rather than spatial, yet it is not clear whether the condition holds for the evolution of specialization in social species. Here, we focus on the influence of environmental variability on specialism in a social group. Environmental variation might alter the group-level task demand, task processing efficiency or its importance to reproductive success, but a group consisting of generalists can adapt to such changes of task conditions. Unlike asocial animals, the adaptation for a stochastic environment in social animals will be more complex because each individual can be generalist or specialist. In other words, the allocation of specialism within the group should be considered to understand the emergence of individual variation, such as worker ant size polymorphism, in the fluctuating environments in which most species have evolved. To our knowledge, there is no theoretical framework for understanding the influence of environmental variability on the allocation of specialism within groups. We used a simulation approach to predict the optimal allocation of specialists and generalists within a colony of eusocial animals as a function of environmental variability. In order to establish a theoretical foundation for understanding these influences, we considered the most simple possible situation: we focus on a colony of eusocial animals (so that all members in the colony share the reproductive success) and assume that the colony must do two tasks (e.g. collect two types of food items) and there is a trade-off between each individual’s abilities to do the two tasks. Rather than limiting each individual’s options to extreme specialism or absolute generalism, we allow degrees of intermediate specialism. We assume that the fitness of the colony is inversely proportional to the total amount of uncompleted tasks averaged across all possible conditions. We modelled environmental variability as a frequency distribution of the required amount of the two tasks and predicted the frequency distribution of individual specialism as that which maximizes colony fitness.",
"discussion": "4 . Discussion Previous studies of specialism under the influence of environmental variability have mostly focused on adaptation at the individual scale, assuming that the mean performance of each asocial animal determines the degree of specialism [ 34 ]. In social animals, however, reproductive success depends on group-level performance. Selection on social animals from environmental variation can therefore involve a distribution of specialization within the group. Here, we have assumed that individuals can be specialized to one of the two tasks along a continuum, which is an advance from previous studies that typically assumed only that individuals can be either (extreme) specialists or generalists. This increased sensitivity enables to us to make a range of predictions about the distribution of specialism in groups and predict four broad categories to enable our predictions to be tested to acquire general insights about the continuous distribution of specialism, such as body size, in nature. We found that when task demand varies, invariable environments select for trimodal or specialist distributions, whereas variable environments select for generalism or moderate specialism, depending on whether all tasks are usually completed. When task efficiency varies, we predict specialism unless task demand is either high or low and the environment is variable. When task importance varies task demand has much less effect and we usually predict generalism or specialism. Finally, the results show that advantage of sociality is strongest in invariable environments where most tasks are usually completed. In previous studies, the continuous distribution of workers tends to be explained by the continuous distribution of required tasks (e.g. food size [ 18 ]), or the variation of the workers is given without any explanation. In this study, interestingly, we showed that a continuous distribution of the classes can be realized depending on the parameter values ( figure 5 ). This means that even if the required tasks are discrete, the optimal strategy can contain a certain range of variation. Such continuous variation is very commonly observed in social animals [ 15 – 18 ], which can be explained by necessity of flexibility in variable environments. Both moderate-specialism and trimodality are adaptations intermediate to specialism and generalism. They improve task performance while keeping some flexibility. While previous studies did not consider them, here we show that under stochasticity they may be expected to be common in social animals. We have found that these two types are qualitatively different and so the condition for the emergence of these types is different. A trimodal distribution has high performance during a certain range of task allocations within the colony (i.e. until all generalists allocated to either task; electronic supplementary material, figure C1a), but it shows low performance when a very biased allocation to either task is required. Contrary to this, moderate-specialism has high performance for very biased allocation, but the performance when both tasks have similar demands is not so high (electronic supplementary material, figure C1b). Because of these features, trimodal type tends to emerge when both tasks are significantly required regardless of the environmental fluctuation (i.e. figure 5b,c ) or when the total task demand is relatively low with small environmental fluctuations (left-bottom area of figure 5a ), while moderate-specialism tends to emerge when the fluctuation of task demand is so large that the group often face a situation where only either task is required (right area of figure 5a ). The only exception is the scenario of stochasticity in importance with moderately invariable environment (upper centre area of figure 5c ); then moderate-specialists are optimal because the allocation to the more important task can be advantageous. The total task demand also has a significant impact on the optimal distribution of specialism. Importantly, in our model, group size is not explicitly considered but the task demand per capita of workers is considered. This means that if the increase in task demand is more rapid than the increase in workforce, the total task demand in our model increases. In other words, if a group increases the number of larvae relative to the number of workers, while the adults need food themselves, the amount of food each adult needs to collect on average would increase. This might explain the fact that with the growth of group size the distribution of worker sizes tends to be multimodal [ 18 , 37 ]. According to our results, the reduction of the total task demand can switch from specialism to trimodal in the scenario of task demand variability with invariable environments (right side of figure 5a ) or the scenario of task efficiency variability even if the stability of environment is not changed. Since this would mean redundancy in the workforce under most conditions, this would provide an adaptive explanation for the puzzling phenomenon of large minority of workers doing little work (e.g. [ 38 ]). We assumed that selection acts on the mean performance at the group-level under environmental variation. Of course, in many—or perhaps all—social animals fitness outcomes are not perfectly correlated. Since workers do not usually share 100% of their genes with the reproducers, there exists the potential for conflict over who reproduces. However, we took this simplification in order to derive clear predictions for the ideal case. In some systems, workers reproduce very rarely so get no direct fitness, and our predictions are likely to be accurate. This depends somewhat on whether the different tasks or degree of specialization affect direct fitness. For instance, worker honeybees ( Apis mellifera ) sometimes lay (male) eggs. If some tasks, such as foraging, have a greater mortality risk, then we might expect worker bees to be ‘reluctant’ to forage. However, if these chances of direct fitness are small, or if there is little difference in direct fitness between tasks or the degree of specialization, then this conflict over reproduction is likely to have small effects on the optimal distribution of specialism in the group. We also showed that specialism distribution strongly depends on the types of environmental variability: whether the task demand, efficiency or importance is altered by the environment. Although in previous studies the benefit of generalists/specialists tends to be discussed only from the perspective of the trade-off of fitness in different environments, this result suggests that this trade-off cannot be simply defined because the distribution of the environment, and its influence can be variable. This implies that we need to pay further attention to details of the influence of the environment on cooperative groups. Our main aim here was to highlight the potential for environmental variation to explain some puzzling phenomena in social groups. Unfortunately, previous empirical studies rarely focused on environmental variation, especially about how the demand, efficiency and importance vary, and so the empirical data about the relationship between the environment variability and specialism are still lacking. Further empirical studies focusing on the environmental variability are required to test our hypothesis. Additionally, further developments of adaptive models of specialism in variable environments could provide a foundation which with to understand specialism in social animals."
} | 3,873 |
24267588 | PMC4053972 | pmc | 4,065 | {
"abstract": "Background ‘ Chlorochromatium aggregatum ’ is a phototrophic consortium, a symbiosis that may represent the highest degree of mutual interdependence between two unrelated bacteria not associated with a eukaryotic host. ‘ Chlorochromatium aggregatum ’ is a motile, barrel-shaped aggregate formed from a single cell of ‘ Candidatus Symbiobacter mobilis”, a polarly flagellated, non-pigmented, heterotrophic bacterium, which is surrounded by approximately 15 epibiont cells of Chlorobium chlorochromatii, a non-motile photolithoautotrophic green sulfur bacterium. Results We analyzed the complete genome sequences of both organisms to understand the basis for this symbiosis. Chl. chlorochromatii has acquired relatively few symbiosis-specific genes; most acquired genes are predicted to modify the cell wall or function in cell-cell adhesion. In striking contrast, ‘ Ca. S. mobilis’ appears to have undergone massive gene loss, is probably no longer capable of independent growth, and thus may only reproduce when consortia divide. A detailed model for the energetic and metabolic bases of the dependency of ‘ Ca . S. mobilis’ on Chl. chlorochromatii is described. Conclusions Genomic analyses suggest that three types of interactions lead to a highly sophisticated relationship between these two organisms. Firstly, extensive metabolic exchange, involving carbon, nitrogen, and sulfur sources as well as vitamins, occurs from the epibiont to the central bacterium. Secondly, ‘ Ca . S. mobilis’ can sense and move towards light and sulfide, resources that only directly benefit the epibiont. Thirdly, electron cycling mechanisms, particularly those mediated by quinones and potentially involving shared protonmotive force, could provide an important basis for energy exchange in this and other symbiotic relationships.",
"conclusion": "Conclusions Genomic data for the phototrophic consortium “Chlorochromatium aggregatum” suggest that a very sophisticated symbiotic relationship has evolved between the central bacterium, “ Ca. S. mobilis”, which apparently is no longer capable of independent growth, and the epibiont, Chl. chlorochromatii , which is still capable of independent growth. We propose that three types of interactions occur between the two partners (Figure 4 ). Firstly, metabolite exchange, which is common in many other symbiotic organisms, also occurs in this consortium, but the wide variety of exchanged metabolites, including carbon, nitrogen and sulfur sources and vitamins, is uncommon [ 40 ]. Secondly and remarkably, “ Ca. S. mobilis” can sense light and probably sulfide, which are most directly beneficial to Chl. chlorochromatii . “ Ca. S. mobilis” can also sense other nutrients and probably the metabolic status of Chl. chlorochromatii . Figuratively, Chl. chlorochromatii cells are the solar panels of this self-perpetuating, solar-energy-powered bacterial machine; “ Ca. S. mobilis” not only provides the bus but also the driver and a navigation system. The degree of specialization observed for these two organisms approaches that seen in multicellular organisms. Although phototrophic consortia are composed of two different organisms, studies of these consortia might offer insights into the evolutionary processes that led from single-celled to multicellular organisms. Thirdly, electron cycling mechanisms, particularly those mediated by quinones and potentially shared proton-motive force, could provide important new mechanistic bases for energy exchange in symbiotic relationships. This study provides many novel insights for this specific bacterial symbiosis, but it also reveals benchmarks for understanding other phototrophic consortia, bacterial symbioses in general, and more complex communities and multicellularity.",
"discussion": "Results and discussion The two genomes of “ Chlorochromatium aggregatum ” The Chl. chlorochromatii genome (GenBank accession number CP000108) is a single circular DNA molecule of 2,572,079 bp with a G + C content of 44.3 mol%. It encodes 2,002 open reading frames (ORFs), one rRNA operon, and 45 tRNAs (Figure 2 A). The size and gene content are very similar to those of 15 other GSB genomes [ 22 ]. Similar to the genomes of other GSB, the Chl. chlorochromatii genome encodes proteins for the photosynthetic apparatus, bacteriochlorophyll biosynthesis, sulfide oxidation, CO 2 fixation via the reverse tricarboxylic acid (TCA) cycle, nitrogen fixation and all housekeeping genes of central metabolism and macromolecule biosynthesis [ 22 - 25 ]. Only 311 ORFs (15%), nearly all of which encode proteins with unidentified functions, have no homologs in genomes of other GSB, which are not known to be involved in phototrophic consortia (Table S1 in Additional file 2 ). These results are consistent with the observation that Chl. chlorochromatii is not obligately symbiotic and can grow independently as a photolithoautotroph [ 14 ]. Thus, only relatively minor changes in gene content were apparently required as the epibiont adapted to a symbiotic lifestyle. Figure 2 Circular maps and genomic islands of the genomes of Chl. chlorochromatii (A) and “ Ca . S. mobilis” (B). From outside in, the circles represent open reading frames (ORFs) on the forward strand, ORFs on the reverse strand, BLASTP scores of ORFs against reference genomes, mol% G + C, and GC skew. Colors of ORFs represent COG (clusters of orthologous groups of proteins) categories. Mol% G + C is plotted using genome averages as baselines, which are 44.3% and 59.1% for the epibiont and the central bacterium, respectively. Genomic islands are marked by red boxes (see Materials and methods for identification of genomic islands). The reference genomes used in this study are: Chlorobaculum parvum NCIB 8327, Chlorobaculum tepidum ATCC 49652, Chlorobium ferrooxidans DSM 13031, Chlorobium limicola DSM 245, Chlorobium phaeobacteroides BS-1, Chlorobium phaeobacteroides DSM 266, Chlorobium phaeovibrioides DSM 265, Chlorobium clathratiforme DSM 5477, Chlorobium luteolum DSM 273, Prosthecochloris aestuarii DSM 271, and Chloroherpeton thalassium ATCC 35110 for Chl. chlorochromatii ; Acidovorax avenae citrulli str. AAC00-1, Rhodoferax ferrireducens DSM 15236, Alicycliphilus denitrificans str. BC, Comamonas testosteroni str. CNB-2, Delftia acidovorans str. SPH-1, Polaromonas naphthalenivorans str. CJ2, Variovorax paradoxus str. EPS, and Verminephrobacter eiseniae str. EF01-2 for “ Ca . S. mobilis.” In contrast, the genome of the “ Ca. S. mobilis” differs dramatically from the genomes of eight close relatives with sequenced genomes (listed in the Figure 2 legend). The “ Ca. S. mobilis” genome (GenBank accession number CP004885) is a single circular DNA molecule of 2,991,840 bp with G + C content of 59.1 mol%. It has two tandemly repeated rRNA operons [ 21 ], 44 tRNAs and 2,626 proteins (Figure 2 B). The closest non-symbiotic relatives of “ Ca. S. mobilis” from the family Comamonadaceae have much larger genomes (4.8 to 6.8 Mbp). “ Ca. S. mobilis” apparently underwent substantial gene loss during its evolution, especially for genes involved in metabolism (Figure 3 ). Eight free-living members of the family Comamonadaceae, each representing a different genus, have a core genome of 1,284 genes, but 409 (32%) of these genes are missing from the “ Ca. S. mobilis” genome (for a list of these missing genes, see Table S2 in Additional file 2 ). This degree of gene loss, which is common in exclusively symbiotic organisms [ 26 , 27 ], supports the experimental observation that “ Ca. S. mobilis” is no longer capable of independent growth and now depends on its photoautotrophic partner for essential metabolites (see below). Figure 3 Comparison of gene contents of “ Ca . S. mobilis” and its relatives based on functional categories. Percentages of genes for each COG category in the genomes are calculated for “ Ca . S. mobilis” and its relatives based on COG assignment of genes provided by Integrated Microbial Genomes [ 28 ]. Averages and standard deviations of the percentages for the eight Comamonadaceae organisms listed in Figure 2 legend are shown. On the other hand, “ Ca. S. mobilis” has also acquired new genes, either through lateral gene transfer or gene duplication and subsequent diversification, that are not found in its close relatives. A comparison identified 1,055 “ Ca. S. mobilis” genes without orthologs in any of eight free-living Comamonadaceae organisms; 444 (42%) of these genes have annotations other than ‘hypothetical protein’ (for a complete list, see Table S3 in Additional file 2 ). Genes involved in signal transduction (138), cell envelope biogenesis (38) and cell motility (44) are overrepresented. These gains and losses of genes resulted in different functional compositions for the genomes of “ Ca . S. mobilis” and its relatives, especially in the categories mentioned above (Figure 3 ). Such differences presumably reflect adaptations of “ Ca. S. mobilis” to an obligately symbiotic lifestyle, and they suggest that the major roles of “ Ca. S. mobilis” are to sense the environment and to provide motility. The increased number of genes for cell wall and envelope biosynthesis is consistent with the importance of previously observed cell-to-cell contacts between the central rod and the epibionts via specialized cell-surface structures [ 17 ]. Horizontal gene transfer The genomes of “ Ca. S. mobilis” and Chl. chlorochromatii were compared to search for potential horizontal gene transfers between these two partner organisms that are constantly in close contact. Thirteen pairs of genes in these two genomes are more similar to one another than to most if not all proteins in databases (Table S4 in Additional file 2 ); however, the functions of most could not be unambiguously assigned. Gene exchange (and gene transfer) between the two partners does not appear to have occurred frequently in this symbiosis. The two genomes were also analyzed to identify genomic islands (GIs), which often harbor recently acquired or highly conserved genes. The identified GIs are marked in Figure 2 and their properties are summarized in Table 1 (GIs in Chl. chlorochromatii are denoted with the prefix ‘EP’; GIs in “ Ca. S. mobilis” are denoted with the prefix ‘CB’). Four genomic islands were identified in Chl. chlorochromatii , and three contain unusually large proteins. These proteins are similar to hemagglutinin and outer membrane adhesin proteins of the RTX toxin family, which contain numerous, internally repeated, calcium-binding domains [ 29 ]. ORFs Cag_0614 and Cag_0616 in EP_GI-1 predict proteins of 36,805 and 20,646 amino acids, respectively. The former protein is larger than human titin (34,350 amino acids), often considered to be the largest known protein [ 30 ]. These two genes are transcribed, encode symbiosis-specific proteins, and have been hypothesized to stabilize contacts between the central bacterium and epibiont cells [ 15 ]. Smaller but related proteins, including the ones in EP_GI-3 (Cag_0738) and EP_GI-4 (Cag_1242), could play similar roles. Table 1 Properties of genomic islands in \n Chl. chlorochromatii \n and “ \n Ca \n . S. mobilis” Genomic islands Size (kb) Number of genes Transposase/integrase Putative gene function EP_GI-1 175 3 No Cell adhesion EP_GI-2 34 36 Yes Cell envelope biogenesis EP_GI-3 36 8 No Cell adhesion EP_GI-4 49 4 No Cell adhesion CB_GI-1 12 10 Yes Cell envelope biogenesis CB_GI-2 37 4 No Cell adhesion CB_GI-3 11 9 No Cell envelope biogenesis CB_GI-4 48 45 Yes CRISPR-associated and hypothetical proteins CB_GI-5 16 17 No Chemotaxis and regulation CB_GI-6 44 33 Yes Poorly defined genes CB_GI-7 22 15 No Cell envelope biosynthesis CB_GI-8 31 27 Yes Poorly defined genes Eight GIs were identified in the “ Ca. S. mobilis” genome (Figure 2 B). The presence of transposases and integrases in most of them suggests that they were probably acquired by horizontal gene transfer. Genes found in the GIs of Chl. chlorochromatii , such as those involved in cell envelope biosynthesis and encoding haemagglutinin/adhesin-like proteins, were similarly found in CB_GI-1, CB_GI-2, CB_GI-3 and CB_GI-7. CB_GI-4 included mainly CRISPR-associated proteins and hypothetical proteins, while CB_GI-5 and CB_GI-7 contained mainly genes of unknown function. CB_GI-4 (Cenrod_1189-Cenrod_1205) encodes chemotaxis and regulatory proteins, and interestingly, this gene cluster is similar in both gene order and sequence to clusters found in several purple sulfur bacteria (for example, Allochromatium vinosum ) (Figure S2B in Additional file 1 ). Purple sulfur bacteria are often found in the same lakes where phototrophic consortia occur [ 31 ], and the central bacterium may have acquired genes from such organisms. Although sequence analysis cannot determine the attractant or repellent molecule(s) sensed by the products of these genes, purple sulfur bacteria are often positively chemotactic to sulfide [ 32 , 33 ]. The horizontal acquisition of genes for sulfide chemotaxis from a sulfide-oxidizing bacterium could explain how “Chlorochromatium aggregatum” gained its known ability to sense and swim towards sulfide [ 13 ]. Compared to the genome average, EP_GI-2 has extremely low G + C mol% and includes two genes encoding transposases or integrases, which suggests that these genes were laterally acquired from another organism. Reflecting probable gene transfer between the two partners, five genes in this cluster have very high sequence identities with homologs in the genome of “ Ca. S. mobilis”, three of which are found in CB_GI-1 (Figure S2A in Additional file 1 ). Because of the very low G + C mol%, these genes are probably not natively found in either Chl. chlorochromatii or “ Ca. S. mobilis”, and they may have been acquired horizontally by one of the partners and subsequently transferred to the other. Most of the genes in EP_GI-2 and CB_GI-1 are probably involved in cell envelope biosynthesis. These results suggest that these two GIs potentially contain genes essential for establishing close cell-to-cell contact and possibly involved in synthesizing symbiosis-specific structures within the consortium. Metabolism and metabolic coupling Genome analyses suggest that “ Ca. S. mobilis” has limited metabolic capabilities. Firstly, “ Ca. S. mobilis” has no pathways for autotrophic CO 2 fixation, and thus it is a heterotroph that relies on exogenous carbon sources. Secondly, it has very limited pathways for energy production. It lacks recognizable genes for anaerobic respiration with nitrate or sulfate as electron acceptors or for oxidation of inorganic electron donors, except for sulfide:quinone oxidoreductase (SqrA; Cenrod_0552). Thus, “ Ca. S. mobilis” presumably depends on aerobic respiration or fermentation to produce ATP (but see discussion of interspecies electron transfer below). Compared to its free-living close relatives, “ Ca. S. mobilis” apparently lost genes for electron transfer proteins such as cytochrome c :ubiquinol oxidoreductase, cytochrome c oxidase, and most soluble electron carriers (Table S2 in Additional file 2 ). However, it has retained a complete set of genes for type-1 NADH dehydrogenase and succinate dehydrogenase (Figure 4 ). The “ Ca. S. mobilis” genome includes a single terminal oxidase, a cytochrome bd -type quinol oxidase, which might allow respiration to occur under the very low O 2 concentrations (approximately 2.9 μM) found in situ [ 34 ]. Figure 4 Cellular overview of central metabolism of Chl. chlorochromatii and “ Ca . S. mobilis”. Only selected pathways and functions are shown to focus on metabolic coupling, chemotaxis and phototaxis. Blue arrows mark the flow of electrons. Question marks denote unidentified proteins or protein complexes. Abbreviations: 2-OG, 2-oxoglutarate; APS, adenosine 5′-phosphosulfate reductase; Bph, bacteriophytochrome; BV, biliverdin; cyt, cytochrome; DSR, dissimilatory sulfite reductase; FMO, Fenna-Matthews-Olson protein; HDR, heterodisulfide reductase; MK, menaquinone; NDH-1, type 1 NADH dehydrogenase; PSR, polysulfide reductase; Q, quinone; RC, photosynthetic reaction center; SQR, sulfide quinone reductase; UQ, ubiquinone; VB 12 , vitamin B 12 . The pairing of an oxygen-sensitive, strict anaerobe and a microaerophile that requires oxygen for some functions is highly unusual. Like other GSB, the epibiont has genes for enzymes involved in protection from reactive oxygen species [ 35 ]. Enzymes to protect the cytoplasm of “ Ca. S. mobilis” from reactive oxygen species include catalase (Cenrod_0449), Fe-Mn superoxide dismutase (Cenrod_1509), alkyl hydroperoxide reductase (Cenrod_0223), and peroxiredoxin (Cenrod_0224, Cenrod_0777, and Cenrod_2189) [ 35 , 36 ]. The expression of some or all of these oxidative stress proteins could be under the control of an OxyR-like, LysR-family transcription factor (Cenrod_2620). Only two c -type cytochromes are encoded by the “ Ca. S. mobilis” genome. One of these is a small, soluble cytochrome c 551 / c 552 (Cenrod_0340), and the other is a periplasmic, diheme cytochrome c peroxidase (Cenrod_1795). Although the latter might play a role in protecting the periplasm and cells from the toxic effects of hydrogen peroxide, recent studies in Shewanella oneidensis suggest that hydrogen peroxide can also serve as an alternative terminal electron acceptor for dissimilatory energy production [ 36 , 37 ]. In S. oneidensis , the electrons for reduction of hydrogen peroxide to water are derived from the quinone pool [ 37 ]. In “ Ca. S. mobilis” a membrane-associated cytochrome b (Cenrod_1223) might deliver electrons from menaquinol to cytochrome c 551 / c 552 , which would serve as the reductant for hydrogen peroxide catalyzed by cytochrome c peroxidase. The “ Ca. S. mobilis” genome encodes genes for the enzymes of glycolysis, the TCA cycle, and the oxidative pentose phosphate pathway (Figure 4 ). The absence of lactate dehydrogenase, pyruvate decarboxylase, and pyruvate-formate lyase limits fermentation possibilities involving pyruvate. However, the presence of pyruvate dehydrogenase (Cenrod_2157 and Cenrod_2158), pyruvate:ferredoxin oxidoreductase (Cenrod_0415, Cenrod_0416, and Cenrod_0417), phosphate acetyltransferase (Cenrod_0908), and acetate kinase (Cenrod_0907) suggests that “ Ca. S. mobilis” can extend the glycolytic pathway beyond pyruvate to acetate, while producing additional ATP by substrate-level phosphorylation. As noted above, under microoxic conditions, respiration could occur by transferring electrons from NADH or menaquinol to oxygen or hydrogen peroxide. The resulting proton-motive force could also be used for ATP synthesis by the F 0 F 1 -type ATP synthase (Cenrod_1756 to 1763). Under strictly anoxic conditions, protons might be the only available electron acceptor other than CO 2 (however, see discussion of interspecies electron transfer below). “ Ca. S. mobilis” encodes two different hydrogenases: a bi-directional group 3d NiFe hydrogenase (Cenrod_0973 and Cenrod_0974) with an associated diaphorase complex (Cenrod_0975 and Cenrod_0976) and a group 3c Mvh hydrogenase (Cenrod_2144, Cenrod_2145, and Cenrod_2148) with an associated heterodisulfide reductase (Cenrod_2147). The diaphorase moiety of the group 3d NiFe hydrogenase should enable the reversible coupling of proton reduction with NADH oxidation [ 38 , 39 ]. During fermentative metabolism, this enzyme could function to reoxidize NADH and reduce protons, but it could alternatively serve as an uptake hydrogenase to oxidize H 2 produced by the epibionts when they are fixing nitrogen (no uptake hydrogenase is present in the epibiont genome). In methanogens, the Mvh hydrogenase (MvhADG)-heterodisulfide reductase (HdrABC) complex is proposed to couple the exergonic reduction of heterodisulfide CoM-S-S-CoB to coenzyme M (CoM) and coenzyme B (CoB) with the energonic reduction of ferredoxin through H 2 -based electron bifurcation [ 40 - 42 ]. However, the “ Ca. S. mobilis” genome does not encode homologs of HdrB and HdrC, which form the site of disulfide reduction. This feature, coupled with the absence of evidence for the utilization of CoM and CoB by this taxon, suggests that this enzyme complex has another function. HdrA binds FAD and is thought to be the site of ferredoxin binding. An intriguing possibility is that this enzyme couples the oxidation of NADH (approximately -280 mV) and ferredoxin oxidation (approximately -500 mV) to the reduction of protons. Supporting this possibility, this HdrA subunit (Cenrod_2147) has a NADH binding domain that is not observed in the HdrA subunits of heterodisulfide reductases of methanogens. This might ensure that oxidized pyridine nucleotides are available even when other terminal electron acceptors are not. Chl. chlorochromatii fixes CO 2 by the reverse TCA cycle, has a complete set of nif genes, and can thus fix N 2 (Figure 4 ). It excretes large amounts of sugars (mainly glucose) and amino acids (mainly glutamate and aspartate) into the growth medium when grown axenically [ 43 ]. In contrast, “ Ca. S. mobilis” can neither fix N 2 nor assimilate nitrate or nitrite, but it has an ammonia permease (Cenrod_1218) and several sugar and amino acid transporters (Figure 4 ). It therefore seems likely that sugars and amino acids are transferred from the photoautotrophic epibionts to heterotrophic “ Ca. S. mobilis”. 2-Oxoglutarate stimulates the growth of “Chlorochromatium aggregatum” [ 13 ], and another phototrophic consortium, “Pelochromatium roseum” , incorporated 2-oxoglutarate in situ [ 44 ]. However, 2-oxoglutarate had no effect on the growth of Chl. chlorochromatii [ 14 ], suggesting that only “ Ca. S. mobilis” assimilates 2-oxoglutarate. Consistent with this idea, the “ Ca. S. mobilis” genome encodes one TRAP-type dicarboxylate transporter (Cenrod_1182, Cenrod_2378 and Cenrod_2379). Growth of Chl. chlorochromatii is stimulated by photo-assimilation of acetate [ 14 ], which is probably produced from pyruvate by oxidation of sugars or 2-oxoglutarate by “ Ca. S. mobilis” (see above). These types of metabolite exchange would be mutually beneficial. “ Ca. S. mobilis” probably takes up amino acids released by Chl. chlorochromatii , and two ABC transporters for ‘branched-chain’ amino acids (Cenrod_0106 to 0109; Cenrod_2184, Cenrod_2264, Cenrod_2266, and Cenrod_2267), as well as other amino acid transporters, are encoded in its genome. Nevertheless, it has not generally abandoned its ability to synthesize amino acids but has streamlined some pathways (Figure 3 ). For example, “ Ca. S. mobilis” cannot perform assimilatory sulfate reduction, but can synthesize cysteine and methionine from sulfide. Instead of using two enzymes, a single protein (Cenrod_2045) similar to aminotransferases AspC and TyrB probably performs both activities. 3-Phosphoglycerate dehydrogenase (SerA) appears to be missing, but it is probably premature to conclude that “ Ca. S. mobilis” cannot synthesize serine [ 45 ]. “ Ca. S. mobilis” also probably depends on the epibiont for essential cofactors. “ Ca. S. mobilis” has a heterodimeric, MetH-type, cobalamin-dependent methionine synthase (Cenrod_2368 and Cenrod_2596) but lacks the genes for cobalamin synthesis. However, it has a putative cobalamin transport system, and this suggests that it obtains vitamin B 12 from the epibiont, which has all genes required for cobalamin synthesis. “ Ca. S. mobilis” apparently obtains menaquinone from Chl. chlorochromatii as well (see below). In summary, as in many other symbiotic systems [ 46 ], metabolic dependence - mainly of “ Ca. S. mobilis” on Chl. chlorochromatii - is apparently an important component of the relationship between these two partners (Figure 4 ). Chemotaxis, phototaxis, and signal transduction Metabolic coupling is obviously critical for the survival of “ Ca. S. mobilis”; however, Chl. chlorochromatii is a photolithoautotroph and does not appear to gain much from such coupling. On the other hand, the motility of the consortium provides a huge advantage to the epibiont over free-living relatives. Swimming motility has not been reported for any GSB, and planktonic GSB with gas vesicles can only reposition themselves slowly [ 47 ]. Flagella-powered taxis towards sulfide and away from darkness towards light - which are the main energy and electron sources of GSB - would allow consortia to adjust more quickly to fluctuating light and oxygen conditions during the diel cycle in their natural habitats [ 34 ]. Diel vertical migration behavior is highly advantageous for the flagellated purple sulfur bacterium Chromatium minus [ 48 ], and directed motility is generally regarded as one of the major advantages that allow phototrophic consortia to outcompete free-living GSB [ 49 ]. Microscopic analyses have shown that “ Ca. S. mobilis” cells possess a single polar flagellum that confers motility to the consortia [ 34 ]. Because two of the strongest attractants, light and sulfide, provide no apparent direct benefit to “ Ca. S. mobilis”, it had been proposed that these attractants were sensed by Chl. chlorochromatii , and that a signal was then transmitted to “ Ca. S. mobilis” [ 13 ]. The genomic data suggest instead that the genome of the central rod contains the dedicated sensory proteins of the consortium, with a complex photosensory apparatus having similarity to those of cyanobacteria and purple photosynthetic bacteria. In the cyanobacterium Synechocystis sp. PCC 6803, multiple photoreceptors have been implicated in regulating phototaxis, with the domain structure of these sensors implicating multiple signaling pathways. PixD is a member of the blue-light-sensor-using-flavin (BLUF) family with no obvious signaling domains, but it is nevertheless able to interact with a response regulator (REC) protein, PixE [ 50 ]. Three members of the phytochrome superfamily are also known to function in determining Synechocystis sp. PCC 6803’s responses to blue light [ 51 - 55 ]. One of these proteins, SyPixJ, possesses a carboxy-terminal methyl-accepting-chemotaxis-protein (MCP in Figure 5 ) domain that is also found in chemotactic signaling proteins. Another, UirS or PixA, has a bipartite histidine kinase domain (H/ATP), while the third protein, Cph2, can function as a sensor for both red and blue light and contains GGDEF and EAL domains associated with metabolism of the bacterial second messenger molecule cyclic-di-GMP. Reported phototactic responses to red light in Synechocystis sp. PCC 6803 [ 56 ] have not been unambiguously assigned to a given photosensor, but this organism possesses additional histidine kinases in the phytochrome superfamily that exhibit the requisite spectral response [ 57 , 58 ]. Bacteriophytochrome members of this superfamily are also responsible for responses to red and far-red light in the anoxygenic photosynthetic bacterium Rhodopseudomonas palustris [ 59 ]. Figure 5 Photosensors of “ Ca. S. mobilis”. (A) Domain structures of the four bacteriophytochromes encoded in the genome of “ Ca. S. mobilis”. The experimentally verified red/far-red photocycle and BV chromophore of Cenrod_2641 are indicated by the darker colors; hypothetical photocycles are in faded colors. (B) Red/far-red photocycle of Cenrod_2641. The gene corresponding to Cenrod_2641 was co-expressed with heme oxygenase, which produces biliverdin (BV) from heme when expressed in E. coli . Purified Cenrod_2641 was characterized by absorbance spectroscopy before and after illumination with 700 ± 20 nm light. The (Before - After) difference spectrum is shown, with peak wavelengths indicated. (C) Dark reversion of the 750 nm photoproduct was characterized. Cenrod_2641 was held at photoequilibrium under 700 nm illumination. Illumination was then discontinued, and absorbance at 710 nm was monitored as a function of time. Data were biphasic, with the second phase only poorly resolved due to low signal-to-noise. We therefore fit the data to a single exponential with a linear second phase (equivalent to burst kinetics), deriving a rate constant of 0.2 s -1 for the fast initial phase. (D) Comparison of the dark-adapted absorption spectrum of Cenrod_2641 (red curve, arbitrary scale) to the absorption spectrum of intact consortia (black curve, arbitrary scale) and to the integrated number of accumulated consortia per 12 nm interval (bars, the scotophobotactic response of the consortia) (data from [ 13 ]). (E) . Absorption spectrum of recombinant CpcA-PEB produced in Escherichia coli . BV, the precursor of phycoerythrobilin (PEB), was produced by Cenrod_2641 (heme oxygenase) and converted to PEB when cells were grown under oxic conditions. No red-colored/gold-fluorescent CpcA-PEB was produced under anoxic conditions, showing that the heme oxygenase encoded by Cenrod_2642 requires oxygen as a co-substrate for heme cleavage. Members of the phytochrome superfamily are thus likely candidate sensors for red-light phototaxis in consortia. Such proteins require linear tetrapyrrole (bilin) chromophores synthesized from heme for photosensory function; in particular, bacteriophytochromes incorporate biliverdin (BV) [ 60 - 62 ]. BV is synthesized from heme by heme oxygenase [ 63 ]. Although Chl. chlorochromatii completely lacks genes encoding known photosensors, the “ Ca. S. mobilis” genome encodes four bacteriophytochromes (Cenrod_1152, Cenrod_1743, Cenrod_2116, and Cenrod_2641) and heme oxygenase (Cenrod_2642) (Figure 5 A). The bacteriophytochrome genes encode the conserved PAS-GAF-PHY photosensory region required for photoperception by phytochromes, but they exhibit diverse domain architectures that implicate signaling pathways similar to those reported for Synechocystis sp. PCC 6803 (Figure 5 A). There are two histidine kinases, one of which also contains a REC domain. Another bacteriophytochrome has GGDEF, EAL, and MCP domains. The fourth protein, Cenrod_2641, lacks apparent output domains, like PixD from Synechocystis sp. PCC 6803. Cenrod_2641 is encoded in an apparent operon with the sole heme oxygenase gene (Cenrod_2642) found in the “ Ca. S. mobilis” genome. The “ Ca. S. mobilis” genome thus strongly implicates bacteriophytochromes encoded by the central rod as sensors for phototaxis, with multiple signaling pathways responding to red/far-red light. We expanded on these results by confirming that one of the putative photosensory proteins (Cenrod_2641) encoded by the “ Ca. S. mobilis” genome, as well as its cognate heme oxygenase (Cenrod_2642), are functional. We heterologously expressed Cenrod_2641 in Escherichia coli strains that allowed the co-expression of BV or two other linear tetrapyrroles, phycocyanobilin and phytochromobilin [ 64 ]. Recombinant bacteriophytochromes produced in these three strains were purified and characterized by absorbance spectroscopy. All three samples had similar absorption spectra with maximal absorption at approximately 710 nm, which suggested that only biliverdin was efficiently incorporated into the protein [ 65 ]. Similar to other phytochromes [ 66 , 67 ], Cenrod_2641 photoswitched between a thermally stable dark state and a photoproduct having distinct spectral properties. Upon illumination of the long-wavelength absorption band with 700 nm light, peak absorbance at 706 nm decreased with concomitant formation of a photoproduct at 754 nm (Figure 5 B). The photoproduct rapidly converted back to the dark form in the dark (Figure 5 C); this process was sufficiently rapid to allow Cenrod_2641 to function as an effective intensity sensor for far-red light [ 58 , 68 , 69 ]. These results showed that Cenrod_2641 has photochemical properties compatible with those of a bona fide photosensor with high affinity for BV. Figure S3 in Additional file 1 shows a phylogenetic tree that includes bacteriophytochrome sequences from a variety of bacteria, most of which are found in members of the Proteobacteria. The Cenrod_2641 bacteriophytochrome produces a clade with sequences from two members of the genus Methylomicrobium . Although distantly homologous bacteriophytochromes occur in some members of the Comamonadaceae as well as other Betaproteobacteria, the bacteriophytochrome encoded by Cenrod_2641 is nested among sequences from Gammaproteobacteria. This result suggests that the gene encoding this bacteriophytochrome (and probably the associated heme oxygenase; data not shown) were acquired by “ Ca. S. mobilis” via horizontal gene transfer from a member of the Gammaproteobacteria. The putative heme oxygenase (Cenrod_2642) was substituted for a functional cyanobacterial heme oxygenase in an E. coli strain that can produce a highly fluorescent CpcA protein when BV is converted into phycoerythrobilin (PEB) by PebS and ligated to CpcA by the phycobiliprotein lyase, CpcE/CpcF [ 64 ]. As shown in Figure 5 E, PEB was produced and ligated to CpcA (λ max = approximately 556 nm) when Cenrod_2642 functionally replaced heme oxygenase in this system under oxic conditions but not under anoxic conditions (data not shown). These results confirm that “ Ca. S. mobilis” produces BV for one and up to four bacteriophytochromes, which should allow photoperception in the wavelength range 700 to 760 nm. This wavelength range matches the action spectrum for the scotophobic response of “Chlorochromatium aggregatum” (Figure 5 D) [ 13 ]. Although light sensing by non-phototrophic bacteria has previously been described in several organisms, in most cases it is associated with protection from reactive oxygen species produced by the interaction of light and photosensitizing molecules [ 60 , 70 ]. The occurrence of scotophobotaxis by a non-phototrophic bacterium - that is, taxis to remain in the light - is extremely rare if not unprecedented. This finding does not completely exclude the original proposal that light is absorbed by chlorosomes and other components of the photosynthetic apparatus of the epibiont cells, which then transmit a signal to “ Ca. S. mobilis”. The scotophobic response in “ Ca. S. mobilis” may have initially been selected and fine-tuned by metabolic signaling (for example, metabolite transfer) from the epibiont to the central rod in the consortium (see below). However, light sensing mediated by bacteriophytochrome(s) is obviously expected to be more direct and to have a more rapid effect on the swimming behavior of “ Ca. S. mobilis”. “ Ca. S. mobilis” also appears to sense many chemical signals. The “ Ca. S. mobilis” genome is enriched in chemotaxis genes, and most of these genes occur in multigene families, including 33 MCP proteins. It is difficult to predict attractants or repellents for non-photosensory MCPs. Some MCP genes are clustered with genes encoding periplasmic solute-binding proteins, which suggests that these MCPs function as signal transducers. Proteins putatively binding phosphate (Cenrod_1484), amino acids (Cenrod_0096) and oligopeptides (Cenrod_0130) were clustered with MCPs, which strongly suggests that cells can probably sense and swim towards (or away from) these compounds. A binding protein for dicarboxylates (Cenrod_1184) might also interact with MCPs, and this might explain chemotaxis of “Chlorochromatium aggregatum” towards 2-oxoglutarate. It is unknown whether chemotaxis towards sulfide is achieved through a similar mechanism, because proteins for sensing sulfide have not yet been identified. However, given the current lack of understanding about such proteins, sulfide sensing remains a strong possibility for these proteins. Chemotaxis towards compounds excreted by the epibiont, for example, amino acids, could indirectly contribute to taxis towards sulfide, because the excretion of amino acids and other fixed carbon and nitrogen compounds by the epibiont should directly depend on the availability of light and sulfide. However, responses to excreted compounds would probably be much slower than any intracellular mechanism(s) possessed by “ Ca. S. mobilis”. Chemical signals sensed by the binding proteins could also have effects on cellular processes other than taxis. Signal transduction between “ Ca. S. mobilis” and Chl. chlorochromatii is suggested by at least one previous experiment [ 44 ]. Epibiont and central rod cells divide synchronously, and this is presumably coordinated by signaling molecules exchanged between the partners. Such signal transduction might be achieved by mechanisms similar to that of chemotaxis. It is possible that some of the above-mentioned MCP-like proteins participate in regulation of cell cycles as in Myxococcus xanthus [ 71 ]. In addition to MCPs, many genes encoding membrane-bound signal transduction proteins, such as two-component system proteins or proteins containing EAL and/or GGDEF domains, are often clustered with periplasmic solute-binding proteins. Proteins containing these domains have been shown to participate in swarming and cell surface adhesion [ 72 ], which is essential for formation of consortia. Potential interspecies electron transfer Besides metabolite exchange and motility, interspecies electron transfer would be extremely advantageous to the consortium in its energy-limited niche. Chl. chlorochromatii relies on having a constant supply of sulfide to provide the electrons it requires for carbon dioxide fixation and growth. Any interaction that increases the availability of sulfide (or electrons) would enhance growth. It was once thought that a sulfur cycle might occur between the two partners. The central bacterium might reduce oxidized sulfur compounds and return the products to the epibiont [ 73 ], which would be similar to the sulfur cycling that occurs in a syntrophic co-culture of Chlorobium vibrioforme and Desulfuromonas acetoxidans [ 74 ]. This hypothesis was supported by an in situ study that concluded that the increase in biomass by “Pelochromatium roseum” far exceeded the maximum possible CO 2 fixation that could be associated with oxidation of sulfide reaching the chemocline from below [ 34 ]. Direct photo-assimilation of acetate and electrons derived from sulfur cycling between consortia and associated sulfate-reducers were suggested as mechanisms to overcome this shortfall. However, because “ Ca. S. mobilis” is a member of Betaproteobacteria, and within the Proteobacteria all known sulfate-reducers are members of the Deltaproteobacteria, a sulfur cycling mechanism seemed unlikely to occur in the consortia . The genomic data are consistent with predictions based on phylogenetic associations. The “ Ca. S. mobilis” genome does not contain known genes for the reduction of sulfate or sulfur to sulfide [ 75 ]. The genomic data were searched for other possible mechanisms of interspecies electron transfer. However, other than the two NiFe-hydrogenases described above, only one other set of electron transfer-related proteins was identified. The “ Ca. S. mobilis” genome encodes six genes (Cenrod_1907 to 1912) that have some sequence similarity to subunits of formate hydrogenlyase (Hyf subunits B, C, E, F, G, and I) [ 76 ] as well as modules of some other electron transfer complexes, including the Mbx complexes thought to be involved in sulfur reduction [ 77 ]. The occurrence of highly similar gene clusters in more than 300 bacteria, including free-living members of the Comamonadaceae that do not live in sulfidic environments, strongly suggests that this complex is not involved in sulfur reduction. Cenrod_1908 exhibits homology with the large subunit of NiFe-hydrogenase but lacks the required L1 and L2 cysteine ligands required to coordinate the NiFe cofactor [ 78 ], which implies that this complex is not involved in H 2 cycling. This complex possibly plays a role in coupling menaquinone oxidation/reduction to proton translocation, but the redox partner for this process and its directionality are presently uncertain. Quinone exchange is a potential mechanism for electron shuttling between the two partners of the consortium. “ Ca. S. mobilis” lacks genes for either of the two known pathways for menaquinone biosynthesis [ 79 - 81 ], and it has an incomplete ubiquinone biosynthesis pathway. However, all free-living members of the Comamonadaceae can synthesize ubiquinone, and these organisms universally have two genes, ubiH/coq6 and ubiF / coq7 , which encode oxygen-dependent enzymes that are missing from the genome of “ Ca. S. mobilis” (Figure 6 ; Table S2 in Additional file 2 ). Either “ Ca. S. mobilis” lacks the ability to synthesize isoprenoid quinones, or it has acquired or evolved unknown genes to replace the activities of these two missing enzymes. The latter seems highly unlikely because only menaquinone-7 and no ubiquinone was detected in intact consortia and cell fractions enriched in “ Ca. S. mobilis” (Figure S3 in Additional file 1 ). Figure 6 Ubiquinone biosynthesis pathway of “ Ca . S. mobilis”. This pathway is compared with the ubiquinone biosynthesis pathways found in 15 members of the Comamonadaceae, including the 8 listed in the Figure 2 legend as well as 3 additional Acidovorax spp., 2 additional Comamonas spp., one additional Polaromonas sp. and one additional Variovorax sp. The ubiC gene was identified in only one of the 15 genomes, possibly because of its extremely low sequence similarity and conservation across species. The ubiH/coq6 and ubiF/coq7 genes are highly conserved and were identified in each of the 15 reference genomes, but these genes were not found in “ Ca . S. mobilis”. The genomic data, however, strongly suggest that “ Ca. S. mobilis” cells utilize quinones. At least four important electron-transport complexes (type-1 NADH dehydrogenase, succinate dehydrogenase, cytochrome bd -type quinol oxidase, and sulfide:quinone reductase) that are encoded in the “ Ca. S. mobilis” genome require a quinone substrate. The presence of these genes strongly suggests that quinones are available to the central bacterium; otherwise, these genes should have been partially or completely lost. Extracellular transfer of quinones has previously been described from wild-type Shewanella putrefaciens to a mutant that was unable to synthesize menaquinone [ 82 ]. Similarly, respiration can be activated in Group B Streptococcus spp. by menaquinone synthesized by Lactococcus lactis [ 83 ]. Finally, exchange of a water-soluble intermediate, 1,4-dihydroxy-2-naphthoic acid, can satisfy the quinone requirement of members of dental plaque [ 84 ]. Thus, we hypothesize that menaquinone-7, or a soluble quinone intermediate synthesized by Chl. chlorochromatii , can be transferred to “ Ca. S. mobilis”. The availability of quinones for respiration in “ Ca. S. mobilis” solves only one of two problems. Consortia are usually cultivated under strictly anoxic conditions in the laboratory and thus should not have any terminal electron acceptor for respiration. Although “ Ca . S. mobilis” can probably produce ATP by fermentation of glucose under anoxic conditions as described above, an energetically more favorable solution would involve bidirectional quinone transfer and sharing of the resulting protonmotive force. Quinones transferred to “ Ca . S. mobilis” would allow energetically more favorable electron transfer processes to occur in the central bacterium, and electrons returned by quinols to the epibiont could be reused for CO 2 fixation. Although this process does not involve sulfide, it produces results similar to sulfur cycling. The exchange of electrons and shared proton-motive force would be beneficial to both symbiotic partners and would additionally allow ATP synthesis in the central rod to be directly coupled to the light reactions of photosynthesis in the epibiont. This might partly explain the phototactic and chemotactic behavior of the central bacterium, and this could additionally explain the substantial loss of genes for energy metabolism from the central bacterium (Figure 3 ). Fermentation could still provide ATP for the central bacterium under anoxic conditions in the dark. For either sulfide- or quinone-dependent electron shuttling and shared proton-motive force to occur, symbiosis-specific, specialized cell wall structures would likely be required. The central rod and epibiont cells are joined by numerous ‘periplasmic tubules’ [ 17 ], which are reminiscent of the bacterial nanowires that have recently been found in many organisms, including Geobacter sulfurreducens and Shewanella oneidensis and between organisms in syntrophic co-cultures of Pelotomaculum thermopropionicum and Methanothermobacter thermoautotropicus . Electrically conductive nanowires in these organisms have been proposed to be conduits for extracellular or interspecies electron transfer [ 85 , 86 ]. The electron carriers in some cases appear to be cytochromes, but other electron carrier molecules could function in organisms devoid of cytochromes [ 85 , 87 ]. The periplasmic tubules of phototrophic consortia could have similar functions, and quinone-like molecules, whether soluble or shuttled by proteins, might facilitate electron exchange between “ Ca. S. mobilis” and Chl. chlorochromatii . Periplasmic tubules are larger in diameter than pili and bacterial nanowires, and they connect the outer membranes of the two cell types, thus creating a joint periplasmic space between the epibionts and central bacterium [ 17 ]. Periplasmic tubules thus provide a mechanism for sharing proton-motive force generated by the proposed electron shuttle between the two organisms. The potential schemes for interspecies electron transfer hypothesized here will obviously have to be tested experimentally in the future. Nevertheless, they provide an additional perspective for the symbiotic relationship of phototrophic consortia. Electron shuttling and shared protonmotive force would join metabolite exchange and phototaxis/chemotaxis in creating a strong, competitive advantage for consortia over free-living members of the GSB."
} | 11,560 |
30275914 | PMC6161606 | pmc | 4,068 | {
"abstract": "ABSTRACT This paper proposes a bimorph piezoelectric vibration energy harvester (PVEH) with a flexible 3D meshed-core elastic layer for improving the output power while lowering the resonance frequency. Owing to the high void ratio of the 3D meshed-core structure, the bending stiffness of the cantilever can be lowered. Thus, the deflection of the harvester and the strain in the piezoelectric layer increase. According to vibration tests, the resonance frequency is 15.8% lower and the output power is 68% higher than in the conventional solid-core PVEH. Compared to the solid-core PVEH, the proposed meshed-core PVEH (10 mm × 20 mm × 280 μm) has 1.3 times larger tip deflection and the maximum output power is 24.6 μW under resonance condition at 18.7 Hz and 0.2G acceleration. Hence it can be used as a power supply for low-power-consumption sensor nodes in wireless sensor networks.",
"conclusion": "Conclusions In this study, we confirmed the validity of the bimorph PVEH where a 3D meshed-core structure acts as an elastic layer. First, in the FEM analysis section, we demonstrated that the bending stiffness can be adjusted by changing the line spacing of meshed-core structure. Second, we showed the fabrication process of the 3D meshed-core PVEH by inclined photolithography and a simple bonding process. According to vibration tests, the resonance frequency of the meshed-core PVEH was 26% lower and the tip deflection was 1.3 times larger as compared to the solid-core PVEH. The maximum attained electrical output, 24.6 µW, is suitable for powering sensor nodes in wireless sensor networks. In conclusion, in this paper, we proposed a method for improving the output power and lowering the resonance frequency without any change in the material, device size, and basic fabrication process.",
"introduction": "Introduction With the growing performance of low-power-consumption devices and the rapid development of Internet of Things (IoT) communication technology, it is said that the era of trillion sensors is arriving. Meanwhile, the power supply required for the enormous number of sensor nodes is a major issue [ 1 – 3 ]. Thus, as a battery for self-powered sensor, energy harvesting has attracted much research attention. Energy harvesting is one of the powering technologies that obtains electric power from external small energy sources, and is expected to omit the need for replacing and charging conventional button batteries. Light, heat, radio waves, and vibration have been extensively studied as sources of energy harvesting. Among them, vibration has been drawing considerable attention because vibration energy has relatively high energy density, and is independent of the operating environment and weather [ 4 ]. Although many vibration energy harvesters have been studied, most of them operate at relatively high external frequencies (above 100 Hz) [ 5 , 6 ]. They are inefficient at low-frequency (under 20 Hz) or low-acceleration (0.1 to 1 G) conditions which relate to various human activities, bridge vibration, and house appliances. Some studied harvesters can operate at low frequencies, but they are either too large to be wearable, or their electrical output is insufficient for powering typical consumption devices [ 7 – 9 ]. Vibration energy harvesting is categorized into three types: electrostatic, electromagnetic, and piezoelectric. Piezoelectric vibration energy harvesters (PVEHs) exhibit (1) simple configuration, (2) high output voltage, and (3) high compatibility with microfabrication technology [ 10 , 11 ]. Many unimorph cantilever-type harvesters (i.e. consisting of a piezoelectric film and an elastic layer to support the piezoelectric film and to control vibration characteristics) have been proposed for PVEHs [ 12 – 16 ]. Because the configuration of a unimorph cantilever is simple and the fabrication process is relatively easy, many unimorph harvesters are fabricated using piezoelectric materials such as lead zirconate titanate (PZT) and polyvinylidene fluoride (PVDF). However, their output power is low because there is only one piezoelectric layer. Moreover, to harvest electric energy from low-frequency band vibration, it is necessary to select a flexible material for the elastic layer so as to lower the resonance frequency, because the types of the piezoelectric materials are limited. However, if the elastic layer becomes flexible, the neutral axis is shifted from the elastic layer side toward the piezoelectric layer side. This shift reduces both the output power and the strain generated in the piezoelectric layer. Therefore, it is difficult to achieve both low resonance frequency and high output power in a unimorph cantilever-type vibration energy harvester. On the other hand, in a bimorph cantilever-type vibration energy harvester [ 17 , 18 ], the elastic layer is sandwiched between two piezoelectric layers. Unlike in the unimorph cantilever, in the bimorph type, the neutral axis is usually at the center of the cantilever regardless of the Young’s modulus and thickness of both piezoelectric and elastic layers. Therefore, by increasing the film thickness of the elastic layer, the distance between the neutral axis and the piezoelectric film can be increased. Hence, the amount of strain in the piezoelectric layers increases under certain deflection, and consequently, the amount of generated power increases as compared to the unimorph type. In addition, several methods have been reported for increasing the output power by optimizing the cantilever shape and thickness of each layer have been reported [ 19 – 21 ]. Hence, the bimorph configuration is effective in improving the amount of output power. However, along with an increase in the elastic layer’s thickness and optimization of the shape for power improvement, the resonance frequency also increases. Additionally, the resonance frequency increases with the miniaturization of the device size. Hence, it is difficult to achieve both improvements in output power and reduction in resonance frequency. Therefore, in this study, we fabricate a bimorph cantilever-type PVEH incorporating a flexible 3D meshed-core elastic layer. The flexible 3D meshed-core elastic layer can lower the bending stiffness and increase the cantilever deflection while maintaining the distance between the neutral axis and the piezoelectric layer. This approach can lower the resonance frequency while improving the output power without any change in the composed material, device size, and basic fabrication process.",
"discussion": "Results and discussion \n Figure 10 shows the output voltage waveform of the fabricated PVEHs under resonance condition. In both meshed- and solid-core PVEHs, the measured output voltage of load resistance shows a sinusoidal wave for the input sinusoidal excitation. The frequency of the output voltage coincides with that of the input sinusoidal waveform. In the meshed-core PVEH, the output voltage is 42.6% higher than that of the solid-core type. In addition, the maximum output voltage is 20.4 V for the meshed-core PVEH and 14.1 V for the solid-core type. The output voltage is measured under the resonance condition with optimum load resistance and the 0.2 G excitation acceleration. 10.1080/14686996.2018.1508985-F0010 Figure 10. Sinusoidal measured voltage of load resistance under each resonance condition (meshed-core 18.7 Hz, solid-core 22.2 Hz), optimum load resistance (meshed-core 17 MΩ, solid-core 13 MΩ), and 0.2 G acceleration. \n \n Figure 11 shows the maximum output power as a function of load resistance value. The output power represents the power consumption at the load resistance when the load resistance value is varied from 1 to 31 MΩ. Here, the result is measured under the resonance condition for each harvester. From the resistance value response of the output power, the optimum load resistance is 17 MΩ for the meshed-core PVEH and 13 MΩ for the solid-core type. These measured load resistance values are relatively high compared to those of the vibration energy harvesters using PZT or barium titanate as the piezoelectric material. The first reason for the high optimum load resistance values is the low resonance frequency such as about 20 Hz. Second is the lowered total capacitance by connecting the piezoelectric films in series. Third is the low relative permittivity of the piezoelectric PVDF film. Although the frequency depends on the external vibration and cannot be controlled, the optimum load resistance value can be reduced by connecting the PVDF films in parallel and improving the electrical properties of the material. 10.1080/14686996.2018.1508985-F0011 Figure 11. Maximum output power as a function of load resistance under each resonance condition (meshed-core 18.7 Hz, solid-core 22.2 Hz) and 0.2 G acceleration. \n \n Figure 12 shows the frequency response from 1 to 40 Hz. In the meshed-core PVEH, the maximum output power is 24.6 μW, which is 68.5% higher than that of the solid-core type. This is because the bending stiffness of the bimorph cantilever is lowered by using the 3D meshed-core structure with voids. In other words, the amount of strain occurring in the piezoelectric film, as well as the amount of power generation, increases as the tip deflection increases due to the low bending stiffness. Furthermore, the resonance frequency is 18.7 Hz for the meshed-core PVEH and 22.2 Hz for the solid-core type. Here, the meshed-core type shows 15.8% lower resonance frequency than the solid-core type due to the low bending stiffness of the meshed-core structure. Besides the flexible characteristics of the 3D meshed-core elastic layer, both elastic layer and piezoelectric films are made of a polymer material. This is why the low resonance frequency, under 20 Hz, can be realized even in a small bimorph-type vibration energy harvester. Here, these experimental results – the results of output power and resonance frequency – agree with the value and tendency of the piezoelectric coupling analysis result. The cause of the errors between the experimental and FEM analysis is the difference in the detailed physical, mechanical, and piezoelectric parameters. For a better agreement with the results, it is necessary to measure and set the parameters more precisely. 10.1080/14686996.2018.1508985-F0012 Figure 12. Maximum output power as a function of vibration frequency under each optimum load resistance (meshed-core 17 MΩ, solid-core 13 MΩ) and 0.2 G acceleration. \n \n Table 3 presents the measured results and calculated values under resonance condition, including the effective voltage, average power, the effective voltage, average power, and tip deflection. Here, the resonance frequency is lower compared with other piezoelectric cantilever-type vibration energy harvesters [ 4 , 5 , 27 ]. 10.1080/14686996.2018.1508985-T0003 Table 3. Experimental results of meshed- and solid-core PVEHs. Meshed-core Solid-core Resonance frequency [Hz] 18.7 22.2 Effective voltage of load resistance (RMS) [V] 14.4 10.1 Average output power [μW] 12.3 7.3 Tip deflection [mm] 6.0 4.6 \n In summary, the performance of the bimorph-type vibration energy harvester is improved by the flexible 3D meshed-core structure of the elastic layer without changing the composed material, harvester size, and the basic fabrication process. Therefore, the approach for making the elastic layer flexible is effective for the bimorph-type PVEHs. Moreover, as reported in previous studies [ 19 – 21 ], the output power can be further improved by optimizing the shape and size and the resonance frequency can be further decreased by adjusting the weight of the proof mass. Furthermore, to obtain high output power at low frequencies, it is necessary to improve both piezoelectric constant and the electromechanical coupling coefficient of flexible piezoelectric polymer materials. In the proposed method, the flexibility of the elastic layer is adjusted by 3D microstructure, and the limit in the device design depends on the flexibility of the piezoelectric material. In addition, when the flexibility of the piezoelectric material becomes higher than the flexibility of the elastic layer, the neutral axis enters the piezoelectric layer and the strain amount decreases in commonly studied unimorph-type PVEHs. Therefore, if more flexible piezoelectric materials are obtained, it is possible to further enhance the performance of the proposed method. Moreover, the piezoelectric constant of piezoelectric polymer such as PVDF is several tens of pC/N, which is 5 to 10 times inferior to inorganic ceramic materials [ 28 , 29 ]. Also, the electromechanical coupling coefficient of piezoelectric polymer is as small as five times that of inorganic ceramics [ 28 , 29 ]. Thus, improvement of these material properties is desired. In addition to that, it is desirable to reduce the cost of materials and fabrication process for the realization of IoT services. If these issues could be solved, the number of practical low-frequency vibration energy harvesters would increase."
} | 3,253 |
33432323 | PMC8023429 | pmc | 4,070 | {
"abstract": "Abstract \n Schlegelella thermodepolymerans is a moderately thermophilic bacterium capable of producing polyhydroxyalkanoates—biodegradable polymers representing an alternative to conventional plastics. Here, we present the first complete genome of the type strain S. thermodepolymerans DSM 15344 that was assembled by hybrid approach using both long (Oxford Nanopore) and short (Illumina) reads. The genome consists of a single 3,858,501-bp-long circular chromosome with GC content of 70.3%. Genome annotation identified 3,650 genes in total, whereas 3,598 open reading frames belonged to protein-coding genes. Functional annotation of the genome and division of genes into clusters of orthologous groups revealed a relatively high number of 1,013 genes with unknown function or unknown clusters of orthologous groups, which reflects the fact that only a little is known about thermophilic polyhydroxyalkanoates-producing bacteria on a genome level. On the other hand, 270 genes involved in energy conversion and production were detected. This group covers genes involved in catabolic processes, which suggests capability of S. thermodepolymerans DSM 15344 to utilize and biotechnologically convert various substrates such as lignocellulose-based saccharides, glycerol, or lipids. Based on the knowledge of its genome, it can be stated that S. thermodepolymerans DSM 15344 is a very interesting, metabolically versatile bacterium with great biotechnological potential.",
"introduction": "Introduction Polyhydroxyalkanoates (PHA) are polyesters of hydroxyalkanoic acids. As the PHA are produced naturally by microbial fermentation, they can be regarded as an environmental friendly alternative to petroleum-based polymers ( Muhammadi et al. 2015 ; Sabapathy et al. 2020 ). Although some facts regarding PHA fermentation are known, for example, microorganisms use PHA to store unused energy and carbon into cytoplasm in a form of intracellular granules and these granules help the organism to cope with stressors ( Obruca et al. 2018 ), additional basic knowledge is needed to establish viable industrial processes. Although production of bioplastics is considered to be the future way and inseparable part of circular economy, less than 1% of the total plastic production comes from bioplastics industry ( Shogren et al. 2019 ). The type strain S. thermodepolymerans DSM 15344 is a thermophilic, Gram-negative bacterium that was originally investigated for its ability to degrade extracellular PHA materials such as copolymers of 3-hydroxybutyrate and 3-mercaptopropionate ( Elbanna et al. 2003 ). So far, two draft genome assemblies of the strain were published. The assembly available under the GenBank accession number GCA_002933415.1 submitted by Zhejiang Academy of Agricultural Sciences consists of 48 contigs with N50 length of 174,537 bp and the assembly GCA_003349825.1 by DOE Joint Genome Institute contains 28 scaffolds with N50 length of 324,832 bp. Although these represent relatively high-quality draft assemblies, probably due to missing high-quality complete genome assembly and functional annotation of the genome, other important features of the strain remained hidden. Only recently, its ability to produce PHA was reported together with the unique capability of xylose utilization ( Kourilova et al. 2020 ). Optimal growth temperature of S. thermodepolymerans DSM 15344, 55 °C, reduces the risk of microbial contamination; therefore, the strain presents an ideal organism for utilization in the “Next Generation Industrial Biotechnology” concept in which biotechnological process is conducted under unsterile conditions ( Chen and Jiang 2018 ). In this article, we present its first high-quality complete genome sequence, which is currently a reference sequence for S. thermodepolymerans species in GenBank database. We annotated the genome, predicted the operon structure, and searched for prophage DNA and CRISPR arrays.",
"discussion": "Results and Discussion Genome Assembly and Properties \n Schlegelella thermodepolymerans DSM 15344 initial genome assembly was reconstructed from nearly 1.8 million Oxford Nanopore Technologies reads with a median read length of 4.9 kb and finalized by mapping more than 2.4 million high-quality (average Phred score Q ≈ 35) Illumina read pairs (88% of all Illumina reads) to the initial assembly. Whole process resulted into the final assembly consisting of one circular chromosome with coverage exceeding 5,500×. The genome has been deposited at the DDBJ/EMBL/GenBank under accession number CP064338.1 . The genome length is 3,858,501 bp and contains 3,650 genes in total, divided into 1,729 operons. Most of the genes are protein-coding sequences (CDSs), but 33 pseudogenes were also found, which is less than 44 and 50 pseudogenes detected in previously published draft genome sequences PSNY00000000.1 and QQAP00000000.1, respectively. The GC content reached the value of 70.28% which is more than the average for Gram-negative bacteria ( Li and Du 2014 ). However, it met our expectations, as it corresponded to the value 70.3% of the previously published draft genomes. High GC content can be associated with the adaptation of the bacterium to high-temperature environments. Although only single copies of rRNA genes were detected in draft genomes of S. thermodepolymerans DSM 15344, the complete genome sequence contains 5S, 16S, and 23S rRNA genes in duplicates. Moreover, copies of 16S and 23S rRNA genes differ in three and one positions, respectively. Such information is useful for future identification of S. thermodepolymerans in metagenomics studies and quantification of its abundance in microbial studies based on amplicon sequencing. The overall sequence features are summarized in table 1 . Table 1 Genomic Features of Schlegelella themordepolymerans DSM 15344 Feature Chromosome Length (bp) 3,858,501 GC content (%) 70.28 Genes 3,650 Operons 1,729 CDS 3,589 Pseudogenes 33 rRNA (5S, 16S, 23S) 2, 2, 2 tRNA 51 ncRNA 4 Functional Annotation The protein-coding genes were classified according to COG into 22 categories. In total, 2,576 CDSs were assigned a COG category with the most prevalent groups E—amino acid metabolism and transport containing 7.80% of the total number of CDS (280 out of 3,589) and C—energy production and conversion containing 7.52% of the total number of CDS (270 out of 3,589). This suggests that S. thermodepolymerans has a functional apparatus capable of utilizing a wide range of substrates as reported recently ( Kourilova et al. 2020 ). Unfortunately, 9.33% (335 genes) were not assigned any COG and 18.89% (678 genes) were assigned group S with an unknown function. In fact, such a result was expected as only a little is known about genomes of thermophilic bacteria capable of PHA synthesis so far. (For details of each group, including the number of assigned genes assigned see supplementary table S1 , Supplementary Material online.) The position of individual features in the circular genome is shown in figure 1 . Each COG is marked with a different color. Moreover, RNAs are divided into tRNA, rRNA, and ncRNA categories and displayed in the fourth outermost circle. Fig. 1 A chromosomal map of the S. thermodepolymerans DSM 15344 genome. The first two outermost circles represent CDSs on the forward and backward strands, respectively; the third circle represents pseudogenes. The colors represent the functional classification of COG. The fourth outermost circle represents RNA genes, distinguishing among tRNA, rRNA, and ncRNA. The inner area represents the GC content and GC skew. Searching for viral DNA resulted only in inconclusively identified prophages. Although Prophage Hunter identified five putative prophages, PHASTER results consisted of a single incomplete prophage that overlapped with one candidate indentified by Prophage Hunter. None of these phages was identified as active. This is according to our expectations as phages are viruses for which temperature is a crucial factor for survivability ( Nasser and Oman 1999 ). Optimal temperature for growth of the strain (55 °C) is too high for most phages ( Farrell and Campbell 1969 ). Although a group of thermophilic phages also exists, they usually occur in specific environment ( Jończyk et al. 2011 ) and were not identified in the S. thermodepolymerans DSM 15344 genome. Only a single 164-bp-long CRISPR array containing two spacer units was found in the S. thermodepolymerans DSM 15344 genome. Unfortunately, no cas or cas -like genes were found in its neighborhood. Nevertheless, this does not prevent the CRISPR-Cas9 being utilized for S. thermodepolymerans DSM 15344 genome editing as a foreign system could be used."
} | 2,178 |
32494605 | PMC7250678 | pmc | 4,071 | {
"abstract": "Capillary networks controlled by simple low-voltage gates open up new possibilities for fluid delivery in point-of-care assays.",
"introduction": "INTRODUCTION The use of microfluidics in lab-on-a-chip devices has already proven its benefits for a broad range of applications, including diagnostics, biochemistry, preclinical research, and cell biology, by reducing the time to results and the consumption of reagents while increasing the throughput of assays ( 1 – 3 ). Despite these strengths, most microfluidic implementations still rely on cumbersome methods to displace liquids, including complex components such as valves, actuators, pumps, and responsive materials ( 4 , 5 ), and involve labor-intensive sample and chip preparation steps. These practical challenges contribute to limiting the scalability, portability, adoption, and commercialization of these devices, particularly if they are developed for point-of-care (POC) diagnostics applications ( 6 ). After the pioneering work from the Quake’s group ( 7 ), monolithically integrated pneumatic valves have become a popular strategy for the scalable and programmable manipulation of liquids in microfluidic channels. However, such a manipulation has been typically addressed by developing complex microfluidic devices with moving structures and using bulky, specialized, and expensive peripherals, which also often require technically skilled users. A myriad of other integrated liquid control strategies, including manual ( 8 ), electrical ( 9 ), chemical ( 10 ), optical ( 11 ), magnetic ( 12 ), and thermal ( 13 ) actuation, have been developed, but they generally lack programmability and real-time feedback and still suffer from fabrication complexities and known issues associated with high-throughput manufacturing and integration of polydimethylsiloxane (PDMS) and hydrogels. Digital microfluidics have emerged as an appealing alternative to program biochemical reactions precisely using droplets manipulated by means of various actuation principles without needing moving parts ( 14 ), such as electrowetting-on-dielectric (EWOD), dielectrophoresis, surface acoustic waves, and magnetic forces. Among these principles, EWOD has become the most extensively used technique, yet it has several practical issues, such as the need for an immiscible oil phase to separate aqueous samples, high-voltage sources, hydrophobic coatings, transparent electrodes, and tens, if not hundreds, of external electrical contacts to address individual electrodes in high-density arrays ( 15 ). A continuous flow of samples, reagents, or particles passing through specific areas of a device is instead preferred or needed for most of applications covered by microfluidics ( 16 , 17 ). For POC devices particularly, such a flow is generated using capillary action because it does not require peripheral equipment ( 18 ). This advantage is nevertheless hindered by limited flexibility in the flow control because the flow path and rate are defined by the design and materials and optimized for a specific assay. Following the work by the groups of Whitesides ( 19 ) and Yager ( 20 ), many research groups also spent substantial efforts to enhance the analytical performance of paper-based microfluidics by adding new functions to control the flow ( 21 ). We and other groups fabricated capillary-driven microfluidics with passive valves using precise structuring of hard materials, such as silicon, glass, and plastics ( 22 ). In general, it is challenging to implement precise, high-density, and programmable valves in paper microfluidics, and closed microfluidic channels implemented on other substrates suffer from complex fabrication, incompatibility with capillary-driven flow (e.g., hydrophobic polymers), and the difficulty of handling liquids (e.g., controlled merging or sequential delivery of liquids) without creating air bubbles. Here, we present a new approach to control liquids in capillary-driven microfluidics by realizing programmable liquid circuits using a set of key functions ( Fig. 1 ). Specifically with these circuits, (i) liquids can be stopped and routed where and when desired using a low-cost and portable peripheral device and a protocol applied from a smartphone, (ii) positions of the liquids can be monitored electronically, (iii) coflow or sequential flow of liquids can be generated, and (iv) synchronized and bubble-free merging of liquids can be done in closed and hydrophilic microchannels fabricated using high-throughput techniques. Stop-and-go flow control is based on e-gates ( 23 ), which use capillary pinning to stop flow based on Gibbs’ inequality condition ( 24 ) and a low voltage (<5 V) electrowetting effect ( 25 ) to resume it. We extend this concept in programmable liquid circuits by providing a multiplexing capability and smartphone control and combining it with passive capillary valves and self-vented channels for controlled merging and sequential delivery of multiple liquids in a compact and portable system. Fig. 1 Programmable liquid circuits implemented in capillary-driven microfluidics. Concept on controlling, monitoring, sequential delivery, and merging of multiple liquids flowing in microfluidic chips using an array of electrically actuated microfluidic gates (e-gates) and a protocol applied from a smartphone. Liquids pipetted to a capillary-driven microfluidic chip autonomously flow inside microfluidic channels by capillary action until the flow is stopped by pinning the liquid meniscus at a trench-patterned orthogonal to the flow path. The flow is resumed by applying a potential difference (<5 V) between the liquid (positive) and an electrode patterned over the trench (ground). The location of the meniscus is monitored using capacitance measurements as a feedback. Using capillary valves with air vents and self-vented channels and e-gates, pipetted liquids can sequentially flow through the same channel in any order and combination, and liquids flowing in opposite directions can be merged without creating air bubbles.",
"discussion": "DISCUSSION The concept of programmable liquid circuits presented here (i) enables the implementation of generic, programmable, and portable microfluidic systems that can be fabricated using high-throughput techniques; (ii) is simple to use; (iii) allows fast and reliable control of multiple liquids; and (iv) provides real-time feedback on the flow conditions of liquids. This concept combines e-gates with passive microfluidic valves and self-vented channels and has many advantages compared with other liquid-handling techniques. First, compared with microfluidic systems with actively pumped liquids, programmable liquid circuits do not require any labor-intensive preparation, such as preparing syringes and manually connecting tubings to microfluidic chips, and they can work with a small droplet of sample or reagent. Capillary forces are used to drive liquids without using any peripheral equipment to create a pressure gradient. The flow is stopped passively by capillary pinning at a trench; therefore, no external energy is required while holding the liquid in place, which can leave the necessary time for functions often implemented in microfluidics such as dissolving reagents, reactions, separating analytes, stimulating cells, etc. Activation of the flow is achieved by applying 3 to 5 V to a selected e-gate for less than 1 s. This allowed us to control many e-gates using a battery-operated device, which is about the size of a matchbox and communicates with a smartphone via Bluetooth. We also showed that the operation of chips is not compromised after 16 months of storage. Second, each e-gate can be individually monitored in real time using capacitance measurements as a feedback to the user (e.g., warning about a failure). In addition, such a feedback can be used in an algorithm to optimize the e-gate parameters and to run an assay protocol fully autonomously. Third, multiple e-gates can be connected to the same external electrical contacts to control continuous flows of multiple liquids in several locations, which is something that cannot be easily implemented in digital microfluidics using EWOD. Like many other techniques, programmable liquid circuits have limitations. First, the pinning capability of e-gates is challenged when solutions with surfactants, human serum, or whole blood are used. A stronger capillary pinning can be achieved by changing the geometry of the channel (e.g., wider channels), making the electrodes hydrophobic ( 23 ), or using a less hydrophilic film for the top sealing layer (fig. S6). Second, unlike mechanical valves, an e-gate can be activated and deactivated only once unless the bubble formed to stop the flow is removed electrochemically. If the flow of a liquid needs to be stopped and resumed repeatedly, an array of e-gates can be patterned along the flow path, preferably in the capillary pump. In addition, the chips are not meant to be reusable not only because it would not be practical to dry channels, which are filled with liquids, but also reusing the chips is not desirable for POC applications where cross-contamination between patients’ samples can be an issue. Third, although activating a single e-gate takes less than 1 s, connecting more e-gates to the same electrode results in an additional delay in the activation time (e.g., 10 s for 10 e-gates). If a fast response is critical for the application, this delay could be reduced by having the electrode biasing the liquid closer to each e-gate instead of having it only in the loading pad. This would also help improve the precision of the capacitance measurements for the feedback by reducing the distance and thus resistance between two electrodes. Fourth, we fabricate these circuits using silicon wafers and clean room processes, which are often considered “expensive” and not easily accessible by the research community working on microfluidics. This statement is generally true for high-end complementary metal-oxide semiconductor (CMOS) chips (e.g., microprocessors) or low-volume prototyping. However, there are many examples of microfluidic implementations benefiting from the unique properties of silicon and the well-established manufacturing infrastructure developed for processing it ( 40 ), a prominent and commercially successful one being the i-STAT POC device from Abbott. In addition, our process is simple and efficient: It requires only three photolithography masks, enables the fabrication and sealing of hundreds of chips simultaneously, and takes the advantage of precision to fit many e-gates in a small footprint, all potentially contributing to reduction in cost. The process is also CMOS compatible; therefore, high-density arrays of e-gates can be postfabricated on top of electronic chips and can be individually addressed using row/column selection. Moreover, we think that the concepts demonstrated here can be implemented in other materials, such as glass or hydrophilic polymers, as long as the manufacturing process enables the patterning of a capillary pinning structure and integrated electrodes. Programmable liquid circuits open exciting possibilities for lab-on-a-chip applications: Microfluidic devices can have generic architectures that can be controlled on demand using a smartphone or be fully automated with a protocol easily changed. For example, holding a liquid for tens of minutes can be used to study cells or reaction kinetics in immunoassays and molecular assays. Programming the delivery of samples, reagents, and rinsing buffers flowing sequentially or in parallel through the same channel can eliminate the need for manual actuation or sliding mechanisms [e.g., V-chip technology ( 41 )], cartridges loaded with reagents, and sophisticated lab-on-a-disk designs. Programmable liquid circuits can also be combined with our recent invention, self-coalescence modules ( 42 ), to realize sample-in-answer-out lab-on-a-chip devices having programmable and precise spatiotemporal control on the dissolution of integrated reagents. One particularly interesting application can be multiplexed homogenous phase assays, such as assays measuring multiple enzymatic reactions. It is typically challenging to synchronize the flow of the reagents and to measure the reaction kinetics of multiple analytes using a single reader. Here, programmable liquid circuits can ensure that all reagents arrive in desired areas in a timely manner, and specific enzymatic reactions can be quenched when desired for the acquisition of a stable, end-point signal using a reader. In addition, the concept can be used to pattern biomolecules on surfaces using cross flows without needing manual manipulation of channels as in the case of highly multiplexed micromosaic immunoassays ( 43 ). Self-vented channels may be used to address one of the main failure mechanisms in microfluidics, which is the formation of bubbles during the filling of microchannels, merging multiple liquids, or locally as a consequence of the assay protocol (e.g., electrochemistry, thermocycling in PCR, gaseous by-products). This concept also opens intriguing possibilities involving programming counterflows of different liquids. Liquids can be brought into contact with well-defined position, and starting time and reactions at the interface between liquids can be precisely studied or implemented, such as crystallization processes, diffusion processes, or kinetics (enzymatic reactions). In conclusion, the versatility, simplicity, and scalability of this concept provide a compelling technology for the development of portable, smart, and interactive lab-on-a-chip devices that can manipulate multiple liquids autonomously with minimal human intervention."
} | 3,434 |
31095388 | null | s2 | 4,073 | {
"abstract": "The electrically conductive pili of Geobacter sulfurreducens are of both fundamental and practical interest. They facilitate extracellular and interspecies electron transfer (ET) and also provide an electrical interface between living and nonliving systems. We examine the possible mechanisms of G. sulfurreducens electron transfer in regimes ranging from incoherent to coherent transport. For plausible ET parameters, electron transfer in G. sulfurreducens bacterial nanowires mediated only by the protein is predicted to be dominated by incoherent hopping between phenylalanine (Phe) and tyrosine (Tyr) residues that are 3 to 4 Å apart, where Phe residues in the hopping pathways may create delocalized \"islands.\" This mechanism could be accessible in the presence of strong oxidants that are capable of oxidizing Phe and Tyr residues. We also examine the physical requirements needed to sustain biological respiration via nanowires. We find that the hopping regimes with ET rates on the order of 10"
} | 250 |
27769259 | PMC5073922 | pmc | 4,074 | {
"abstract": "Background Engineering of single-species biofilms for enzymatic generation of fine chemicals is attractive. We have recently demonstrated the utility of an engineered Escherichia coli biofilm as a platform for synthesis of 5-halotryptophan. E. coli PHL644, expressing a recombinant tryptophan synthase, was employed to generate a biofilm. Its rapid deposition, and instigation of biofilm formation, was enforced by employing a spin-down method. The biofilm presents a large three-dimensional surface area, excellent for biocatalysis. The catalytic longevity of the engineered biofilm is striking, and we had postulated that this was likely to largely result from protection conferred to recombinant enzymes by biofilm’s extracellular matrix. SILAC (stable isotopic labelled amino acids in cell cultures), and in particular dynamic SILAC, in which pulses of different isotopically labelled amino acids are administered to cells over a time course, has been used to follow the fate of proteins. To explore within our spin coated biofilm, whether the recombinant enzyme’s longevity might be in part due to its regeneration, we introduced pulses of isotopically labelled lysine and phenylalanine into medium overlaying the biofilm and followed their incorporation over the course of biofilm development. Results Through SILAC analysis, we reveal that constant and complete regeneration of recombinant enzymes occurs within spin coated biofilms. The striking catalytic longevity within the biofilm results from more than just simple protection of active enzyme by the biofilm and its associated extracellular matrix. The replenishment of recombinant enzyme is likely to contribute significantly to the catalytic longevity observed for the engineered biofilm system. Conclusions Here we provide the first evidence of a recombinant enzyme’s regeneration in an engineered biofilm. The recombinant enzyme was constantly replenished over time as evidenced by dynamic SILAC, which suggests that the engineered E. coli biofilms are highly metabolically active, having a not inconsiderable energetic demand. The constant renewal of recombinant enzyme highlights the attractive possibility of utilising this biofilm system as a dynamic platform into which enzymes of interest can be introduced in a “plug-and-play” fashion and potentially be controlled through promoter switching for production of a series of desired fine chemicals. Electronic supplementary material The online version of this article (doi:10.1186/s12934-016-0579-3) contains supplementary material, which is available to authorized users.",
"conclusion": "Conclusions The urgent demand for the green, sustainable and cost-effective generation of fine chemicals continues to drive the need for new and effective tools for biotransformations. It is predicted that in the near future almost one-third of industrial chemical synthesis will be mediated by enzymes. To embrace this challenge, not only must new enzymes be discovered and developed, but robust and generic approaches toward the immobilisation, stabilisation and protection of the biocatalyst must be established. Readily engineered, single species biofilms represent an exciting opportunity as biocatalytic platforms into which genes encoding enzymes that catalyse valuable biotransformations can be introduced. The biofilm thereby produces, immobilises and protects the biocatalyst. We envisage the possibility of utilising this biofilm as a cell factory in which enzymes of interest can be introduced into this platform in a “plug and play” fashion for the generation of desired fine chemicals. We had previously observed the biofilm possesses striking biocatalytic longevity, this, we had postulated, was likely to be predominantly due to the protection by the EPS. Our studies of the lifespan and regeneration of the recombinant enzyme, using SILAC, demonstrate that the recombinant enzyme is being constantly regenerated in the matured biofilm, which we believe is fundamental to the longevity of its catalytic activity. Remarkably, we see similar levels of fresh label incorporation in a 9 day-old biofilm as in a 3 day-old biofilm indicating a similar generation level of the recombinant enzyme in the developed biofilm as in the newly formed biofilm. This result is surprising and exciting as it opens the potential, through the careful choice and application of promoters, to switch the biocatalytic function of a mature biofilm, and the products that it generates.",
"discussion": "Results and discussion Application of pulse-chase SILAC to follow the fate of the recombinant enzyme expressed in the biofilm Pulse-chase SILAC experiments involve dynamically following the metabolic behaviour of a cell culture in the presence of an isotopically labelled amino acid, followed by media replacement and the growth of the culture in the presence of the unlabelled amino acid. In this case we wished to explore whether the production of the recombinant enzyme tryptophan synthase was continuous, in engineered biofilms. In a typical SILAC experiment, at given time points, cells are harvested for preparation of protein samples and target proteins are isolated and tracked for label incorporation. Lysine and arginine are the most commonly used labelled amino acids for these studies as they present a trypsin cleavage site (provided they are not followed by a proline residue) and a convenient C terminal label for mass spectrometry (MS) analysis [ 74 , 75 ]. Other stable isotope labelled amino acids are also frequently used [ 76 ] and the choice is usually dictated by the abundance of each amino acid in the protein under investigation. Importantly, the labelled form of the peptides resulting from the trypsin digestion of the parent protein must have a distinct mass, compared to the unlabelled peptide pool in order to be detected in the MS analysis. The optimal additional mass conferred by an isotopically labelled amino acid is plus 4 Da, when exploring expression profiles of a complex series of different proteins or an entire proteome [ 74 ]. However, when exploring a single protein, the additional mass of plus 2 Da per amino acid incorporated is more than sufficient to enable ready detection of incorporation, as, for a doubly charged peptide fragment, the incorporation of such a label would result in an increase of 1 Da in the m/z. Conventional SILAC analysis involves a single pulse of one isotopically labelled amino acid followed by a single chase [ 76 – 78 ]. However, to gain a greater understanding of our biofilm and whether it regenerates its recombinant biocatalytic enzyme over the course of its maturation, we designed a multistep labelling regiment using a series of two labelled and unlabelled amino acids. To ascertain which two labelled amino acids should be utilised in the SILAC experiment, the amino acid composition and the tryptic digest of the β subunit of TrpBA were evaluated in silico (summarised in Additional file 1 : Tables S1, S2, respectively). In TrpBA, lysine and phenylalanine are abundant, at around 5 and 3 % of all amino acids. Of the unique tryptic peptides with five or more amino acids, 71 % contain lysine and 33 % contain phenylalanine. Due to the observation of a high frequency of occurrence of lysine in the tryptic peptides of TrpBA, we therefore chose to use [4,4,5,5- 2 H 4 ]- l -lysine as the SILAC amino acid. We chose [2,6- 2 H 2 ]- l -phenylalanine as the second labelled amino acid due to our ability to generate the isotopic phenylalanine in plentiful supply, in a cost effective manner, in house. Growing the biofilm in the presence of each of these labels would provide an anticipated shift of 2 m/z unit per each [4,4,5,5- 2 H 4 ]- l -lysine residue incorporated and a shift of 1 m/z unit per each [2,6- 2 H 2 ]- l -phenylalanine residue. To provide statistically robust results, in order to explore definitively whether the recombinant enzyme in the biofilm was regenerated, six series of pulse-chase experiments were carried out, in triplicate, as summarised in Fig. 1 (full details provided in the Methods section). Our labelling regimen involved supplementation of sets of individual cultures of the E. coli cells, to be used in biofilm formation, each with one of the two isotopically labelled amino acids. After the cultures had grown in the presence of the label, these cells were spin-coated onto glass slides that were then placed within deep-well plates, in the same manner as we have previously reported for the promotion of rapid biofilm formation [ 65 ]. Fresh media containing the same labelled amino acid (either labelled lysine or phenylalanine), as the cultures had been initiated in, was reintroduced to each well, and then incubated for 3 days whilst the biofilms started to mature. After 3 days the medium was removed and replaced with fresh media supplemented now with the unlabelled variant of the initial amino acid that had been used for each culture/biofilm i.e. unlabelled phenylalanine (Fig. 1 , rows 2, 3) or unlabelled lysine (Fig. 1 , rows 5, 6). The biofilms from both rows 1 and 4 were harvested for preparation of target proteins subjected to tryptic digestion followed by liquid chromatography-mass spectrometry (LC–MS) analysis (as detailed in the ‘‘ Methods ’’ section). After a further 3 days of maturation, biofilms in rows 2 and 5 were harvested and processed for downstream analysis. Again, the media were removed from all of the other biofilms, and the isotopic labelling regimen was swapped with the biofilm in row 3, that had previously been cultured in the presence firstly of deuterated then unlabelled phenylalanine now being supplemented with labelled lysine. Conversely, the biofilm in row 6 that had previously being supplemented firstly with labelled then unlabelled lysine, now being supplemented with labelled phenylalanine. The incubation continued until day 9 with biofilms in rows 3 and 6 being harvested at this stage. Fig. 1 Workflow for the pulse-chase SILAC experiment. For biofilm generation, E. coli PHL644 cells in stationary phase were spun down onto poly- l -lysine coated slides placed in 9-deep-well plates. Triplicate sets of biofilms were initially matured in minimal M63 media supplemented with either [2,6- 2 H 2 ]- l -phenylalanine ( rows 1-3, filled blue circles ) or [4,4,5,5- 2 H 4 ]- l -lysine ( rows 4–6, filled orange circles ). After 3 days of maturation, biofilms from rows 1, 4 were harvested (as denoted by the crosses ) to prepare protein samples. Labelled media were replaced with fresh unlabelled media ( empty blue circles for l -phenylalanine and empty orange circles for l -lysine) for the chase phase. Following a further 3 days of incubation, the biofilms in rows 2, 5 that had matured for 6 days were harvested to extract proteins. The media of the remaining biofilms was again exchanged; fresh media containing [2,6- 2 H 2 ]- l -phenylalanine were provided to the biofilms that had been previously supplemented with lysine, and conversely fresh labelled media supplemented with [4,4,5,5- 2 H 4 ]- l -lysine were provided to the biofilms that had previously been supplemented with phenylalanine. At day 9, biofilms from rows 3 and 6 were harvested \n Identifying and quantifying peptides from SILAC samples reveals the replenishment of the recombinant biocatalytic enzyme within the biofilm As described above, and in Fig. 1 , we designed a labelling regime which included pulsing with labelled amino acids, followed by a chase phase in which unlabelled amino acids, then an alternative labelled amino acid was administered to maturing biofilms. At each time point, where the label was changed (as illustrated in Fig. 1 ) biofilms were harvested for preparation of target proteins subjected to tryptic digestion, and the tryptic peptides were submitted for LC–MS analyses. The MS data were analysed using the Mascot algorithm (Matrix Science, London, UK) [ 79 ] with the modified masses of SILAC amino acids, i.e., [2,6- 2 H 2 ]- l -phenylalanine and [4,4,5,5- 2 H 4 ]- l -lysine, added as variable modifications in the searches against an internal database at the BSRC (Biological Science Research Complex, University of St Andrews, UK). The data were also searched against the National Centre for Biotechnology Information (NCBI) database [ 80 ]. The fragments of the β subunit of TrpBA identified by Mascot, based on at least five biofilm samples, are listed in Additional file 1 : Table S3. In total, the identified fragments covered 53 % of all amino acids of TrpBA. The aim of pulse-chase SILAC experiment performed in this study is to evaluate whether the recombinant enzyme expressed in the biofilm is replenished over time; if the system is static and the catalytic longevity is simply due to the protection of the initial enzyme population, little change or no incorporation in the label would be expected for target proteins coming from biofilms after 6 days of maturation. If the engineered biofilm enables catalytic longevity by renewal of the enzyme and the system is highly dynamic we would anticipate an observation of a change in the incorporation level of the respective labelled amino acid, at 6 days of maturation and beyond. After peptide identification, the MS spectra and ion chromatograms of two tryptic peptides (VGIYFGMK and DPEFQAQFADLLK) from the β subunit of TrpBA were extracted and examined at the MS level to quantify the incorporation level of each SILAC amino acid (the distribution of two peptides along the protein sequence is depicted in Additional file 1 : Figure S2). The signal intensities (areas under the curves) from light and heavy peptides provide a quantitative comparison of their relative abundances [ 75 , 78 , 81 ]. The MS spectra of two reference peptides, which each gave nearly identical quantification results, are provided in Additional file 1 : Figures S3, S4. We examined the incorporation level of SILAC amino acid into target proteins from biofilm samples harvested at each time point (day 3, day 6 and day 9). The level of incorporation was quantified by calculating the median of the labelled (heavy, H)/unlabelled (light, L) ratios according the accepted procedure [ 78 ]. In accordance with this standard literature procedure for determination of the median of H/L peptide ratios, the peak areas of the extracted ion chromatograms (XICs) of the labelled peptides were measured against the unlabelled peptides. The degree of labelling on target protein was quantified with two reference peptides, as listed above (see Additional file 1 : Figures S5, S6 for the XICs of the two peptides). Labelling analysis of the recombinant tryptophan synthase produced by 3 day-old biofilms showed isotopic incorporation levels of ~93 % for biofilms that had been cultured in minimal M63 medium supplemented with [2,6- 2 H 2 ]- l -phenylalanine (Fig. 1 , row 1 samples), and isotopic incorporation levels of about 38 % for biofilms that had matured in [4,4,5,5- 2 H 4 ]- l -lysine supplemented medium (Fig. 1 , row 4 samples). The lower incorporation level of deuterated l -lysine was observed, even though supplemented at ten-fold higher concentration, potentially due to the direction of this amino acid towards alternative metabolic pathways, and highlights the benefits of utilising a pair of labelled amino acids. To evaluate whether fresh enzymes were produced in both sets of samples, as described above, after 3 days maturation of the engineered biofilm we started the chasing by replacing the labelled medium with fresh medium supplemented with the respective unlabelled amino acids (Fig. 1 , rows 2, 3 for phenylalanine and rows 5, 6 for lysine). After 3 more days of maturation, biofilms from rows 2 and 5 chased with unlabelled phenylalanine and lysine respectively, were harvested for preparation of target proteins. As seen in Fig. 2 , for the row 2 samples, it was observed that the incorporation level of deuterated l -phenylalanine had dropped from 93 to 10 %; for the row 5 samples, the incorporation level of [4,4,5,5- 2 H 4 ]- l -lysine was also observed to decrease from 38 to 16 %. The reduced level of SILAC amino acids observed for three reference peptides suggests that new recombinant enzyme was dynamically generated de novo. We also examined the MS spectra of two reference peptides, detected from the tryptic digest of recombinant enzyme coming from the biofilms chased with unlabelled phenylalanine (Additional file 1 : Figures S3, S4; row 2) or unlabelled lysine (Additional file 1 : Figures S3, S4; row 5). A drop in the incorporation level of the stable isotope labelled amino acids was observed as indicated by the ratios in the MS spectra of the correlated heavy and light peptides, which is consistent with the quantification analysis based on XICs. Fig. 2 Summary of changes in the incorporation level of SILAC amino acids into target protein. The labelling efficiency is calculated based on the XICs of the two peptides, VGIYFGMK and DPEFQAQFADLLK, using the formula: Incorporation % = [H/L]median/(1 + [H/L]median) ×100. The heavy/light (H/L) SILAC ratios are determined by analysing the ion chromatograms of the heavy and light peptides as they elute from a C18 column , and then calculating the ratio of the areas under XICs curves. The two reference peptides were detected in the tryptic digest of the recombinant enzyme extracted from 3 day-old biofilms pulsed with deuterated l -phenylalanine ( row 1 ) or with deuterated l -lysine ( row 4 ), 6 day-old biofilms chased with unlabelled phenylalanine ( row 2 ) or with unlabelled lysine ( row 5 ), and 9 day-old biofilms cross pulsed with deuterated l -lysine ( row 3 ) or with deuterated l -phenylalanine ( row 6 ) \n To extend our studies on the enzyme regeneration we sought to explore whether a further change in labelling regiment, past day 6, would continue to differentially label the tryptic peptides. At day 6, biofilm that had previously been administered l -phenylalanine was now pulsed with 300 μM of [4,4,5,5- 2 H 4 ]- l -lysine (Fig. 1 , row 3) and conversely the biofilm that had been administered l -lysine was now pulsed with [2,6- 2 H 2 ]- l -phenylalanine (Fig. 1 , rows 6). After a further 3 days of maturation, the biofilms were harvested and processed for isolation of target proteins. Incorporation of labelled lysine into the recombinant tryptophan synthase was observed for the biofilms initially matured in medium containing phenylalanine and vice versa (see Additional file 1 : Figures S3, S4 for incorporation of [4,4,5,5- 2 H 4 ]- l -lysine and [2,6- 2 H 2 ]- l -phenylalanine). Strikingly, incorporation of labelled phenylalanine is observed at ~90 % for biofilm samples in row 6, close to the incorporation level observed for the 3 day-old biofilms in row 1. Conversely, and in agreement with this result, the 9 day-old biofilms in row 3 that had been switched to the labelled lysine pulse now showed an incorporation level of labelled lysine at ~43 %, very similar to the incorporation level of ~38 % observed for the 3 day-old biofilms in row 4. This consistency in labelling level reveals that the recombinant enzyme within the biofilm continues to be completely replenished without perceivable difference in regeneration rates between the 3 day-old and 9 day-old biofilms. For our assessment of the ability of the biofilm samples to catalyse biotransformation, slides containing biofilms that had matured for 7 and 9 days were transferred to the reaction buffer supplemented with 5-chloroindole and incubated at 28 °C for 24 h in an orbital shaker incubator, as detailed in the Methods section. No significant difference was observed in terms of overall percentage chlorotryptophan yield between biotransformations with 7 and 9 days-old biofilms (54 vs 59 %; Additional file 1 : Figures S7, S8), confirming that the generated recombinant tryptophan synthases in biofilms are catalytically active. Overall, these findings demonstrate that a key contributor to the striking and useful longevity of the biocatalytic biofilm is the regeneration of the active enzyme."
} | 5,035 |
39443479 | PMC11499872 | pmc | 4,075 | {
"abstract": "Understanding how biotic interactions shape ecosystems and impact their functioning, resilience and biodiversity has been a sustained research priority in ecology. Yet, traditional assessments of ecological complexity typically focus on species-species interactions that mediate a particular function (e.g., pollination), overlooking both the synergistic effect that multiple functions might develop as well as the resulting species-function participation patterns that emerge in ecosystems that harbor multiple ecological functions. Here we propose a mathematical framework that integrates various types of biotic interactions observed between different species. Its application to recently collected data of an islet ecosystem—reporting 1537 interactions between 691 plants, animals and fungi across six different functions (pollination, herbivory, seed dispersal, decomposition, nutrient uptake, and fungal pathogenicity)—unveils a non-random, nested structure in the way plant species participate across different functions. The framework further allows us to identify a ranking of species and functions, where woody shrubs and fungal decomposition emerge as keystone actors whose removal have a larger-than-random effect on secondary extinctions. The dual insight—from species and functional perspectives—offered by the framework opens the door to a richer quantification of ecosystem complexity and to better calibrate the influence of multifunctionality on ecosystem functioning and biodiversity.",
"introduction": "Introduction All ecosystems are composed of species participating in a myriad of entangled interactions with other co-existing species 1 – 3 . These interactions involve the many different ecological roles that species perform, which define the multiple dimensions of their Eltonian niche 4 , 5 . To better understand the rich phenomenology 6 , 7 of these interactions, species 8 , and their interaction diversity 9 can be quantified by the degree to which species participate in different ecological functions 10 , 11 (e.g., pollination, seed dispersal, nutrient uptake, decomposition, etc.). A standard modeling approach to describe ecosystem functioning places coexisting species at the center, and thus represents it as an entangled web of species interacting via a concrete interaction type (e.g., food webs 12 – 16 , mutualistic networks 3 , 17 – 20 , etc.). Network science 18 , 21 has been instrumental in this approach, providing quantitative insights on e.g., the emergence of species extinction cascades 18 , 21 , 22 , or the impact of network structure on biodiversity 13 , 23 , 24 , among others 17 , 25 . While not always strictly necessary 26 , 27 , incorporating more than one type of interaction between species into a single model often suggests using multilayer network theory 28 – 31 , i.e., where different species-species networks (one per interaction type) can be represented, what would, in principle, enable us to understand e.g., how multifunctionality impacts ecosystem’s biodiversity 13 , 14 , 23 , 32 – 35 , among other important ecological questions 17 , 25 . However, and despite some notable examples 36 , 37 , embracing multilayer network theory in ecology faces at least three challenges that have precluded substantial advances to date: first, from an experimental angle, accessing the necessary fine-grained empirical observations of species interactions is inherently a difficult task 38 , often resulting in incomplete observations or indirectly-inferred data 39 , 40 . Second, interactions that explicitly contribute to different ecological functions are usually measured with different methods, and thus their estimated strength has often different units. For example, it is not straightforward to compare e.g., how a flowering plant being visited by three pollinators is comparable to a plant being eaten by three herbivores (see ref. 41 for a recent effort to address this challenge through the use of energy fluxes). Third, the proper quantification of ecologically relevant properties in terms of multilayer network metrics is still in its infancy. All in all, integrating several ecological functions into a single modeling framework—both theoretically and empirically—thus represents both a necessity and a challenge 42 . We call this Challenge 1 , and it constitutes the first motivation of this paper. Interestingly, ecosystem’s functioning could be probed from other perspectives as well, not only a species-centric one. As advanced at the beginning, one could focus on how entangled species and functions are—i.e., how different species participate in interactions cataloged as different ecological functions–, resulting in “species-function” networks. Such representation would allow to quantify the importance that different (i) species and (ii) functions have. Analysis of point (i) inquires whether there are species that are disproportionally participating and connecting more functions. This would enrich the polyhedric concept of keystone species 43 – 47 —traditionally defined as those species disproportionately important for community functioning, regardless of their abundance—but considering here the concomitant participation of species in different functions 48 —and their role in connecting them—as the measures under analysis. Analysis of (ii) would inform a similar analysis but conceived here in the context of functions rather than species, inquiring whether, even if all ecological functions are important, their roles and impact as ecosystem connectors are similar or not, and whether there exists a core of ecological functions that play a salient role. This species-function perspective opens up further questions: first, the ecosystem could be modeled as an entangled web of functions 49 , 50 (e.g., herbivory interfering pollination, feedback loops between pollination and seed dispersal, etc.), effectively resulting in function-function networks where links between two functions are based on, e.g., whether there are species that participate in both functions. Understanding how ecological functions relate to one another within a single ecosystem would provide a functional perspective of important questions, such as the role of indirect effects, or the ecosystem’s resilience against function perturbations 51 . Second, a similar question could be raised now from the species-centric viewpoint, inquiring how species would relate to each other based on the functions they share. In a nutshell, ecosystems are inherently multidimensional complex systems, and inspection of different properties require representing the ecosystem in different ways. Leveraging multilayer network theory to implement the species-function perspective described above, along with the outlined analysis, constitutes what we call Challenge 2 and is the second motivation of this paper. Here we take steps to address Challenges 1 and 2 discussed above, both theoretically and empirically. On the theoretical side, expanding from multilayer network theory, we develop a modeling approach inspired by the consumer-resource paradigm 19 , 52 , whereby plant species are seen as “resources”, and “consumers” encapsulate different taxa of animals or fungi involved in both mutualistic and antagonistic interactions. These biotic interactions can be of different types and, following Garland and co-authors 10 , are cataloged into different ecological functions. Indeed, functions are defined here as interaction types with specific ecological repercussions, see Methods for details. On the experimental side, we leverage the relative simplicity of a small island community —Na Redona, in the Balearic Islands (Western Mediterranean Sea)—to test our methodological framework. We develop methods to standardize field-sampling in Na Redona, resulting in a database encompassing a total of 1537 weighted interactions between plants, animals and fungi across six ecological functions that, for the purpose of this work, we categorize as pollination, herbivory, seed dispersal, decomposition, nutrient uptake, and fungal pathogenicity (see Methods) and then apply our theoretical framework to unveil the multifunctional architecture of this ecological community and its impact in various ecologically-relevant properties. Operationally, our modeling framework starts by recasting our whole dataset into a resource-consumer-function (RCF) tensor—a generalization of a matrix with three indices instead of two, hereafter RCF tensor—that we define below (see Fig. 1 for the work’s roadmap and Table 1 for a glossary of the concepts introduced herein). By suitably interpreting the indices of this tensor as nodes or layers respectively, the RCF can then be visualized as a multilayer (multifunctional) weighted network. Subsequently, by mathematically integrating out the consumer index in the RCF tensor, we obtain a resource-function matrix (effectively, a bipartite species-function network) that encodes how plant species and functions participate one onto each other within the ecosystem. We show that, applied to the Na Redona community, such resource-function matrix displays statistically significant nested pattern 53 , providing evidence that both species and functions play heterogeneous and dual roles and participate into each other in a non-random way. This also opens the possibility of quantifying and ranking the “importance” of both species and functions accordingly. Among many possibilities, here we do this (i) by computing a score-based on the direct connections in the bipartite species-function network and another score-based on how species indirectly connect functions and viceversa, (ii) by certifying that the resulting rankings are in good agreement with each other, and (iii) by checking which positions in these rankings are statistically significant according to suitable null models. Also, since a connection or a path is not necessarily an effect 44 , we perform an extinction analysis and confirm that removing species and functions in the order predicated by these rankings has a larger-than-random effect on secondary extinctions in the system. Application to the Na Redona dataset unveils a hierarchical pattern and allows us to indentify a small subset of (multifunctional) “hub” plant species and a single “hub” function. We further show that these actors play an important role in the assembly of the species-function participation pattern, as the removal of these species and functions have a larger effect in the subsequent extinction of species/functions than expected, hence calling them “keystone”. We end up by discussing these results, their ecological implications and outlining a number of concluding remarks. Fig. 1 Conceptual framework. (see also Table 1 for a glossary of terms). Ecosystems are multidimensional complex systems whose interactions are captured by a rank-3 resource-consumer-function (RCF) tensor (here, a plant-animal/fungus ecological interaction tensor) with entries \\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}$${f}_{ix}^{\\alpha }$$\\end{document} f i x α . This tensor can be visualized as a multilayer (multifunctional) ecological network (see Fig. 2 ) when identifying the indices i and x with resource and consumer nodes, respectively, and index α with ecological function layers. Integrating consumers out (see Eq. ( 1 ) in the text and Methods), we obtain a resource-function matrix P (Fig. 3 ) that encapsulates how plant species and functions are intertwined in the ecosystem. Further projections of this matrix yield function-function networks Φ (Fig. 4 ) that characterize how each plant species connects different functions (phytocentric embedding) and plant-plant networks Π (Fig. 5 ) that characterize how each ecological function connect different plant species (function-centric embedding). Inspection of these networks allows us to rank species and functions based on how they participate and connect within the ecosystem. Created in BioRender 99 . Table 1 Glossary of terms and concepts sequentially introduced throughout the text, along with a short explanation Term Explanation Resource-consumer-function (RCF) tensor \\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}$${{\\mathcal{F}}}=\\{{f}_{ix}^{\\alpha }\\}$$\\end{document} F = { f i x 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}$${f}_{ix}^{\\alpha }$$\\end{document} f i x α is the probability of observing a resource plant species i interacting with a consumer species x via a function α . For phytocentrical field-sampling, \\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}$${f}_{ix}^{\\alpha }={m}_{ix}^{\\alpha }/{n}_{i}$$\\end{document} f i x α = m i x α / n i , where \\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}$${m}_{ix}^{\\alpha }$$\\end{document} m i x α is the number of annotated occurrences of i interacting with x via α , and n i is the number of individuals of observed resource species i . \\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}$${{\\mathcal{F}}}$$\\end{document} F is a rank-3 tensor summarizing the whole observational dataset, the choice of covariant and contravariant indices are set for convenience. Multilayer ecological network A specific multilayer network visualization of the RCF tensor, where we choose resources i (plant species) and consumers x (animals/fungi) to be the nodes, and functions α to be the layers. The values 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}$${f}_{ix}^{\\alpha }$$\\end{document} f i x α provide the weight of the link between i and x at each layer α (such weight is indeed a probability). After color-coding each layer, the multilayer network is visualized as an edge-colored one (Fig. 2 ). Since within each layer interaction only takes place between i and x (not directly between i and i or x and x ), the multilayer network is also bipartite. Resource-function bipartite network P , with entries \\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}$$\\{{P}_{i}^{\\alpha }\\}$$\\end{document} { P i α } (Fig. 3 ) Obtained from the RCF tensor by suitably integrating out the consumer index according to Eq. ( 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}$${P}_{i}^{\\alpha }$$\\end{document} P i α is the probability of observing a resource i participating in a function α . The matrix P is interpreted as the weighted biadjacency matrix of a bipartite resource-function network that accounts for how intertwined resources and functions are within the ecosystem. Phytocentric embedding Projection of functions in a resource-feature space (Fig. 4 ) Function-function network, with weighted adjacency matrix Φ = P ⊤ P and elements {Φ α β } \\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}$${\\Phi }^{\\alpha \\beta }={\\sum }_{i}{P}_{i}^{\\alpha }{P}_{i}^{\\beta }$$\\end{document} Φ α β = ∑ i P i α P i β is the number of different plant species that simultaneously participate in both functions α and β . Conditioned function-function network Φ ∣ i = {Φ α β ∣ i } with elements \\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}$${\\Phi }^{\\alpha \\beta }{| }_{i}:={P}_{i}^{\\alpha }{P}_{i}^{\\beta }$$\\end{document} Φ α β ∣ i : = P i α P i β Disaggregation of Φ : for each (resource) plant species i we have a different conditioned function-function network Φ ∣ i illustrating how similar functions are in such species embedding. (Multifunctional) species keystoneness score k species ( i ) \\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}$${k}_{{{\\rm{species}}}}(i)={\\sum }_{\\alpha }\\left[\\frac{{\\sum }_{\\beta }{\\Phi }^{\\alpha \\beta }{| }_{i}}{{\\sum }_{\\beta }{\\Phi }^{\\alpha \\beta }}\\right]$$\\end{document} k species ( i ) = ∑ α ∑ β Φ α β ∣ i ∑ β Φ α β Function-centric embedding Projection of resource species in a function-feature space (Fig. 5 ) Plant-plant network, with weighted adjacency matrix Π = P P ⊤ and elements {Π i j } Its elements \\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}$${\\Pi }_{ij}={\\sum }_{\\alpha }{P}_{i}^{\\alpha }{P}_{j}^{\\alpha }$$\\end{document} Π i j = ∑ α P i α P j α quantify the expected number of shared functions by two plant species i and j , or alternatively how similar these two plant species are according to the functions they share. Conditioned plant-plant network Π ∣ α = {Π i j ∣ α } with elements \\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}$${\\Pi }_{ij}{| }^{\\alpha }={P}_{i}^{\\alpha }{P}_{j}^{\\alpha }$$\\end{document} Π i j ∣ α = P i α P j α . Disaggregation of Π : for each ecological function α we have a different conditioned plant-plant network Π ∣ α illustrating how similar plant species are in such function embedding. Function keystoneness score k function ( 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}$${k}_{{{\\rm{function}}}}(\\alpha )={\\sum }_{i}\\left[\\frac{{\\sum }_{j}{\\Pi }_{ij}{| }^{\\alpha }}{{\\sum }_{j}{\\Pi }_{ij}}\\right]$$\\end{document} k function ( α ) = ∑ i ∑ j Π i j ∣ α ∑ j Π i j For more details, see Methods.",
"discussion": "Discussion The RCF tensor we have presented facilitates data standardization and notation, by incorporating the interaction of species via different ecological functions into a resource-consumer(-function) paradigm. This offers a possible working solution for Challenge 1 on the matter of having a single and flexible modeling framework, as presented in the Introduction. Such RCF indeed offers flexible visualizations in terms of multilayer networks (Fig. 2 ). Observe at this point that the RCF is a rank-3 tensor, while standard tensorial formulations of multilayer networks are generally rank-4 tensors 28 (two indices for interacting nodes, and two indices characterizing the layer in which each node is located). The difference stems from the fact that in our case—and, to some extent, in multilayer ecological networks more generally—three indices are enough. Ecological interpretation of the results The reduction of the RCF tensor into a resource-function matrix provides valuable insights into how resources (plant species) and ecological functions are intertwined within the ecosystem. The Na Redona case unveils the emergence of a (statistically significant) non-random, nested pattern in the way resources and functions participate with each other. While future work should confirm whether this pattern holds for other ecosystems, it is interesting to remark that many previous works have related the onset of nested structures in (single-function, species-species) ecological networks with important aspects of ecosystem functioning such as robustness, coextinction cascades, stability, feasibility or sustainment of biodiversity: see ref. 53 and references therein. Our framework and data thus open the possibility to investigate similar questions in the multilayer networks, e.g., would allow us to potentially link multifunctionality and biodiversity. Subsequently, unfolding the species-function matrix allowed us to propose a measure of species keystoneness, specifically based on the fact that the ecosystem harbors different types of ecological interactions and that different species (i) participate in, and (ii) indirectly connect different ecological functions. Observe that the traditional definition of a keystone species 43 – 47 —species disproportionately important for community functioning, regardless of their abundance—is deliberately vague as it relies on the multifaceted concept of “community functioning”, and thus allows for different mathematizations depending on the particular facet of the community. In this sense, here we have focused on the concomitant effect of considering at the same time different ecological functions 48 , and have accordingly extended the concept of keystone species to a multifunctional one, that takes into account two topological properties: (i) the species participation in different ecological functions and (ii) how well the species indirectly connect different ecological functions. The resulting scores and their rankings (Figs. 3 d and. 4 c) are indeed in good agreement with each other (Supplementary Fig. 8 further confirms that species abundance is not a confounding factor in these rankings). Additionally, an extinction analysis performed on the resource-function matrix (Fig. 4 d and Supplementary Figs. 4 and 7 ) shows that a larger-than-random effect is observed on secondary extinctions when removing species or perturbing functions in the order prescribed by these rankings. This is our interpretation of the “disproportional importance for community functioning” of a keystone actor and justifies that our species rankings can be interpreted as such. In the Na Redona islet, these rankings indicate that plant species contribute heterogeneously to multiple ecosystem functions, i.e., they multitask 48 . Interestingly, the first six species in the rankings, i.e., those with the highest keystone scores, are all woody shrubs. Within that set, the first two species Withania frutescens and Lavatera maritima are indeed multifunctionally keystone (having a score significantly larger than a null model). The rest, except for Ephedra fragilis , are all herbaceous. Now, herbs such as Chenopodium murale and Heliotropium europaeum , with keystone scores significantly smaller than a null model, appear to play a minor role in connecting different functions. Their presence suggests that these species have a very concrete role—e.g., are probably important for very particular ecological functions. The finding that woody shrubs are those more strongly involved in different functions might be attributed to the longer lifespan of such species compared to herbs, which allows them to link to a wider array of species in each type of interaction. However, more in-depth studies are needed to unveil the exact mechanism of such multitasking. Interactions between plants and fungi (especially saprotrophic and pathogenic fungi) were found to play a salient role. Microbial decomposers, together with plants and herbivorous insects, are also important drivers of ecosystem functioning in grasslands, where a positive association has been documented between richness or abundance and multiple ecosystem services 65 . We have also introduced the concept of keystone function—that, to the best of our knowledge, had gone unnoticed to date. This concept emerges naturally thanks to the species-function duality observed in the resource-function matrix. Operationally, in this work we called a function keystone when (i) the scores based on their participation by different plant species (Fig. 3 c) and the scores based on their role indirectly connecting species (Fig. 5 c) were in agreement and larger than the 90th percentile scores of suitable null models (Supplementary Figs. 3 and 6 ), and when (ii) the effect of perturbing functions on secondary species extinction in the order prescribed by these scores were (statistically significantly) larger-than-random (Fig. 5 d and Supplementary Figs. 4 and 7 ). We propose that this new concept aligns with approaching the ecosystem through a function-centric lens, rather than a traditional species-centric (e.g., phytocentric) one. Indeed, just as robustness and resilience in the face of a disturbance is usually calculated at the species level 66 , it is also possible to assess such responses of the ecosystem at the functional level: the response of the ecosystem to some disturbances may overall affect entire functions. For instance, non-native herbivores can disrupt chemically-mediated interactions between plants and herbivores, pollinators, predators, and parasites that respond to herbivore-induced plant volatile cues 67 . Because there is a wide variety of interactions involving native organisms that a single non-native could potentially impact, defining and identifying key ecological functions is a crucial first step toward better understanding their role in ecosystem development, balance, functioning, and resilience 15 . In the Na Redona islet, our results indicate that fungi-led interactions are more widespread. More specifically, saprophytic-type interactions exhibit a disproportionate prevalence, and decomposition emerges as the only keystone function, in both rankings (Figs. 3 c and 5 c). While such a result should be confirmed for other ecosystems, at this point, we can comment that this is in agreement with a relatively recent shift in the interest and relevance of underground -in contrast to above-ground- interactions within ecosystem functioning 68 . On the other hand, in our database seed dispersal is found to have a significantly low score. In hindsight, this specific result can be related to the fact that Na Redona is an islet with a shortage of plants with fleshy fruits, and in this sense, in other ecosystems where the abundance of fleshy fruits is higher, the score of seed dispersal might be larger. In any case, understanding the origin for the presence of actors with disproportionally (and statistically significant) low keystone scores—such as the case of seed dispersal in Na Redona—and why species or functions with apparently weaker connecting roles are still observed in the ecosystem is reminiscent of similar questions on the rare biosphere : low-abundance microbial populations that in turn display specific and sometimes unique ecology and serve as a broad reservoir of ecological resiliency 69 . Observe that finding (statistically significant) heterogeneous keystone scores both for plant species and functions essentially means that there are some plant species and functions (those considered keystone) for which the number of observed indirect connections to other species and functions is enhanced with respect to a null model. Interestingly, previous works have found that indirect effects between species are more likely to predominate in nested networks 3 , and impacts species fitness 70 . In our context, our findings open the door to (i) relate the structure of indirect species-species relations ( Π ) to e.g., biodiversity maintenance, but also (ii) investigate the impact of indirect function-function relations ( Φ ) on similar ecological questions. Finally, it is worth noting that our whole framework is in principle metric-agnostic. While we used some specific quantification metrics, other complementary ones are also possible 71 : for instance, participation strengths—instead of participation probabilities—could also be built by summing up contributions 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}$${f}_{ix}^{\\alpha }$$\\end{document} f i x α , rather than by building \\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}$${P}_{i}^{\\alpha }$$\\end{document} P i α via Eq. ( 1 ). However, as already anticipated, there is a merit in building scores from \\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}$${P}_{i}^{\\alpha }$$\\end{document} P i α , as these are probabilities and are therefore not severely affected by potential sampling biases (see also below). Limitations Now, it is important to acknowledge that there are certain limitations to our analysis and methodology, mainly associated with the unavoidable specifics of data collected in the Na Redona islet, that we synthesize in five points. First, our fieldwork observations were in principle designed so as to link different interaction types with different ecological functions (see Methods). We acknowledge that such mapping could be debatable, specially the mapping of fungal interactions to functions, as there is a shortage of literature on the specific function associated to fungal interactions, and more work is needed in this aspect. Second, the particular mathematical method we used to integrate out consumers in the RCF tensor is based on the fact that in each layer (e.g., for each function), the interactions are bipartite; that is, there are no direct interactions between plants or between animals/fungi. Consequently, incorporating competition between plants and/or animals/fungi would require either to add more indices in the tensor, or to express it as \\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}$${f}_{ij}^{\\alpha }$$\\end{document} f i j α , where now both i and j are indices that run both over resources and consumers alike, i.e., the partition between resources and consumers would be obscured. Third, while multifunctional, our collected data is eminently phytocentric (centered in observing plant species), instead of zoocentric (centered in observing consumers—animals, insects, etc.–). If newer data allows us to account for purely zoocentric observations (ideally mixed phyto-zoo-centric observations), retaining the complete RCF tensor would be convenient instead of integrating out the consumer index, and direct manipulation of the RCF tensor would easily follow (for instance, allowing to assess consumer-function participation patterns as well). Fourth, since again field observations were focused primarily on plants, we also lack specific information, such as the trajectory of insect pollinators. Consequently, we cannot directly quantify the probability that a plant is included in the diet of a particular insect pollinator species. In this case, the parsimonious approach is to assume independence, and this is the base of our derivations. However, the contribution of a plant species to a function is typically mediated by the participation of several animal/fungal taxa, and the existence of correlations in the behavior of different species is possible. Take for example, again, pollination. In our calculations, we assumed that a universal probability governs whether a specific plant is visited or not. However, we do know that plants may attract specific pollinator species (specially the most specialized ones that have particular flower traits, e.g., long corolla tubes), resulting in a latent correlation kernel. Accordingly, the advent of new data should be used to test the validity of our parsimonious assumption. And lastly fifth, even if the sampling effort and the sampling protocol for each function were carefully designed and followed the standard guidelines of the field (see Methods), all fieldwork data probably (and unavoidably) suffers from some sampling and observational biases in the consumer index (possibly except fungi-mediated interactions, which are easier to observe as these are static and observations are subsequently resolved via genetic techniques). Comparing to, say, insect-mediated ones, which are by design more difficult to observe, a logical consequence is that, in the multilayer ecological network, the layers associated to fungal interactions have substantially more consumer nodes than other layers. Further fieldwork efforts are needed to quantify and control these uncertainties and to confirm the generality of our results. That being said, we explicitly were able to alleviate some of these biases by quantifying resource-function participation using probabilities of observing such events ( \\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}$${P}_{i}^{\\alpha }$$\\end{document} P i α ), instead of using (more traditional) raw weights that measure the actual number of observed occurrences. Final remarks While applied in an ecological context, this framework is conceptually general and can be easily extended to characterize e.g., the interplay between resources and functions in other complex systems. For instance, it can be applied to genetics, where our resource-function mapping resembles a classical genotype-phenotype map 72 , illustrating how genes interact to give rise to phenotypes in various animals. Similarly, in economic systems, this interplay can shed light on how goods are traded among countries across different economic sectors 73 . Going back to the ecological case, the resource-function matrix (and its projections Φ and Π ) unveils the duality of plant species and functions (phyto vs function-centric perspectives), where the concept of (multifunctional) keystone species and the concept of (multispecies) keystone functions naturally emerge as two (interconnected) sides of the same coin. The former refers to species that play key roles in connecting functions in a multifunctional system -with possible impact on e.g., network stability 48 -. In contrast, the latter refers to the different roles functions play in keeping species coexistence in an ecosystem. Our initial assessment in the Na Redona dataset shows that a drastic perturbation of keystone species 51 , 74 propagate into functions (via secondary “function extinctions”) more than expected at random, and the opposite is true when perturbing keystone functions. While further work is needed to refine these results (e.g., perturbing species gradually instead of abruptly would be interesting to assess the impact of losing pollinators on fruit production), our findings indicate that both concepts (species and functions) are indeed intertwined, potentially feeding back into each other. For instance, in the context of climate change, it is not uncommon to witness drastic and sustained temperature increases over large geographic regions. If such exogenous perturbations induce, e.g., phenological mismatches between flowering plants and insect pollinator visits, then the complete pollination function might be threatened before any of the species are themselves threatened 75 , 76 , i.e., perturbation takes place initially at the function level. It can then propagate with potential cascading effects for both species and other functions, as prescribed by the resource-function matrix P . Conversely, the decline or extinction of a seed disperser (initially at the animal species level) may trigger declines or plant extinctions, which in turn cascade to affect species involved in other functions, such as underground fungi 77 . Furthermore, the extinction of a keystone plant species can also influence other species’ interactions, either by causing interaction rewiring or by modifying interaction strengths 78 – 82 . Such cascading effects across interaction types become particularly problematic in double-mutualistic interactions, i.e., when the same animal acts, for example, as pollinator and seed disperser of the same plant species 11 . Yet, not only the disruption of mutualistic interactions but also of antagonistic interactions could derive functional losses, e.g., the loss of top predators may indirectly affect ecosystem productivity and metabolism 83 . However, few studies still exist on how human activities can alter ecosystem multifunctionality, both directly on ecosystems and indirectly through the loss of multifunctional biodiversity 32 , 84 . Moreover, how organisms at different trophic levels interact to influence ecosystem multifunctionality in the presence of multiple concurrent anthropogenic drivers remains largely unexplored 65 , 85 . Thus, we hope our framework offers a promising approach for evaluating the relative vulnerability of ecosystem functions to anthropogenic stressors. As we delve deeper into understanding ecosystems, the integration of temporal, spatial, and dynamical features within this framework, coupled with its application to ecological data from other environments, also emerges as exciting avenues for future research."
} | 9,912 |
39924797 | PMC11923527 | pmc | 4,078 | {
"abstract": "Abstract Soft materials with reversible electrical and mechanical properties are critical for the development of advanced bioelectronics that can distinguish between different rates of applied strain and eliminate performance degradation over many cycles. However, the current paradigm in mechano‐electronic devices involves measuring changes in electrical current based on the accumulation of strain within a conductive material that alters the geometry through which electrons flow. Attempts have been made to incorporate soft materials like liquid metals and concentrated solutions of conjugated polymers and salts to overcome materials degradation but are limited in their ability to detect changes in the rate of the applied strain. Herein, the anisotropic electrical performance of a soft semiconducting composite prepared with silver‐coated microspheres dispersed within a swollen copolymer gel is demonstrated. This composite exhibits an electrical response proportional to the magnitude of the applied shear force to enable a rate‐of‐strain dependent conductivity. Furthermore, a 100‐fold increase in the conductivity of the composite is observed when the electric field is oriented parallel to the flow direction. This improvement in the electrical response can be attributed to the enhanced alignment of microspheres in viscoelastic media and can be leveraged in the development of mechanically responsive electronic devices.",
"conclusion": "3 Conclusion In summary, we demonstrate the ability to engineer the electrical response of a reversibly deformable AgMS‐MG soft solid. This new class of electrically dynamic, soft solids will enable new paradigms in the field of mechano‐electronic transduction for the advancement of soft electronics. Impedance measurements performed at steady shear rate with two different electrode configurations have elucidated the connection between microstructural dynamics and electrical transport properties of these composites. Initially, the AgMS‐MG composite displayed a reduction in electrical conductivity when compared to their oil counterparts with an electric field oriented in the gradient direction. The microstructural origin of this decrease was investigated with a custom rheometer attachment that reoriented the electric field along the flow direction. This attachment detected a 100‐fold increase in electrical conductivity that we attributed to improved electron delocalization facilitated by the chained microstructure of noncolloidal particles in viscoelastic dispersants. Although the dynamics of noncolloidal particle systems [ \n \n 40 \n , \n 41 \n \n ] and the effects of a viscoelastic medium [ \n \n 37 \n , \n 39 \n , \n 42 \n \n ] have been previously investigated, the focus of these studies was on primarily fundamental measurements of ideal systems of non‐conductive particles to better understand their underlying rheology, without connecting this microstructural alignment to an anisotropic electrical response. Overall, this work provides new insight into how tuning particle microstructure and electric field orientation can be used to engineer the anisotropy of the shear‐driven electrical response of a dynamic material to accelerate the development of advanced robotic devices.",
"introduction": "1 Introduction Developing soft materials with an engineered electrical response to mechanical forces is critical for the deployment of sensors for human health monitoring [ \n \n 1 \n , \n 2 \n , \n 3 \n \n ] and soft robotics. [ \n \n 4 \n , \n 5 \n \n ] These materials require an electrical property that reversibly and reproducibly changes in response to mechanical stimuli while conforming to soft and compliant surfaces. [ \n \n 6 \n \n ] The most common sensors for this purpose are micropatterned arrays of deposited metals [ \n \n 7 \n , \n 8 \n \n ] and nanostructured carbon. [ \n \n 9 \n , \n 10 \n \n ] These arrays are patterned on flexible and electrically insulating substrates, and when deformed, changes in capacitance or electrical resistance are detectable due to accumulated strain. [ \n \n 11 \n \n ] Patterned arrays can detect deformation over a large surface area and with great sensitivity, but unfortunately are limited in their long‐term use by irreversible morphological changes that occur within the material over many cycles of deformation. [ \n \n 12 \n \n ] Further, this approach uses inorganic solid conductors that are stiff and generally incompatible with the mechanical properties of human skin. [ \n \n 13 \n \n ] \n Alternatively, soft force sensors can be constructed from conductive nanocomposites. For example, Minev et al. embedded platinum nanoparticles into a PDMS elastomer to form a conductive composite electrode. [ \n \n 14 \n \n ] This composite combines the compliance of a silicone elastomer with the electrochemical sensing properties of platinum to detect strain and sense the local electrochemical environment. A recent review highlighted many conductive phases including carbon nanotubes, liquid electrolytes, metallic nanoparticles, and conjugated polymers embedded in a hydrogel matrix that can be leveraged to produce conductive composites for mechanical sensing. [ \n \n 15 \n \n ] Further improvements in flexibility and signal reliability can be achieved by functionalized liquid metal droplets during the synthesis of the nanocomposite. [ \n \n 16 \n \n ] While these materials possess the necessary mechanical properties, their electrical response is generally more limited with improvements needed in sensitivity and dynamic detection range. Similar flexibility and reliability can be achieved using carbon nanofibers or graphene nanoparticles, but generally, changes in electrical conductivity are non‐linear for large strains. [ \n \n 17 \n , \n 18 \n \n ] Moreover, the properties of the nanocomposites can change after deformation due to the Payne effect, as the storage modulus of the rubber can decrease at high strains, especially at high conductive filler concentrations. [ \n \n 19 \n , \n 20 \n \n ] \n Regardless of the material category, prior approaches rely on detecting changes in electrical properties that are proportional to accumulated strain for force sensing. This approach fails to distinguish between different strain rates or does so only by online signal processing and control in robots, ultimately limiting our ability to directly probe both motion and position, unlike what can be monitored in biological force sensing. [ \n \n 21 \n \n ] As seen in vertebrates, muscle spindles contain neurons that respond to not just the overall change in muscle fiber length but also to the rate of muscle length change. [ \n \n 22 \n , \n 23 \n \n ] The latter functionality is often overlooked in soft robotics, but such rate‐of‐strain detection is required for feedback within emerging sensors and motion controllers. For example, curvature is easily mapped by traditional soft robotic strain sensors in a continuum robot. [ \n \n 24 \n \n ] However, controllers require feedback on both curvature and rate of curvature change. Moreover, current sensors cannot detect the continuous rotation of a robotic element due to their limited deformability, but the local shear field generated by rotation can be directly probed if immersed in a dynamic material that detects the rate of deformation, potentially enabling control over prosthetic joint rotation. As a result, anisotropic conductive soft materials would enhance the adaptability and sensitivity of soft robots for natural interaction with environmental stimuli. The recently discovered rate‐dependent conductivity response of metallic, non‐Brownian particles in Newtonian fluids [ \n \n 25 \n \n ] provides an opportunity to electrically detect the rate of strain directly, establishing a new modality of mechano‐electronic transduction. The conductivity in this system is driven by the formation of shear‐induced clusters that promote electron delocalization. Conceptually, these electrically dynamic materials can be incorporated into microfluidic devices to directly probe the rate of motion in a robotic limb in tandem with traditional force sensors that detect position. In this work, we develop a soft semiconducting composite whose electrical properties depend on the rate of strain. The soft composite was prepared by combining silver‐coated glass microspheres (AgMS) within a micro‐organogel (MG) matrix. The MG matrix contains a mixture of triblock and diblock copolymers swollen in a hydrocarbon solvent. The copolymers allow the composite to reversibly flow in response to deformation and resolidify upon flow cessation. [ \n \n 26 \n \n ] Using rheo‐electric measurements, we evaluate the influence of matrix viscoelasticity on electrical conductivity as a function of the shear rate and particle loading. We find that the electrical properties of the AgMS–MG composite are anisotropic, with a significant enhancement of the electronic conductivity in the flow direction for the AgMS‐MG composites driven by reorienting the electric driving force along the particle microstructure to enhance electron delocalization.",
"discussion": "2 Results and Discussion 2.1 Rheological Characterization of Conductive Soft Composites Conductive composites were prepared by combining AgMS with an electrically insulating MG matrix. The MG matrix consisted of a 1:1 mixture of the polystyrene‐block‐ethylene/butylene‐block‐polystyrene (SEBS) triblock and polystyrene‐block‐ethylene/propylene (SEP) diblock copolymers dissolved in hexadecane. This concentration was chosen based on the rheology of the MG sample summarized in Figure \n 1 \n . The 1:1 SEBS:SEP copolymer mixture exhibited a fluid‐to‐solid transition as the concentration of the copolymer mixture increased in hexadecane. This fluid‐solid transition was identified by combining frequency‐dependent small amplitude oscillatory shear tests on solid‐like samples summarized in Figure S1 (Supporting Information) and the steady state flow curves (Figure S2 , Supporting Information) of more dilute, liquid‐like samples. Fitting a power‐law relationship of the plateau modulus, G 0 , according to G 0 ∼ ( C − C ∗ ) n , yielded a n = 0.75 and C*= 24.3 mg mL −1 , where C is the concentration of polymer in mg mL −1 . Using this same concentration, the average viscosity, η, followed a Krieger‐Dougherty [ \n \n 27 \n \n ] like scaling upon approach to C * as shown in Figure 1A . The fluid‐solid transition agrees with similar measurements reported by O'Bryan et al., where the SEBS:SEP MG loses its elasticity at a critical concentration as the total copolymer concentration decreases. [ \n \n 26 \n \n ] The MG matrix was formulated at 40 mg mL −1 of the copolymer mixture as, at that concentration, the sample formed a strong gel but also exhibited a reversible flow response for independent loadings of the composite on the rheometer (Figures S3 and S4 , Supporting Information and the images in Figure 1B ). AgMS‐MG composite was formulated as a function of AgMS volume fraction and compared to AgMS‐oil suspensions in AR200. The steady state flow curves of AgMS‐oil suspensions and AgMS‐MG composites are summarized in Figure 1B . In both suspending media, the relative viscosity (η r ) increases with AgMS loading. The AgMS‐oil suspensions were Newtonian, whereas the AgMS‐MG composites exhibited strong shear‐thinning, consistent with the concentration‐dependent yield stress of other filled viscoelastic media. [ \n \n 28 \n , \n 29 \n \n ] The addition of non‐Brownian particles to the microgel network could serve to confine it, enhancing the shear thinning. [ \n \n 30 \n \n ] The presence of confinement can be confirmed with a quantitative analysis of the yield stress, as shown in Figure S5 (Supporting Information). The decrease in both the power law index and critical shear rate with particle loading extracted from the modified Herschel‐Bulkley model [ \n \n 31 \n \n ] that was fitted to the stress data demonstrates a stronger shear‐thinning behavior due to this confinement effect. More details on this analysis can be found in the caption of Figure S5 (Supporting Information). Further, the increase in the viscosity at high shear rates with particle loading is consistent with the corresponding viscosity change in the Newtonian oil, while the viscosity at low shear rates is dominated by the MG and its yield stress. The strong yield stress of the MG matrix prevented AgMS sedimentation and the AgMS particles remained well suspended in both dispersants for the duration of the experiments. Figure 1 Rheological response of swelled SEB‐SEPS copolymer assembly and composites prepared with AgMS particles. A) Rheological state diagram for the 1:1 SEB:SEPS mixture in hexadecane. The fluid phase viscosity data (shown with circles) was fit to a modified Krieger‐Dougherty equation shown by the black dotted line. The viscosity values determined from steady state flow curves are marked with a filled circle, and the viscosity values measured from frequency‐dependent small amplitude oscillatory shear tests are marked with empty circles. The storage moduli of the neat gels (shown with triangles) were fit to a power law to determine the liquid‐solid transition, marked by the black solid line at 24.3 mg mL −1 . The inset photograph is a stir bar suspended in neat MG. B) Flow sweeps of relative viscosity (η r ) for AgMS in organogel and AR200 silicone oil. The suspension viscosity data was normalized to the viscosity of the silicone oil and the organogel data was normalized to the viscosity of hexadecane. The AgMS‐MG samples (shown in the top photograph) display yield stress behavior, while the AgMS‐oil samples exhibit a Newtonian response and spread along the angled spatula (shown in the bottom photograph). 2.2 Conductivity of AgMS‐MG Sample Probed in the Gradient Direction To evaluate the change in electrical conductivity in the presence of MG matrix, rheo‐electric measurements were performed using a custom‐built parallel plate geometry shown in Figure \n 2 A . The steel plates are electrically connected through a wire in the shaft and are insulated from the electronic components of the rheometer by a polyetheretherketone thermoplastic mount. When a bias is applied between the plates, this geometry produces an electric field ( E ⇀ ⊥ ) oriented along the gradient direction, which is perpendicular to the direction of flow driven by the applied shear rate, γ ˙ . In Figure 2B , we show the transient current density, j , as a function of time subject to different γ ˙ for the 30 v% AgMS‐MG sample under an applied DC‐potential of 1V. Notably, the conductivity is probed using a relatively weak electric field strength of ≈10 2 V m −1 , which is far below the threshold (10 6 V m −1 ) to induce long‐range ordering of particles, commonly seen in electro‐rheological fluids. To quantitatively confirm that the AgMS dynamics remain unperturbed by the electric field, the Mason number, or the ratio between the viscous and electrostatic forces, was estimated to be between 10 7 to 10 9 according to the equation η MG γ ˙ / 2 ε r , MG ε 0 β E 0 2 over the range of γ ˙ used. [ \n \n 32 \n \n ] However, increasing the voltage or decreasing the geometry gap is a potential way to couple shear‐driven microstructural changes with electric‐field driven changes, such as those seen in electro‐rheology. [ \n \n 33 \n \n ] The measured current is below the noise limit of our instrument in the quiescent state and shows an instantaneous and reversible electrical response that scales with γ ˙ upon flow startup, consistent with the response of AgMS‐oil suspensions. [ \n \n 25 \n \n ] In these suspensions, the formation of shear‐driven clusters of conductive particles facilitates electron delocalization. Critically, the rate of cluster formation is proportional to the strain rate. One hallmark of materials used in tactile sensing devices is the linearity of the electrical response that is clearly demonstrated here with the proportional change in electrical current to shear rate. To further quantify the electrical transport behavior, we measured the AC‐conductivity (σ) as a function of frequency ( f ) at several shear rates. The corrected conductivity for the same 30 v% composite is shown in Figure 2C . As the shear rate increased, the conductivity increased across all frequencies tested, consistent with prior measurements of AgMS in AR200. The DC‐conductivity, σ 0 , was extracted at each shear rate from the plateau value identified at the lowest frequencies tested. [ \n \n 34 \n , \n 35 \n \n ] Shear rates where a clear DC plateau could not be identified were excluded from subsequent analysis. The conductivity curves for the other volume fractions are provided in Figure S6 (Supporting Information). The shear rate dependence of σ 0 as a function of volume fraction of AgMS is shown in Figure 2B . For the range of shear rates tested, there is a monotonic increase in σ 0 with a characteristic power law of σ 0 ∼ γ ˙ 1.23 − 1.43 , with indices that remain relatively similar for the three particle loadings tested. Furthermore, dramatic changes in the magnitude of σ 0 with AgMS loading are observed, consistent with an identical experiment with AgMS‐oil samples where the conductivity scales strongly with particle loading, shown in Figure S7 (Supporting Information) with AgMS from the same batch of particles dispersed in silicone oil. Figure 2 Electrical behavior of AgMS‐MG composites for an electric field oriented perpendicular to flow direction. A) Annotated image of gradient direction rheo‐electric geometry on Ares G2 rheometer. The 25 mm parallel plates are electrically connected to wires in the geometry and generate an electric field ( E ⇀ ⊥ ) perpendicular to the direction of particle velocity (or parallel to the gradient direction). B) Sequential step‐up and step‐down of γ ˙ in 180 s intervals show how the measured electrical signal changes proportionally and reversibly with flow rate. C) Corrected AC conductivity plotted against alternating current frequency as a function of γ ˙ for 30 v% AgMS‐MG sample. D) Scaling of the terminal conductivity plateau in the low frequency region with γ ˙ . The curves were fit to a power law that is shown by the dashed line with the power law index as indicated. Error bars were calculated from the average σ for frequencies <50 Hz and represent one standard deviation from the mean. Comparing the shear‐dependent σ 0 of the AgMS‐MG composites to that of suspension in AgMS‐oil sample improves our understanding of how MG alters the electrical transport. The shear rate dependent σ 0 are shown in Figure S8 (Supporting Information). The inset of Figure \n 3 \n depicts the orthogonal orientation of the electric field relative to the shear field applied to the flowing sample. Taking the ratio of the DC‐conductivity at the same shear rate and volume fraction of the AgMS‐MG composite and AgMS‐oil suspensions in Figure 3 , we find that the MG matrix had diminished conductivity along the gradient direction compared with the oil sample. This decrease in conductivity is a function of both volume fraction and shear rate, indicating that microstructural changes taking place in the microgel matrix are having a remarkable influence on the electron transport properties of the AgMS. A rescaling of σ 0 with γ ˙ and the particle radius squared shows how changes in electrical transport arise from a nontrivial relationship with microstructural differences in MG versus oil. In Figure S9A (Supporting Information), we can see that this ratio remains relatively constant. Further details on the connection of this scaling to the mean‐squared valence are in the caption of Figure S9 (Supporting Information). However, with this E ⇀ ⊥ orientation, shear flow in AgMS‐oil suspensions enables a considerable change in the ability of electrons to delocalize shown in Figure S9B (Supporting Information), suggesting a strong coupling between microstructure and electric field orientation. Figure 3 Comparison of electrical transport for suspensions in MG versus oil from the relative σ 0 plotted for each γ ˙ and ϕ tested. The corresponding dispersant phase is denoted in the superscript. With increasing ϕ, the conductivity of the AgMS‐MG measured with an electric field oriented in the gradient direction exhibits a stronger inverse dependence on γ ˙ . The red dashed line represents a conductivity ratio of 1. The inset is a schematic of the electrodes (orange) and corresponding electric field lines in the gradient direction (red) relative to the shear field (navy). 2.3 Electrical Response of the AgMS‐MG Composite in the Flow Direction To better understand the microstructural origins of this conductivity decrease, we performed rheo‐electric measurements using a custom‐built bottom plate depicted in Figure \n 4 A . A circular pattern of radial, interdigitated electrodes was printed onto a Kapton film with an aerosol jet printer and silver nanoparticle ink. Electrical measurements were performed with an electrically insulated top plate, ensuring that a large portion of the fringing electric field is directed along the flow direction. The inset of Figure 4A depicts the orientation of the electrodes relative to the flowing sample. A more detailed schematic of the electrode pattern and rheometer attachment with a comparison of the electric field lines is provided in Figure S10 (Supporting Information). The cell constant of 15.9 m −1 was calculated from KCl solutions of known conductivity in Figure S11 (Supporting Information). The dramatic difference in this value compared to the cell constant of 1.01 m −1 reported in Lin et al. confirms the different path of the electric field lines on the new attachment. [ \n \n 25 \n \n ] However, without simulations, the projection of the electrical flux along the flow direction is difficult to isolate in our measurements. To ensure that the AgMS‐MG composite exhibited reversible electrical properties on this attachment, the transient current density was monitored with the same protocol from Figure 2B . In Figure 4B , the electrical response of the AgMS‐MG composite is shown to also exhibit a similar proportional and reversible response with this electrode orientation. For the range of γ ˙ tested in Figure 4C , the composite exhibits a stronger monotonic increase in conductivity than the gradient electrode orientation that follows a characteristic power law of σ 0 ∼ γ ˙ 1.31 − 3.70 . A qualitative comparison to the scaling in Figure 2B indicates that there is a similar monotonic increase with volume fraction, but a steeper linear response for the configuration with an electric field oriented parallel to the flow direction. The corresponding conductivity sweeps are shown in Figure S12 (Supporting Information). The differences in the power law scaling could originate from two contributions, a change in the microstructure of the noncolloidal particles in the viscoelastic dispersant or transport being measured along a larger distribution of the radially varying γ ˙ on a parallel plate geometry. Figure 4 Investigating electron transport in the flow direction for AgMS. A) Photograph of the flow direction electrode attachment on the DHR rheometer. The inset is a schematic of the electric field (red) orientation, denoted with E ⇀ ∥ , parallel to the shear field direction (navy). B) DC‐electrical response for 30 v% AgMS‐MG sample with constant voltage bias of 1V. Sequential step‐up and step‐down of γ ˙ in 180 s intervals show how the measured electrical signal changes proportionally and reversibly with flow rate on this electrode attachment. C) Shear‐dependent σ 0 plotted for 25v%, 30v%, and 35v% AgMS‐MG composite fitted to a power law represented by the corresponding dashed line. D) Shear‐dependent σ 0 plotted for 25v%, 30v%, and 35v% AgMS‐oil suspensions plotted on log‐log axes and fitted to an exponential curve represented by the corresponding dashed line. The inset is the same data plotted on log‐linear axes to emphasize the different scaling with γ ˙ . We then compared the electrical response of the AgMS‐MG composite to the same noncolloidal particles dispersed in silicone oil on this electrode attachment to connect changes in the electron transport physics to the particle microstructure. The corresponding conductivity sweeps used to obtain σ 0 are shown in Figure S13 (Supporting Information) for the fluid suspension on the flow direction electrode attachment. In Figure 4D , the shear rate dependence of σ 0 is shown for comparison. Replotting the data on a semilog plot (Figure 4D inset) highlights the exponential scaling of the electrical response for the suspensions that demonstrates a greater enhancement at higher particle loadings. The different scaling of σ 0 when compared to what was measured on the gradient direction electrodes indicates that the dynamic cluster mechanism observed in Lin et al. [ \n \n 25 \n \n ] is not facilitating transport in this case. In Lin et al., noncolloidal particles form dynamic clusters that increase in size with the volume fraction. The fluctuation of charge among the particles in these clusters and their dynamic rearrangement is responsible for the shear‐dependent transport properties of the suspension. As these clusters orient with respect to the flow direction, an increase in conductivity is expected because the dynamics of charge exchange are enhanced along this direction. This is supported by analyzing the ratios of σ 0 for the MG versus silicone oil dispersants on the flow electrodes in Figure S14 (Supporting Information) over the range of γ ˙ . For almost all the conditions tested, the ratio is not dramatically different than 1 and displays no clear trend with γ ˙ , indicating that the mechanism of transport is similar for both dispersants. An analogous rescaling of the σ 0 power law in Figure 4C and Figure 4D further confirms the changes in the transport. In Figure S15A (Supporting Information), σ 0 for the AgMS‐MG composite displays a much stronger increase with γ ˙ when compared to the same measurements performed on the gradient electric field from Figure S9A (Supporting Information), suggesting that reorienting the electric field with respect to the direction of flow facilitates electron transport. Towards the development of a mechanically responsive semiconductor, we sought to assess the dependence of the electrical performance of the AgMS‐MG composites on electrode orientation relative to the direction of flow and understand how the macroscopic conductivity can be altered by engineering the particle microstructure during flow. In Figure \n 5 A , the relative DC conductivities for the fluid suspension of AgMS in oil measured with an electric field parallel to flow ( σ 0 ∥ ) versus perpendicular to flow ( σ 0 ⊥ ) are shown as a function of ϕ. For the γ ˙ range tested for the suspensions, the relative σ 0 experiences only a modest deviation below a ratio of 1, suggesting that shear‐driven clusters do not facilitate electron flow optimally with this electric field orientation. In comparison to the results of Lin et al., shear‐driven clustering governs the ability of electrical delocalization in the gradient direction, [ \n \n 25 \n \n ] but in this case, without a potential applied in the same orientation of these clusters, transport is diminished. This decrease can be explained based on the simulations of the collective diffusivity from Leshansky and Brady, [ \n \n 36 \n \n ] where the magnitude of clustering only increases with ϕ and γ ˙ in the gradient direction. Without an electric field driving electron flow along this microstructure, the relative σ 0 below 1 across the suspension conditions tested is expected. However, a different trend is observed for the AgMS‐MG composites in Figure 5B . Here, there is an improvement to electrical transport detected by the interdigitated electrodes indicated by the relative σ 0 increasing as a function of both γ ˙ and ϕ. This trend can be explained by the enhancements to noncolloidal particle alignment in viscoelastic media, consistent with simulations performed by Jaensson et al. [ \n \n 30 \n \n ] and optical microscopy measurements of microparticles in solutions of polyisobutylene or polyacrylamide [ \n \n 37 \n , \n 38 \n \n ] and cetyl pyridiniumchloride. [ \n \n 39 \n \n ] In Jaensson et al., particles are predicted to align when they are dispersed in a matrix with a low ratio between the solvent viscosity and zero‐shear rate matrix viscosity and with a large Weissenberg number, which is the dimensionless scaling between the elastic and viscous forces. Alignment stems from regions of low normal stress in the gap between adjacent particles. The AgMS‐MG composite exhibits strong elastic properties at ambient conditions in the flow sweeps from Figure 1B . In Figure S16 (Supporting Information), a time‐temperature superposition analysis was performed on the MG to obtain a crossover frequency between the storage and loss moduli. The relaxation timescale was determined from the inverse of the crossover frequency of 0.0008 s −1 . By multiplying by γ ˙ of 1 s −1 , we obtain a Weissenberg number of >1000, confirming that the elastic properties dominate the rheological response. Since the MG did not exhibit a low‐shear rate plateau during the flow sweep in Figure 1B , the viscosity at γ ˙ is 1 s −1 was used to determine the ratio of 4.5 × 10 −5 between the hexadecane solvent viscosity (3.03 mPa · s) and the MG zero‐shear rate viscosity. These two parameters, in tandem with the high particle loadings, indicate that the AgMS should exhibit strong alignment during flow. Since the particle alignment is in the direction of the electrical driving force, electrons can flow across a bridge of particles over longer length scales. Figure 5C shows a diagram of the proposed mechanism of electronic transport within the AgMS‐MG samples. In the quiescent state, the particles are evenly distributed throughout the MG matrix with no net electron transport. When a shear rate is applied to the sample, the particles align in the direction of the fringing electric field. The enhanced alignment brings the particles closer together, which increases the collision rate of the particles and promotes electron delocalization along the direction of flow. This bridging effect increases the magnitude and linearity of the detected electrical signal, making this electrode positioning and composite an ideal candidate for the fabrication of biocompatible electronics. Figure 5 Analysis of electrical transport for AgMS‐MG samples for different electric field orientations. A) Ratios of σ 0 measured on the flow direction electrodes (denoted with ∥) to σ 0 measured on the gradient direction electrodes (denoted with ⊥) as a function of γ ˙ for the AgMS fluid suspensions. The red dashed line represents a ratio of 1. B) Ratios of σ 0 measured on the parallel electrodes to σ 0 measured on the gradient electrodes as a function of γ ˙ for the AgMS‐MG composites. C) Schematic of proposed electron transport mechanism due to enhanced AgMS alignment in the presence of viscoelastic medium facilitated by the fringing electric field. The flow field is denoted by u ⇀ and the electric field is denoted by E ⇀ ∥ ."
} | 7,835 |
29308237 | PMC5750004 | pmc | 4,079 | {
"abstract": "In comparison to the transportation and storage of hydrogen, methane has advantages in the practical application, while the emerging product termed as ‘biohythane’ could be an alternative to pure hydrogen or methane in a new form of energy recovery from microbial electrolysis cell (MEC). However, the cathodic catalyst even for biohythane still bothers the performance and cost of total MEC. Herein, we fabricated the MEC reactor with surrounding stainless steel mesh (SSM) to investigate the feasibility of stainless steel mesh as an alternative to precious metal in biohythane production. The columbic efficiency (CE) of anode was around at 80%, representing the SSM would not limit the activity of anodic biofilm; the SEM image and ATP results accordingly indicated the anodic biofilm was mature and well constructed. The main contribution of methanogens that quantified by qPCR belonged to the hydrogenotrophic group ( Methanobacteriales ) at cathode. The energy efficiency reached more than 100%, reached up to approximately 150%, potentially suggesting the energetic feasibility of the application to obtain biohythane with SSM in scale-up MEC. Benefiting from the likely tubular configuration, the ohmic resistance of cathode was very low, while the main limitation associated with charge transfer was mainly caused by biofilm formation. The total performances of SSM used in the tubular configuration for biohythane production provide an insight into the implementation of non-precious metal in future scale-up pilot with energy recovery.",
"conclusion": "4. Conclusion The performance of MEC with cycling cathode proved the non-precious metal could be an alternative to precious one. Besides, the CE and activity of anodic biofilm implied that there were no obvious negative influences caused by the utilization of SSM. Hence, the conclusion from the evaluation of SSM was that it is feasible for MEC to produce biohythane at low cost benefiting from SSM application.",
"introduction": "1. Introduction Energy crisis was a potential threat for human advance as the depletion of fossil fuel occurred at a high rate and was unrenewable and unsustainable. Biohydrogen production by dark- and photo-fermentation provided a new way that was clean and effective to solve this threat [ 1 ]. As an innovative way to convert organic matter to electrons at anode and produce hydrogen at cathode, microbial electrolysis cell have attracted more and more attention [ 2 ]. Microbial electrolysis cell (MEC) was a breakthrough for dark-fermentation with glucose as it can use volatile fatty acid (VFA) for hydrogen evolution. More and more studies focused on factors in terms of electrode spacing [ 3 ], catholyte [ 4 ], anode microbial community [ 5 ], ion transport resistance [ 6 ], buffer solution [ 7 ], substrate [ 8 ] etc. have enhanced the performance of hydrogen production of microbial electrolysis cell. Under the condition that performance of microbial electrolysis cell has been enhanced significantly, more modified configurations adapted to the scale-up tests need to be done to evaluate the performance of MEC in applications. Among, the material of cathode was a restriction for MEC application, especially for Pt/C that was a kind of precious metal with expensive price. Hence, many studies have concentrated on searching for low-cost and high-performance alternative material for MEC application [ 9 , 10 ]. Nickel foam (NF), stainless steel wool (SSW), platinum coated stainless steel mesh (Pt), and molybdenum disulfide coated stainless steel mesh (MoS 2 ) electrodes were assessed at different initial pHs using unbuffered catholytes in microbial electrolysis cells [ 11 ]. Recently, stainless steel mesh (SSM) was widely applied for microbial electrolysis cell as alternative cathode catalyst [ 12 ], because of its low cost [ 13 ] and high surface area [ 14 ]. Another inevitable obstacle that was methane having been evolved in single microbial electrolysis cell (SMEC) as end product limited further application of MEC for biohydrogen. Methane was detected only in the glucose-fed microbial fuel cell (MFC) rather than acetate type, which means that anode respiring bacteria (ARB) could out-compete acetoclastic methanogens [ 15 ]. Wang et al . [ 16 ] deemed that methane production was related to applied voltage, while there is no significant relevance with methanogen. Cheng et al . [ 17 ] supported the theory that electromethanogenesis enhanced methane production at cathode. Methane also may be synthesised via converting CO 2 with proton and electron at cathode, according to the electrosynthesis equation:\n C O 2 + 8 H + + 8 e − = C H 4 + 2 H 2 O . \nThis testified that methane can be produced from electrosynthesis as CO 2 was trapped in SMEC at cathode [ 18 , 19 ]. Considering the multiple pathways for methane generation, as well as the methane, which takes advantages in the safety of transportation and storage, could be an alternative sustainable energy to hydrogen. Moreover, the biohythane was becoming a better choice to be produced in MEC. However, although the recent focuses have been transferred from hydrogen recovery to achieve biohythane generation, the proper cathode material that potentially adapted to practical implication is scarcely insufficient. Considering MEC is a promising assisted strategy to enhance energy recovery from wastes; however, the insufficient investigations related to cathodic catalysts that predominantly determines the cost for practical application restricted the development of it. Herein, a new reactor was constructed with circled stainless steel mesh as cathode, we aimed to evaluate the performances of MEC shelled with stainless steel mesh, in terms of biohythane production, anodic bio-activity and cathodic resistance.",
"discussion": "3. Results and discussion 3.1. Start-up and operation period of single microbial electrolysis cell Three single microbial electrolysis cell reactors were constructed and operated in 48 h-batch model to obtain similar performance with acetate as solely carbon source. In order to achieve similar coulombic efficiency (CE), some reactors were duplicately inoculated here. During the start-up period, the value of CE was up to nearly 160% and that was similar between different reactors. 1# reactor achieved highest value of 156%. The rest of reactors, 2#, 3#, reached 149% and 152%, respectively. The higher coulombic efficiency in single microbial electrolysis cell could be attributed to hydrogen recycle, in which consumption of hydrogen at anode by anode respiration bacteria have been testified, and this will be a restriction of SMEC advance. Thus methane has been considered as end-product in SMEC for it can prevent extra energy consumption from hydrogen recycled [ 26 ]. After the start-up period, as shown in figure 1 , hydrogen was the main product for initial few days. Then, methane generated and increased gradually until remaining constant in subsequent 48 h-batch. The proportion of methane in the content of gases that were produced from SMEC went up from 13% to 55%, which represented the content of methane increased as longer operation period and the depletion of hydrogen. The portion of hydrogen that is depleted during the operation period is not corresponding to the content of additional of methane. Hydrogen is not the sole source, however, to transform into methane by hydrogenotrophic methanogens or anode bacteria that can convert H 2 and CO 2 to acetate firstly; electrosynthesis of methane also may play an important role in that part. The initial percentage of methane was 13%, representing methane synthesized when hydrogen just evolved; this also supported that hydrogen was not the sole substrate for methane because the time was too short for methanogens growth.\n Figure 1. Proportion of biogas.\n 3.2. Evaluation on reactor performance During the stable operation period, as shown in figure 2 , in addition to the hydrogen or methane production, the coulombic efficiency could reveal the microbial activity of anode. The coulombic fluctuated around 80%, where the average value was 79.9 ± 2%; this could be ascribed to the methane evolution which avoided the hydrogen recycle compared to higher value in start-up period. Although previous studies showed yield coefficients of f s 0 was 0.05 for Geobacter sulfurreducens [ 27 ], which was considered as predominant bacteria responsible for extracellular electron transfer, considering the multiple trophic level in anodic biofilm in the presence of syntrophic fermenters which possess higher coefficient [ 28 ], moreover, the potential loss should be one of contributors, the coulombic efficiency around 80% was reasonable and satisfactory. Comparing with more than 100% values during start-up period, the phenomenon of hydrogen recycle would be gradually evitable as the growth of methane generation, which was favourable to decrease the ohmic loss that could be ascribed to hydrogen recycle. Another important indication behind the higher coulombic efficiency suggested the modified cathode could be useful to expand the ability of anode without the impediment of the cathodic reaction rate. The cathode electron recovery was of importance to evaluate the performance of catalytic efficiency. As the intrinsic electrochemical property of stainless steel mesh, the electron recovery was low around at 50%; however, the growth of methanogens that had been proved in previous publications could consume electrons for biomass synthesis; moreover, other autotrophic bacteria that could be cooperator with methane generation also led to the loss of electrons. Obviously, it was inevitable for microbial growth in multi-scale application; however, the bio-affinity of cathode also could be enhanced in view of the main contributed methane by microbes. Although the electrochemical methane generation was commonly reported, the strong binding energy of CO was essential, which limited the range of transient metals; copper would be a better choice rather than iron [ 29 , 30 ]. Therefore, the methanogens commonly functioned the duty for methane production from MEC. The modification in the surface of non-precious with carbon materials would be proper to enhance methane generation [ 31 ]. However, the lower cathode electron transfer was reasonable if considering the effect of biofilm. Importantly, it seemed that the surrounding structure has boosted the anodic ability in transferring electrons to the electrode without limitation of cathodic reaction rate. This configuration tried to solve the distance between anode and cathode in stimulation of scale-up applications, where the long-range transportation of ionic migration would be the main loss of energy. The positive achievement in energy efficiency would be appreciated for economic feasibility. The energy efficiency stayed beyond the bottom line of 100%, which showed the economic feasibility of this configuration. Although the heat value of methane was lower than hydrogen, while the energy efficiency exceeding 100% represented methane recovery also achieved positive evaluation in energy input and output. Additionally, the finally collected biogas was composed of hydrogen and methane; the biohythane (hydrogen accounted for 12.3 in mixture of hydrogen and methane) was thermodynamically favourable during combustion process that greatly enhanced the methane powered vehicles [ 32 ]. Apparently, the biohythane would be a better choice to pure hydrogen or methane in MEC in future application.\n Figure 2. Performance of MEC reactors.\n 3.3. Anodic biofilm The biofilm at anode, which drives the electron transfer from organics to electrode, was observed with FE-SEM, as shown in the SEM image ( figure 3 a ). The microbes attached on the carbon brush closely, the rod bacteria seemed like physical morphology of Geobacter . Although the electron transfer pathway for anode biofilm has been clearly elucidated, consisting of pili-mediated, electron shuttles, and cytochrome. The electron shuttles were soluble and diffused in the substrate. The cytochrome generally attached on the membrane, which took responsibility for electron transfer through physical contact. Both of them were hard to observe directly. The pili, which owned the filament structure, was potentially easier to see. Although some literature reported the observed pili through SEM, it was the far distant view of it, because the real diameter of single nanowire was 4.0 × 10 −9 m [ 33 ], which was invisible with the SEM. In sum, the SEM image not only provided the physical morphology of bacteria attached on the electrode, but also revealed the robust connecting information of bacteria and electrode. Herein, the SEM image showed the anodic biofilm was successfully formed on the electrode.\n Figure 3. ( a ) SEM images of anodic biofilm. ( b ) Cell number of anodic biofilm.\n Besides, the SEM only provided the morphology of biofilm, which failed to give the quantitative details. The ATP detection successfully quantified the cell numbers of bacteria (as shown in figure 3 b ). The variation of ATP in the suspension was accordingly similar to the change of current. The initial high ATP value indicated the rapid response of bacteria to the change of substrate, while the error bar could be influenced by the residue oxygen in the influent. After several hours, the ATP value implied the stable microbial activity. As the decrease in current, the ATP value dropped slightly, which could be caused by the consumption of acetate. 3.4. Cathodic electrochemical property The resistance of electrode determined the energy loss, the EIS detection generally revealed the ohmic resistance, charge transfer and diffusion [ 34 ]. Herein, a sine sigmoidal wave was applied to the cell ranging from 100 000 to 0.1 Hz to evaluate the performance of cathode. In order to timely investigate the variation of resistance, the measurement was completed in different current value, which represented the working status of MEC. The measurement was completed at 6.9 mA ( figure 4 b ) prior to the current decrease to 1.7 mA ( figure 4 a ), where was the second point. According to the results of EIS, two semicircles were obtained during the test, where the first could be ascribed to the electron transport on conductive skeleton, and the second could be caused by the charge transfer. There was no obvious difference in ohmic resistance for lower or higher current value. The inner resistance for low current was 3.667 Ω , and that for high current was 2.994 Ω (as shown in electronic supplementary material, figures S1 and S2 and table S2). However, the charge transfer resistance of higher current was significantly lower than that of lower current (93.48 Ω versus 120.6 Ω ).\n Figure 4. EIS results at low current ( a ) and high current ( b ).\n The ohmic resistance and electron transport resistance should be mainly related with the property of cathode, where the stainless steel mesh, as a kind of transient metal, owns good performance in conductivity, thereby the ohmic resistance was low. The charge transfer was controlled by the chemical reaction rate in the inter-surface of liquid and electrode, a sharp decrease could be regulated by the activity of microbes. The formation of biofilm, which covered the active sites for catalyst in the cathode, dominated the reaction that occurred at the cathode, thus, controlled the charge transfer directly. The decrease could be caused by the variation of microbial activity. Obviously, at initial hours, the high current could be supported by the hydrogen evolution as the microbial community for methane production is unmatured. Once the methane proportion increased, that implied mature community would improve the methane generation to increase the charge transfer resistance with low current. 3.5. Cathodic methanogens Figure 5 reveals the significant difference of 16S rRNA gene copies of two hydrogenotrophic methanogens orders and two acetoclastic methanogens families in cathodic samples. The numbers of the Methanobacteriales and Methanomicrobiales 16S rRNA gene which presented by hydrogenotrophic methanogens significantly dominated. The number of Methanobacteriales in the cathode biofilm was highest compared with other methanogens (4.6 × 10 8 copies µl −1 ), which was accordant to the result of Illumina sequencing analysis. Methanomicrobiales which represented hydrogenotrophic methanogens was also enriched at the cathode based on the abundant 16S rRNA gene copies (9.2 × 10 7 copies µl −1 ). However, there was a clear low number of the acetoclastic methanogens contains Methanosarcinaceae and Methanosaetaceae . At initial hours of operation, the number of methanogens stays low, there is a significant increase as the current decreases in the end of operation period. Not only the hydrogenotrophic methanogens increased significantly, the acetotrophic methanogens also enriched, which is similar to previous studies that proved the two pathways for methane generation by co-effort of hydrogenotrophic and acetoclastic methanogens [ 35 , 36 ]. Obviously, the hydrogenotrophic pathway should be the main contribution to the methane production. The variation of methanogens accordingly verified the charge transfer could be regulated by microbial biofilm at cathode.\n Figure 5. Quantitative analysis of methanogens."
} | 4,344 |
25732131 | PMC4346804 | pmc | 4,082 | {
"abstract": "This study investigates interactions between recently identified denitrifying anaerobic methane oxidation (DAMO) and anaerobic ammonium oxidation (anammox) processes in controlled anoxic laboratory reactors. Two reactors were seeded with the same inocula containing DAMO organisms Candidatus Methanoperedens nitroreducens and Candidatus Methylomirabilis oxyfera, and anammox organism Candidatus Kuenenia stuttgartiensis. Both were fed with ammonium and methane, but one was also fed with nitrate and the other with nitrite, providing anoxic environments with different electron acceptors. After steady state reached in several months, the DAMO process became solely/primarily responsible for nitrate reduction while the anammox process became solely responsible for nitrite reduction in both reactors. 16S rRNA gene amplicon sequencing showed that the nitrate-driven DAMO organism M. nitroreducens dominated both the nitrate-fed (~70%) and the nitrite-fed (~26%) reactors, while the nitrite-driven DAMO organism M. oxyfera disappeared in both communities. The elimination of M. oxyfera from both reactors was likely the results of this organism being outcompeted by anammox bacteria for nitrite. K. \n stuttgartiensis was detected at relatively low levels (1–3%) in both reactors.",
"discussion": "Discussion The process data strongly suggest that, in both reactors, the DAMO and anammox processes were jointly responsible for the nitrogen and carbon conversions. Independent of the forms of oxidized nitrogen (nitrate vs. nitrite) in the feed, M. nitroreducens was responsible for nitrate reduction to nitrite and the anammox process responsible for nitrite reduction, when steady states were reached. This finding was supported by the microbial community data, which showed that M. nitroreducens , able to reduce nitrate to nitrite with methane as the electron donor 9 , was abundant in both reactors, while M. oxyfera , able to reduce nitrite to nitrogen gas with methane as the electron donor 7 , was not present in the steady state communities. Also, Kueneniaceae , a known anammox bacterium, was found in both communities despite its relatively low abundance suggested the possible presence of other anammox organisms. In the inoculum for both reactors, M. oxyfera was present at significant abundance (estimated to be ~20% of the community). We hypothesize that M. oxyfera disappeared from both cultures because it was outcompeted by anammox bacteria and M. nitroreducens . Nitrite is a key substrate for both M. oxyfera and anammox bacteria. Although both M. oxyfera and anammox bacteria have low affinity constant for nitrite 5 18 , the nitrite consumption rates reported in literature by anammox bacteria were much higher than M. oxyfera . Previous studies have also shown that DAMO cultures containing M. nitroreducens are capable of nitrate reduction at much higher rates compared to DAMO cultures containing M. oxyfera only 8 , suggesting either that M. oxyfera cannot reduce nitrate 7 , or its nitrate reduction rate would likely be much lower than that of M. nitroreducens . Based on the results of current study and information available in literature, we have proposed a hypothetical conceptual model to show the potential interactions between DAMO and anammox microorganisms in anoxic environments rich in ammonium and methane with either nitrate or nitrite being externally supplied ( Figure 5 ). In the diagram we still included the DAMO process from nitrite to nitrogen gas as a possibility as it occurred during the transient periods in both reactors. It should also be highlighted that our understanding of the growth kinetics of DAMO archaea and bacteria, and the environmental factors regulating their competition is very limited at present, and therefore, it cannot be ruled out that M. oxyfera may form an important member of the community under environmental conditions that are different from those used in this work. Indeed, a recent study showed that M. oxyfera coexist with M. nitroreducens and anammox bacteria in a MBfR reactor, where ammonium/nitrate and methane were transferred to the biofilm through counter diffusion 13 . The findings of this study could have important implications to the nitrogen and carbon conversion in natural environments. In some natural environments, such as waterways receiving nutrient rich runoff from farms, nitrate and ammonium in the water body may come in contact with methane produced in sediments. With nitrate being the primary oxidized nitrogenous compound, M. nitroreducens could be one of the denitrifying microorganisms that reduce nitrate to nitrite and become the partner of anammox bacteria. The cooperation of anammox and DAMO processes could substantially affect the carbon and nitrogen conversion in these environments. Isotopic tracing method would be required for the future studies of this interaction in natural systems due to the extremely low reactions rates expected. The co-culture of M. nitroreducens and anammox bacteria can potentially be used for wastewater treatment. The anammox process is already used in full-scale for nitrogen removal from wastewater 1 . However, nitrate is produced as a by-product, which requires downstream treatment to accomplish the whole denitrification process. In some other cases, nitrate may be present in the feed, along with ammonium and nitrite. This study shows that the DAMO and anammox processes can be combined in one reactor to simultaneously remove nitrate and ammonium, with methane as an additional electron donor. This is particularly attractive as methane can be produced at a wastewater treatment plant through anaerobic wastewater or sludge digestion 19 . The feasibility of using a co-culture of DAMO and anammox organisms for wastewater treatment has been investigated recently 14 . However, the co-culture used in that study comprised of M. oxyfera and anammox bacteria, which does not remove nitrate, and in fact may not be stable if ammonium feed is in excess 14 . The co-culture of M. nitroreducens and anammox bacteria would be a more suitable candidate for this process. A key challenge for future research is to enhance the reaction rates to meet the requirement of industrial application. The denitrification rate obtained here is about 20 mgN/gVSS.d, which is an order of magnitude lower than the denitrification rate achievable with methanol 20 . Another challenge for future research is to grow the biomass in a short time, since both of these microorganisms are well-known slow growers. Results of the current study showed that our understanding of DAMO organisms and their potential interactions with other microbial groups are far from being complete. The syntrophic relationship between DAMO and anammox microorganisms should be further explored to understand its implications to nitrogen and carbon cycles in natural environments. The potential interactions between DAMO organisms and other microbial groups, such as nitrite/nitrate producers/reducers also remain to be investigated."
} | 1,768 |
26551153 | PMC4678148 | pmc | 4,083 | {
"abstract": "Anaerobic digestion enables the water industry to treat wastewater as a resource for generating energy and recovering valuable by-products. The complexity of the anaerobic digestion process has motivated the development of complex models. However, this complexity makes it intractable to pin-point stability and emergent behaviour. Here, the widely used Anaerobic Digestion Model No. 1 (ADM1) has been reduced to its very backbone, a syntrophic two-tiered microbial ‘ food chain ’ and a slightly more complex three-tiered microbial ‘ food web ’, with their stability analysed as a function of the inflowing substrate concentration and dilution rate. Parameterised for phenol and chlorophenol degradation, steady-states were always stable and non-oscillatory. Low input concentrations of chlorophenol were sufficient to maintain chlorophenol- and phenol-degrading populations but resulted in poor conversion and a hydrogen flux that was too low to sustain hydrogenotrophic methanogens. The addition of hydrogen and phenol boosted the populations of all three organisms, resulting in the counterintuitive phenomena that (i) the phenol degraders were stimulated by adding hydrogen, even though hydrogen inhibits phenol degradation, and (ii) the dechlorinators indirectly benefitted from measures that stimulated their hydrogenotrophic competitors; both phenomena hint at emergent behaviour.",
"introduction": "1 Introduction Microbial degradation of organic compounds in methanogenic environments is a sequential process catalysed by a series of different micro-organisms. Syntrophy plays a pivotal role in these feeding webs: degradation of compounds like propionate and phenol is only sustainable if their degradation products, hydrogen and acetate, are removed by methanogens. The thermodynamic rational behind syntrophy is well understood, but its kinetic framework is less established. This raises questions about the stability of these feeding chains and the factors that govern them. As a first step towards answering these questions a simple mathematical model was previously developed describing the interactions in a two-tiered feeding chain, populated with a set of parameters that apply to propionate degraders and hydrogenotrophic methanogens ( Xu et al., 2011 ). Mathematical analysis of the model indicated that the system was always stable: there were no conditions where the populations of the two organisms oscillate or show other forms of emergent behaviour. The objective of the present paper is to introduce an additional organism into a similar feeding chain and evaluate its effect on stability and potential emergent behaviour of the resulting ‘food web’. The organism of choice is a chlorophenol-dechlorinating bacterium. The other two organisms are a phenol degrader and a hydrogenotrophic methanogen. The complete removal of phenolic compounds from the system is hereby referred to as chlorophenol mineralisation. The salient feature of the chlorophenol degrader here is that production of phenol is coupled to consumption of hydrogen by hydrogen cycling. Thus, as a hydrogen consumer, the dechlorinator competes with the methanogen for hydrogen ( Dolfing and Tiedje, 1986 , Dolfing and Tiedje, 1991 ). The working hypotheses are (i) that the dechlorinator can (partially) replace the methanogen as the syntroph in a phenol-degrading consortium and (ii) that introduction of this organism can potentially lead to unexpected emergent behaviour related to the intricacies of the multi-species relationships. It should be noted that chlorophenol is the chosen compound for this study due to the availability of data for parameterisation of the model, but the analysis will hold, generally, for any similar food-web demonstrating equivalency. It has been shown that deterministic modelling of biological systems, typically through a system of coupled ordinary differential equations (ODEs), provides important understanding of these often complex processes, specifically in determining changes to the system behaviour given perturbations in the inputs. For anaerobic digestion, higher dimensional models are useful for capturing the phenomenological behaviour of the multi-step processes and are often the de-facto method for understanding plant operation ( Batstone et al., 2002 ). On the other hand, simplified or reduced models have received more attention in process monitoring, control design ( Bernard et al., 2001 , Gaida et al., 2012 ), and optimisation ( Vavilin et al., 2001 ). Simplified models have also been applied to determine the global ( Benyahia et al., 2012 , Shen et al., 2007 ) or local ( Simeonov and Diop, 2010 ) stability of the system under investigation. Typically, these are two-species models, whereas here a case considering a three-species food web is presented. Whilst a strictly analytical approach is not possible given the dimensions of the ensuing model, the approach taken here derives analytic expressions for all steady-states, supported by numerical simulations to determine the regions of local stability within sensible operating conditions. As such, it is possible to gain a formal understanding of the emergent properties of all states.",
"discussion": "5 Discussion In this work, a mathematical analysis of a three-tiered ‘food web’ comprising three organisms with hydrogen addition and inhibition has been presented. Although mechanistic models of microbial interactions are somewhat ubiquitous, analytical approaches have been limited to simple two-species systems ( Xu et al., 2011 , Dubey and Hussain, 2000 , Wu et al., 2004 ). More recently, attempts at analysing more complete systems, such as the anaerobic digestion process, have been performed with some degree of rigour ( Bornhöft et al., 2013 , Weedermann et al., 2013 ), however the practicality of these approaches is limited by the need for generalisation and increasing numbers of assumptions to allow for mathematical tractability. Although the three-tiered system is considered only a sub-process of anaerobic digestion and the analysis limited to a specific compound, the approach is general enough to provide information about the characteristics of such a process and allows for the possibility of extending the work to other systems and other compounds. Indeed the results shown here point to the fact that biological knowledge can inform mathematical approaches, whilst mathematical models can indicate or confirm biological properties of a system, succinctly and rationally. Here, four models were analysed by a combination of analytical and numerical techniques to obtain information regarding the extent and characteristics of system stability in a three-organism process anaerobically degrading chlorophenol. In this case, only the hydrogen part of the pathway was considered, with acetate being excluded from the analysis. The simple two-tiered food chain considering only phenol degradation with two species was shown to have the same characteristics observed as a previously studied system investigating propionate ( Xu et al., 2011 ); three steady-states and always stable. A second model introduced chlorophenol as the primary substrate and a dechlorinating organism forming a tri-culture that resulted in the emergence of bistable conditions between the complete washout steady-state and the two other viable states. Analysis of these bistabilities has shown that the desired operating condition (SS6) has the strongest basin of attraction such that complete washout can only occur when the initial condition for one of the biomass concentrations is zero. Although it is interesting to see the extent under which full chlorophenol mineralisation can occur using this standard model, of greater interest from an engineering perspective is the possibility of driving the system towards its limits of operational viability without compromising its function. With this in mind, the inclusion of additional input terms for hydrogen and phenol was undertaken, and corresponding stability analysis performed. In the case of hydrogen addition, it was expected that this would lead to a wider region of stability for the methanogen and, thus, extend the operational domain for SS6. Indeed, this was the case under relatively high concentrations of chlorophenol input, under which the methanogen population was maintained up to a theoretical maximum, dictated by its maximum growth rate. However at low chlorophenol input ( < 0.5 kgCOD / m 3 ), the nature of the resource competition between the dechlorinator and methanogen is such that a switching of behaviour occurs in localities not conducive to stability of all three organisms. Under the standard three-tiered chlorophenol model, resource competition dictates that the dechlorinator is able to utilise the available hydrogen for growth more readily than the methanogen and under SS4 a competitive exclusion principle occurs and the latter is washed out. This case confirms that in specific operating regions hypothesis (i), which states that the dechlorinator can (partially) replace the methanogen as the syntroph, may be achieved. Although full chlorophenol mineralisation cannot be obtained in this state (some phenolic compounds remain unconsumed), the results compare well with experimental observations for an equivalent chlorobenzoate degrading system ( Dolfing and Tiedje, 1986 , Dolfing, 1990 ). With an abundance of additional hydrogen, however, the methanogen may access enough hydrogen to maintain a population at steady-state. However, below a threshold concentration and under specific dilution rates, an excess of hydrogen leads to inhibition of the phenol degrader and washout. In effect, the addition of hydrogen at this threshold results in a switching between SS4 and SS5, rather than a stabilisation at SS6. Nevertheless, the addition of phenol under specific operational conditions can result in the emergence of SS6 at low chlorophenol input conditions. Here, a specific form of competition between the dechlorinator and methanogen occurs (as with SS6 in the standard model), in which both organisms benefit from the production of hydrogen by the intermediate phenol degrader, whilst the phenol degrader is stabilised by the syntrophic hydrogen removal, a further confirmation of hypothesis (i). In other words, the presence of the chlorophenol degrader allows for the production of phenol, which benefits both the phenol degrader and, indirectly, the methanogen. The presence of the methanogen reduces the inhibition on the phenol degrader, thus allowing the hydrogen resource to be maintained for both hydrogenotrophic populations. This can be seen as a form of mutualism rather than competition. The phenol addition plays a significant role under conditions where the chlorophenol degrader cannot produce enough phenol to maintain the phenol degraders, and under such conditions it is possible to achieve full chlorophenol mineralisation beyond the standard model system. A schematic of these models and their interactions for the low chlorophenol input condition is shown in Fig. 8 . Although higher dimensional systems are analytically restricted and lack generality, the work reported here for a three-tiered ‘food web’ underlines the potential for applying localised stability analysis within meaningful operating and parameter ranges, to identify properties of the system that both increase fundamental understanding of the behaviour of such microbial systems, but also guide thought on ways to manipulate or control them for potential process improvement. Further work will include a thermodynamic rather than a kinetic inhibition term for the effect of hydrogen on the syntroph, and the extension of the model to polychlorinated phenols."
} | 2,931 |
37877089 | PMC10591227 | pmc | 4,085 | {
"abstract": "Rhizobia are soil bacteria that can establish a nitrogen-fixing symbiosis with legume plants. As horizontally transmitted symbionts, the life cycle of rhizobia includes a free-living phase in the soil and a plant-associated symbiotic phase. Throughout this life cycle, rhizobia are exposed to a myriad of other microorganisms that interact with them, modulating their fitness and symbiotic performance. In this review, we describe the diversity of interactions between rhizobia and other microorganisms that can occur in the rhizosphere, during the initiation of nodulation, and within nodules. Some of these rhizobia-microbe interactions are indirect, and occur when the presence of some microbes modifies plant physiology in a way that feeds back on rhizobial fitness. We further describe how these interactions can impose significant selective pressures on rhizobia and modify their evolutionary trajectories. More extensive investigations on the eco-evolutionary dynamics of rhizobia in complex biotic environments will likely reveal fascinating new aspects of this well-studied symbiotic interaction and provide critical knowledge for future agronomical applications.",
"conclusion": "7 Conclusion and perspectives The rhizobium-legume symbiosis has long been a model system to study both the molecular and eco-evolutionary aspects of host-microbe interactions. In the recent years, we have witnessed an increased interest in incorporating the effect of complex microbial communities on the functioning of this symbiosis, and numerous interactions with a multitude of microbes have already been detected throughout the rhizobial life cycle in both laboratory and field conditions ( \n Table 1 \n ). However, certain stages of the rhizobial life cycle have been understudied. For instance, interactions within the nodule microbiome, although much less complex than the rhizosphere microbiome, still lack a comprehensive understanding. Similarly, interactions of bacteria released from senescent nodules with soil communities remain largely unknown. In addition, research has predominantly focused on pairwise interactions so far, while in nature, interspecies interactions occur in multispecies communities. In such complex ecosystems, higher-order interactions can profoundly impact the fitness of a focal strain ( Levine et al., 2017 ). Another set of open questions relates to the genetic bases of inter-microbial interactions. Once we start to uncover the molecular mechanisms involved in these interactions and to describe the existing natural genetic variations in the life history traits, it will be particularly interesting to further test whether there are genetic trade-offs or couplings between these different traits, including those involved in the interaction with the host plant. In parallel, assessing the eco-evolutionary dynamics of these interactions with laboratory evolution or field experiments will provide complementary information on the selective pressures acting on rhizobial populations. Therefore, we have probably only scratched the surface of the extent to which rhizobial-microbial interactions contribute to the establishment and functioning of legume-rhizobia symbioses. Additional discoveries are expected as research progresses on this topic, concerning both the mechanisms that mediate these interactions and their ecological and evolutionary consequences. A future challenge will be to integrate all these findings in a coherent framework, and use this knowledge to improve agricultural and ecosystem services that can be obtained from rhizobia. An ambitious goal would be to be able to design synthetic communities where microbial interactions enhance rhizobial fitness and symbiotic services, and mitigate the effects of plant pathogens. This will require cooperation between several disciplines (molecular microbiology, ecology and evolutionary biology, plant physiology, agronomy…) and cross-fertilisation between laboratory and field experiments.",
"introduction": "1 Introduction Ecological systems are complex. They involve a multitude of organisms that can interact with each other. These interactions, ranging from antagonism to mutualism, strongly influence the fitness of each individual and, consequently, the structure of the communities in which they live. Microbial communities, termed microbiomes, in particular have received much attention because of the fundamental role they play in Earth’s biogeochemical cycles and in plant and animal health. Common mechanisms governing interactions within microbiomes include competition for resources, predation, the production of antagonistic/toxic molecules, cross-feeding processes, the production of public goods, or the formation of protection structures such as biofilms ( Konopka, 2009 ; Pierce and Dutton, 2022 ). These interactions are particularly prevalent and significant in dense host-associated microbial communities, such as the mammalian gut or the rhizosphere ( Hassani et al., 2018 ; Coyte and Rakoff-Nahoum, 2019 ; Kern et al., 2021 ; Chepsergon and Moleleki, 2023 ). In these ecosystems, positive or negative interactions between microbiome members can allow or inhibit, respectively, the proliferation of pathogens or beneficial microbes, with important effects on host health. For example, some rhizospheric bacteria were shown to inhibit the growth of fungal pathogens and protect plants against disease ( Carrión et al., 2018 ; Durán et al., 2018 ). Notable members of the rhizosphere community are rhizobia. These bacteria are able to form mutualistic associations with legume plants, during which they fix atmospheric nitrogen to the benefit of the host, in exchange for carbon compounds from photosynthesis ( Poole et al., 2018 ). Rhizobia are gram-negative bacteria classified in 18 different genera of Alpha- and Beta-proteobacteria including Rhizobium, Sinorhizobium, Bradyrhizobium, Mesorhizobium, Azorhizobium, Cupriavidus , and Paraburkholderia ( Masson-Boivin et al., 2009 ; Tang and Capela, 2020 ). Rhizobia are horizontally-transmitted symbionts. Their biphasic life cycle is composed of a free-living saprophytic phase, where rhizobia are part of the soil and rhizosphere microbiomes, and a symbiotic phase in their host. Soil bacteria are attracted to the germinating seeds or the mature roots following the perception of chemoattractants present in plant exudates ( Compton and Scharf, 2021 ). In the plant, rhizobia are hosted in specific root organs, called nodules. Nodule formation is initiated by the exchange of compatible signals between rhizobia and legumes ( Walker et al., 2020 ). In most rhizobia, the expression of nod genes, responsible for the synthesis of lipochito-oligosaccharides called Nod Factors (NF), is induced by specific flavonoids exuded by host plants. NF, whose structures vary between rhizobium strains, are then specifically recognised by plant receptors. The perception of NF allows the entry of bacteria in root tissues, where they start to proliferate extracellularly. NF perception and downstream signaling also trigger a plant development program, which leads to nodule organogenesis. In most legumes of the Papilionoideae and Mimosoid clades ( Sprent, 2009 ; De Faria et al., 2022 ), rhizobia are then engulfed in the cytoplasm of nodule cells, where they form structures surrounded by the plant plasma membrane called symbiosomes. Rhizobia differentiate into bacteroids that fix nitrogen, and persist for several weeks or months within nodule cells. In legumes of the Inverted Repeat-Lacking Clade and Dalbergioid clade, this differentiation is terminal, meaning that bacteroids cannot resume growth after nodule senescence ( Mergaert et al., 2006 ; Czernic et al., 2015 ; Montiel et al., 2016 ). During nodule senescence, undifferentiated bacteria and non-terminally differentiated bacteroids present in nodules are released and can recolonise the soil and the rhizosphere. The ability of a given rhizobial strain to successfully complete the different steps of this complex life cycle will determine how fit it is in its current environment. Studying the different factors governing rhizobial fitness is critical to understand the diversity, ecology and evolution of these important plant symbionts. All along their life cycle, rhizobia interact with other microorganisms composing the soil, rhizosphere and nodule microbiomes, and are therefore involved in a diversity of interactions that affect their fitness either directly or indirectly through plant-mediated mechanisms. This review focuses on how the microbial community context, i.e. the ecological interactions between rhizobia and other microorganisms, contributes to determining rhizobial fitness. We first discuss the notion of fitness in the case of rhizobia and then describe how the diverse rhizobia-microorganisms (including rhizobia-rhizobia) interactions affect the fitness of rhizobia and their evolutionary dynamics."
} | 2,234 |
24037739 | PMC4033532 | pmc | 4,086 | {
"abstract": "The significance of horizontal gene transfer (HGT) in eukaryotic evolution remains controversial. Although many eukaryotic genes are of bacterial origin, they are often interpreted as being derived from mitochondria or plastids. Because of their fixed gene pool and gene loss, however, mitochondria and plastids alone cannot adequately explain the presence of all, or even the majority, of bacterial genes in eukaryotes. Available data indicate that no insurmountable barrier to HGT exists, even in complex multicellular eukaryotes. In addition, the discovery of both recent and ancient HGT events in all major eukaryotic groups suggests that HGT has been a regular occurrence throughout the history of eukaryotic evolution. A model of HGT is proposed that suggests both unicellular and early developmental stages as likely entry points for foreign genes into multicellular eukaryotes.",
"conclusion": "Conclusions and outlook A large percentage of eukaryotic genes are unquestionably of bacterial origin. Because mitochondria and plastids represent fixed gene pools, from which many genes have been lost completely during their evolution, OGT alone cannot adequately explain the large number of bacterial genes in eukaryotic genomes. The occurrence of recent HGT events in all major eukaryotic groups indicates that there are no insurmountable barriers to HGT, even in complex multicellular forms. Additionally, the finding of many anciently acquired genes in eukaryotes suggests that HGT is a dynamic process that has operated continually throughout the history of eukaryotic evolution. The weak-link model of HGT hypothesizes that unicellular and early developmental stages are the most likely entry points for foreign genes into recipient cells. Given the universal existence of these weak-link entry points, HGT is expected to occur frequently, on an evolutionary time scale, in all groups of eukaryotes. The weak-link hypothesis makes several explicit predictions that can be tested either by genome analyses or by experiments under controlled conditions. Future work is critically needed to understand the overall scale of HGT, but also the contribution of HGT, compared to other genetic mechanisms such as de novo gene generation and duplication, to the expansion of gene pool in different eukaryotic lineages throughout evolutionary time. Such work can be accomplished through careful evolutionary genomic analyses and will benefit our understanding of the role of HGT in the innovation and evolution of eukaryotes.",
"introduction": "Introduction About a decade ago, Doolittle et al. raised a question about the number of bacterial genes in protists, speculating that many bacterial genes should have accumulated in genomes of protists through feeding activities 1 , 2 . Back then, horizontal gene transfer (HGT) had been documented widely as a mechanism to gain foreign genetic materials in prokaryotes, but remained largely an exotic concept in eukaryotes, with little substantial evidence. It is now clear that HGT has occurred in all major eukaryotic lineages. Horizontally acquired genes are not only frequent in unicellular eukaryotes 3 – 5 , but also found in various multicellular eukaryotes, including cnidarians 6 , 7 , mites 8 , insects 9 – 12 , nematodes 13 – 15 , fish 16 , and land plants 17 – 22 . Although reports of HGT in eukaryotes are still frequently met with skepticism, evidence for HGT throughout eukaryotic evolution is abundant and increasing. In this paper, I discuss issues related to HGT in eukaryotes. Because most foreign genes reported in eukaryotes thus far are from bacteria, I will focus on bacterial genes. I argue that many bacterial genes in eukaryotes cannot be explained simply as gene transfers from mitochondria or plastids; rather, HGT in eukaryotes should be widespread and expected. Further, I propose a mechanism for integration of foreign DNA into eukaryotic genomes during unicellular or early developmental stages, when their nuclear DNA is relatively exposed to potential sources of HGT."
} | 1,003 |
23415234 | null | s2 | 4,087 | {
"abstract": "The bacterial type VI secretion system (T6SS) is a dynamic organelle that bacteria use to target prey cells for inhibition via translocation of effector proteins. Time-lapse fluorescence microscopy has documented striking dynamics of opposed T6SS organelles in adjacent sister cells of Pseudomonas aeruginosa. Such cell-cell interactions have been termed \"T6SS dueling\" and likely reflect a biological process that is driven by T6SS antibacterial attack. Here, we show that T6SS dueling behavior strongly influences the ability of P. aeruginosa to prey upon heterologous bacterial species. We show that, in the case of P. aeruginosa, T6SS-dependent killing of either Vibrio cholerae or Acinetobacter baylyi is greatly stimulated by T6SS activity occurring in those prey species. Our data suggest that, in P. aeruginosa, T6SS organelle assembly and lethal counterattack are regulated by a signal that corresponds to the point of attack of the T6SS apparatus elaborated by a second aggressive T6SS(+) bacterial cell. PAPERFLICK:"
} | 256 |
22074982 | PMC3256112 | pmc | 4,088 | {
"abstract": "Background Softwoods are the dominant source of lignocellulosic biomass in the northern hemisphere, and have been investigated worldwide as a renewable substrate for cellulosic ethanol production. One challenge to using softwoods, which is particularly acute with pine, is that the pretreatment process produces inhibitory compounds detrimental to the growth and metabolic activity of fermenting organisms. To overcome the challenge of bioconversion in the presence of inhibitory compounds, especially at high solids loading, a strain of Saccharomyces cerevisiae was subjected to evolutionary engineering and adaptation for fermentation of pretreated pine wood ( Pinus taeda ). Results An industrial strain of Saccharomyces , XR122N, was evolved using pretreated pine; the resulting daughter strain, AJP50, produced ethanol much more rapidly than its parent in fermentations of pretreated pine. Adaptation, by preculturing of the industrial yeast XR122N and the evolved strains in 7% dry weight per volume (w/v) pretreated pine solids prior to inoculation into higher solids concentrations, improved fermentation performance of all strains compared with direct inoculation into high solids. Growth comparisons between XR122N and AJP50 in model hydrolysate media containing inhibitory compounds found in pretreated biomass showed that AJP50 exited lag phase faster under all conditions tested. This was due, in part, to the ability of AJP50 to rapidly convert furfural and hydroxymethylfurfural to their less toxic alcohol derivatives, and to recover from reactive oxygen species damage more quickly than XR122N. Under industrially relevant conditions of 17.5% w/v pretreated pine solids loading, additional evolutionary engineering was required to decrease the pronounced lag phase. Using a combination of adaptation by inoculation first into a solids loading of 7% w/v for 24 hours, followed by a 10% v/v inoculum (approximately equivalent to 1 g/L dry cell weight) into 17.5% w/v solids, the final strain (AJP50) produced ethanol at more than 80% of the maximum theoretical yield after 72 hours of fermentation, and reached more than 90% of the maximum theoretical yield after 120 hours of fermentation. Conclusions Our results show that fermentation of pretreated pine containing liquid and solids, including any inhibitory compounds generated during pretreatment, is possible at higher solids loadings than those previously reported in the literature. Using our evolved strain, efficient fermentation with reduced inoculum sizes and shortened process times was possible, thereby improving the overall economic viability of a woody biomass-to-ethanol conversion process.",
"conclusion": "Conclusion A strain of Saccharomyces cerevisiae (XR122N) was evolved by continuous exposure to pretreated pine-wood biomass to develop the daughter strain AJP50. Adding a preculture or short adaptation phase of 24 hours in 7% w/v pretreated pine enhanced the performance of the all strains, including AJP50. AJP50 more rapidly fermented pretreated pine-wood biomass at a high solids loading than its parent, or other Saccharomyces strains reported in the literature. Growth comparisons between XR122N and AJP50 in a model hydrolysate medium containing inhibitory compounds found in pretreated biomass showed that AJP50 exited lag phase faster under all conditions tested. This ability is due, in part, to AJP50 rapidly converting FF and HMF to their less toxic alcohol derivatives and recovering from ROS damage more quickly than XR122N. Under industrially relevant conditions of 17.5% w/v pretreated pine solids loading, additional evolutionary engineering was required to decrease the pronounced lag phase. Using a combination of adaptation by inoculation first into a fermentation with a solids loading of 7% w/v for 24 hours, followed by a 10% v/v inoculum (approximately equivalent to 1 g/L cell dry weight) into 17.5% w/v solids, the final strain (AJP50) produced ethanol at more than 80% of the maximum theoretical yield after 72 hours of fermentation and reached more than 90% of the maximum theoretical yield after 120 hours of fermentation. Our results show that that fermentations of pretreated pine containing liquid and solids, including any inhibitory compounds generated during pretreatment, are possible at higher solids loadings than previously reported in the literature. These fermentations used reduced inoculum sizes and had shortened process times, thereby improving the overall economic viability of a pine-to-ethanol conversion process. Results from future studies characterizing the stability of the strain and analyzing the performance under conditions used with industrial processes (for example, after lyophilization) will be important for optimizing use of AJP50 in industrial applications.",
"discussion": "Results and Discussion Pine fermentations with the industrial yeast strain XR122N Fermentations using pine pretreated with SO 2 steam explosion (without washing or inhibitor removal) as the substrate at dry weight solids loadings of 5, 10, and 12% w/v were conducted using the industrial S. cerevisiae yeast strain XR122N (North American Bioproducts Corporation, Duluth, GA, USA). Compositional analysis of the pine before and after pretreatment is provided in Table 1 and the list of 13 inhibitory compounds and their concentrations in the pretreated pine sample used for fermentations are listed in Table 2 . Freeze-dried XR122N was inoculated at an initial concentration of 4 g/L dry cell weight (dcw), similar to its use in corn-ethanol fermentations, and enzymes for biomass saccharification were added simultaneously with the inoculum (15 filter paper units (FPU) cellulase and 60 cellobiase units (CU) cellobiase per gram dry weight (gdw) of pretreated pine). Table 1 Compositional analysis of pine subjected to sulfur dioxide steam explosion a Sample Glucan Xylan Mannan ASL b AIL c Sum Untreated Pine d 42.9 6.0 12.9 0.5 33.2 99.1 d 3.3% SO 2 213°C e 53.0 1.2 0.4 0.4 44.0 99.0 a Shown as percentage of each component on a dry weight basis b Acid-soluble lignin. c Acid-insoluble lignin. d Before pretreatment, the pine wood also contained 2.5%galactan and 1.1% arabinan, which were not detected pine-wood sample after pretreatment. Sum includes the galactan and arabinan fractions. e Reaction time of 5 minutes in SO 2 ; percentage and temperature indicated. Table 2 Concentrations (g/L) of each inhibitory compound studied, divided into classes Furans Aromatics Acids PH a Model b PH a Model b PH a Model b HMF c 2.153 2.000 3,4-DHBA d 0.003 0.003 Formic acid 0.425 0.400 Furfural 1.180 1.000 3-HBA e 0.005 0.005 Lactic acid 0.100 0.100 Furoic acid 0.018 0.020 Vanillic acid 0.050 0.050 Acetic acid 2.153 2.000 Vanillin 0.022 0.020 Succinic acid 0.028 0.030 Benzoic acid 0.015 0.015 Levulinic acid 0.410 0.400 a Concentration of compound measured in pretreated pine hydrolysate (PH) used in 12% w/v solids fermentations. b Concentration of compound in model inhibitor medium. c Hydroxymethylfurfural. d Dihydroxybenzaldehyde. e Hydroxybenzaldehyde. Simultaneous saccharification and fermentation (SSF) was desired for fermentations, because the added enzymes release monomeric forms of carbohydrates from the solids content of pretreated pine, and the fermenting yeast consumes the sugars as soon as they are released, thus minimizing end-product inhibition [ 32 , 33 ]. The optimal conditions for the fungal enzyme preparations used in these experiments are a pH of 4.5 and a temperature of 45°C, conditions too harsh for the fermenting yeast. Thus, to optimize enzyme activity during SSF experiments while minimizing the effects on the yeast, the pH was held at 5.0, just slightly above the enzyme optimum pH, and the temperature for fermentation decreased from 45°C to between 35 and 37°C. Attempts to increase the fermentation temperature above 37°C dramatically reduced ethanol production (data not shown). Ethanol production from the different biomass concentrations is presented in Figure 1A . Figure 1 Effect of solids loading on Saccharomyces cerevisiae strain XR122N . (A) Freeze-dried XR122N was inoculated at an initial concentration of 4 g/L cell dry weight (dcw) into small-scale bioreactors containing pretreated pine at a solids loading of 5% (green diamonds), 10% (blue circles), and 12% (red triangles) w/v. Cellulases and cellobiase were added simultaneously with the inoculum (15 FPU cellulase, and 60 CU cellobiase per gdw of pretreated pine). (B) XR122N was inoculated into 12% w/v solids loading of pretreated pine in a freeze-dried state at an initial concentration of 4 g/L dcw (black squares), 2.0 g/L dcw (red diamonds), 1.0 g/L dcw (blue circles), or 0.5 g/L dcw (green diamonds). Fermentations were maintained at 35°C, pH 5.0, and performed in triplicate. Error bars represent one standard deviation from the mean. FPU, filter paper units; dcw, cell dry weight; gdw, gram dry weight; CU, cellobiase units. The effect of inoculum size on pretreated pine fermentations at a 12% w/v solids loading is presented in Figure 1B . Initial attempts at inoculation of pretreated pine solids at or above 5% w/v using a low inoculum level equal to 0.2 g/L dcw resulted in cell death of XR122N (absence of growth on solid or liquid medium) and no ethanol was detected in these cultures. An inoculum size of 0.5 g/L produced ethanol in pretreated pine fermentations at a 10% w/v solids concentration (data not shown), but at a 12% w/v solids concentration no ethanol production was detected (Figure 1B ). Increasing the inoculum level to 1 g/L dcw in 12% w/v solids fermentations resulted in ethanol production, albeit with a pronounced lag phase of 72 hours. An inoculum of 2 g/L dcw produced almost as much ethanol as 4 g/L, and was selected as the inoculum size for further studies. One of the most promising pretreatments for softwoods, including pine, spruce, and Douglas fir, is SO 2 steam explosion [ 34 ], and various combinations of SO 2 concentration , reactor temperature, and time of reaction have been published. Table 3 compares the available data on SO 2 single-step pretreatments followed by SSF to produce fuel ethanol. Owing to the toxic nature of the pretreated softwood, many of the fermentations were conducted with solids loadings of 5 to 12% w/v. The inoculum level for yeasts was routinely 4 to 5 g/L and enzyme loadings ranged from 0 to 42 FPU cellulase per gdw of cellulose. Many softwood fermentations were conducted using washed solids [ 35 , 36 ], diluted solids with filtration [ 37 ], or lower solids loading of 5 to 8% w/v dry matter [ 25 , 35 ]. Hoyer and colleagues [ 38 ] obtained excellent results (94.7% of maximum theoretical yield based on glucose and mannose in the pretreated material) during fermentations with 10% w/v solids content. However, when using the same material at 12% w/v dry-matter solids loading, the maximum theoretical ethanol yield decreased to only 37%. All of these previous studies highlight the difficulties involved in fermenting pretreated softwood. Similarly, in the present study, we saw a decrease in the maximum theoretical yield (from 98% to 76%) when the dry-matter solids loading was increased from 10% to 12% w/v. Table 3 Comparison of simultaneous saccharification and fermentation methods using SO 2 pretreatment of softwoods with Saccharomyces cerevisiae strains Yeast strain a Wood type Pretreatment b Solids, % dry weight/volume Inoc, g/L Cellulase, FPU/gram dry weight Max EtOH, g/L Time to maximum EtOH production, hours % TM Reference SO 2 conc . Reaction temp, °C Duration, min Tembec 1 Lodgepole pine 4.0 200 5 5% (washed) 5 40 FPU/g cellulase, 20 CU/g cellobiase 17.0 24 68 c Ewanick et al. [ 36 ] (note: 6 hours enzyme preincubation) Tembec 1 Douglas fir 4.5 195 4.5 d 40 mL, WSF 5 No enzymes added 13.8 24 87 e Keating et al. [ 37 ] Y-1528 Douglas fir 14.7 24 92 f Baker's yeast Spruce 2.5 215 5 8% 5 32 FPU/g cellulase, 28 IU/g cellobiase Not stated 72 60 f Alkasrawi et al. [ 25 ] Baker's yeast g 72 92 f TMB 3000 48 89 f Baker's yeast Spruce 3.0 215 5 5% 5 15 FPU/g cellulose, 23 CU/g cellobiase Not stated 24 49 f Söderström et al. [ 35 ] Baker's yeast Spruce 3.0 210 5 12% WIS 5 15 FPU/g cellulose, 23 CU/g cellobiase 20.0 (graph) 72 37 f Hoyer et al. [ 38 ] XR122N Pine 3.3 215 5 10% 4 15 FPU/g cellulose, 60 CU cellobiase 28.7 48 98 c This study XR122N Pine 3.3 215 5 12% 4 15 FPU/g cellulose, 60 CU cellobiase 23.6 48 76 c This study Abbreviations: FPU, filter paper unit; Inoc, inoculation; CU, cellobiase unit; temp, temperature; WIS, water-insoluble solids; WSF, water-soluble fraction. a Saccharomyces . b All biomass was pretreated with SO2 in a single step and was not delignified before pretreatment or fermentation. c Theoretical yield based on cellulose and hemicellulose content derived from gravimetric and analytical analyses of pretreated material. d Steam explosion output was diluted to 15% w/w and filtered, and the pH altered to 6.0. Suspended solids not filtered out. e Theoretical yield was based on the content of glucose and mannose in the pretreated material. f Theoretical yield was based on the content of glucose and mannose in the liquid and of glucan in the solid material. g In hydrolysate. Evolution of XR122N for fermentation at high solids loading To reach the ethanol concentrations necessary for cost-efficient distillation, the solids loading must be 15 to 20% w/v [ 39 ]. However, as the biomass content increases in the fermentation, the concentration of inhibitory compounds also increases. Previous studies with Saccharomyces spp. illustrated that some strains are able to adapt to varying degrees by preculturing on hydrolysate or via cell recycle [ 25 - 27 ]; the exact mechanisms for increased performance are still unknown for many of these strains. Using FF alone for adaptation experiments results in different phenotypes, depending upon the method used for selection. In previous work, increased rates of FF reduction were seen in selection regimens in which FF was added during logarithmic growth [ 40 ]. By contrast, challenging cells at a low inoculum size to relatively high concentrations of FF did not change the FF reduction rates, but significantly reduced the lag phases and allowed growth in glucose minimal medium containing 40% v/v of spruce acid hydrolysate sample, a medium that killed the parental strain [ 28 ]. In the present study, inoculation of high solids loading (>10% w/v solids) using a low inoculum level of XR122N provided multiple stressors (increase in particulate content and inhibitory compounds), and selection was targeted at yeast survival and ethanol production. Directed evolution experiments were started at a concentration of 2 g/L dcw inoculum of XR122N added to pretreated pine fermentations at a 17.5% w/v solids loading as described in Methods (Figure 2 ). Fermentation was stopped after 168 hours, and aliquots equal to 10% v/v were transferred to fresh 17.5% w/v fermentations. When ethanol was not detected after 96 hours and aliquots from the fermenters did not exhibit growth in yeast-peptone-dextrose (YPD) media, 2 g/L dcw of XR122N cells were added to the fermentation vessels. Ethanol production was detected after another 24 hours of fermentation in one vessel, and continued to increase for an additional 48 hours. A 10% v/v inoculum (approximately 1 g/L dcw) was removed from the fermentation vessel where ethanol production was detected, and used to inoculate a third fermentation vessel containing 17.5% w/v pretreated pine and enzymes. No additional ethanol was produced after 96 hours, even though aliquots of the cells grew in liquid media. Another 2 g/L dcw of XR122N was then added to the fermentation. This process of inoculating a 17.5% w/v solids fermentation with a 10% v/v inoculum from a previous fermentation, monitoring ethanol production for 96 hours without observing an increase in ethanol content, and adding 2 g/L dcw of XR122N, was repeated for a total of six full cycles. During the seventh cycle, ethanol production increased by 24 hours, and continued to increase at 48 hours. At 48 hours of fermentation, a 10% v/v inoculum was transferred to a fresh 17.5% w/v solids fermentation and ethanol production monitored. Samples from this fermentation (removed after 48 hours) were frozen in glycerol at -80°C, and designated AJP40 (Figure 2 ). A similar set of fermentations using 20% w/v solids failed to produce high concentrations of ethanol, even after the addition of 2 g/L dcw of XR122N (data not shown). Figure 2 Evolution and adaptation of XR122N to high solids loading of pretreated pine to produce AJP40 . XR122N was inoculated into a 17.5% w/v solids fermentation, and allowed to ferment for 168 hours. 10% v/v aliquots were removed as indicated in the text, and used to inoculate 17.5% w/v solids fermentations. Ethanol was measured every 24 hours, and an additional 2 g/L cdw of XR122N added as indicated. After six full cycles the pattern changed, and ethanol was produced after 24 and 48 hours of fermentation without the addition of more XR122N cells. Cycles 4 and 5 had identical performance to cycles 2 and 3, and are omitted for clarity. AJP40 was subjected to additional transfers in 17.5% w/v solids loading of pretreated pine. Inoculation of AJP40 into 17.5% w/v solids directly produced little ethanol (Figure 3 ); however, if 10% v/v aliquots from this unproductive fermentation were inoculated into less concentrated solids, ethanol was produced (data not shown). Inoculation of AJP40 glycerol stocks (approximately 0.2 g/L dcw) into a 7% w/v solids fermentation resulted in the maximum theoretical yield of ethanol production after 24 hours of fermentation, and a 10% v/v aliquot was used to inoculate a 17.5% w/v solids fermentation. Ethanol production was seen at 48 hours, and when a 10% v/v inoculum of this fermentation was transferred into a fresh 17.5% w/v solids fermentation, ethanol was detected after 24 hours. Additional transfers into 17.5% w/v solids were made as described in Methods, for a total of 50 transfers. Figure 3 Comparison of AJP50 and AJP40 in fermentations with 17.5% w/v pretreated pine solids loading . Direct inoculation of AJP40 or AJP50 from freezer stocks (approximately 0.2 g/L dcw; green diamonds) was carried out. A short adaptation protocol of inoculation (0.2 g/L dcw) into 7% w/v solids for 24 hours was used, and a 10% v/v aliquot (approximately 1 g/L dcw) from this fermentation was used to inoculate 17.5% w/v solids using either AJP40 (red circles) or AJP50 (blue triangles). The curve of XR122N (black squares) at 2 to 4 dcw/L is provided for comparison. The resulting strain exhibiting the phenotype of increased ethanol production and decreased lag time in high solids fermentations was designated AJP50, and used for subsequent studies. Inoculation of 17.5% w/v solids fermentations with AJP50 taken directly from revived freezer stocks (0.2 g/L dcw) did not produce ethanol levels of above 10 g/L. However, inoculating AJP50 (0.2 g/L dcw) into a fermentation with reduced (7% w/v) solids loading for a short adaptation period (24 hours), followed by removal of a 10% v/v inoculum (approximately 1 g/L dcw) into 17.5% w/v solids fermentations, improved ethanol production significantly (Figure 3 ). With this short adaptation period, the evolved strain, AJP50, had a reduced lag time and produced over 80% of the maximum theoretical yield in 72 hours of fermentation and over 90% of the maximum theoretical yield of ethanol in 120 hours. Growth and ethanol production in the presence of inhibitors AJP50 appeared to have acquired the ability to grow and ferment high concentrations of solids, but with increasing solids concentrations, there were increased amounts of inhibitory compounds present as well. To determine whether AJP50 had an advantage over the parental strain in the presence of inhibitory compounds, we compared the growth profiles of both strains in different combinations of inhibitory compounds typically found in biomass fermentations (Table 2 ). Growth of both AJP50 and XR122N was not inhibited by the aromatic mixture and was very weakly inhibited by the acid mixture under concentrations tested (Figure 4A,B ). Low concentrations of weak acids have been shown to stimulate ethanol production in S. cerevisiae , but high concentrations were inhibitory to the activity of the organism in previous studies [ 5 , 15 ]. Figure 4 Growth of XR122N (solid blue) and AJP50 (dashed black) in the presence of various mixtures of inhibitory compounds found in biomass fermentations . Growth in (A) the aromatic mixture; (B) the acid mixture; (C) a combination of hydroxymethylfurfural (HMF), furfural (FF), and acetic acid; and (D) the furan mixture. All compounds and their concentration in the media are shown in Table 2. The inhibitory compounds were dissolved in tryptic soy broth with 2% w/v glucose. Error bars represent one standard deviation from the mean. XR122N required a higher volume of revived culture to obtain a cell concentration equivalent to 4.0 × 10 5 cells/ml; this increased the wood particulate matter in the culture and led to the higher initial optical density seen in some XR122N cultures. The inhibitory factors present in the largest concentrations in biomass fermentations are HMF, FF, and acetic acid, thus both strains were also grown in the presence of a mixture of these; the parental strain was strongly inhibited while the evolved strain showed an increase in lag phase. (Figure 4C ). Growth of both strains was strongly inhibited by the mixture of the furan compounds HMF, FF, and furoic acid (Figure 4D ). With this combination, no growth of XR122N was seen over 30 hours. Growth of AJP50 had a longer lag phase than in the other conditions; however, the furan-inhibited AJP50 cultures did eventually reach the same final optical density (OD) as the uninhibited cultures. The effects of FF and HMF on certain strains of S. cerevisiae have been described previously by a number of groups [ 12 , 19 , 41 ]. FF completely inhibited the growth of yeast strains at a concentration of 5.76 mg/ml. and partially inhibited growth at a concentration of 2.88 mg/ml during an incubation period of 125 hours. HMF completely inhibited one strain, and partially inhibited another at 7.6 mg/ml; various degrees of partial inhibition were seen at a concentration of 3.8 mg/ml. These concentrations are higher than those previously reported for pine-wood biomass fermentations, however, the amounts of inhibitory compounds might increase with increased severity of the pretreatment, and with increased concentrations of biomass at high solids loadings. To further study inhibition of the strains by these compounds, ethanol production of both strains was compared in the presence of 13 inhibitory compounds (Table 2 ) and in the absence of any inhibitors. Growth data were compared with ethanol data for both strains (Figure 5 ). Even though XR122N failed to grow in the presence of all 13 compounds, it still produced a small amount of ethanol after 30 hours. By contrast, AJP50 produced the theoretical maximum concentration of ethanol at 18 hours. Interestingly, in the absence of inhibitory compounds, AJP50 was able to produce ethanol after 6 hours and reached a maximum at 12 hours, whereas XR122N did not produce ethanol until 12 hours, and took 18 hours to reach maximum. Figure 5 Growth and ethanol production of both strains in the presence or absence of the selected inhibitory compounds present in pine-wood biomass fermentations . Lines represent cell culture density measured at an optical density of 580 nm (secondary y axis). Bars represent ethanol concentration in g/L (primary y axis). The red, solid and blue, dashed lines and bars show data from XR122N and AJP50 at 4.0 × 10 5 cells/ml initial cell density. Growth and ethanol production in the (upper panel) absence of inhibitors and (lower panel) in the presence of all 13 inhibitory compounds are shown. Conversion of furfural and hydroxymethylfurfural to alcohol derivatives A similar approach to the one used to generate AJP50 was used by Martín and colleagues to adapt S. cerevisiae to the inhibitory compounds in sugar-cane bagasse [ 27 ]; their study used media with known concentrations of inhibitors added, whereas in the present study, we used pretreated biomass as the media for adaptation and further directed evolution. In the study by Martín et al ., the advantage of the evolved strain was attributed to its ability to more rapidly detoxify FF and HMF [ 27 ]. Heer and Sauer were able to evolve another S. cerevisiae strain to FF alone, and this evolved strain had a marked decrease in lag phase, later attributed to increased action of certain oxireductases [ 28 , 29 ]. Although we used pretreated biomass for the evolutionary adaptation instead of FF or HMF directly, the resulting strain AJP50 is also able to rapidly detoxify FF and HMF by converting them to their less toxic alcohol derivatives (Figure 6 ). Figure 6 Conversion of furfural (FF) and hydroxymethylfurfural (HMF) to their less toxic alcohol derivatives . XR122N and AJP50 were compared for their ability to convert FF and HMF to their less toxic alcohol derivatives FF alcohol (FF-OH) and HMF alcohol (HMF-OH). The concentration of each compound is presented for each organism during a 30-hour fermentation in tryptic soy broth with 2% w/v glucose. Stability of the AJP50 inhibitor-resistant phenotype on rich media To determine if AJP50 would retain its phenotype during routine culturing, the strain was cultured on YPD media without inhibitory compounds. The ability of the resulting culture to grow in inhibitory media was then assessed. After culturing on rich solid and liquid media, AJP50 maintained resistance to the effects of inhibitors found in lignocellulosic biomass fermentations (Table 4 ). After 24 hours of growth, 14 of 100 cultures had an optical density of greater than 1.5, and 40 cultures had an OD of between 1.2 and 1.5. ODs of this level indicate resistance to the inhibitory compounds; XR122N cultures uniformly have ODs of less than 0.3 after 24 hours of growth under these conditions. Only six cultures had optical densities of less than 0.3, indicating that only a few cultures displayed no resistance after culturing on YPD media. After 30 hours of growth, the number of cultures with an OD of greater than 1.5 had increased to 43; at this time point only two cultures possessed ODs of less than 0.3, and 91% of the cultures had ODs greater than 1.2. However, multiple transfers of AJP50 onto YPD media results in a widely variable loss of the inhibitor-resistant phenotype (data not shown), thus for this reason YPD was supplemented with all 13 inhibitors in the following experiments, to act as a selective pressure, causing AJP50 to invariably retain its phenotype during routine culturing and isolation. Table 4 Optical densities at OD 580 of AJP50 cultures in inhibitory media after growth on rich media OD 580 24 hours 30 hours 48 hours 0.0 to < 0.3 6 2 2 0.3 to <0.6 5 1 0 0.6 to < 0.9 13 2 0 0.9 to < 1.2 22 4 6 1.2 to < 1.5 40 48 50 ≥1.5 14 43 42 a Values are a percentage of the cultures out of 100 replicates Analysis of isolated clones and verification of the inhibitor-resistant phenotype To verify the phenotype of individually isolated clones from the evolved yeast population, samples of AJP50 fermentations with 7% w/v solids were grown in YPD broth containing all 13 inhibitory compounds (YPD broth + inhibitors; YPD-BI) and then plated onto YPD agar containing all 13 inhibitory compounds (YPD agar + inhibitors; YPD-AI) to obtain isolated colonies. Individual colonies from these plates were subcultured onto a second YPD-AI plate for isolation. Individual colonies from the second plate were either inoculated into YPD-BI for growth-curve experiments, or plated again to produce isolated colonies. The growth curves of individual colonies plated for isolation on a series of two, three, or four plates, prior to inoculation for growth-curve measurements, were plotted (Figure 7 ). The results were similar for replicates within the same plating series, and all individual growth curves for each type of plating regimen are plotted as one line, with error bars depicting one standard deviation from the mean. ODs of greater than or equal to 1.2 after 24 hours of growth in YPD-BI indicates resistance to the inhibitory compounds. XR122N did not grow in YPD-AI or YPD-BI, and is omitted from the graph (Figure 7 ). Figure 7 Verification of phenotype in individually isolated clones from the evolved yeast population . Glycerol freezer stock samples from AJP50 fermentations plated onto yeast-peptone-dextrose (YPD) agar containing all 13 inhibitory compounds (YPD-AI) yielded isolated colonies. Individual colonies were then subcultured on additional YPD-AI once (two platings), twice (three platings), or thrice (four platings), as described in Methods. Isolated colonies were grown in YPD broth containing all 13 inhibitory compounds (YPD-BI). Growth curves for each series of platings was plotted as a single line with error bars representing one standard deviation from the mean (two platings (red), n = 20; three platings (blue), n = 20; four platings (green), n = 40). XR122N did not grow in YPD-BI or YPD-AI, and is not represented on the graph. Reactive oxygen species in AJP50 and XR122N cultures incubated with inhibitory compounds Both XR122N and AJP50 underwent considerable damage from reactive oxygen species (ROS) when revived in media from glycerol stocks at -80°C. AJP50 was able to recover from this damage more rapidly than XR122N in the presence of inhibitory compounds found in biomass fermentations (Figure 8 ). XR122N was able to reduce its level of ROS in the absence of inhibitory compounds, but was only able to slightly alleviate the ROS damage in the presence of inhibitors. In the presence of all 13 inhibitors and the mixture of HMF, FF, and acetic acid, AJP50 experienced similar levels of ROS to those seen in the absence of these compounds. XR122N and AJP50 experienced similar levels of recovery from ROS in the uninhibited and H 2 O 2 -supplemented controls, indicating that the faster reduction of ROS by AJP50 in the inhibitory media is related to the presence of the inhibitory compounds. Figure 8 Levels of reactive oxygen species in XR122N and AJP50 cultures grown in media containing biomass inhibitors . XR122N is represented by solid blue lines and squares, AJP50 by dashed black lines and circles. At each time point, at least 100 cells were surveyed and, the percent of cells fluorescing was recorded. Data from (A) uninhibited control; and cultures grown in media containing (B) 5 mmol/l H 2 O 2 , (C) hydroxymethylfurfural (HMF), furfural (FF), and acetic acid, (D) and all 13 inhibitors listed in Table 1. Error bars represent one standard deviation from the mean."
} | 7,760 |
21648431 | null | s2 | 4,089 | {
"abstract": "The goal of this research was to quantify the variations in redox potential and pH in Shewanella oneidensis MR-1 biofilms respiring on electrodes. We grew S. oneidensis MR-1 on a graphite electrode, which was used to accept electrons for microbial respiration. We modified well-known redox and pH microelectrodes with a built-in reference electrode so that they could operate near polarized surfaces and quantified the redox potential and pH profiles in these biofilms. In addition, we used a ferri-/ferrocyanide redox system in which electrons were only transferred by mediated electron transfer to explain the observed redox potential profiles in biofilms. We found that regardless of the polarization potential of the biofilm electrode, the redox potential decreased toward the bottom of the biofilm. In a fully redox-mediated control system (ferri-/ferrocyanide redox system), the redox potential increased toward the bottom when the electrode was the electron acceptor. The opposite behavior of redox profiles in biofilms and the redox-controlled system is explained by S. oneidensis MR-1 biofilms not being redox-controlled when they respire on electrodes. The lack of a significant variation in pH implies that there is no proton transfer limitation in S. oneidensis MR-1 biofilms and that redox potential profiles are not caused by pH."
} | 335 |
26925036 | PMC4757742 | pmc | 4,092 | {
"abstract": "In recent years, there has been an increase in the rate and severity of diseases affecting habitat-forming marine organisms, such as corals, sponges, and macroalgae. Delisea pulchra is a temperate red macroalga that suffers from a bleaching disease that is more frequent during summer, when seawater temperatures are elevated and the alga’s chemical defense is weakened. A bacterial cause for the disease is implied by previous studies showing that some isolated strains can cause bleaching in vitro and that host-associated microbial communities are distinct between diseased and healthy individuals. However, nothing is known about the successional events in the microbial community that occur during the development of the disease. To study this aspect in the future, we aimed here to develop an experimental setup to study the bleaching disease in a controllable aquarium environment. Application of a temperature stress (up to 27°C) did not cause a clear and consistent pattern of bleaching, suggesting that temperature alone might not be the only or main factor to cause the disease. The results also showed that the aquarium conditions alone are sufficient to produce bleaching symptoms. Microbial community analysis based on 16S rRNA gene fingerprinting and sequencing showed significant changes after 15 days in the aquarium, indicating that the native microbial associates of D. pulchra are not stably maintained. Microbial taxa that were enriched in the aquarium-held D. pulchra thalli, however, did not match on a taxonomic level those that have been found to be enriched in natural bleaching events. Together our observations indicate that environmental factors, other than the ones investigated here, might drive the bleaching disease in D. pulchra and that the aquarium conditions have substantial impact on the alga-associated microbiome.",
"introduction": "Introduction Anthropogenic environmental stressors (e.g., pollution and climate change) are increasing the rate and severity of marine diseases worldwide ( Harvell et al., 1999 , 2002 ; Webster, 2007 ; Burge et al., 2014 ). Particularly concerning is the recent rise in reports of disease outbreaks causing mass mortality to habitat-forming species, such as corals, sponges, and macroalgae. Many diseases have been linked to changes in the microbial communities that live in association with these habitat-formers and in some cases, specific microbial pathogens have been identified ( Rosenberg et al., 2007 ; Webster, 2007 ; Harvell et al., 2009 ; Egan et al., 2013 ). However, for most microbial diseases the interaction between pathogen, host, and environmental factors are not well understood ( Egan et al., 2013 ). There is, however, increasing evidence that environmental stressors, such as elevated seawater temperature, can either increase the virulence or abundance of opportunistic pathogens or weaken the host’s innate defense systems ( Harvell et al., 2002 , 2009 ; Webster, 2007 ; Egan et al., 2013 ; Burge et al., 2014 ). It has also been recognized that the health of marine organisms depends on their associated microbial community, which supply nutrients or provide defense against secondary colonization and biofouling. As such a host and associated microorganisms form an entity, termed holobiont, whose function and stability will be influenced by environmental conditions ( Rosenberg et al., 2007 ; Egan et al., 2012 ; Webster and Taylor, 2012 ; Fan et al., 2013 ). Several macroalgae (seaweeds) suffer from microbial diseases, but there is a general lack of understanding for the mechanistic processes and ecological factors that determine disease ( Gachon et al., 2010 ; Egan et al., 2013 ). The bleaching disease of the red alga Delisea pulchra is arguably one of the best-studied models for macroalgal disease ( Egan et al., 2012 ; Harder et al., 2012 ). D. pulchra possess a chemical defense system against bacterial colonization ( Manefield et al., 1999 ) and invertebrate grazing ( Williamson et al., 2004 ) based on the production of furanone compounds. Furanone concentrations decrease during summer ( Wright et al., 2000 ), when ultra-violet light radiation and temperature are elevated, and this coincides with an increase in the frequency of a disease that is characterized by spot-bleaching of the thallus ( Campbell et al., 2011 ). Experimental reduction of furanone concentration has also been shown to increase the incidence of the bleaching disease ( Campbell et al., 2011 ). The involvement of bacteria in the disease was indicated by two bacterial isolates, Nautella italica R11 and Phaeobacter gallaeciensis LSS9, being able to cause bleaching in the laboratory, preferentially under conditions where furanone concentrations are decreased and water temperature is increased ( Case et al., 2011 ; Fernandes et al., 2011 ). Furthermore bleached algae in the field had significantly different microbial communities from healthy individuals ( Fernandes et al., 2012 ; Zozaya-Valdes et al., 2015 ) and an operational taxonomic units (OTUs) with high similarity to P. gallaeciensis LSS9 was significantly enriched in a bleaching event ( Zozaya-Valdes et al., 2015 ). These observations together indicate a link between environmental stressors, weakened host defenses, and bacterial-induced disease, however, how these factors interplay with each others, in particular as a series of events, is not understood. Time-series experiment under controlled conditions can provide valuable insight into processes of disease development and specific environmental and biological factors that drive it. For example, for the sponge Rhopaloides odorabile controlled aquarium experiments have shown that an increase in temperature resulted in reduced expression of symbiotic functions in both the host and its microbial community, which was then followed by the proliferation of opportunistic, scavenging bacteria that ultimately led to tissue necrosis ( Fan et al., 2013 ). In order to study in a similar way the disease in D. pulchra , we aimed here to establish a controllable aquarium model for the algae. We used flow-through aquaria to assess the reproducibility and predictability of bleaching symptoms in response to temperature and assessed changes in the microbial communities in response to aquarium conditions with Terminal Restriction Fragment Length Polymorphism (TRFLP) and sequencing of the 16S rRNA gene.",
"discussion": "Discussion Effect of Temperature and Aquarium Conditions on the Incidence of D. pulchra Bleaching Infection assays using D. pulchra cultured from spores in the laboratory have previously shown that specific bacteria, such as Nautella italica R11, can cause bleaching in a temperature-dependent way ( Case et al., 2011 ; Fernandes, 2011 ). Furthermore seasonal field observations have shown that warmer waters are positively correlated with higher incidence of bleaching in D. pulchra ( Campbell et al., 2011 ). However, no experiment has been previously performed to test if temperature alone is sufficient to cause bleaching in D. pulchra and therefore we subjected here the algae to a temperature-stress under controlled aquarium conditions. Increases of temperature to 25°C, which is the peak level observed in the field ( Hedge et al., 2014 ) (trial 1 and 2), or 2°C above it (trial 3), had no clear and reproducible effect on the frequency of bleaching beyond the levels seen in control thalli (i.e., low-temperature treatment). Field observations have shown an overall weak, but statistically significant correlation ( R 2 = 0.063, df = 565, P < 0.005) between bleaching incidence and water temperature for D. pulchra , but deeper (7–10 m) populations had no significant correlation ( R 2 = 0.006, df = 289, P < 0.192; Campbell et al., 2011 ). These field and aquarium results together indicate that temperature alone is not the only or major driver of D. pulchra bleaching disease. Solar radiation was also shown to have a very weak correlation with the incidence of bleaching ( Campbell et al., 2011 ). It would thus appear that other factors (e.g., nutrients, physical damage, presence of pathogens, etc.) or combinations thereof need to be investigated to fully understand the conditions that drive disease development and progression. In the aquarium set-up used here, we also observed that up to half of the D. pulchra thalli bleached, even when no temperature stress was applied. Considering the relatively short duration of the experiments (3–6 weeks), this suggests that handling and/or the aquarium conditions impose a stress with consequences for the algae’s health. Transfers to an aquarium have previously been observed to cause stress in other marine sessile organisms, including corals, sponges and macroalgae ( Gachon et al., 2010 ; Luter et al., 2011 ; Sheridan et al., 2013 ). In D. pulchra , general and environmentally mediated stress has been proposed to negatively impact the furanone-based chemical defense, which could result in bacterial infection ( Campbell et al., 2011 ; Case et al., 2011 ). Furthermore, variability of furanone concentration have been reported for individual thalli of D. pulchra collected from the field ( Wright et al., 2000 ). Together aquarium-mediated stress and between-individual variability could have contributed to the observed bleaching under control conditions and/or the maintenance of health for some individuals in the aquarium after 3–6 weeks, even under high temperatures. Microbial Community Changes in Response to the Transfer of D. pulchra from a Natural to an Aquarium Setting One of the factors that could influence the performance of D. pulchra is the community of its associated microorganisms and here we observed clear changes in microbial structure, composition, and richness 15 days after transfer to the aquarium. To our knowledge, this is the first time that this has been described for macroalgae, however, similar observations have been made for other marine sessile organisms. For example, using sequencing of 16S rRNA gene clone libraries and denaturing gradient gel electrophoresis (DGGE), Mohamed et al. (2008a , b ) observed changes in the abundance of microorganisms associated with sponges Mycale laxissima and Ircinia strobilina after 6 and 3 months in a flow-through and recirculating aquarium, respectively. Also, Kooperman et al. (2007) found a reduction in the diversity and number of phyla for the microbiota in the surface mucus of the coral Fungia granulosa after being held for just 3 weeks in an aquarium with artificial seawater. However, some host-associated communities have also been reported to experience little or no noticeable change when moved from the field to aquaria conditions. For example, DGGE and metagenomic data found that the microbial communities of wild specimens of the sponge Rhopaloides odorabile were highly similar to those kept in a flow-through aquarium for up to 4 weeks ( Webster et al., 2011 ; Fan et al., 2013 ). DGGE analysis also indicated that most of the microbial community of the sponge Aplysina aerophoba can remain stable after cultivation under different artificial conditions ( Gerçe et al., 2009 ). The different responses seen in these studies may be explained by the inherent biological properties of the host and its associated microbial communities and their sensitivity or resilience to experimental handling or environmental factors, such as depth, light, nutrients, and salinity. In fact, this kind of environmental factors have all been shown to correlate with shifts in the microbial communities associated to different hosts in natural settings ( Guppy and Bythell, 2006 ; Ainsworth and Hoegh-Guldberg, 2009 ; Hengst et al., 2010 ; Meron et al., 2011 ; Olson and Gao, 2013 ; Morrow et al., 2015 ). As previously proposed for corals ( Rosenberg et al., 2007 ; Bourne et al., 2009 ), macroalgae and their associated microbial communities should be considered as functional entites or holobionts ( Egan et al., 2012 ). In line with this hypothesis, the observed changes in the microbial communities of D. pulchra upon transfer from the field to the aquarium could result in two possible outcomes. Firstly, changes in the microbial community could cause bacterial infection and this would lead to bleaching, as observed here. The thalli, which were used to test the effect of the aquarium conditions on the microbiota associated with D. pulchra , had no bleaching symptoms during the course of the experiment. Further maintenance in the aquarium could have led to bleaching and also additional changes in the microbial community composition. However, a taxonomic comparison with a previous study ( Zozaya-Valdes et al., 2015 ) showed no indication that the microbial communities in the aquarium were shifting toward those seen in bleached D. pulchra from the field. Specifically, aquarium conditions favor OTUs belonging to orders such as Kordiimonadales, Alteromonadales, and Cytophagales, while bleached samples on the field were mostly enriched in OTUs assigned to the Flavobacteriales, Rhodobacterales, and Rhizobiales ( Zozaya-Valdes et al., 2015 ; Supplementary Figure S5 ). Bacteria that were enriched under aquarium conditions belong to orders that are commonly found in the marine environment, including those that are in association with sediments and multicellular marine eukaryotes. The Kordiimonadales, for example, are globally distributed alphaproteobacteria, which have been isolated from coastal ( Thompson et al., 2011 ; Yang et al., 2013 ) and open-ocean waters ( Pham et al., 2008 ; Wang et al., 2010 ), estuarine and deep-sea sediments ( Tian et al., 2008 ; Li et al., 2009 ), marine sponges ( Anderson et al., 2010 ), hydrothermal vents ( Peng et al., 2010 ) and from ballast water tanks ( Xu et al., 2011 ). Bacteria belonging to the Kordiimonadales normally occur in their natural habitats at relative abundances below 2% ( Xu et al., 2014 ). Here, however, OTU10 (classified to the genus Kordiimonas ) had an average relative abundance of 12%, which was the highest for any OTU significantly enriched in algae held under aquarium conditions ( Supplementary Figure S4 ). The second most abundant aquarium-enriched OTU (OTU4; 10.4%; Supplementary Figure S4 ) belonged to the genus Glaciecola (order Alteromonadales, phylum Gammaproteobacteria), which contains species that have been isolated from diverse marine environments, such as coastal surface seawater ( Baik et al., 2006 ; Chen et al., 2009 ), arctic ocean seawater ( Van Trappen et al., 2004 ), sea-ice diatom assemblages from Antarctic coasts ( Bowman et al., 1998 ), marine invertebrates ( Romanenko et al., 2003 ), and sea sediments ( Matsuyama et al., 2006 ; Zhang et al., 2006 , 2011 ; Yong et al., 2007 ). The third and fourth most abundant aquarium-enriched OTUs (OTU32 and OTU56; Supplementary Figure S4 ) are members of the Cytophagales (phylum Bacteroidetes), which are found in coastal environments rich in organic material, such as living or dead macroalgae, aerobic and anaerobic seafloor sediments and decaying marine animals ( Reichenbach, 2006 ). Secondly, microbial changes could represent an adaptive response of the holobiont to the aquarium environment as has been suggested for corals ( Kooperman et al., 2007 ; Pratte et al., 2015 ). This outcome is supported by the observation that microbial members of D. pulchra are primarily shifting in abundance, rather than being replaced by foreign (e.g., aquarium-derived) microorganisms. If this is true, then the new microbial community, although being different from the ones in the field, could obtain or preserve functions to sustain the health of the host. Future studies therefore need to define the functionality of aquarium-based microbiomes associated with these marine hosts and how they relate to host function in natural situations."
} | 3,990 |
34056152 | PMC8153368 | pmc | 4,093 | {
"abstract": "The search for suitable\nstrategies to manufacture self-healable\nnitrile rubber (NBR) composites is the most promising part in the\nindustrial field of polar rubber research. In recent years, some important\nstrategies, specifically, metal–ligand coordination bond formation,\nionic bond formation, and dynamic hydrogen bond formation, have been\nutilized to develop duly self-healable NBR composites. This paper\nreviews the continuous advancement in the research field related to\nself-healable NBR composites by considering healing strategies and\nhealing conditions. Special attention is given to understand the healing\nmechanism in reversibly cross-linked NBR systems. The healing efficiency\nof a cross-linked NBR network is usually dependent on the definite\ninteraction between functional groups of NBR and a cross-linking agent.\nFinally, the results obtained from successful studies suggest that\nself-healing technology has incredible potential to increase the sustainability\nand lifetime of NBR-based rubber products.",
"conclusion": "4 Conclusions\nand Future Perspectives In the present decade, the discovery\nof self-healable and environmentally\nsound NBR composites is a new-fangled field in rubber technology.\nThe unique surface functional groups of NBR and XNBR offer sufficient\nscope to develop properly self-healable materials. In this review,\nwe revealed some attractive ways regarding the formation of self-healable\nNBR and XNBR composites via dynamic metal–ligand coordination\nand ionic bonding. In the case of the metal–ligand coordination\nbond, the electronic configuration of metal can control the healing\nproperty of XNBR composites. Cobalt neocaprate (30 phr) can be used\nto prepare NBR composites with 100% healing efficiency after healing\nat 190 °C for 10 min. On the other side, the combination of DAP/zinc(II)\nsalt has proven to be an ideal cross-linking agent to prepare XNBR\ncomposites with 100% healing efficiency after healing at 80 °C\nfor 24 h. Moreoever, MGTR and PEI/CNC are interesting cross-linking\nmaterials for the preparation of XNBR composites with good healing\nefficiency and excellent mechanical properties. Indeed, the standardization\nof an optimum healing condition for a particular cross-linked NBR\nsystem is great importance from an industrial standpoint. However,\nthe research based on the preparation and characterization\nof self-healable NBR compounds is still in the preliminary stage.\nThere are two major limitations related to the application of self-healable\nNBR compounds in the industrial area of rubber technology. These major\nlimitations are presented below point by point. (a) Until now, researchers have found\ninformation about the laboratory-scale production of self-healable\nNBR composites. However, the suitability of large-scale application\nof self-healable NBR composites in different rubber-related industries\nis a questionable matter. (b) Most of the researchers have tried\nto develop self-healable NBR composites for unfilled rubber systems.\nHowever, the addition of different reinforcing fillers, such as carbon\nblack and silica, is the mandatory part to obtain the desired mechanical\nproperties required for the commercial application of NBR. Thus, it\nis necessary to establish some strategies for the development of self-healable\nfilled NBR composites. It will be quite a tough challenge to achieve\nthe proper balance between mechanical properties and healing efficiency\nof filled NBR composites.",
"introduction": "1 Introduction Currently, one of the most serious issues concerning environmental\ndamage is the unswerving disposal of industrial rubber waste materials\ninto the environment without appropriate reprocessing. 1 , 2 In the present decade, the quantity of waste rubber products has\nincreased day by day due to the unregulated growth of the automotive\nindustry. 1 , 2 In this respect, successful design of self-healable\nrubber composites for the extension of product lifetime is the most\ncommonly adopted and popular way exercised by rubber scientists. 1 − 14 Self-healing indicates the self-repair of damage in a product with\nor without the presence of healing materials. The healing ability\nof rubber compounds in the absence of any externally added healing\nmaterials is known as an intrinsic self-healing property. So far,\nemphatic focus was given by rubber scientists on understanding the\nself-healing mechanism of intrinsic self-healable rubber composites.\nAs reported by various rubber scientists, intrinsic self-healing occurs\nvia several factors, like hydrogen bonds, 3 − 6 disulfide bonds, 7 − 9 metal–ligand bonding interactions, 10 Diels–Alder reactions, 11 transesterification\nreactions, 12 − 14 etc. In some cases, external stimulus, like temperature\nor pressure, plays a vital role to improve the healing efficiency\nof self-healable rubber composites. However, it is possible to achieve\nautonomous self-healing, that is, healing without external stimulus\nin rubber composites. 1 Now, both cross-linking\nsystems and filler structures make a significant contribution to the\nself-healing efficiency of rubber composites in the presence of a\nparticular filler. On one side, a three-dimensional irreversible covalent\ncross-linking system has the tendency to prevent the healing of rubber\nmaterials. Thus, a reversible cross-linking system is necessary to\ncause effective self-healing of rubber materials. On the other side,\nthe interfacial interaction between surface functional groups of rubber\nand filler is another influential aspect regarding the preparation\nof self-healable filled rubber composites. Thus, rubber researchers\nhave to properly select the cross-linking system and filler material\nin order to develop a self-healable filled rubber system. In reality,\nthe challenges lying with the design of autonomous self-healable filled\nrubber composites for industrial engineering are intricate and variegated\nin nature. Nitrile rubber (NBR) is an important rubber due to\nits successful\napplication in oil-resistant materials, such as hoses, seals, gaskets,\nO-rings, and gloves. In the last 2–3 years, some research groups\nhave reported different interesting mechanistic studies related to\nthe development of self-healable NBR composites. The main aim of the\npresent review is to explore the recent progress and future prospects\nof self-healable advanced NBR composites."
} | 1,581 |
37274162 | PMC10232882 | pmc | 4,094 | {
"abstract": "The effective and cheap production of platform chemicals is a crucial step towards the transition to a bio-based economy. In this work, biotechnological methods using sustainable, cheap, and readily available raw materials bring bio-economy and industrial microbiology together: Microbial production of two platform chemicals is demonstrated [lactic (LA) and succinic acid (SA)] from a non-expensive side stream of pulp and paper industry (fibre sludge) proposing a sustainable way to valorize it towards economically important monomers for bioplastics formation. This work showed a promising new route for their microbial production which can pave the way for new market expectations within the circular economy principles. Fibre sludge was enzymatically hydrolysed for 72 h to generate a glucose rich hydrolysate (100 g·L −1 glucose content) to serve as fermentation medium for Bacillus coagulans A 541, A162 strains and Actinobacillus succinogenis B1, as well as Basfia succiniciproducens B2. All microorganisms were investigated in batch fermentations, showing the ability to produce either lactic or succinic acid, respectively. The highest yield and productivities for lactic production were 0.99 g·g −1 and 3.75 g·L −1 ·h −1 whereas the succinic acid production stabilized at 0.77 g·g −1 and 1.16 g·L −1 ·h −1 .",
"introduction": "1 Introduction The chemical production of lactic or succinic acid is facing new challenges, associated with sustainability issues and the usage of fossils for their production. An alternative way to produce them is the biotechnological utilization of residual forms of lignocellulosic biomass as second generation sugar rich feedstocks, including industrial streams such as sulphite fibre sludge, respecting the “food first” principle. The use of affordable, industrial, side streams as feedstock is of great interest to establish circular economy, and to decrease the cost of the final products. Sulphite fibre sludge (SFS) is a residual side stream obtained from pulp mills and biorefineries. It is usually relatively easy to hydrolyse it enzymatically, without prior thermochemical pre-treatment, which is advantageous, as pre-treatment may result in formation of substances that inhibit microbial growth, such as furfural or phenolic compounds ( Xie et al., 2018 ; Ludwig et al., 2013 ). The annual production of SFS is ∼1000 dry tonnes/paper mill plant, making it a valuable feedstock for value added bio-based products and specialty chemicals. Lactic and succinic acid are two monomers that belong to the group of 12 main platform chemicals ( Rodrigues et al., 2017 ; Alexandri and Venus, 2017 ; Lu et al., 2021 ; Yankov, 2022 ; Rawoof et al., 2021 ). The market share of biotechnological processes for the production of platform chemicals is expected to increase in the coming years from 5% to 20% ( Yankov, 2022 ). The global lactic acid production is expected to reach 5.8 billion by 2030, according to a new report by Grand View Research, Inc., ( Grandviewresearch, 2022 ), which only shows how the market interest is increasing. The market growth can be assigned with demand for lactic acid in food, beverages, pharma industry, and as a feedstock in the production of poly-lactic acid (PLA), which is going to drive the market globally. Lactic acid contains three carbons, one hydroxyl and the carboxyl group, which makes this molecule extremely attractive in many fields, such as materials science, food packaging, among others ( Murali et al., 2017 ; Ismail et al., 2018 ; P. Pawar et al., 2014 ). Lactic acid is often added as pH stabilizer, or to increase taste features of food products. Similarly, succinic acid plays an important role in biomaterials, bio-surfactants, precursor for other chemicals, etc. The succinic acid market is estimated to reach USD 182.8 million by 2023, increasing at a CAGR of 6.8% from 2018 ( Malanca et al., 2022 ). Companies, such as, Biosuccinium, BioAmber, Myriant, or Succinity have been responsible for the main production of succinic acid via microbial fermentation. Unfortunately, due to economic competitiveness, most of the succinic acid is still produced using petrochemical routes ( Kuenz et al., 2020 ). Succinic acid (SA) is a C4 platform molecule, with two carboxyl groups. It serves as an intermediate building block for other chemicals, such as, esters, 1,4-butanediol, itaconic, maleic, aspartic acid, among others ( Yang et al., 2020 ). Succinic acid is also a precursor for polyethylene succinate that has been widely used in the plastic industry. Concerning biotechnological SA production, Actinobacillus succinogenesis was considered to be the most promising bacterial strain ( Kuenz et al., 2020 ). Additionally, it was shown that succinic acid can be also produced from lignocellulosic biomass, but more efficient microbial cultivation must be developed to produce it more effectively ( Lu et al., 2021 ). Although, both lactic acid and succinic acid are well known and are widely used in many disciplines, their sustainable production is still developing. Therefore, the decrease in production costs could be achieved by a cheap feedstock and its long-term supply. Additionally, their production from lignocellulose biomass tends to increase, due to the fact, that this type of feedstock does not compete with food and feed sector. Lignocellulose is the most abundant renewable source on Earth, and is mainly composed of cellulose, hemicellulose and lignin ( Lu et al., 2021 ). Lignocellulosic biomass contains a mixture of C6 and C5 sugars. Usually, only C6 sugars are utilized by microbes in fermentation process, but this study shows that C5 sugars, such as xylose, can be successfully converted to organic acids. Bacillus coagulans is a spore-forming, facultative anaerobe, thermophilic, able to grow at higher temperatures, above 50°C. It has the ability to convert hexose and pentose sugars to L -(+)-lactic acid with high titers ( Glaser and Venus, 2018 ). Therefore, its potential in utilizing lignocellulosic materials is rising. A. succinogenes (B1) is able to produce succinic acid anaerobically from a broad range of carbon sources, such as, arabinose, cellobiose, fructose, galactose, glucose, lactose, mannitol, among others ( Borges and Pereira, 2011 ). It is a Gram-negative bacterium, utilizing CO 2 as an electron acceptor, which induces the metabolism of the substrate to succinate at high CO 2 levels ( Van der Werf et al., 1997 ). Basfia succiniciproducens (B2) was isolated from bovine rumen and described by the German chemical company BASF in Ludwigshafen, Germany ( Scholten and Dägele, 2008 ). This facultative anaerobic microorganism also has a broad substrate utilization spectrum, including lignocellulosic biomass ( Ventorino et al., 2017 ; Bartos et al., 2021 ). To summarize microorganisms used in this study, this approach presents a possibility to combine production of low-cost feedstock with high-value-added products, such as organic acids within the concept of bio-refinery. Lactic acid production by two strains of B. coagulans (A541) and B. coagulans (A162) was investigated, whereas succinic acid production was performed by B1 and B2 strains. Both monomers were studied using batch fermentation method. Conversion of SFS to lactic acid was studied with thermotolerant A541 and A 162 strains, whereas succinic acid production was performed at 30°C.",
"discussion": "4 Discussion In this study, sulphite fibre sludge (SFS) hydrolysate was used as the feedstock and carbon source for lactic and succinic acid production. Notably, SA and LA yields were higher when SFS was used, comparing to control fermentations with glucose, what is summarized in Table 3 . That shows that all strains prefer a mixture of C5 and C6 sugars for a sustainable growth, which is consistent with previous studies on batch fermentation of single sugar ( Ferone et al., 2017 ). SFS contains a mixture of C5 and C6 sugars, with glucose as a predominant sugar. Cellobiose and xylose were detected in this stream as well. In addition, a mixture of phosphorus and nitrogen, or other ions, such as magnesium, or potassium was detected which likely enabled strains for a better nutrient provision and in consequence for better performance. Lactic acid fermentation, to be economically feasible, requires low-cost feedstock. Therefore, SFS was one of the choices concerning not only this aspect, but also serving as a valuable carbon source. Its low inhibitor content enabled the growth of B. coagulans strains without any difference, comparing to standard, glucose medium. Moreover, it enhanced the growth of LA producing bacteria, thanks to additional nutrients present in the hydrolysate that can be seen in Table 2 . Lactic acid production from lignocellulosic feedstock, has been already reported and summarized by ( Yankov, 2022 ), emphasizing that cellulosic biomass is an abundant and sustainable source for organic acids production. Therefore, the next step is required in the development of industrial lactic acid production via biotechnological routes, meaning the final shift from oil to renewable resources. As shown in this study, B. coagulans strains were able to grow and consume sugars achieving almost 100% conversion to lactic acid, with yields of 0.98 g·g −1 and 0.92 g·g −1 for both strains used. Food waste was also a potential biomass for lactic acid production ( López-Gómez et al., 2019 ), but recently, the interest in the usage of lignocellulosic waste has been further increasing. Several studies utilizing corn stover ( Yi et al., 2016 ), oil palm empty fruit bunch ( Ye et al., 2014 ), rice straw ( Kuo Cheng et al., 2015 ), among others have been reported. TABLE 2 Composition of SFS after enzymatic hydrolysis. All values are in g·L −1 . Analysis methods are described in Section 3.1 . Component Batch 1 Batch 2 Batch 3 Glucose (g·L −1 ) 100 99.7 98.7 Cellobiose (g·L −1 ) 3.34 3.15 4.04 Xylose (g·L −1 ) 1.69 1.70 1.35 Lactic acid (g·L −1 ) 6.60 6.56 4.07 Acetic acid (g·L −1 ) 0.76 0.70 0.45 Ethanol (g·L −1 ) 0.45 0.29 0.12 Total nitrogen (mg·L −1 ) 190 188 201 Total phosphorus (mg·L −1 ) 15.8 15.8 16.7 Cl − (mg·L −1 ) 36.0 35.1 15.5 SO 4 \n 2+ (mg·L −1 ) 152 150 213 Na + (mg·L −1 ) 1910.0 1868.0 1334.0 K + (mg·L −1 ) 19.5 19.4 32.0 Mg 2+ (mg·L −1 ) 16.6 16.9 17.7 Ca 2+ (mg·L −1 ) 14.6 14.1 14.7 Furfural (mg·L −1 ) 2.04 1.58 <0.0124 HMF (mg·L −1 ) <0.004 <0.004 <0.004 Phenol (mg·L −1 ) <0.079 <0.079 <0.079 Catechol (mg·L −1 ) 15.5 15.1 <0.027 In SA batch fermentation, a lag phase was observed that lasted less than 5 h and the exponential growth phase was coupled with fast consumption of sugars and production of succinic acid. However, two other acids acetic acid (AA) and formic acid (FA) were detected. After about 40 h, the base consumption stopped, which indicated that the cell growth also stopped. At this point fermentations were kept running due to unconsumed sugars, but after 50 h were terminated. The final concentration of SA reached 45.4 g·L −1 utilizing the B1 strain. The summary of all titers, productivities, and yields, shown in Table 3 . Although B. succiniciproducens showed the ability to metabolize a wide spectrum of carbon sources, A. succinogenes was able to convert sugars effectively. This could be related to the natural habitat of B1 strain, where the variety of carbon sources is very broad. Comparing other wild type microorganisms able to produce SA, reported in this study ( Jiang et al., 2017 ), B1 strain showed similar behaviour to strains reported. Only one strain, CGMCC 1593, was able to produce 60.2 g·L −1 of SA from glucose ( Yu-Peng et al., 2008 ). B. succiniciproducens was used in succinic acid production to develop a cost-competitive bioprocesses with respect to the formulation of low cost and efficient fermentation medium ( Stylianou et al., 2021 ). But among other microorganisms, A. succinogenes is recognized as one of the most promising candidates for industrial production of succinic acid ( Carvalho et al., 2016 ). In another study, A. succinogenes was able to utilize SPS, but it was also shown that this strain can utilize straw ( Pu et al., 2009 ), or even sugarcane bagasse hemicellulose hydrolysate ( Borges and Pereira, 2011 ), among others. By-product formation could be related to the CO 2 source. In other studies utilizing MgCO 3 ( Guettler et al., 1996 ) showed that MgCO 3 could have an influence on the metabolic pathway. Therefore, other studies, utilizing other CO 2 sources are necessary to reduce the amount of by-products formation. On the other hand, Carvalho et al. used fed-batch system, utilizing carob pods and A. succinogenes in order to reduce by-product formation ( Carvalho et al., 2016 ). TABLE 3 Yield, global productivity, final acid concentration, and the amount of residual sugars for LA and SA producing strains. Conditions Y LA (g/g) Pg LA (g/L*h) LA (g/L) Residual sugars Y SA (g/g) Pg SA (g/L*h) SA (g/L) Residual sugars Glucose + YE A162 0.93 2.80 75.0 0.0 — — —- — A541 0.95 3.18 76.2 0.0 — — —- — B1 — — —- — 0.70 0.99 41.0 5.95 B2 — — —- — 0.48 0.93 28.3 1.01 Fiber sludge hydrolysate A162 0.22 0.49 19.7 85.2 — — —- — A541 0.17 0.39 15.0 91.79 — — —- — B1 — — —- — 0.09 0.12 6.22 64.08 B2 — — —- — 0.02 0.02 0.98 77.4 Hydrolysate + YE A162 0.98 3.50 79.1 1.08 — — —- — A541 0.92 3.58 77.2 1.38 — — —- — B1 — — —- — 0.77 0.96 45.4 5.71 B2 — — —- — 0.52 0.63 30.6 4.04 To conclude, fiber sludge serves as a cheap, but reach in simple sugars, that enable a successful fermentation to LA and SA. Since SFS can be produced at quantities varying from 1000 tonnes to 2000 tonnes per plant per year (info from the fibre sludge provider), depending on the size of the plant and the production process, it is regarded as an excellent way to valorize the side stream for the pulp and paper industry, if the process is integrated in the pulp mill. It also enables to perform further studies on technical and pilot scale. This work performed here paves the way for the valorization of more side streams from pulp and paper industry."
} | 3,529 |
29666242 | PMC5948967 | pmc | 4,095 | {
"abstract": "Significance Synthetic polymers are ubiquitous in the modern world but pose a global environmental problem. While plastics such as poly(ethylene terephthalate) (PET) are highly versatile, their resistance to natural degradation presents a serious, growing risk to fauna and flora, particularly in marine environments. Here, we have characterized the 3D structure of a newly discovered enzyme that can digest highly crystalline PET, the primary material used in the manufacture of single-use plastic beverage bottles, in some clothing, and in carpets. We engineer this enzyme for improved PET degradation capacity and further demonstrate that it can also degrade an important PET replacement, polyethylene-2,5-furandicarboxylate, providing new opportunities for biobased plastics recycling.",
"conclusion": "Conclusions The discovery of a bacterium that uses PET as a major carbon and energy source has raised significant interest in how such an enzymatic mechanism functions with such a highly resistant polymeric substrate that appears to survive for centuries in the environment. This work shows that a collection of subtle variations on the surface of a lipase/cutinase-like fold has the ability to endow PETase with a platform for aromatic polyester depolymerization. These findings open up the possibility to further utilize and combine the extensive platform of cutinase and lipase research over the past decades with directed protein engineering and evolution to adapt this scaffold further and tackle environmentally relevant polymer bioaccumulation and biobased industrial polyester recycling.",
"discussion": "Discussion The high-resolution structure described in the present study reveals the binding site architecture of the I. sakaiensis 201-F6 PETase, while the IFD results provide a mechanistic basis for both the wild type and PETase double mutant toward the crystalline semiaromatic polyesters PET and PEF. Changes around the active site result in a widening of the cleft compared with structural representatives of three thermophilic cutinases ( SI Appendix , Fig. S3 ), without other major changes in the underlying secondary or tertiary structure. Furthermore, we demonstrated that PETase is active on PET of ∼15% crystallinity; while this observation is encouraging, it is envisaged that its performance would need to be enhanced substantially, perhaps via further active-site cleft engineering similar to ongoing work on thermophilic cutinases and lipases ( 26 , 30 , 53 , 54 ). Enzyme scaffolds capable of PET breakdown above the glass transition temperature (≥∼70 °C for PET) ( 20 ) will also be pursued in future studies. Coupling with other processes such as milling or grinding, which can increase the available surface area of the plastic, also merits investigation toward enzymatic solutions for PET and PEF recycling. Furthermore, in light of recent studies that demonstrate the impressive synergistic effect of combining multiple PET-active lipases ( 26 , 30 , 53 , 54 ), we expect that incorporation of I. sakaiensis MHETase will further increase the performance ( 55 ), and this will be pursued in future work. The highly basic surface charge of PETase requires further investigation since it is not observed in other close structural homologs, but it is noteworthy that the MHETase partner is predicted to be a fairly acidic protein, with a pI in the region of 5.2. Both the IFD results and MD simulations independently indicate the PETase binding site is characterized by highly flexible, large aromatic side chains, such as Trp185, Tyr87, and Trp159, and Phe238 in the PETase double mutant. Binding of PET and PEF induces conformational changes in these residues relative to the crystal structure; thus, modeling protein flexibility in response to PET/PEF is critical to predict catalytically relevant binding modes. Additionally, results of these flexible docking studies agree with experimentally observed trends in performance in the wild type relative to the double mutant, and provide structural insight to explain this enhancement. PETase activity on both PET and PEF, but not on aliphatic polyesters such as PBS and PLA, provides the basis for characterizing this enzyme more broadly as an aromatic polyesterase rather than solely as a PETase. It is likely that the enhanced gas barrier properties of PEF will lead to its adoption for beer bottles, and that this recalcitrant material will thus ultimately find its way to the environment. It is therefore encouraging that PETase is also natively capable of PEF degradation. It is also noteworthy that in this study, PETase was freeze-dried and shipped between continents, and that it retained similar performance profiles after freeze-drying, which is a positive feature for its potential use in applications that require enzyme production and use be distinct, as it would potentially be the case for most biobased recycling options. The problem of plastics depolymerization by enzymes closely mirrors that of enzymes that depolymerize polysaccharides, such as cellulose and chitin ( 56 , 57 ). Indeed, strategies that have been used to understand and improve glycoside hydrolases, including the development of quantitative assays for measuring enzyme (or enzyme cocktail) performance on solid substrates, likely can serve as inspiration for more quantitative metrics for comparing plastics-degrading enzymes and enzyme mixtures, which will be reported in future studies. Moreover, the method of PETase action is of keen interest for further protein and enzyme mixture engineering studies. The direct catalytic mechanism could be studied with mixed quantum mechanical/molecular mechanics MD-based approaches similar to previous work on carbohydrate-active enzymes ( 58 ). Beyond the active site, the enzyme may interact with and cleave the substrate in an endofashion by cleaving PET (or PEF) chains internal to a polymer or in an exofashion by only cleaving PET from the chain ends. Methods employed in the cellulase and chitinase research community, such as substrate labeling with easily detected reporter molecules or examination of product ratios, could potentially shed light on this question, and will be pursued in future efforts ( 59 ). Lastly, at low substrate loadings, many polysaccharide-active enzymes rely on multimodular architectures, with a carbohydrate-binding module attached to the catalytic domain ( 57 ). For polyesterase enzymes, hydrophobins, carbohydrate-binding modules, and polyhydroxyalkanoate-binding modules have been used to increase the catalytic efficiency of cutinases for PET degradation ( 60 , 61 ). Certainly, further opportunities exist for engineering or evolving for higher binding affinity of accessory modules to increase the overall surface concentration of catalytic domains on the PET surface. Given the fact that PET was only patented roughly 80 y ago and put into widespread use in the 1970s, it is likely that the enzyme system for PET degradation and catabolism in I. sakaiensis appeared only recently, demonstrating the remarkable speed at which microbes can evolve to exploit new substrates: in this case, waste from an industrial PET recycling facility. Moreover, given the results obtained for the PETase double mutant, it is likely that significant potential remains for improving its activity further. This enzyme thus provides an exciting platform for additional protein engineering and evolution to increase the efficiency and substrate range of this polyesterase, as well as to provide clues of how to further engineer thermophilic cutinases to better incorporate aromatic polyesters, toward to the persistent challenge of highly crystalline polymer degradation."
} | 1,922 |
32085468 | PMC7074800 | pmc | 4,096 | {
"abstract": "Anaerobic digestion (AD) has been used for wastewater treatment and production of renewable energy or biogas. Propionate accumulation is one of the important problems leading to an unstable system and low methane production. Revealing propionate-degrading microbiome is necessary to gain a better knowledge for alleviation of the problem. Herein, we systematically investigated the propionate-degrading cultures enriched from various anaerobic sludge sources of agro-industrial wastewater treatment plants using 16S rRNA gene sequencing. Different microbial profiles were shown even though the methanogenic activities of all cultures were similar. Interestingly, non-classical propionate-degrading key players Smithella , Syntrophomonas, and Methanosaeta were observed as common prevalent taxa in our enriched cultures. Moreover, different hydrogenotrophic methanogens were found specifically to the different sludge sources. The enriched culture of high salinity sludge showed a distinct microbial profile compared to the others, containing mainly Thermovirga , Anaerolinaceae , Methanosaeta , Syntrophobactor, and Methanospirillum . Our microbiome analysis revealed different propionate-degrading community profiles via mainly the Smithella pathway and offers inside information for microbiome manipulation in AD systems to increase biogas production corresponding to their specific microbial communities.",
"conclusion": "5. Conclusions The microbiome of the propionate-degrading communities enriched from different inoculum sources was investigated using 16S rRNA gene sequencing analysis. Interestingly, we found Smithella as the dominant propionate-degrading bacteria in most of the studied samples, suggesting the dismutation pathway of propionate degradation instead of the classical MMC pathway. The experiment supported a key role of Smithella and Syntrophomonas that implied a multi-trophic interaction of these two microorganisms to convert propionate to acetate and butyrate, and butyrate to acetate, respectively. A major abundance of Methanosaeta was observed as a main methanogen using acetate, while dominant HMs were found specific to different inoculum sources. The Seafood sludge sample shows a distinctive microbial profile containing Thermovirga , Anaerolinaceae, and Methanosaeta as dominant taxa, as well as Syntrophobacter and Methanospirillum which are mostly reported as regular syntrophic propionate-degrading culture through the MMC pathway. The highest HM:AM ratio was found in the Seafood sample, which corresponds to the MMC pathway producing more hydrogen that is utilized by HMs than the Smithella pathway. On the other hand, the relative abundances of AMs in the samples with the dismutation pathway were higher than in the Seafood sample, as more acetates are produced from that pathway. Furthermore, several uncultured bacteria of the class Anaerolinea were revealed in the enriched cultures. Our study shows that digesters with comparable performance and methane production could contain different communities of propionate-degrading microbes corresponding to their original sludge sources. The result suggests that inside information of specific propionate-degrading communities could be further applied to microbial monitoring and manipulation of wastewater treatment systems to increase biogas production.",
"introduction": "1. Introduction Biogas is an alternative fuel that can be produced by wastewater treatment under the absence of oxygen, called anaerobic digestion (AD). This process consists of various complex organic degrading sub-processes which are driven by microbial communities [ 1 , 2 ]. Even though the AD system has been considered as a promising solution for wastewater treatment and biogas production, the operational stability in several systems is still poor and yields low biogas production. Various factors have been reported as AD inhibitors causing system instability, such as volatile fatty acids (VFAs), long-chain fatty acids (LCFAs), toxic chemical substances, etc. [ 3 , 4 ]. Many studies have been set up to determine optimal process parameters for gaining high biogas production [ 5 , 6 , 7 , 8 ]. The anaerobic digestion process entails four steps: hydrolysis, acidogenesis, acetogenesis, and methanogenesis [ 9 ]. During hydrolysis, lipids, proteins, polysaccharides, and soluble organic matter are all degraded, with the final products being further treated through acidogenesis to yield volatile fatty acids (VFAs). The acidogenesis step is followed by acetogenesis, during which the VFAs are digested by acetogenic microorganisms producing a smaller molecule, acetate. The last step is methanogenesis, in which methane is generated. This process involves microorganisms called methanogens, which can be categorized into two groups according to their substrates. Acetoclastic methanogens (AMs) use acetate, while hydrogenotrophic methanogens (HMs) use H 2 /CO 2 as substrates [ 10 ]. Through these AD steps, VFA accumulation often occurs because of the rapid degradation from the acidogenic process and thermodynamically unfavorable degradation [ 11 ]. The accumulation of propionic acid, one of the VFAs, has been reported as one of the important reasons for low methane production, as its propagation in the system decreases pH and subsequently inhibits methanogenic activity [ 6 , 12 ]. Enriched cultures of propionic-degrading microorganisms for bioaugmentation have been introduced as a solution to alleviate the acid accumulation, resulting in a more stable system and higher biogas productivity [ 13 , 14 , 15 , 16 ]. The technique is the practice of adding a particular microbial culture, which can be grown by using specific substrate as a carbon and energy source, to the unstable AD system for enhancing or boosting process performance. This relies on the fact that the propionate-degrading microbes are a key factor for the improvement of stability and efficiency of anaerobic treatment. Understanding the structure and microbial dynamism of the propionic-degrading communities, including mainly propionate degraders and methanogens, is required to better control and manage the microorganisms for reliability of the treatment systems. A number of propionate-degrading microbes have been reported, with two main pathways of methylmalonyl Co-A (MMC) and dismutation. The MMC pathway was observed with Syntrophobacter sp. and Pelotomaculum sp. [ 17 , 18 ], and was mostly reported as a route of classical propionate degradation in AD. The overall reaction is: Propionate − + 3H 2 O → Acetate - + HCO 3 − + H + + 3H 2 ; ΔG° = 76.1 kJ/mol [ 19 ]. Methanospirillum sp. has been found as the main HM, required to maintain H 2 partial pressure for syntrophic activities with Syntrophobacter sp. [ 20 , 21 , 22 ]. On the other hand, the dismutation pathway was found with Smithella propionica which dismutates propionate to acetate and a butyrate through a six-carbon intermediate molecule. The overall equation is: 2Propionate − + 2H 2 O → 3Acetate - + H + + 2H 2 ; ΔG° = 48.4 kJ/mol [ 23 , 24 , 25 ], giving more acetate and less hydrogen per one mole propionate compared to the MMC pathway. The Smithella was found as syntrophic-oxidizing bacteria with a number of HMs such as Methanospirillum sp. [ 26 ] and Methanoculleus sp. [ 27 ]. However, we believe that all related microbes of the processes have not been completely revealed. Next-generation sequencing (NGS) technologies have been developed, generating a large amount of genetic sequences allowing culture-independent study of living organisms [ 28 , 29 , 30 ]. This provides a big advantage to understanding microbial communities as beforehand only a few percent of microorganisms could be studied by cultivation in laboratories. The 16S rRNA gene is a commonly used marker to identify microorganisms from a particular environment using NGS. It has also been applied to explore the AD systems for both lab-scale and full-scale digesters [ 31 , 32 ]. Several microorganisms in the AD process were revealed through NGS-based techniques in different digester conditions [ 33 , 34 ]. To our knowledge, a small number of propionate-degrading community studies have been reported [ 35 , 36 ]. Variation of the communities as a whole system from different wastewater sources have still not been completely revealed. There is a need to extend the investigation of the microorganisms in propionate-degrading microbial communities, providing insight for microbial monitoring and manipulation to control the system stability and prevent failure. Here, we observed anaerobic propionate-degrading communities via the enriched cultures inoculated from different sources of agro-industrial wastewater treatment plants. The microbiome profiles were investigated using a 16S rRNA-based sequencing approach. Firstly, we investigated the shift of microbiome profiles from inoculum to enrichment stages for revealing propionate-degrading communities. Then, we identified common and unique propionate-degrading microbes among the different sludge sources. We discuss this and conclude with the possible propionate-degrading communities and pathways specific to the original sludge sources.",
"discussion": "4. Discussion 4.1. The Schematic Propionate-Degrading Pathway in the Enriched Cultures for Methane Production With the limited carbon source of only propionate in the enriched cultures, microbial diversities in the samples were lower than in the inoculum sludges ( Table S1 ). The discovered microbial community profiles and their degradation processes could be affected by the single carbon source feeding. Excluding the Seafood sample, our experiment revealed very small percentages of Syntrophobacter (<0.5%), which was previously proven as a propionate-degrading bacterium and found in most of the propionate-degrading communities along with HMs [ 22 , 35 , 44 , 45 ]. Interestingly, Smithella was found to be the dominant propionate-degrading bacterium [ 26 ] in our experiment, instead of the regular Syntrophobacter . There might be two main reasons for the presence of Smithella in the enriched cultures: (1) the nature of the original sludge containing a higher number of Smithella than Syntrophobacter ( Figure 2 ; Table S4 ) and (2) Syntrophobacter prefers to grow with propionate and sulfate in the medium [ 23 ], which corresponds to our experiment that fed the medium without adding sulfate. The results suggest that the main reaction of the propionate degradation ( Figure 4 and Table S8 ) is through Smithella, which can produce acetate and butyrate via a six-carbon intermediate, called the dismutation pathway [ 23 , 24 , 25 ]. The total reactions produced more acetate molecules compared to the classical pathway which belongs to Syntrophobacter and Pelotomaculum [ 23 ]. Following this theoretical perspective, we observed a higher abundance of Methanosaeta , which produces methane by acetate degradation, in the enriched samples [ 46 ]. Furthermore, Syntrophomonas was observed in several enriched samples. It was reported as a butyrate utilizer to produce acetate for AMs in the AD system [ 47 ]. Therefore, our studies suggest multi-trophic interaction of Smithella that can degrade propionate directly to acetate and convert propionate to butyrate, which is a substrate for Syntrophomonas ( Figure 4 ). Consequently, Methanosaeta utilizes the resulting acetate from both organisms to produce methane and functions as a key AM in the enriched cultures. 4.2. Different Taxa of Hydrogenotrophic Methanogens Found Specifically to Different Sludge Sources While a single genus of AM was found as dominant taxa in all enriched samples, various genera of HMs were found particular to different sludge sources ( Table 3 and Figure 4 ). In this study, Methanobacterium , Methanoculleus , and Methanolinea, were found in the FruitJuice, PalmOil, and Starch samples, respectively. Different OTUs of Methanoregula were found in the Domestic and PigManure samples. All of these HMs were reported in various mesophilic environments [ 48 , 49 ], and some of them, e.g., Methanolinea and Methanoculleus, were isolated from propionate-enrichment cultures as prevalent methanogen [ 50 , 51 ]. Although relatively smaller amounts of these HMs compared to AMs have been observed, they could also play a role in our systems for methane production by conversion of CO 2 /H 2 . These small amounts could also result from less H 2 produced from the dismutation pathway compared to the MMC pathway ( Table S8 ). The observed HMs could refer to the syntrophic contribution of propionate degradation with Smithella [ 23 ]. Several types of HMs resulting from different wastewater treatment sludges suggest possible various pairs of syntrophic propionate oxidation and methane production between Smithella and HMs. The information of specific microbial taxa or communities of propionate degradation could be used as a guideline for microbial management, leading to efficient biogas production. 4.3. Unique Microbial Community in the Propionate-Degrading Culture Enriched from Seafood Sludge The Seafood sludge revealed statistically distinct microbial profiles compared to the other sludges from different wastewater sources ( Figure 2 and Table S3 ). Thermovirga and Anaerolineaceae uncultured groups affiliating to phylum Synergistetes and Chloroflexi, respectively, were found as prevalent organisms in the enriched propionate-degrading culture. Thermovirga were reported as amino acid degrading bacteria and were found dominantly in high salinity environments [ 52 ]. This is consistent with the condition of the Seafood sample, that originally contained high salinity. Anaerolineaceae were found in the AD system relating to granular formation and maintenance [ 53 ]. Both Thermovirga and Anaerolineaceae have been revealed dominantly with Methanosaeta in several AD experiments [ 54 , 55 , 56 ], suggesting that these microbes would play an important role in propionate degradation and biogas production pathways. Syntrophobacter and Methanospirillum were found as syntrophic propionate-oxidizing bacteria and H 2 -utilizing methanogen, respectively [ 22 , 35 ]. These microbes have relatively higher abundance in the Seafood sample compared to the other five samples, suggesting an observation of the classical MMC pathway instead of our main discovered Smithella pathway ( Figure 4 ). Furthermore, the Seafood sample showed the highest HM:AM ratio compared to other samples ( Table S9 ). This corresponds to the result of a higher percent methane production but less SMA, indicating AM activities of utilizing acetates as substrates, compared to other samples ( Table 1 ). The result suggested that the HMs would play more of a role in this sample as the MMC pathway provides more H 2 than the dismutation pathway ( Table S8 ). The result showed that the Seafood sample has a unique profile and could be further investigated for the enrichment of methanogenic propionate degradation in a saline environment. 4.4. Overall Microbial Profiles of Propionate-Degrading Cultures and Unculturable Microbes Revealed Through Amplicon-Based Sequencing The utilization of NGS allows the study of microbes taken directly from the samples without cultivation, showing all existing microbes with their abundance in the studied sample. Beforehand, a small number of known microbes has been studied, limited by cultivation [ 22 , 26 , 57 ]. Since microbes live as a community, this high-resolution technique provides a great opportunity to derive an overall picture of a microbial community and provides more insights to understand the dynamism of the studied consortium. In this study, a set of propionate-degrading communities was revealed according to their original sludge sources. Many OTUs of the class Anaerolineae were empirically revealed as predominant uncultured microbes in the enriched propionate-degrading cultures ( Table S6 ). This microbe has been discovered dominantly in several AD systems [ 56 ]. In addition, Mcllroy S.J. et al. [ 56 ] reported a member of Anaerolineae co-located with Methanosaeta spp., which was discovered in our study as major archaea. The function of the Anaerolineae and its synergistic relationship to Methanosaeta could be worth further investigation. The information from high-throughput sequencing provided a whole microbial community leading to better understanding of the control and management of the AD systems, as the microorganisms work together in the process."
} | 4,152 |
21513516 | PMC3107774 | pmc | 4,098 | {
"abstract": "Background The substitution of plastics based on fossil raw material by biodegradable plastics produced from renewable resources is of crucial importance in a context of oil scarcity and overflowing plastic landfills. One of the most promising organisms for the manufacturing of medium-chain-length polyhydroxyalkanoates (mcl-PHA) is Pseudomonas putida KT2440 which can accumulate large amounts of polymer from cheap substrates such as glucose. Current research focuses on enhancing the strain production capacity and synthesizing polymers with novel material properties. Many of the corresponding protocols for strain engineering rely on the rifampicin-resistant variant, P. putida KT2442. However, it remains unclear whether these two strains can be treated as equivalent in terms of mcl-PHA production, as the underlying antibiotic resistance mechanism involves a modification in the RNA polymerase and thus has ample potential for interfering with global transcription. Results To assess PHA production in P. putida KT2440 and KT2442, we characterized the growth and PHA accumulation on three categories of substrate: PHA-related (octanoate), PHA-unrelated (gluconate) and poor PHA substrate (citrate). The strains showed clear differences of growth rate on gluconate and citrate (reduction for KT2442 > 3-fold and > 1.5-fold, respectively) but not on octanoate. In addition, P . putida KT2442 PHA-free biomass significantly decreased after nitrogen depletion on gluconate. In an attempt to narrow down the range of possible reasons for this different behavior, the uptake of gluconate and extracellular release of the oxidized product 2-ketogluconate were measured. The results suggested that the reason has to be an inefficient transport or metabolization of 2-ketogluconate while an alteration of gluconate uptake and conversion to 2-ketogluconate could be excluded. Conclusions The study illustrates that the recruitment of a pleiotropic mutation, whose effects might reach deep into physiological regulation, effectively makes P. putida KT2440 and KT2442 two different strains in terms of mcl-PHA production. The differences include the onset of mcl-PHA production (nitrogen limitation) and the resulting strain performance (growth rate). It remains difficult to predict a prioriwhere such major changes might occur, as illustrated by the comparable behavior on octanoate. Consequently, experimental data on mcl-PHA production acquired for P. putida KT2442 cannot always be extrapolated to KT2440 and vice versa, which potentially reduces the body of available knowledge for each of these two model strains for mcl-PHA production substantially.",
"conclusion": "Conclusions This work shows substantial differences of physiology between the two closely related P. putida KT2440 and KT2442 upon growth on gluconate. A strong reduction of specific growth rate was observed for P. putida KT2442 as well as a smaller growth yield on carbon and difficulties to cope with nitrogen starvation. P. putida KT2442 is often preferred over P. putida KT2440 to generate metabolically engineered organisms with enhanced production of mcl-PHA because the procedure is simplified by the rifampicin resistance [ 17 , 35 ]. However, the productivity of mcl-PHA - which is correlated to its cost - depends not only on the polymer content in the cells but also on their growth rate. Thus, the benefits of an increase in polymer accumulation from carbohydrates by metabolic engineering would be counteracted by a slow growth rate if P. putida KT2442 was used as host instead of P. putida KT2440.",
"discussion": "Discussion How close are P. putida KT2440 and KT2442? P. putida KT2440 and P. putida KT2442 have been extensively studied for the last 30 years, not only because of their interesting ability to accumulate mcl-PHA, but also as model organisms for laboratory studies and applications in bioremediation and biocatalysis [ 20 , 21 ]. P. putida KT2440 and P. putida KT2442 are supposedly identical except regarding the rifampicin resistance. However, we observed different phenotypes between the two strains cultivated on gluconate: P. putida KT2442 displayed a reduced growth rate along with a lower growth yield for carbon and difficulties to cope with nitrogen limitation. Rifampicin activity consists of inhibiting the bacterial DNA-dependent RNA polymerase by binding to it and stopping mRNA elongation [ 14 ]. Rifampicin-resistant mutants produce RNA polymerases that have a slightly different β-subunit structure preventing the binding of rifampicin [ 16 ]. Jatsenko et al . also showed recently that out of 167 rifampicin resistant mutants generated from P. putida PaW85 ( P. putida mt-2 derivative cured of the TOL plasmid), all of them harbored the mutation of interest in the cluster I of rpoB gene [ 15 ]. Because of the essential role of the RNA polymerase in gene transcription even slight modifications of its structure can have important and pleiotropic effects on the cell physiology. In particular, the regulatory nucleotide ppGpp was shown to bind at the interface between the β and β' subunits of E. coli RNA polymerase at 27 Å from the rifampicin binding site [ 22 - 25 ]. Therefore, modifications of RNA polymerase structure, even minor, could alter the binding of ppGpp with various consequences on the cell physiology. Indeed, ppGpp is a global transcription regulator mostly known for inhibiting growth and protein synthesis upon amino acid starvation but also involved in the regulation of many other functions [ 24 , 26 ]. Besides, since P. putida KT2442 is a spontaneous mutant of P. putida KT2440 and not the result of a targeted procedure [ 6 ], the strain could harbor other mutations that may be made responsible for its poorer fitness. The determination of this (these) mutation(s) would require careful resequencing of KT2442. Nevertheless, a first step would be to determine whether the rifampicin resistance mutation is involved by reintroducing the wild-type rpoB gene from P. putida KT2440 in KT2442. Gluconate transport and metabolism The difference of growth rate observed between P. putida KT2440 and KT2442 on gluconate can reside in the transport of gluconate, in its metabolism, or in their regulation. The general model describing the transport and metabolism of gluconate in P. putida is depicted in Figure 4 . First, gluconate crosses the outer membrane by facilitated diffusion mostly through the specific porin OprD, which is also utilized by basic amino acids [ 27 ]. The role of this porin is only important at low substrate concentrations which would correspond to the end of the exponential phase in our experiments. Indeed, similar growth rates were observed between the wild-type P . aeruginosa strain and its OprD mutant on gluconate 10 mM whereas the OprD mutant exhibited a 3-fold reduced growth rate on gluconate 1 mM [ 27 ]. Therefore, a lack of OprD porins cannot explain the reduced growth rate of P. putida KT2442 during the exponential phase. Once in the periplasm, gluconate can pass through the cytoplasmic membrane via the active transporter GntP. The transport of gluconate and its subsequent phosphorylation in the cytoplasm in under the control of GnuR repressor [ 28 ]. Nevertheless, this route is not the preferred one, gluconate being preferentially converted into 2-ketogluconate by Gad enzymes bound to the periplasmic side of the cytoplasmic membrane [ 29 , 30 ]. It was observed in this work that 50% of the gluconate taken up during the exponential growth phase was converted into 2-ketogluconate by P. putida KT2440 and secreted (q C(Gln) = - 2.0 g g -1 h -1 , q C(2-KGln) = + 1.0 g g -1 h -1 ; Table 1 , Figure 4B ) whereas >70% of the produced 2-ketogluconate was released in the extracellular fraction in case of P. putida KT2442 (q C(Gln) = - 0.7 g g -1 h -1 , q C(2-KGln) = + 0.5 g g -1 h -1 ;Table 1 , Figure 4C ). The conversion of gluconate into 2-ketogluconate was thus working efficiently in P. putida KT2442. The molecules of 2-ketogluconate that are not secreted into the medium are actively transported in the cytoplasm by KguT proteins (putative transporter gene PP_3377 [ 29 ]). There, the molecules are phosphorylated and further metabolized for energy production via the Entner-Doudoroff pathway and for biomass production. Interestingly, the genes involved in the periplasmic conversion of gluconate to 2-ketogluconate and the genes responsible for the transport and cytoplasmic conversion of 2-ketogluconate to 6-phosphogluconate are clustered in two independent operons located next to each other. These two operons are under the control of a PtxS regulator, which specifically recognizes 2-ketogluconate [ 31 ]. If growth is stoichiometrically limited, for instance by nitrogen, the excess of carbon can be accumulated as a storage compound such as glycogen or mcl-PHA. The production of glycogen was however negligible under the growth conditions tested (< 4 wt %, data not shown) and most of the excess carbon was directed towards synthesis of mcl-PHA. An inefficient transport of 2-ketogluconate through the cytoplasmic membrane or an impaired step in the further metabolization would therefore be reasonable explanations for the reduced growth rate of P. putida KT2442. Figure 4 Gluconate metabolism in P. putida strains KT2440 and KT2442 . A. The route before gluconate depletion is indicated by the numbers \"1\" and the route after gluconate depletion one with \"2\". The dotted arrows describe the direct transport of gluconate into the cytoplasm which is possible but of minor importance. This figure was adapted from Daddaoua et al . [ 31 ]. Abbreviations: Eda = 2-keto-3-deoxygluconate aldolase, Edd = phosphogluconate dehydratase, Gad = gluconate dehydrogenase, Glc-1P = glucose-1-phosphate, Gln = gluconate, Gln-6P = 6-phosphogluconate, GntP = gluconate permease, Gnuk = gluconokinase, G3P = glyceraldhyde 3-phosphate, KDPG = 2-keto-3-deoxy-6-phosphogluconate, 2-KGln = 2-ketogluconate, 2-KGln-6P = 2-keto-6-phosphogluconate, KguD = 2-ketogluconate reductase, KguK = 2-ketogluconate kinase, KguT = 2-ketogluconate transporter, PYR = pyruvate, TCA = tricarboxylic acid cycle. B. Specific uptake rate of gluconate (q C(Gln) ), specific production rate of 2-ketogluconate (q C(2-KGln) ), carbon specific uptake rate (q C* ) and nitrogen specific uptake rate (q N ) for P. putida KT2440 growing exponentially on gluconate in bioreactor. The width of the arrows expresses the actual values. C. Same as B but for P. putida KT2442. Energy metabolism, nitrogen transport, and growth under nitrogen limitation P. putida KT2440 and KT2442 grew with the same maximum specific growth rate on octanoate, indicating that the main energy production pathway (tricarboxylic acid cycle) worked properly. The slow growth rate observed for P. putida KT2442 on gluconate is therefore substrate-specific. However, P. putida KT2442 grew more slowly than P. putida KT2440 on citrate (μ max = 0.34 ± 0.02 h -1 and 0.54 ± 0.03 h -1 , respectively). This could be the result of a problem with the expression of a citrate transporter or activator of citrate transport. An alternative explanation would be that the tricarboxylic acid cycle was only slightly slowed down in P. putida KT2442 so that it became growth limiting only when the cells were growing fast (e. g. on citrate) but not when they were growing more slowly (e. g. on octanoate). When ammonium is present at high external concentrations as during the exponential phase, it enters the cytoplasm via unspecific diffusion of NH 3 [ 32 ] and does not require specific transporters. Therefore, the low specific uptake rate of nitrogen for P . putida KT2442 must be the consequence and not the cause of its slow growth rate. This conclusion is also supported by the fact that P. putida KT2442 and KT2440 had identical growth rates on octanoate. P. putida KT2440 and KT2442 reacted differently with respect to nitrogen starvation. While the PHA-free biomass continued to increase a little and then remained constant for P. putida KT2440, it quickly decreased for P. putida KT2442 (Figure 4A and 4D ). Also, the respiratory quotient of the latter strain progressively and significantly increased, whereas it remained stable for P. putida KT2440. This indicates a change of metabolism occurring for P. putida KT2442 as a result to nitrogen starvation. Although the gene expression in response to nitrogen limitation has been studied for P. putida KT2440 and KT2442 by Hervas et al . [ 8 ], it was not possible to formulate a reasonable hypothesis as to what caused this different behavior. Nitrogen limitation is required for the accumulation of mcl-PHA from gluconate in P. putida KT2440 and KT2442 The data presented herein showed that nitrogen limitation was required to activate the production of mcl-PHA from gluconate in both P. putida KT2440 and KT2442. In contrast, we had observed previously that P. putida KT2440 cultivated on octanoate accumulated significant amounts of mcl-PHA even before nitrogen depletion (data not shown). Also, Sun et al . were able to produce more than 70 wt % of mcl-PHA from nonanoic acid in P. putida KT2440 without nitrogen limitation. Therefore, the requirement of a nutrient limitation to produce mcl-PHA seems to be substrate-dependent. As mentioned above, the synthesis of mcl-PHA by P. putida involves two different pathways depending on the precursor. Unrelated carbon sources such as gluconate are converted into polymer via de novo fatty acid synthesis and the intervention of the 3-hydroxy-acyl carrier protein (ACP)-CoA transacylase PhaG [ 33 ], whereas alkanes and fatty acids are channeled through the β-oxidation pathway [ 34 ]. The origin for the need or not of nitrogen limitation may thus be linked to enzymes belonging to these pathways. Indeed, the enzyme PhaG was shown to be overexpressed under nitrogen starvation in P. putida KT2440 and KT2442 [ 8 ]. However, other control systems may be involved as well."
} | 3,523 |
27386575 | PMC4928966 | pmc | 4,099 | {
"abstract": "Coherent X-rays reveal defects in photonic crystals of butterfly wings.",
"introduction": "INTRODUCTION Light interference, as was realized as early as the beginning of the 19th century ( 1 ), is a common cause of the bright coloring of various animals such as the spine of the sea mouse ( 2 ), butterfly wings ( 3 – 7 ), feathers of birds of paradise ( 8 , 9 ), or the skin of chameleons ( 10 ). The appearance ranges from narrowband colors corresponding to well-ordered nanostructures to broadband sparkly reflectance due to Anderson localization of light in strongly disordered natural photonic crystals ( 11 , 12 ). The remarkably diverse engineering of photonic crystals in animals and plants has practical applications such as mating and camouflage. These photonic crystals are not only interesting for evolutionary biology ( 13 ) but also appealing for metamaterial research ( 14 – 18 ) and exciting applications such as designing Weyl points ( 19 ). Recently, photonic crystal synthesis from butterfly wings has been successfully demonstrated by replacing the chitinous material with various metals to achieve tunable photonic properties ( 20 , 21 ). However, the initial growth of these photonic crystals in nature is yet to be understood, and once the self-assembly process can be duplicated in the laboratory, the new synthesis pathway will undoubtedly open up new opportunities for developing photonic devices with desired mechanical, structural, and photonic properties. The nanoscale structure of biological photonic crystals has been studied using electron microscopy ( 7 , 22 , 23 ), typically by slicing techniques. The crystallographic space group symmetry of various butterfly and beetle species has recently been characterized using x-ray diffraction ( 7 , 24 ). Furthermore, the orientation of the photonic crystals can be visualized and mapped using optical light and cross-polarizers ( 8 , 25 ). Present understanding suggests that a butterfly wing scale is a thin object (about 10 μm in thickness and 100 μm in size) and forms from a single cell ( 26 ). The interior of the scale contains photonic microcrystals (reflectors) that are somewhat randomly oriented and consist of chitin, which slowly polymerizes in the larval stage of the butterfly after the formation of the outermost layer of the scale ( 7 , 26 , 27 ). The naked eye typically cannot resolve individual microcrystals, and the observer sees reflection for a range of wavelengths (pointillism) ( 28 , 29 ). Whether the chirality of the gyroid crystals observed in some species is connected to the molecular chirality of chitin is currently being debated ( 23 ). Recently, by comparing two-dimensional transmission electron micrograph sections of the green gyroid scales of Parides sesostris to computer models of a single-network gyroid, Yoshioka et al. ( 25 ) found that domains were not randomly oriented but preferentially oriented with the [110] direction normal to the top (or obverse) surface of the scale. EXPERIMENT We used x-ray diffraction to investigate the spatial and angular distributions of the photonic crystals in a single wing scale of a Kaiser-i-Hind butterfly, Teinopalpus imperialis (Papilionidae) (see Fig. 1A ). The green upper wing scales of male species containing multiple domains of single-network gyroids ( I 4 1 32) ( 7 , 30 ) were investigated. By quantitative analysis of the orientation of photonic crystals in the entire scale, we find that the gyroid domains are preferentially oriented with the [111] direction perpendicular to the scale boundary, as opposed to the [110] direction observed in P. sesostris (Papilionidae) ( 25 ). Additionally, we used a coherent x-ray diffractive imaging technique [ptychography ( 31 )] to reveal and document two qualitatively different types of gyroid domain boundaries: first, abrupt interfaces at the boundaries of domains with distinctive orientations that merge during growth, and second, boundaries with edge dislocations between subregions of a single-crystal domain with very slight variations in orientation. We anticipate that these observations will shed new light on the structural mechanisms of self-assembly ( 32 ) and the development of photonic structures in butterfly wing scales. Fig. 1 Experimental description. ( A ) An image of the T. imperialis (Kaiser-i-Hind) butterfly ( 43 ). ( B ) A schematic of the experiment. X-ray radiation (1.8-keV photon energy) is generated by the undulator source and spatially filtered by a 5-μm pinhole. The sample is positioned behind the pinhole, and the detector records coherently scattered radiation. A semitransparent beam stop mounted on a metallic wire was used. ( C ) An optical micrograph of a single wing scale. ( D and E ) Typical diffraction patterns recorded from different sample areas with x-rays incident normal to the scale. Insets to (D) and (E) show the intensity in the vicinity of the (110) Bragg peaks. Scale bars, 5 cm (A), 50 μm (C), and 0.05 nm −1 (D and E). The experimental setup is shown in Fig. 1B . Coherent x-rays were spatially filtered by a pinhole and were incident on an isolated, free-standing butterfly wing scale (see Fig. 1C for an optical micrograph of the scale and Materials and Methods for details). Strong Bragg peaks reveal a highly ordered sample, and a pattern of hexagonally symmetric peaks indicates a gyroid lattice with a lattice spacing of 330 nm in the 〈110〉 direction, in agreement with the literature ( 7 ). In contrast to typical x-ray diffraction on atomic crystals, here, because of the large unit cell dimensions, the Ewald sphere is almost flat, and several reflections can be recorded simultaneously ( 33 ). In Fig. 1D , one set of hexagonal peaks is observed and suggests scattering from a single domain. Four orders of peaks can clearly be seen, with a maximum recorded spatial frequency corresponding to less than 60 nm. The intensity close to a {110} Bragg peak (inset to Fig. 1D ) is reminiscent of an Airy pattern due to circular pinhole diffraction, indicating that the sample is a homogeneous single crystal within the pinhole area. By contrast, in Fig. 1E , two hexagonal sets of peaks with slightly different orientations are observed, indicating two domains in the illuminated region. Moreover, the diffracted intensity around the Bragg peak lacks circular symmetry because of domain boundaries in the beam (inset to Fig. 1E ). The peak on the top left of the inset to Fig. 1E appears to have a minimum intensity in its center, which is a clear indicator of the presence of an edge dislocation within the illuminated volume of the sample. In both diffraction patterns, horizontal fringes around the Bragg peak reveal an additional periodicity on top of the gyroid lattice, which we ascribe to the vertical ridges, visible in Fig. 1C . We mapped crystallographic orientations within the scale by scanning the pinhole across the sample with a step size of 2 μm for different angles of incidence ranging from −20° to +20° about the normal of the scale. These scans were used to determine the complete spatially resolved orientation (three angles) of the gyroid reciprocal lattice (see Materials and Methods and figs. S1 and S2). The orientation of the grains may be presented with the following three angles: α is the angle between the x axis and a {110} peak (see Fig. 1 , D and E), β is the angle between the z axis and the normal to the plane defined by the hexagonal peaks n 111 , and γ is the angle between the x axis and the projection of the normal vector n 111 along the z axis (see fig. S3 for the definition of the angles).",
"discussion": "DISCUSSION Our findings are consistent with the following growth model for these photonic nanostructures. The appearance of domains with random orientation of the gyroid lattice in the plane of the scale suggests that photonic crystals nucleate from multiple random locations. The preferred orientation of the domains, normal to the scale plane, is quite remarkable and is consistent with crystal nucleation at the scale boundary and crystal growth outward. The orientation could also arise from a secondary growth mechanism, in which domain orientations favored by surface energy grow at the expense of less-favored domain orientations ( 36 ). However, this rearrangement requires sufficient mobility, and both dislocations and rough domain boundaries, revealed by high-resolution x-ray data, suggest that the crystal structure is very rigid and is trapped in a nonequilibrium state (in particular, see the two edge dislocations with opposite Burgers vectors in Fig. 3A ). The fact that we only observe one domain within the scale thickness further suggests that the domains grow from only one scale boundary. The study of the nanoscale structure reveals two kinds of domain boundaries; first, we observe sharp interfaces with an abrupt change of the lattice orientation. We attribute these domain boundaries to the merging of domains independently nucleated during growth, that terminate at the mutual domain boundary. The thickness of the interface between domains appears to be on the order of one unit cell, which is extremely sharp, considering that Fig. 3 shows a projection of about 10 layers (for example, see the region between cyan and red in Fig. 3B ). Second, a different type of domain boundary appears between only slightly misaligned domains and is accommodated by a series of edge dislocations. These edge dislocations may form as a result of the merging of different domains with a low-angle tilt ( 37 ). However, edge dislocations with opposite Burgers vectors likely form as a result of the growth process itself and are introduced to mitigate internal stresses, possibly due to the curvature of the underlying scale or the plastic deformation during growth. A recent microscopic model of the growth of these crystals proposes an asymmetric triblock copolymer development (ABCB′A′) ( 7 , 24 ), and the out-of-equilibrium structures observed here indicate a rapid solvent evaporation, analogous to block copolymer structures trapped in a nonequilibrium state during solvent evaporation ( 38 ). The discovery of the edge dislocations in the biological photonic crystals is particularly remarkable because artificially manufactured topological defects in photonic crystals lead to interesting optical properties such as Anderson localization of light ( 14 ). Two intriguing questions are whether nature-engineered defects for a particular purpose and whether mimicking similar growth conditions allows for controlled manufacturing of defects in artificial photonic structures. In summary, we have used x-ray diffraction to study domain morphology and domain boundaries within photonic crystals in a single butterfly wing scale. The photonic crystal is reminiscent of a thin polycrystalline film, with the domains being highly oriented in the direction normal to the scale boundary, which suggests a layer-by-layer crystal growth process starting at the cell membrane. Ptychographic imaging on the nanoscale has revealed two types of domain interfaces: abrupt boundaries likely due to the merging of independently nucleated domains and smooth interfaces with edge dislocations. We anticipate that the latter results from strain relaxation during crystal growth. Our study was performed nondestructively (nonslicing) and can, in principle, be extended to in vivo studies during the growth of these structures. Understanding and artificially reproducing these growth processes in the laboratory environment will be invaluable for developing future photonic devices. Finally, the multiple-Bragg-peak ptychography opens up high-resolution imaging of photonic crystals in the soft x-ray regime as well as of granular atomic crystals with coherent, high-energy x-rays (~100 keV) at the future diffraction-limited storage rings ( 39 )."
} | 2,971 |
38459042 | PMC10923942 | pmc | 4,101 | {
"abstract": "The development of advanced materials capable of autonomous self-healing and mechanical stimulus sensing in aquatic environments holds great promise for applications in underwater soft electronics, underwater robotics, and water-resistant human-machine interfaces. However, achieving superior autonomous self-healing properties and effective sensing simultaneously in an aquatic environment is rarely feasible. Here, we present an ultrafast underwater molecularly engineered self-healing piezo-ionic elastomer inspired by the cephalopod’s suckers, which possess self-healing properties and mechanosensitive ion channels. Through strategic engineering of hydrophobic C–F groups, hydrolytic boronate ester bonds, and ions, the material achieves outstanding self-healing efficiencies, with speeds of 94.5% (9.1 µm/min) in air and 89.6% (13.3 µm/min) underwater, coupled with remarkable pressure sensitivity (18.1 kPa –1 ) for sensing performance. Furthermore, integration of this mechanosensitive device into an underwater submarine for signal transmission and light emitting diode modulation demonstrates its potential for underwater robotics and smarter human-machine interactions.",
"introduction": "Introduction Bionic skins, developed from iontronic materials, exhibit immense potential for diverse aquatic applications, including wearable electronics for divers 1 , underwater soft robotics 2 , and underwater tactile sensing 3 , 4 . These materials offer notable advantages, encompassing low energy consumption, exceptional sensitivity, and high spatial resolution 5 – 7 . Furthermore, their remarkable deformability facilitates efficient ion pumping and seamless integration. Nevertheless, a significant challenge arises owing to their susceptibility to unpredictable mechanical damage, resulting in performance degradation and device failure. Consequently, the incorporation of self-healing properties becomes crucial to restore functionality, extend device lifespan, and ensure long-term stability. Traditional self-healing iontronic materials, based on noncovalent bonds such as hydrogen bonds, ionic interactions, and metal-ligand coordination, are susceptible to water molecule absorption, which disrupts the dynamic bonds, compromising the self-healing properties 3 , 8 , 9 . Moreover, water molecule ingress can introduce electrical interferences, short circuits, and electrochemical corrosion, thereby disrupting the iontronic material’s conduction mechanism 4 . To mitigate water ingress, previous studies have employed robust hydrophobic groups as a protective measure to shield the dynamic bonds and ionic interactions from water molecules. For instance, Cao et al. 3 and Xu et al. 10 . employed C–F groups, which not only facilitated dynamic ion-dipole interactions as the driving force for self-healing but also imparted hydrophobicity, owing to the high electronegativity of fluorine and the robust electrostatic characteristics of C–F bonds. This design concept enabled the material to exhibit self-healing and sensing capabilities even in underwater conditions. However, these materials exhibited relatively low self-healing efficiencies and speeds owing to the limited synergistic effect between the hydrophobic groups and dynamic bonds 10 – 14 . Therefore, the development of iontronic materials capable of autonomous self-healing and superb sensing performance in aquatic environments, with high self-healing efficiency and speed, remains a substantial challenge. Marine invertebrates, particularly cephalopods 15 , possess remarkable abilities to self-heal and perceive external stimuli, facilitating autonomous injury repair and interaction with their natural environment. An exemplar in this context is the squid, distinguished by its resilient biological materials comprising semicrystalline proteins forming ring teeth (RT) structures within its suckers. These RT proteins exhibit distinctive characteristics characterized by hydrogen bonds and abundant hydrophobic interactions, which significantly contribute to their self-healing and stabilization properties 16 – 18 . Additionally, another cephalopod species, the octopus, possesses specialized mechanosensory cells in its sucker epithelium 19 . These cells incorporate tethered ion channels, enabling the octopus to sense and respond to external mechanical stimuli within its surroundings. Herein, we present the development of molecularly engineered self-healing piezo-ionic elastomer (MESHPIE) characterized by dynamic hydrophobic-hydrolytic domains, exhibiting exceptional self-healing properties in both aquatic and ambient environments, coupled with mechanosensitive piezo-ionic dynamics. Our inspiration stems from the observed self-healing capabilities within cephalopod’s RT structures and the presence of mechanosensitive ion channels in their sucker epithelium. To achieve this, we incorporated hydrophobic C–F side groups and hydrolytic boronate ester groups into a polyurethane (PU) matrix. When immersed in water, this composite could repel water molecules owing to the presence of dense hydrophobic barrier. Particularly noteworthy is the reversible hydrolysis exhibited by the dynamic boronate ester bonds 20 , 21 when exposed to small quantities of water molecules, further accelerating the self-healing process. Optimization of the hydrophobic domain allows the ingress of small quantities of water while effectively repelling the majority of interfacial water molecules. This strategy prevents the complete hydrolysis of boronate ester bonds, ensuring efficient underwater self-healing capabilities. Through meticulous molecular engineering and systematic composition, we demonstrate that the coupling of hydrophobic and hydrolytic groups within a polymer can synergistically achieve high self-healing efficiency and speed at room temperature. Additionally, the introduction of 1-butyl-3-methylimidazolium bis(trifluoromethylsulfonyl)imide ([BMIM] + [TFSI] – ) ionic liquid (IL) initiates a piezo-ionic mechanism, showing mechanosensitive ion trap and release characteristics. This behavior stems from the ion-dipole interactions between the C–F groups and ion pairs. To showcase the potential applications that harness the capabilities of our device, we integrated the mechanosensitive MESHPIE-based device into a toy submarine connected to a light-emitting diode (LED). This allowed us to visually represent pressure changes when the submarine collided with an underwater object, both before and after unexpected damage occurred. In addition, we demonstrated the device’s proficiency as a pressure-induced tactile sensor, efficiently modulating LED brightness.",
"discussion": "Discussion We have molecularly engineered a mechanosensitive piezo-ionic elastomer with dynamic hydrophobic-hydrolytic domains, demonstrating remarkable self-healing properties and pressure sensing capabilities in both ambient and aquatic environments. The material exhibits autonomous, ultrafast self-healing speeds of 9.1 µm/min in air and 13.3 µm/min underwater. Notably, the synergy between hydrophobic chain density and boronate ester hydrolysis is pivotal in achieving high underwater self-healing efficiency (89.6%) and speed. The boronate ester bonds undergo metathesis bond exchange reactions in air and reversible hydrolysis reactions with minimal water exposure, facilitating enhanced self-healing speed in aquatic environments. The hydrophobic C–F side groups establish dense hydrophobic barrier, repelling the majority of water molecules, thereby shielding the boronate ester bonds and ionic interactions from complete hydrolytic reactions, enabling effective self-healing and sensing in underwater condition. Furthermore, the C–F groups play a crucial role in facilitating ion-pumping phenomenon established via ion-dipole interactions between ions and C–F dipoles, enabling superb mechanosensitivity. We integrated our MESHPIE-based device into an underwater toy submarine for signal transmission and LED illumination to visually indicate collisions with an underwater object. Additionally, we successfully demonstrated the device’s capacity to function as a tactile sensor, modulating LED intensity in response to applied pressure. These demonstrations emphasize the potential applications of our self-healing piezo-ionic device in soft electronics, underwater robotics, smarter human-machine interfaces, and innovative wearable technologies."
} | 2,100 |
24136711 | null | s2 | 4,102 | {
"abstract": "Elastin-like polypeptides (ELPs) are genetically encoded protein polymers that reversibly phase separate in response to stimuli. They respond sharply to small shifts in temperature and form dense microdomains in the living eukaryotic cytosol. For the first time, this communication illustrates how to tune the ELP sequence and architecture for either co-assembly or sorting of distinct proteins into microdomains within a living cell."
} | 108 |
39747054 | PMC11695776 | pmc | 4,105 | {
"abstract": "Photosynthesis harvests solar energy to convert CO 2 into chemicals, offering a potential solution to reduce atmospheric CO 2 . However, integrating photosynthesis into non-photosynthetic microbes to utilize one-carbon substrates is challenging. Here, a photosynthesis system is reconstructed in E. coli , by integrating light and dark reaction to synthesize bioproducts from one-carbon substrates. A light reaction is reconstructed using the photosystem of photosynthetic bacteria, increasing ATP and NADH contents by 337.9% and 383.7%, respectively. A dark reaction is constructed by designing CO 2 fixation pathway to synthesize pyruvate. By assembling the light and dark reaction, a photosynthesis system is established and further programmed by installing an energy adapter, enabling the production of acetone, malate, and α-ketoglutarate, with a negative carbon footprint of −0.84 ~ −0.23 kgCO 2 e/kg product. Furthermore, light-driven one-carbon trophic growth of E. coli is achieved with a doubling time of 19.86 h. This photosynthesis system provides a green and sustainable approach to enhance one-carbon substrates utilization in the future.",
"introduction": "Introduction Natural photosynthesis, consisting of light and dark reactions, converts solar energy and atmospheric CO 2 into biomass, which can be used as food, timber, and biofuels 1 – 4 . However, the large-scale implementation of natural photosynthesis faces significant challenges due to constraints, such as competition for agricultural and forestry resources vital to human survival, difficulties in processing cellulosic biomass, and uncertainties in climatic conditions 5 , 6 . Cyanobacteria and algae have harnessed their inherent photosynthetic capabilities to establish light-driven microbial cell factories, effectively addressing some of these constraints and enabling carbon-negative biomanufacturing 7 – 9 . Despite these advancements, new challenges have emerged, including the limited availability of synthetic biology toolkits, prolonged growth cycles, and the need to enhance productivity to meet industrial demands 10 . To overcome these challenges, new-to-nature photosynthesis system (NPS) has garnered significant interest by restructuring and mimicking the key structural elements and functions of natural photosynthesis, this approach is expected to revolutionize agriculture and significantly reduce the carbon footprint 11 – 13 . NPS have been proven to efficiently capture solar energy and convert CO 2 into valuable chemicals 14 and can be generally categorized into hemi-NPS and holo-NPS. Recently, hemi-NPS have been developed from the hybridization of photoelectrochemical devices 15 (e.g., artificial leaf 16 and photochemical diodes 17 ) with microbial cells to whole-cell photosensitization 18 , 19 . In hemi-NPS, natural metabolic pathways and multi-enzyme cascade reactions effectively convert simple feedstocks (e.g., CO 2 , H 2 , and N 2 ) into valuable chemicals 20 , 21 . Advances in synthetic biology have expanded the range of hemi-NPS products from small-molecule chemicals (e.g., acetate 22 , 23 , isopropanol 24 , butyrate, and threonine 25 ) to more complex products (e.g., carotenoids, poly β-hydroxybutyrate (PHB) 26 , and proteins 21 ). However, despite the relatively high product selectivity of hemi-NPS, they are constrained by sluggish charge transfer kinetics at the biohybrid interface 27 , biotoxicity, and the non-self-regeneration of photosensitizers 28 . To address these limitations, holo-NPS have attracted widespread attention due to their use of biogenic, genetically tractable, and stable components. Recent progress in holo-NPS includes the integration of proteorhodopsin (PR) into E. coli for light-driven ATP generation 29 , the insertion of a rhodopsin protein from Ustilago maydis into the vacuole membrane of S. cerevisiae to enhance heterotrophic metabolism 30 , 31 , the encapsulation of plant-derived photosynthesis systems into chondrocytes to increase intracellular ATP and NADPH levels for improved anabolism 32 , and the introduction of cyanobacteria into S. cerevisiae to establish endosymbiotic holo-NPS for cell growth 33 . Although these holo-NPS have successfully demonstrated bioenergetic and anabolic functions within cells, further enhancing the adaptability and tunability between the conversion efficiency of solar energy to metabolic energy and the biosynthetic efficiency of host cells is essential to fully realize the potential of holo-NPS. In this study, a new-to-nature photosynthesis system (NPS) comprising a light reaction, dark reaction, and energy adapter is developed and integrated into E. coli (Fig. 1 ). The light reaction is achieved by constructing a biogenic photosystem to generate intracellular ATP and NADH, while the dark reaction is established through a synthetic CO 2 fixation pathway. The energy adapter, consisting of an energy responder and a protein capacitor, is designed to dynamically match light and dark reactions. This system is further programmed and optimized to enable E. coli to utilize one-carbon substrates for the synthesis of acetone, malate, and α-ketoglutarate with a negative carbon footprint, as well as to support light-driven one-carbon trophic growth. Fig. 1 New-to-nature photosynthesis system in E. coli for one-carbon substrates utilization. E. coli photosynthesis system contains light reaction, dark reaction, and energy adapter. The light reaction converts light energy into metabolic energy, such as ATP and NADH by constructing a biogenic photosystem NPM*. Dark reaction utilizes CO 2 to synthesize central metabolite and further expands to the output of various bioproducts driven by the light reaction. An Energy adapter is installed to dynamically match light reactions and dark reactions. Abbreviations: hv, photon energy; e - , electron; CO 2 , carbon dioxide; CH 3 OH, methanol (as an electron sacrificial agent for NPM*); HCOOH, formate; IM, inner membrane; ETC, electron transport chain; NPM*, biogenic photosystem NuoK* + PufL + MgP (NuoK*, the mutant of NADH dehydrogenase complex subunit K; PufL, core protein of photosynthesis reaction center from Rhodopseudomonas viridis ; MgP, magnesium protoporphyrin IX); ATP/ADP, adenosine triphosphate/diphosphate; NADH/NAD + , nicotinamide adenine dinucleotide reduced/oxidized.",
"discussion": "Discussion In this study, a new-to-nature photosynthesis system was engineered to utilize one-carbon substrates. Firstly, a tailored light reaction was constructed to convert light energy into ATP and NADH, by constructing a biogenic photosystem NPM*. Secondly, a sustainable photosynthesis system was established for the synthesis of key central metabolites, such as pyruvate, by integrating the light and dark reactions to utilize one-carbon substrates. Finally, a programmable photosynthesis system was implemented by installing an energy adapter to enable the production of different chemicals, such as acetone, malate, and α-ketoglutarate, with a negative carbon footprint. This system was further optimized to achieve light-driven one-carbon trophic growth. Although a promising proof of concept remains incomparable to natural photosynthetic bacteria, this system provides new insights into the development of fully photoautotrophic E. coli cell factories capable of producing value-added bioproducts in the future. The tailored light reaction equips heterotrophic microbial cells with the ability to convert light energy into metabolic energy. Recently, three classical photosystems have been developed: (i) the natural photosystem in photoautotrophic microbes (e.g., cyanobacterial and microalgae) 39 , 40 ; (ii) the light-powered proton pump PR 41 , 42 ; (iii) photosensitive electron-source nanomaterials 14 , 18 . While the natural photosystem has been modified to enhance the performance of photoautotrophic microbes, further improvements are required to optimize their productivity of industrial applications 10 , 43 . Conversely, non-natural photosystems have been widely used to enhance the efficiency of microbial cell factories, but the challenges, such as photosensitizer biotoxicity and the biotic-abiotic interface effects remain significant obstacles to their advancement 20 , 28 . In our study, the light reaction was developed by restructuring the photosystem of photosynthetic bacteria, which exhibited excellent biocompatibility due to its biologically derived components. Moreover, NPM* in the light reaction was integrated into the ETC-harboring IM using the transmembrane mechanism of NuoK, which not only was bio-friendly to host cells but also improved the kinetics of electron transfer. Consequently, the electrons generated by NPM* were capable of regenerating NADH and contributing to the establishment of a proton gradient to drive ATP synthesis. However, potential toxicity from MgP under increased light intensity may limit the efficiency of light reactions. Future efforts should focus on the development of intelligent light intensity control circuits, which combining biosensors and real-time photosource devices, and the construction of intracellular detoxification modules by enhancing superoxide dismutase expression to overcome these limitations. In addition, establishing a standard operating procedure (SOP) for NPM*, including standardizing ETC performance and NPM* loading, will be crucial for constructing an efficient light reaction through iterative rounds of the Design-Build-Test-Learn cycle 44 . Furthermore, exploring the interaction between native energy metabolism and the tailored light reaction is essential. Understanding the process and mechanism of incorporating photogenerated electrons into the native ETC will facilitate the development of strategies to minimize transfer losses of photogenerated electrons. Lastly, optimal strategies, such as assembling light-harvesting antennas onto NPM* to expand its three-dimensional structure, will be critical to achieving a more efficient new-to-nature photosystem. A sustainable photosynthesis system serves as a carbon sink, enabling the utilization of one-carbon substrates with light energy. Currently, two types of NPS have been developed: (i) hemi-NPS, such as the Co-Pi-formate dehydrogenase (FDH) system 45 and Moorella thermoacetica /gold nanoclusters biohybrid system 46 ; (ii) holo-NPS, such as the chloroplast mimic system (encapsulating photosynthetic membranes and CETCH cycle in droplets) 47 and the cyanobacterial/yeast endosymbiotic system 33 . Although these NPS have been utilized for CO 2 fixation in cell growth and bioproduction, they exhibit several limitations: (i) hemi-NPS assembled in vitro lack the self-replication capability requeired for large-scale application; (ii) the continuous replication of whole-cell biocatalysts reduces the ratio of semiconductor material to biomass due to the absence of self-regeneration 28 ; and (iii) while the endosymbiotic system can enhance yeast growth through bioenergetic functions, its stability requires improvement for biosynthesis applications. In our study, a photosynthesis system was constructed in E. coli by coupling two bioheritable components: the light reaction and the dark reaction, demonstrating self-replication and sustainable bioproduction. This engineered E. coli with a sustainable photosynthesis system effectively utilized one-carbon substrates, laying a solid foundation for achieving carbon-negative biomanufacturing. Furthermore, compared to the previous iPRCC strategy 7 , the iPBRC strategy developed in this study offers unique advantages, including the ability to achieve photosynthesis and resting catalysis in an engineered strain, along with a broader capability for one-carbon substrate utilization. In the future, as part of the synthetic biology toolbox, the sustainable photosynthesis system can be engineered and adapted to different application scenarios with enhanced universality and stability. In addition, this sustainable NPS will serve as a novel model for transforming non-photosynthetic microbes into fully photoautotrophic microbes. To achieve this ambitious goal, several challenges must be addressed: (i) enhancing the efficiency of light energy harvesting and conversion for the tailored photosystem; (ii) improving the biosynthesis efficiency of the dark reaction ADRP to support cell growth by optimizing metabolic carbon flux; (iii) establishing an SOP for regulating and optimizing the global metabolic network of the NPS. To overcome these obstacles, efforts will focus on exploring more effective strategies, such as designing specialized photobioreactors to mitigate shading effect during high-density cultivation, developing light-harvesting antennas, reducing transfer losses of photogenerated electrons in the ETC, engineering key enzymes in the ADRP pathway, alleviating formaldehyde-induced DNA-protein crosslinking 48 , and enhancing the overall performance of the NPS through metabolic network model prediction and multi-omics joint analysis. A programmable photosynthesis system in E. coli enables versatile bioproduction by installing an energy adapter to customize the distribution of photogenerated electrons. Although NPS have been widely used in chemical synthesis, two major limitations have hindered their broader application: (i) NPS have predominantly been used to synthesize simple products, such as formate 45 and acetate 46 from CO 2 , without extending to the production of longer carbon-chain and more diverse compounds 28 ; (ii) while NPS have been employed to enhance biosynthetic efficiency through the upgrading photoelectrochemical materials and mitigation biotic-abiotic interface 20 , little attention has been given to strategic regulation of electron distribution to improve the performance of microbial cell factories. To address these bottlenecks, a programmable photosynthesis system was developed, capable of converting one-carbon substrates into a series of chemicals by rationally controlling electron distribution through an energy adapter. This system features user-defined functions and plug-and-play capabilities, serving as a foundational platform with multiple composability and extendibility, thereby facilitating the production of various biofuels and biochemicals. Future refinements in this programmable photosynthesis system will focus on the development of energy molecules-specific biosensors and energy levels-optimized oscillators. These advancements will enable the fine-tuning of the photosynthetic platform to meet the needs of a wide range of synthetic biology applications. The essence of nature has been effectively utilized in different new-to-nature research fields, leading to numerous remarkable achievements 13 . In this study, the new-to-nature photosynthesis system was developed. Future efforts to enhance the new-to-nature photosynthesis system should focused on the following aspects: (i) improving the light-harvesting efficiency of the photosystem; (ii) enhancing carbon flux within the dark reaction; (iii) optimizing the intelligent coordination of the energy adapter; (iv) minimizing crosstalk with native energy metabolism; (v) developing fine-tuning toolkits for metabolic energy levels. By addressing these aspects, the new-to-nature photosynthesis system provides a roadmap for transforming non-photosynthetic microbes into novel photosynthetic life forms, offering a green and sustainable solution for enhancing the utilization of one-carbon substrates in the future."
} | 3,886 |
23965677 | null | s2 | 4,106 | {
"abstract": "High shear stresses are known to trigger destructive bond-scission reactions in polymers. Recent work has shown that the same shear forces can be used to accelerate non-destructive reactions in mechanophores along polymer backbones, and it is demonstrated here that such mechanochemical reactions can be used to strengthen a polymer subjected to otherwise destructive shear forces. Polybutadiene was functionalized with dibromocyclopropane mechanophores, whose mechanical activation generates allylic bromides that are crosslinked in situ by nucleophilic substitution reactions with carboxylates. The crosslinking is activated efficiently by shear forces both in solvated systems and in bulk materials, and the resulting covalent polymer networks possess moduli that are orders-of-magnitude greater than those of the unactivated polymers. These molecular-level responses and their impact on polymer properties have implications for the design of materials that, like biological materials, actively remodel locally as a function of their physical environment."
} | 264 |
38390295 | PMC10883063 | pmc | 4,107 | {
"abstract": "Lowland meadows represent aboveground and belowground biodiversity reservoirs in intensive agricultural areas, improving water retention and filtration, ensuring forage production, contrasting erosion and contributing to soil fertility and carbon sequestration. Besides such major ecosystem services, the presence of functionally different plant species improves forage quality, nutritional value and productivity, also limiting the establishment of weeds and alien species. Here, we tested the effectiveness of a commercial seed mixture in restoring a lowland mixed meadow in the presence or absence of inoculation with arbuscular mycorrhizal (AM) fungi and biostimulation of symbiosis development with the addition of short chain chito-oligosaccharides (CO). Plant community composition, phenology and productivity were regularly monitored alongside AM colonization in control, inoculated and CO-treated inoculated plots. Our analyses revealed that the CO treatment accelerated symbiosis development significantly increasing root colonization by AM fungi. Moreover, the combination of AM fungal inoculation and CO treatment improved plant species evenness and productivity with more balanced composition in forage species. Altogether, our study presented a successful and scalable strategy for the reintroduction of mixed meadows as valuable sources of forage biomass; demonstrated the positive impact of CO treatment on AM development in an agronomic context, extending previous observations developed under controlled laboratory conditions and leading the way to the application in sustainable agricultural practices.",
"introduction": "Introduction In an agricultural context, management intensification is a major driver of biodiversity loss ( Sala et al., 2000 ; Foley et al., 2005 ; Culman et al., 2010 ). Despite their importance, lowland meadows are critically endangered habitats in many European countries, because of hydrological perturbation and land-use change leading to the decline of meadow cover area and distribution, and the alteration of their species composition ( Poschlod et al., 2005 ). The category of ‘agricultural grasslands’ includes silage and hay fields, pastures under intensive production, and semi-natural grasslands. Over the last decades, silage made from arable crops such as maize has become much more widely adopted in irrigated areas than hay production, due to economic reasons, with serious consequences on biodiversity at different trophic levels, such as high mortality of ground-nesting birds and resource removal for other taxa, especially pollinators ( Stoate et al., 2009 ). Furthermore, the intensive use of pesticides, herbicides, and fertilizers had a strong impact on soil biodiversity, causing cultivated varieties to become partially reluctant to the development of beneficial interactions with soil-borne microorganisms ( Duhamel and Vandenkoornhuyse, 2013 ). Moreover, humans significantly altered the composition of many natural plant communities through the deliberate or accidental introduction of exotic species ( Van der Putten et al., 2007 ; Milardi et al., 2020 ), reducing biodiversity and compromising ecosystem functionality ( Griffiths and Philippot, 2013 ; Agathokleous et al., 2020 ). Several studies reported that repeated monoculture cropping, the inclusion of non-mycorrhizal crops within rotation and fallowing affect mycorrhizal activity and decrease crop yields ( Baltruschat and Dehne, 1988 ; Hetrick et al., 1996 ; Douds et al., 1997 ; Arihawa and Karasawa, 2000 ; Harrier and Watson, 2004 ). In addition to their importance for biodiversity, lowland meadows also provide significant ecosystem services: water retention and filtration, forage production, soil protection from erosion and contribution to its fertility, and potential for carbon sequestration ( Hopkins and Holz, 2006 ; Stoate et al., 2009 ). Finally, lowland grasslands also have a significant aesthetic value and support recreation in the countryside ( Boval and Dixon, 2012 ). Besides its ecological implications, the biodiversity of lowland meadows also provides several benefits for farmers. Indeed, the presence of functionally different plant species improves forage quality and nutritional value. In this frame, French (2017) demonstrated that forage from species-rich grasslands contained more protein, phosphorus, potassium, and calcium than cereals and conventional hay. Moreover, higher biodiversity, especially in terms of functional dispersion and species evenness, enhances the productivity of plant communities and consequently reduces available space for the establishment of weeds and alien species, representing an effective and low-cost strategy for weed control ( Sanderson et al., 2012 ; Suter et al., 2017 ). For all these reasons, the reintroduction of lowland meadows has become a major goal in the last two decades, in particular in cattle farms where both animal health and dairy product quality take advantage of hay-based feeding. Moreover, grasslands management requires lower energy and fertilizer input than cereals, thus supporting more efficient, sustainable, and adaptable agricultural practices with a reduced environmental impact, especially in those farms where grasslands were replaced decades ago by cereal monoculture. Lastly, permanent grasslands constitute no tillage areas, with a major positive impact on the maintenance of the microbial communities in the soil ( Guldberg et al., 2022 ). When comparing the results of different agronomic techniques in restoring meadow biodiversity, Sengl et al. (2017) found that sod transplantation and hay transfer were more successful than seeding. However, sod transplantation requires the destruction of valuable grassland habitat, whereas hay transfer is often associated with low seed germination rate; furthermore, both approaches require the availability of source sites and are relatively expensive. As a consequence, the use of commercial seed mixtures remains the most convenient technique in highly productive areas, albeit its weak effectiveness in biodiversity restoration needs to be improved. This goal can be achieved by exploiting the potential of soil microbial biodiversity in influencing plant diversity in grasslands. Although the functional implications for restoration require further investigations, the soil communities of diverse grasslands tend to be dominated by decomposer fungal communities and mycorrhizal networks ( Bardgett, 1996 ; Smith et al., 2003 ; Walker et al., 2004 ). In particular, the latter are believed to play a key role in driving ecosystem processes, such as nutrient cycling and plant productivity, as well as controlling community composition and structure during the early phases of succession ( Walker et al., 2004 ). Arbuscular mycorrhiza (AM), involving root colonization by specialized soil fungi belonging to Glomeromycotina, represents the most widespread plant symbiosis ( Genre et al., 2020 ). Indeed, around 72% of plant species - including the vast majority of forage and crop plants - host AM fungi in their root tissues. By exploring a larger volume of soil, the extraradical mycelium grants roots a more efficient access to mineral nutrients (namely phosphorus and nitrogen) and water ( Smith et al., 2010 ). Furthermore, AM symbiosis increases plant tolerance to water stress and reinforces defense against pathogens ( Shi et al., 2023 ). In return, AM fungi are fed with a percentage of plant metabolites, such as sugars and lipids, that are essential for the completion of their life cycle, in a truly mutualistic relationship ( Smith and Read, 2008 ; Jiang et al., 2017 ; Keymer et al., 2017 ; Luginbuehl et al., 2017 ). In this frame, due to their broad host range, different AM fungi have been shown to provide different degrees of benefits to different host species, overall generating a complex and versatile exchange mechanism that influences the structure of plant communities ( van der Heijden et al., 2015 ) and has been likened to a biological market ( Wyatt et al., 2014 ). Generally, AM fungal diversity was observed to be positively related to plant species diversity and productivity, due to a relaxation of plant competitive interactions and to the promotion of subordinate species ( Bardgett, 1996 ; Walker et al., 2004 ). Moreover, mycorrhizas may promote seedling establishment with important advantages in the early stages of development of the plant community ( van der Heijden, 2004 ). Concerning forage species, evidence is accumulating that their symbiotic status is a basic requirement for sustainable feed production and any advance in the optimization of this symbiotic system may lead to an improvement in forage productivity and nutritional properties ( Baslam et al., 2014 ; Hack et al., 2019 ). Therefore, due to their ecological and nutritional functions, AM fungi must be seen as an important biotechnology in sustainable agriculture, leading to improved agricultural management of soil and crops ( Lanfranco et al., 2016 ) and eventually increasing the efficiency of lowland meadow restoration. Currently, the most commonly introduced change in soil management to promote AM associations has been to limit acknowledged harmful practices, such as deep tillage and fungicide use, and introduce AM fungal inocula in crop fields. The main drawback in this approach is related to the lack of information on how a commercial AM fungal strain is performing with each crop species and variety; how it adapts to local soil and climate conditions; how it competes with the native AM fungal community ( Douds et al., 2005 ; Gosling et al., 2006 ). Furthermore, due to the prolonged selection of crop cultivars for their productivity in highly fertilized soils (with rather limited attention to their symbiotic associations), many cultivated species are recalcitrant to engage in AM symbiosis and AM inoculation alone may have limited effects on their mycorrhizal status ( Duhamel and Vandenkoornhuyse, 2013 ). An innovative approach to address this problem has been to boost pre-symbiotic signaling by exogenously treating the plants with fungal molecules that promote symbiosis development. Such mycorrhizal factors (or myc-factors) are known to be released by symbiotic fungi and trigger cellular and molecular responses that accelerate symbiosis establishment ( Volpe et al., 2023 ). In this frame, short chain chito-oligosaccharides (COs) have been shown to be recognized as myc-factors in a wide range of host plants, including legumes and monocots ( Genre et al., 2013 ; Sun et al., 2015 ) and their use as promoters of AM establishment paved the way to possible applications in sustainable agriculture and pasture management ( Volpe et al., 2020 ; Volpe et al., 2023 ). In this research we tested the effectiveness of a commercial seed mixture in restoring a lowland mixed meadow in an area of the Po plain, where grasslands have been replaced by cereals for two decades. Furthermore, we evaluated the impact of a commercial AM inoculum combined with myc-factor treatment on the composition of the plant community and its productivity.",
"discussion": "Discussion The current study provides first evidence that the combined application of CO and a mycorrhizal inoculum during sowing of a mixed meadow promotes AM symbiosis under field conditions, at least in the first year of application, in line with previous studies in controlled laboratory conditions ( Volpe et al., 2020 ; Volpe et al., 2023 ), and has a major impacts on plant community. However, mixed meadow management had a positive impact, over time, on the activity of the native AM community also in the absence of any additional treatment. Previous studies have demonstrated the CO-dependent promotion of AM under controlled conditions ( Volpe et al., 2020 ). More recent investigations studies, carried out in the model legume Medicago truncatula , revealed that the observed acceleration of AM development in CO-treated plants was correlated with the stimulation of pre-symbiotic responses in the host root, including the regulation of gene expression and the triggering of cellular responses that are known to take place during early fungal colonization ( Volpe et al., 2023 ). Our current observation of a comparable promotion of AM colonization under field conditions confirms CO bioactivity and efficiency also in an agricultural context, short of the presence of natural uncontrollable environmental variables, and represents a major advancement toward the use of CO as biostimulants in sustainable agriculture. Boosting AM colonization, productivity and plant community composition In more detail, our results showed that the frequency of AM colonization in plant roots was significantly higher in the meadow treated with a combination of CO and a commercial microbial inoculum (MYC+CO) compared to both the untreated meadow (CTR) and the meadow treated only with the commercial inoculum (MYC), and this increase was most noticeable during the first months following the treatment (April 2017 sampling). This booster effect of CO application on AM development was not mirrored on the increase of aboveground biomass. A significantly higher productivity was in fact recorded in April 2017 for both MYC+CO and MYC meadow compared to control conditions, the higher average value of MYC+CO samples not being significantly different from the MYC samples. The increase in plant biomass production upon AM inoculation, known as the ‘growth effect’, is related to both the direct improvement of plant nutrition by AM fungi and - particularly in natural and agronomical ecosystems - the establishment of synergistic interactions with other beneficial microorganisms, such as plant-growth promoting rhizobacteria (PGPRs), nitrogen fixing and phosphate-solubilizing bacteria ( Raklami et al., 2019 ). Furthermore, a faster plant development and/or a greater vegetation density can be the consequence of the improved root system development ( Kalamulla et al., 2022 ) and better seedling establishment in inoculated fields ( van der Heijden, 2004 ; Zhang et al., 2012 ). Plant community composition was also affected by our treatments: MYC and MYC+CO meadows showed significantly different species assemblage and a significantly higher species evenness compared to control in April 2017. A lower percentage cover of grasses (especially Festulolium ), which instead dominated the control, was observed in both inoculated meadows, in favor of a higher cover of forb species, such as Medicago sativa and T. pratense . This observation is consistent with previous studies establishing that AM colonization tends to increase plant species diversity when the dominant species in the community is a weakly mycotrophic plant, such as annual species and C3 grasses (e.g., Festulolium ), by increasing the competitive ability of the subordinate species that generally are represented by perennial forbs and legumes such as M. sativa and T. pratense ( Karanika et al., 2008 ; Bahadur et al., 2019 ). Moreover, the increased belowground competitiveness of legume species may generate a positive feedback in the aboveground competition, especially in the case of M. sativa , whose extensive canopy can reduce light access by neighboring species ( Klabi et al., 2014 ). Weed suppression through increased functional dispersion represents an additional benefit to the multiple ecosystem services of forage mixtures for sustainable grassland production. Such benefits can arise from positive species interactions and complementary use of resources ( Nyfeler et al., 2011 ; Hoekstra et al., 2016 ), suggesting that high-yielding mixtures capture and transform increased amounts of resources into biomass ( van Ruijven and Berendse, 2005 ). Moreover, Suter et al. (2017) found that functionally diverse grass-legume mixtures can also have direct effects on plant community composition by reducing weed biomass and survival, and consequently the need for herbicide use, in particular when the mixture includes species of different rooting depth (as in the case of the shallow-rooted Lolium perenne and the deep-rooted Trifolium pratense ). Furthermore, the fast development of the sown species in the first months after sowing is critical to reduce weed establishment and reproduction by limiting available resources (light, water, and minerals) ( Weisberger et al., 2019 ), with a direct impact on the community composition over a longer period of time after meadow establishment. The observed differences in the plant community structure had important implications for forage quality, so that, during the second year of the study, when the three meadows showed the greatest differences in terms of species composition, we found a significantly higher pastoral value in MYC+CO compared to MYC and control. This finding was consistent with the higher contribution of legumes and the lower contribution of weeds to the aboveground biomass of the MYC+CO meadow. Indeed, legume species generally show a higher Index of Specific Quality (ISQ) for their productivity, palatability, and preference by livestock ( Cavallero et al., 2007 ). Furthermore, legumes enrich the forage protein content with positive effects on its quality ( French, 2017 ). A similar effect was observed also for the grass species Dactylis glomerata , which in our study was found to be significantly associated with the MYC+CO meadow ( French, 2017 ). Although we did not perform a chemical characterization of the forage, previous studies found increased P levels in forage from AM inoculated plants ( Smith et al., 2003 ; Chippano et al., 2021 ). Applicative perspectives AM fungal development is known to be subject to seasonal cycles that impact on spore germination and mycelial growth in the soil, as well as the colonization of host roots ( Jakobsen et al., 2003 ; Kemmelmeier et al., 2022 ). Under this respect, the temporal extension of this study (i.e., 24 months) allowed us to investigate the effect of AM inoculation and CO treatment over a markedly longer period of time compared to previous studies. In this frame, while the early boost in AM colonization of MYC+CO plant roots was remarkable, a significant effect was also evident during the July-October 2017 period, while after our second CO application by spray, AM colonization levels were constantly and significantly higher in MYC+CO compared to both MYC and CTR samples but did not show any booster effect. This pattern is in line with the promotion of symbiosis development by exogenous CO application in controlled conditions ( Volpe et al., 2020 ). Nevertheless, the observation of such a marked effect under field conditions - and over a period of several months after each treatment - is particularly significant and reinforces the conclusion that CO application has long term effects on AM symbiosis ( Volpe et al., 2023 ). The observed rise in AM colonization of MYC and CTR plants during the summer of the second year of this investigation (with root colonization of MYC plants reaching the same level as MYC+CO samples), warrants a distinct, yet equally significant, consideration. Most likely, this is the result of the revitalization of both native and inoculated AM propagules following the establishment of the mixed meadow after decades of monocultures ( Johnson et al., 2005 ; Fester and Sawers, 2011 ). This effect of plant biodiversity on soil microbial population is well known but does not weaken the usefulness of either AM inoculation or CO application: the combination of these treatments at sowing can in fact support the early development and stabilization of symbiotic associations in the delicate period of meadow establishment. Altogether, the combined impact of mixed sowing and mixed microbial inoculation on soil microbial activity - of which AM colonization was used here as a proxy - is very promising for regenerative and sustainable agricultural applications. In this scenario, the introduction of CO treatment has been a catalyst for AM development since the early months: a significant advantage for farmers, thanks to the positive effect of AM colonization on plant nutrition and health ( Johnson et al., 2005 ). Following this first study, focused on the plant community and a single group of beneficial microbes (AM fungi), it will now be very interesting to investigate the effect of microbial inoculation and CO treatment on the whole soil microbiota, through metagenomics analyses revealing the phylogenetic and functional composition of fungal and bacterial communities under each experimental condition. In this sense, it has already been demonstrated as the co-application of CO and AM fungi has an impact on the rhizosphere microecology, favoring the beneficial bacteria community and increasing soil microbial biomass carbon content ( Ma et al., 2023 ). An intriguing aspect to be clarified is the effect of CO-dependent AM promotion on rhizobial infection in legumes, which host both symbionts in a largely unexplored physiological and metabolic balance. Lastly, an analogous approach to the one we used can be developed for the restoration of natural ecosystems with grasslands, another promising field of application for AM symbiosis and plant growth-promoting microbes in general ( Singh Rawat et al., 2022 )."
} | 5,342 |
37854302 | PMC10580283 | pmc | 4,108 | {
"abstract": "The undesired spontaneous deposition and accumulation\nof matter\non surfaces, better known as fouling, is a problematic and often inevitable\nprocess plaguing a variety of industries. This detrimental process\ncan be reduced or even prevented by coating surfaces with a dense\nlayer of end-grafted polymer: a polymer brush. Producing such polymer\nbrushes via adsorption presents a very attractive technique, as large\nsurfaces can be coated in a quick and simple manner. Recently, we\nintroduced a simple and scalable two-step adsorption strategy to fabricate\nblock copolymer-based antifouling coatings on hydrophobic surfaces.\nThis two-step approach involved the initial adsorption of hydrophobic-charged\ndiblock copolymer micelles acting as a primer, followed by the complexation\nof oppositely charged-antifouling diblock copolymers to form the antifouling\nbrush coating. Here, we significantly improve this adsorption-based\nzipper brush via systematic tuning of various parameters, including\npH, salt concentration, and polymer design. This study reveals several\nkey outcomes. First of all, increasing the hydrophobic/hydrophilic\nblock ratio of the anchoring polymeric micelles ( i.e. , decreasing the hydrophilic corona) promotes adsorption to the surface,\nresulting in the most densely packed, uniform, and hydrophilic primer\nlayers. Second, around a neutral pH and at a low salt concentration\n(1 mM), complexation of the weak polyelectrolyte (PE) blocks results\nin brushes with the best antifouling efficacy. Moreover, by tuning\nthe ratio between these PE blocks, the brush density can be increased,\nwhich is also directly correlated to the antifouling performance.\nFinally, switching to different antifouling blocks can increase the\ninternal density or strengthen the bound hydration layer of the brush,\nleading to an additional enhancement of the antifouling properties\n(>99% lysozyme, 87% bovine serum albumin).",
"conclusion": "4 Conclusions and Outlook The antifouling\nperformance of the two-step adsorbed zipper brush\nwas optimized via systematic tuning of various parameters, including\npH, salt concentration, and polymer design. By using a dissolving\nmedium with a neutral pH and a low ionic strength of 1 mM, brushes\nwith improved antifouling properties were obtained. Adsorption of\npolymeric micelles with a higher PS/PAA block ratio and a smaller\nPAA corona ( i.e. , PS 81 - b -PAA 81 ) resulted in the most densely packed, uniform,\nand hydrophilic primer layers, as these micelles had to overcome a\nsmaller deformation energy in order to adsorb. By tuning the PE block\nratio, the number of diblock copolymers binding to a single PAA chain\ncould be maximized (PAA/PDMAEMA ≈ 3), resulting in zipper brushes\nwith the highest grafting density and wettability, which enabled an\nincreased suppression against BSA adsorption. Finally, changing the\nantifouling block from linear PEG to comb-like POEGMA or zwitterionic\nPMPC led to a further enhancement of the antifouling properties, presumably\ndue to the increased internal density of the POEGMA brush and the\nstrong electrostatically induced hydration layer of the PMPC brush.\nThe latter specifically showed a superior antifouling performance\n(>99% lysozyme, 87% BSA), which can be attributed to its higher\nsurface\ncoverage and uniformity as well as its significantly hydrated character. Overall, the optimization strategies employed have led to a low-density\nPMPC-based zipper brush with a considerable antifouling efficacy,\nwhich, combined with its straightforward application strategy, could\nbecome an attractive contender for future antifouling coatings produced\non hydrophobic surfaces. Additionally, the incorporated salt- and\npH-sensitive PE complex may endow the adsorbed PMPC brush with a triggered\nreversibility property, allowing easy regeneration of the (contaminated)\nbrush without the need of tedious cleaning protocols: rinsing with\neither a low/high pH solution or a high ionic strength solution should\nfacilitate the disintegration and removal of the top complexed layer.\nSubsequent regeneration of the brush via a one-step\ncomplexation procedure should permit the preparation of a new, fully\nfunctional antifouling coating. Further research is required to investigate\nthe potential triggered reversibility of these two-step adsorbed zipper\nbrushes as well as their stability under varying solvent conditions\n( e.g. , pH, salinity, temperature, and static/dynamic\nflow) over an extended period of time. Finally, alternative strategies\nneed to be explored to further enhance the grafting density and reach\ncharge neutrality, as these factors ultimately determine the antifouling\nefficacy of the brush.",
"introduction": "1 Introduction Polluted drinking water,\nincreasing shipping costs, and frequent\noccurrences of healthcare-associated infections are among the many\nissues primarily caused by one phenomenon: fouling. 1 − 3 Fouling involves\nthe uncontrollable adhesion and accumulation of unwanted material\nfrom the surroundings onto surfaces. 4 Due\nto the many types of fouling, including organic, inorganic, and biological,\nall with their own size, shape, and composition, it presents an inevitable\nand complex challenge in many fields. 4 , 5 For the maritime\nindustry alone, the estimated cost for transport delays, hull repairs,\ncleaning, and general maintenance caused by biofouling is set to 150\nbillion dollars annually, 2 while in the\npublic health domain, more than 45% of the hospital-contacted infections\ncan be attributed to biofilm-infected medical devices ( e.g. , catheters). 6 Polymers are promising\ncandidates to reduce or even prevent fouling,\nas they are affordable, easy to process, exhibit a wide-range efficacy\nagainst an array of fouling agents, and their functionalities are\nreadily modified to suit the application of interest. 4 , 7 , 8 Specifically, when they are densely\nend-grafted to a surface, either chemically or physically, the obtained\npolymer brush can provide both a steric and energetic barrier to prevent\nfouling agents from adsorbing. 9 − 12 Over the past decade, many polymer brush systems\nhave been developed, including hydrophilic, hydrophobic, zwitterionic,\nand amphiphilic brushes, which have been discussed extensively in\nnumerous reviews. 4 , 13 − 16 However, these systems are predominantly\nfabricated on hydrophilic and charged surfaces, generally via covalent\ngrafting procedures, which are not easily extended to hydrophobic\nsurfaces. Contrary to their hydrophilic counterparts, hydrophobic\nsubstrates are less prone to chemical interactions and require more\nmodification steps ( e.g. , surface activation, ultraviolet\n(UV) cross-linking, hydrosilylation) before a dense and stable coating\ncan be produced. 17 − 20 The lack of efficient solutions toward protecting said surfaces\nleads to significant complications, as they are essential for many\nfouling-prone applications within the medical sector ( e.g. , catheters, vascular grafts, prosthetics, and implants), 13 , 19 , 21 , 22 maritime transport ( e.g. , painted ship hulls), 23 and industry ( e.g. , pipelines\nand packaging). 24 Furthermore, the inevitable\nfouling process limits the lifetime of any antifouling coating, which\nin the case of covalently grafted coatings necessitates the use of\nexpensive and environmentally unfriendly cleaning protocols. 25 − 28 Efforts to overcome these substrate-specific and nonrenewable\nissues\nled to the development of the “zipper brush” approach. 29 , 30 In this strategy, renewable and dense antifouling brushes were generated\non hydrophobic surfaces by complexing diblock copolymers comprising\na charged anchoring block and a neutral antifouling block to a preadsorbed\nand oppositely charged polyelectrolyte (PE) brush. The grafting density\nof the formed neutral “zipper brushes” could be controlled\nby tuning the chain length and grafting density of the PE brush as\nwell as by the chain length of the charged anchoring block. Moreover,\nconsidering the electrostatic nature underlying the formation of these\nbrushes, the complexed brush could be disintegrated and released by\nsimply adding salt or by varying the pH, thereby restoring the original\nPE brush, which could subsequently be recoated in a similar fashion.\nOne major downside accompanying this promising approach is the use\nof a time-consuming and scale-limiting Langmuir–Blodgett (LB)\ntechnique, which prevents its translation to large-scale applications. 29 , 30 To build on this work, we recently introduced a scalable two-step\nadsorption strategy to fabricate zipper brushes on polystyrene surfaces. 31 In this approach, we exchanged the scale-limiting\nLB-attached PE brush with an adsorbed layer of diblock copolymer micelles,\nconsisting of a hydrophobic core and a weak PE corona ( i.e. , the primer). This negatively charged primer was subsequently complexed\nwith another diblock copolymer, comprising an oppositely charged weak\nPE block and a neutral hydrophilic block, to form an antifouling polymer\nbrush. While these adsorption-based zipper brushes managed to effectively\nsuppress the attachment of positively charged lysozyme, they could\nnot prevent the adhesion of negatively charged bovine serum albumin\n(BSA). Hence, albeit a highly promising strategy, foulants could still\nadhere to the adsorbed brush, which can occur in three ways: (i) adsorption\non top of the brush; (ii) adsorption within the brush; and (iii) penetration\nthrough the brush and adsorption onto the substrate. 11 Hence, by minimizing the distance between tethered chains\n(high grafting density), increasing the distance between the substrate\nand foulant (sufficient brush thickness), eliminating any electrostatic\ninteractions (charge neutrality), and/or strengthening the bound hydration\nlayer (hydrophilicity), these modes of adsorption can be reduced.\nMany parameters such as the pH, salt concentration, and polymer design\ncan considerably affect the aforementioned brush characteristics and,\ntherefore, present the perfect tool to tune the antifouling properties. Here, we demonstrate a significant enhancement of the antifouling\nefficacy of the previously established adsorption-based zipper brush\nby investigating these parameters ( Scheme 1 ). The effect of each of these parameters\non the adsorption kinetics, surface topography, thickness, grafting\ndensity, and wettability of the resulting primer layers and zipper\nbrushes, as well as the antifouling capability against two fouling\nagents ( i.e. , lysozyme and BSA), was investigated\nusing a combination of techniques, including quartz crystal microbalance\nwith dissipation (QCM-D), atomic force microscopy (AFM), ellipsometry,\nand contact angle (CA) measurements. Scheme 1 Schematic Representation\nof the Adsorption-Based Zipper Brush Obtained\nvia a Two-Step Adsorption Strategy That Involves the Initial Adsorption\nof Negatively Charged PS- b -PAA Micelles, Followed\nby the Complexation of Oppositely Charged and Antifouling PDMAEMA- b -R Diblock Copolymers (R = PEG, POEGMA, or PMPC) The zipper brush characteristics\n( i.e. , grafting density, thickness, wettability,\nand charge) can be optimized by tuning various parameters, including\npH, salt concentration, polymer block ratios, and the nature of the\nantifouling block.",
"discussion": "3 Results and Discussion 3.1 Coating Formation The adsorption\nkinetics of the previously established adsorption-based zipper brush\nare most easily explained via a schematic QCM-D graph ( Figure 1 ). 31 In QCM-D, two parameters are simultaneously recorded: the frequency\nresponse (Δ f ), which is related to the mass\nadsorbed, and the change in energy dissipation (Δ D ), representing the rigidity of the adsorbed layer. When the dissipation\nis (close to) zero, the adsorbed polymer film is relatively rigid,\nbut when the dissipation increases, it indicates the formation of\na more viscous and hydrated layer. Figure 1 Schematic QCM-D graph illustrating the\nadsorption kinetics of the\npreviously established adsorption-based zipper brush, involving the\nsuccessive adsorption of PS- b -PAA micelles (step\n1) and PDMAEMA- b -PEG diblock copolymer (step 2).\nQCM-D records the frequency response (Δ f , blue)\nrelated to the mass adsorbed, as well as the change in energy dissipation\n(Δ D , red) representing the rigidity of the\nformed polymer coating. Here, the kinetics of both adsorption steps\ncan be described by a fast adsorption regime, an equilibrium regime,\nand subsequent removal of weakly attached material during rinsing. Prior to the two-step adsorption protocol, the\ngold QCM-D sensors\nwere rendered hydrophobic by spin-coating a polystyrene thin film\non top (∼40 nm). The PS- b -PAA diblock copolymers\nwere dispersed in ethanol, a selective solvent for PAA, which facilitated\ntheir self-assembly into micelles, consisting of a hydrophobic PS\ncore and a negatively charged PAA corona, as evidenced by DLS ( Figure S11 and Table S5 ). The first step involves\nthe adhesion of these self-assembled PS- b -PAA micelles,\nwhich is marked by three distinct regimes ( Figure 1 , step 1): (i) an initial rapid adsorption\nof micelles to the PS-coated sensor (Δ f <\n0), followed by (ii) an adsorption equilibrium (plateau) as the approaching\nmicelles have to overcome an osmotic barrier generated by formerly\nadsorbed micelles (Δ f = 0), and finally (iii)\nmass loss of loosely attached or unbound micelles when rinsed with\nthe reference solution (Δ f >\n0). While undetectable in QCM-D, it is assumed that micelle adsorption\ninvolves initial deformation of the corona, which is necessary to\nbring the hydrophobic core into contact with the surface to form a\nstrong bond; a phenomenon that has been observed before. 32 , 33 During rinsing, the dissipation moves back to zero, suggesting the\nformation of a rigid PS- b -PAA primer. Before the\nsecond adsorption step, the reference solution is switched to buffer.\nThe resulting frequency and dissipation shifts are predominantly related\nto a change in medium viscosity and density, but it also marks the\nslight hydration of the primer by bound water ( i.e. , dynamic mass). 34 Once a stable baseline\nis achieved, the PDMAEMA- b -PEG copolymer is added\nto the system ( Figure 1 , step 2). The kinetics of this complexation step can once again\nbe described by a fast adsorption regime, an equilibrium regime, and\nsubsequent removal of weakly complexed material. The final rinsing\nstep is generally characterized by a minor frequency change, which\nimplies a strong interaction between the two complexed polymer layers.\nAt low salt concentrations, the complexation step is defined by a\npositive dissipation shift, emphasizing the viscous and hydrated nature\nof the final zipper brush. Yet, at higher salt concentrations, a negative\ndissipation shift is often observed, which could be explained by a\nloss of flexibility and/or the release of bound counterions and water\nmolecules when the PDMAEMA- b -PEG copolymers penetrate\nand complex to the stretched out PAA chains. 35 For reference, a complete QCM-D data set including the adsorption,\ncomplexation, and antifouling steps of the most well-established PEG-based\nzipper brush can be found in the SI ( Figure S12 ). However, for the purpose of clarity, all QCM-D graphs included\nin the main text only consider the fifth harmonic overtone. 3.2 pH The zipper brush formation is\ncomplete after complexation between two weak PE blocks: the negatively\ncharged PAA block (p K a = 4.5) 36 of the primer and the oppositely charged PDMAEMA\nblock (p K a = 7.8) 37 of the complexing copolymer. While strong polyelectrolytes have\na fixed degree of dissociation and are essentially always charged,\nthe net charge of these two weak polyelectrolytes is strongly determined\nby the pH. 7 , 38 Hence, the pH must be carefully tuned in\norder to maximize the charge density on both blocks, thereby strengthening\nthe complex and potentially enabling the formation of a charge-neutral\nbrush via full charge compensation. Here, it is important to be aware\nof charge regulation: when two weakly charged polyelectrolytes complex,\nthey may mutually induce further charging. 39 , 40 To investigate the effect of pH on the complexation behavior\nand antifouling performance of the adsorbed zipper brushes, the two-step\nadsorption procedure was performed in phosphate buffers of varying\npH (pH 6 to 8), but with a constant salt concentration (10 mM) and\nby using only one combination of diblock copolymers (PS 81 - b -PAA 81 with PDMAEMA 29 - b -PEG 90 ). The minimum pH was set at pH 6, as\nboth PE blocks should have a similar degree of dissociation at this\npH, based on their dissociation constants. 30 According to the obtained QCM-D data ( Figure 2 a), complexation between the PE blocks is\nmost efficient at pH 6, as evidenced by the significant net frequency\nshift. At this pH, both blocks are sufficiently charged, which explains\nthe substantial complexation driving force seen. At a higher pH, the\nelectrostatic interaction seems weakened, indicated by a minimized\ndecrease in the frequency shift. Figure 2 QCM-D graphs showing the effect of (a,\nb) pH and (c, d) ionic strength\non the complexation behavior and antifouling performance of the formed\nzipper brush coatings. The complexation of PDMAEMA 29 - b -PEG 90 diblock copolymers to preadsorbed PS 81 - b -PAA 81 was followed in situ in (a) 10 mM phosphate buffers of varying pH and\nin (c) pH 7 phosphate buffers of varying ionic strength. (b, d) Antifouling\nperformance of the obtained zipper brushes, tested against BSA at\na constant pH and ionic strength (pH 7, 10 mM). Due to the pH dependence of charged BSA (pI 4.5), 41 it was decided to first equilibrate all brushes\nin pH 7\nbuffer after which the antifouling performance was tested and assessed.\nInterestingly, the efficiency of complexation does not necessarily\ndictate its antifouling performance ( Figure 2 b): adhesion of negatively charged BSA is\nminimized for the zipper brush formed at pH 7. However, one has to\nkeep in mind that a change in pH can affect many polymer properties,\nincluding the charge density, solubility, chain flexibility, and conformation.\nAll of these factors will weigh in when complexing to the primer and\nwill determine its antifouling efficacy. For instance, a too high\nadsorption of PDMAEMA- b -PEG copolymer at pH 6 could\nlead to an excess of positive charge in the final coating, which subsequently\npromotes BSA adsorption. Since the adsorbed zipper brush obtained\nat pH 7 possessed the\nbest antifouling efficacy, all successive zipper brushes were produced\nat this optimal pH. 3.3 Salt Concentration Salt concentration\npresents another parameter that determines the strength of complexation\nbetween PAA and PDMAEMA. While salt ions are essential to facilitate\nproper dissociation of the respective weak polyelectrolytes, the driving\nforce for their complexation decreases at higher ionic strengths,\nas the entropy gain upon the release of their counterions is reduced. 7 , 42 Hence, the ionic strength of the dissolving medium must be carefully\nselected. To investigate the effect of salt on the complexation\nbehavior and antifouling performance of the adsorbed zipper brushes,\nthe two-step adsorption procedure was performed in phosphate buffers\nof varying ionic strength (1 mM to 1 M), but with a constant and optimized\npH of 7 and by using only one combination of diblock copolymers (PS 81 - b -PAA 81 with PDMAEMA 29 - b -PEG 90 ). According to the QCM-D data,\ncomplexation appears to be most efficient at the lowest ionic strength\nof 1 mM, as was expected ( Figure 2 c). At the highest salt concentration of 1 M, complexation\nis completely inhibited by a significant screening of charges, preventing\nthe proper formation of a zipper brush. 42 Due to an increased screening of the negatively charged BSA\nat\nhigher ionic strengths, it was decided to first equilibrate all brushes\nin 10 mM buffer, after which the antifouling performance was tested\nand assessed. Interestingly, the efficiency of complexation also translates\nto the antifouling performance of the resulting coatings ( Figure 2 d): zipper brushes\nformed at lower ionic strengths can more effectively suppress the\nadhesion of BSA. Surprisingly, even though complexation seemed hindered\nat a 1 M salt concentration, BSA was not completely repelled by the\nremaining like-charged primer. This phenomenon has been studied before\nby de Vos et al., in which they concluded that the main driving force\ncan be attributed to charge regulation, suggesting that the protein\ncan reverse its charge in the vicinity of a like-charged brush. 43 Hence, the best-performing zipper brushes\nare produced at neutral\npH and at a low ionic strength of 1 mM. 3.4 Block Ratio and Block Length Molecular\nweight and composition represent two other parameters that allow control\nover the final grafting density and thickness of the brush. In this\nsection, we study how a change in block ratio or length can affect\nthe adsorption kinetics, surface topography, thickness, and wettability\nof the resulting primer layers and zipper brushes. For the sake of\nclarity, this section is divided into two parts, initially focusing\non the optimization of the adsorbing diblock copolymer followed by\nthe complexing one. 3.4.1 Adsorbing Diblock Copolymer: PS- b -PAA Regarding the adsorbing PS- b -PAA polymeric micelles, a correct balance between the hydrophobic\nanchoring core and the hydrophilic extending corona is crucial to\nmaximize the film density while simultaneously providing sufficient\nstability. 12 , 44 It is hypothesized that a higher\nPS/PAA block ratio would lead to stronger anchoring of the layer because\nof the larger hydrophobic PS core, while a lower block ratio ( i.e. , longer PAA chains) would enhance the complexation\nto PDMAEMA- b -PEG diblock copolymers in the second\nstep. To investigate the influence of the PS/PAA block ratio and PAA\nblock length of the PS- b -PAA micelles on the properties\nof the adsorbed primer, four different diblock copolymers were compared:\nPS 81 - b -PAA 81 , PS 32 - b -PAA 100 , PS 27 - b -PAA 287 , and PS 27 - b -PAA 436 , with PS/PAA block ratios of 1.00, 0.32, 0.09, and 0.06,\nrespectively. The adsorption of the self-assembled polymeric\nmicelles was monitored in situ by means of a QCM-D\n( Figure 3 a). Irrespective\nof the PS/PAA block ratio, each copolymer rapidly adsorbs to the PS-coated\nsensor surface, transforming into a relatively rigid film after rinsing\n(Δ D ≈ 0). An increased PAA chain length\n(PAA 287 , PAA 436 ) endows the coating with a slightly\nmore viscous character, which can be explained by the lengthy and\nhydrated PAA chains extending outward into the solution. The fitted\nwet thickness corroborates this finding ( Table S6 ): considering the copolymers with (almost) identical PS\nblock lengths, a longer PAA block leads to an increased wet thickness.\nInterestingly, at first glance, a change in the block ratio does not\ninvoke a clear trend in the amount of mass adsorbed, as seen from\nthe relatively indistinct frequency shifts after rinsing. However,\nwhen compensating for the difference in unit mass for each type of\ncopolymer, the frequency shifts now represent the relative number\nof polymer units adsorbing to the surface rather than its total mass\n( Figure 3 b). From this\ngraph, the efficiency of binding becomes clear: a higher PS/PAA block\nratio ( i.e. , a smaller PAA corona) facilitates the\nadsorption of more micelles to the surface. This finding is consistent\nwith the literature: for the core to adsorb, the corona must be compressed\nand deformed. This energy barrier is easier to overcome when the corona\nis small. 45 , 46 Figure 3 Data displaying the effect of the PS/PAA block\nratio and PAA block\nlength on the adsorption behavior and layer characteristics of the\nformed primers. (a) QCM-D graph showing the in situ formation of the PS- b -PAA primer layers. (b) Weight-normalized\nQCM-D graph in which the frequency is normalized by the molecular\nweight ratio, illustrating the relative number of micelles adsorbing\nto the surface. (c) Tapping mode AFM height images of the adsorbed\nPS- b -PAA primer layers. The corresponding phase images\nand cross-sectional profiles are available in the SI ( Figure S14 ). The difference in binding efficiency also manifests\nitself in the\nobtained morphologies, as seen in AFM ( Figure 3 c). The adsorbed PS 81 - b -PAA 81 and PS 32 - b -PAA 100 primer layers with the highest PS/PAA block ratio\nand smallest PAA corona are characterized by a relatively dense and\nhomogeneous micellar topography, while a low-density, nonuniform film\nis obtained for adsorbed PS 27 - b -PAA 436 . Hence, the surface density increases with an increased\nblock ratio. The dry thickness, grafting density, and surface roughness\nfollow accordingly ( Table S6 ): a higher\nblock ratio increases the dry film thickness and grafting density\nand minimizes the surface roughness. It is worth mentioning that all\nprimer layers exhibited an increased wettability (68–74°)\nwith respect to the hydrophobic PS substrate (93°), resembling\nthat of a PAA-based film (57–73°). 47 − 49 This confirms\nthe anticipated conformation of the adsorbed micelles: the PS cores\nadsorb to the surface, forcing the PAA chains to stretch outward.\nMoreover, since an increased PS/PAA block ratio facilitates micelle\nadsorption, the surface becomes enriched by a greater number of micelles\n( i.e. , a higher concentration of PAA at the interface),\nresulting in a (slightly) improved wettability of the primer at increased\nblock ratios ( Table S6 ). This will facilitate\ncomplexation to the second (antifouling) diblock copolymer. Overall, it can be concluded that PS- b -PAA micelles\nwith a higher PS/PAA block ratio ( i.e. , a smaller\nPAA corona) produce the most densely packed, uniformly distributed,\nand hydrophilic layers, and PS 81 - b -PAA 81 was therefore selected for the successive experiments. 3.4.2 Complexing Diblock Copolymer: PDMAEMA- b -PEG Since the block ratio has been optimized\nfor the adsorbing diblock copolymer (PS 81 - b -PAA 81 ), the same should be established for the complexing\none: PDMAEMA- b -PEG. According to data reported previously\nby de Vos et al. concerning zipper brushes, it is expected that the\nnumber of diblock copolymers complexing to the preadsorbed PS 81 - b -PAA 81 primer is determined\nby full charge compensation between the charges present. 29 , 30 As a consequence, it is possible to control the grafting density\nof the final brush by tuning the PE block ratio between PAA and PDMAEMA:\nif the PDMAEMA block is (much) smaller in length than the PAA chains\n(PE block ratio >1), multiple PDMAEMA blocks can bind to a single\nPAA chain, thereby increasing the grafting density and enhancing its\nantifouling performance. 11 , 29 , 30 On the contrary, a complexing block that is too small would lack\nsufficient adsorption energy to produce a stable final coating. To explore this maximization of grafting density, four PDMAEMA x - b -PEG 90 diblock\ncopolymers with varying PDMAEMA block lengths ( x =\n29, 53, 84, and 114) were complexed to the PS 81 - b -PAA 81 primer using the optimized buffer conditions\n(pH 7, 1 mM) ( Figure 4 a). The corresponding PE block ratios are 2.8, 1.5, 1.0, and 0.7.\nOnce the copolymer reaches the primer, complexation occurs rapidly\nand stabilizes almost instantaneously, independent of the PE block\nratio. The negligible change in frequency during rinsing and the net\npositive dissipation shift suggest the formation of a strongly bound\nand hydrated zipper brush. The efficiency of complexation, however,\nis strongly correlated to the chosen block ratio, which is best illustrated\nby the weight-normalized graph of Figure 4 b: decreasing the PDMAEMA block length increases\nthe efficiency of binding, which would suggest an increase in the\ngrafting density. Figure 4 Data displaying the effect of the PE block ratio on the\ncomplexation\nbehavior and layer characteristics of the formed zipper brush coatings.\n(a, b) QCM-D graphs showing the in situ complexation\nof the PDMAEMA x - b -PEG 90 diblock copolymers to the preadsorbed PS 81 - b -PAA 81 primer (pH 7, 1 mM) (a) before and (b)\nafter normalizing the frequency by molecular weight ratio. (c) Tapping\nmode AFM height images of the adsorbed PEG-based zipper brush coatings.\nThe corresponding phase images and cross-sectional profiles are available\nin the SI ( Figure S15 ). Depending on the PDMAEMA block length, the obtained\nbrushes were\neither characterized by a too low grafting density to be defined as\na true “brush”, or were found to be within the mushroom-to-brush\ntransition regime, which occurs for grafting densities higher than\n0.05 nm –2 ( Table S7 and Section 2 ). The AFM height images clearly depict an increase in surface\ncoverage when complexing to copolymers with smaller PDMAEMA block\nlengths ( i.e. , higher PE block ratios) ( Figure 4 c). Additionally,\na higher PE block ratio increases the final film thickness and grafting\ndensity, minimizes surface roughness, and improves the wettability\n( Table S7 ). The zipper brush containing\nthe smallest PDMAEMA block ( x = 29) has a noticeably\nlower contact angle (52.4°) than the other three zipper brushes\n(63.3–67.5°), which implies that more PEG chains are positioned\nat the interface, thereby corroborating the aforementioned hypothesis\nof having a higher grafting density. Still, all zipper brushes exhibited\nonly a slightly increased hydrophilicity with regard to the PS- b -PAA primer, rather representing a PDMAEMA film (65°) 50 than a PEG-based film (36–39°). 51 In our previous work, it was hypothesized that\nthe root cause for this low wettability could be related to an incorrect\nconformation of several PDMAEMA- b -PEG copolymer chains\nduring complexation, where PEG chains interact with the preadsorbed\nPAA chains via hydrogen bonding, thereby positioning the positively\ncharged PDMAEMA chains at the interface. 31 , 52 On the other hand, none of the brushes managed to attain full charge\ncompensation ( Table S7 ), indicating that\nfree PAA chains (θ = 57–73°) may still dominate\nthe interface, which provides another explanation for the relatively\nhigh contact angles seen. In fact, the calculated charge compensation\nof the current brushes\nis unexpectedly low compared to previous work on zipper brushes reported\nby de Vos et al. in which they showed complete charge compensation. 29 , 30 We believe there are two possible explanations for this discrepancy\nin charge compensation. First of all, desorption processes may occur\nduring the complexation step: if the electrostatic interaction between\npreadsorbed PS- b -PAA and oppositely charged PDMAEMA- b -PEG is sufficiently strong, it may initiate their release\nfrom the surface into solution. This process is indiscernible in QCM-D\nsince desorption will be a relatively minor process compared to the\nsimultaneously occurring complexation of chains. As a consequence,\nthe number of PS- b -PAA chains available for complexation\nis effectively lower than the initially calculated grafting density\nof the primer would suggest. This would also explain the relatively\nsmall increase in the film thickness after complexation, measured\nby ellipsometry. In other words, the thickness of the second layer\nmay in reality be appreciably larger than the specified value, which\nconsequently equals a charge compensation higher than currently indicated.\nMoreover, ellipsometry may fail to accurately determine the dry thickness\nof the coating: to properly fit the data, the software assumes a homogeneous\nthin film, which is an incorrect assumption regarding the rough coatings\nas evidenced by AFM ( Figure 4 c and Table S7 ). Due to the unreliability\nof the employed methods and calculations, it was decided to neglect\nfurther assessment of charge compensation for all experiments discussed\nonward. Finally, the antifouling performance of each zipper\nbrush was tested\nagainst negatively charged BSA ( Figure 5 ). None of the adsorbed zipper brushes were able to\nfully suppress its adhesion (Δ f ≠ 0),\nwhich could be ascribed to an insufficient brush density or uniformity\nand/or the presence of residual charge. However, protein attachment\nwas more effectively reduced for zipper brushes containing smaller\nPDMAEMA blocks ( i.e. , having a relatively higher\ngrafting density). Figure 5 QCM-D graph presenting the antifouling performance of\nthe adsorbed\nPEG-based zipper brush coatings tested against BSA (pH 7, 1 mM). Hence, by tuning the PDMAEMA block length ( i.e. , the PE block ratio), the number of blocks binding\nto a single PAA\nchain can be controlled, which is directly correlated to the acquired\ngrafting density and, therefore, its antifouling performance. 3.5 Choice of Antifouling Block Even\nthough the adsorbed PEG-based zipper brush had been optimized considerably\nthrough tuning of the pH, salt concentration, and polymer block ratios,\nit still resulted in substantial attachment of BSA. The final optimization\nstrategy therefore involved switching to a different antifouling block\nof comparable composition ( i.e. , block ratio and\nlength) ( Figure 6 ).\nWhile PEG has been considered the golden standard for decades, owing\nto its charge-neutral and hydrated character, 53 , 54 poly(oligo(ethylene glycol) methyl ether methacrylate) (POEGMA)\npossesses similar properties, but with a bulkier comb-like architecture.\nThis could enhance the internal brush density to generate an even\nmore impenetrable layer. 55 − 58 Alternatively, zwitterionic poly(2-methacryloyloxyethyl\nphosphorylcholine) (PMPC) can strongly bind eight water molecules\nper monomer unit (instead of one for PEG) and its hydration shell\nis formed by ion-dipole interactions, which are much stronger than\nhydrogen bonds, therefore creating a stronger energetic barrier toward\napproaching foulants. 13 , 53 , 59 Hence, both POEGMA- and PMPC-based brushes may demonstrate an enhanced\nbarrier against fouling relative to that of the PEG-based brush. Figure 6 Schematic\nrepresentation of the utilized antifouling diblock copolymers\nand the corresponding adsorbed zipper brushes, including (a) PDMAEMA- b -PEG, (b) PDMAEMA- b -POEGMA, and (c) PDMAEMA- b -PMPC. The diblock copolymers have comparable compositions\n( i.e. , block ratio and length) but differ in the\nexcluded volume and ionic nature. The complexation of each diblock copolymer to the\nPS 81 - b -PAA 81 primer was monitored in situ by using QCM-D ( Figure 7 a). In contrast to the quick complexation\nand stabilization of the PEG-containing polymers, the POEGMA- and\nPMPC-based polymers required a longer time to complex and equilibrate,\nas evidenced by the slow increment in frequency over time. For POEGMA,\nthe rate of complexation could be impeded by the increased steric\nhindrance induced by its bulky comb-like architecture, while for PMPC,\nit could be related to the thermodynamically unfavorable disruption\nof the electrostatically induced hydration shell accompanying it.\nThe presence of a tightly bound hydration layer formed by ionic solvation\nof the charged PMPC groups is confirmed by the significant positive\nshift in dissipation, indicating the formation of a more viscous and\nhydrated layer. In accordance with the frequency creeping up, the\ndissipation slowly decreases over time, which could indicate the loss\nof bound counterions and water molecules, and/or a reduced chain flexibility\ndue to rearrangements at the surface, resulting in a more collapsed\nand rigid structure. According to the net frequency shifts, it appears\nthat the efficiency of complexation of the PMPC copolymers surpasses\nthat of the other two. However, the binding efficiency is best illustrated\nby the weight-normalized graph in Figure 7 b, which actually suggests a superior complexation\nof the PEG-containing polymers. Comparison of the calculated grafting\ndensities indeed confirms a significantly (3×) higher grafting\ndensity for the PEG zipper brush ( Table S8 ). The PMPC and POEGMA brushes have a similar, but lower grafting\ndensity than PEG, as was expected based on sterics (POEGMA) and extensive\nhydration (PMPC). Figure 7 Data displaying the effect of the antifouling block on\nthe complexation\nbehavior and layer characteristics of the formed zipper brush coatings.\n(a, b) QCM-D graphs showing the in situ complexation\nof the antifouling diblock copolymers to the preadsorbed PS 81 - b -PAA 81 primer (pH 7, 1 mM) (a) before\nand (b) after normalizing the frequency by molecular weight ratio.\n(c) Tapping mode AFM height images of the adsorbed zipper brush coatings\nwith different antifouling blocks. The corresponding phase images\nand cross-sectional profiles are available in the SI ( Figure S18 ). According to the AFM images ( Figure 7 c), the surface coverage looks slightly higher\nfor\nthe PEG brush with respect to the POEGMA brush and is characterized\nby a lower surface roughness (1.1 vs 1.7 nm). The\nPMPC brush, however, distinguishes itself from the other two: its\nsurface morphology reveals a remarkably homogeneously covered film.\nWe believe the highly hydrated PMPC copolymers may more easily spread\nupon complexation, thereby covering a larger surface area. Independent\nof the choice of antifouling block, all obtained zipper brushes have\na highly hydrated character, indicated by the significant wet thickness,\nand they result in similarly thick coatings after drying ( Table S8 ). However, the surface roughness decreases\nand the wettability increases when changing the antifouling block\nfrom POEGMA, to PEG, to PMPC, which is in accordance with the AFM\ndata. The PEG and POEGMA zipper brushes exhibit a slightly more hydrophilic\ncharacter (52.4 and 60.9°) than the PS- b -PAA\nprimer layers, rather representing an intermediate between a PAA film\n(57–73°) 47 − 49 and a PEG-based (36–39°) 51 or a POEGMA-based (44°) film, respectively. 60 , 61 The PMPC zipper brush is characterized by an exceedingly higher\nwettability, but the contact angle (31°) is not nearly as low\nas the one recorded for covalently grafted PMPC brushes (<3°). 62 , 63 The relatively high contact angles may be explained by the available\nPAA chains still remaining at the interface, which is expected based\non the low grafting density. The surface zeta potential (ZP)\nwas recorded at each stage of the\nzipper brush formation using the streaming potential technique ( Figure S19 ). According to these measurements,\nall surfaces, including the zipper brushes, were characterized by\na net negative surface charge. However, it should be emphasized that\nthe employed technique calculates the absolute values by assuming\nthat the surfaces are uniformly charged and are homogeneously covered,\nsomething which is impossible to achieve for the current adsorbed\nbrushes. 64 Hence, it was decided to ignore\nthe recorded absolute values and focus on the trends instead. As expected,\nthe ZP decreases substantially after the first adsorption step, caused\nby the negatively charged and polar PAA chains contained within the\nPS- b -PAA primer. The ZP increases after the complexation\nstep, which can be explained by the hydrophilic and (net) charge-neutral\nchains now dominating the interface. Interestingly, even though the\nchoice of the antifouling block offered control over the grafting\ndensity, roughness, and wettability, it did not seem to affect the\nsurface potential: all zipper brushes were characterized by a comparable\nZP. Finally, the antifouling efficacy of each zipper brush was\ntested\nagainst two fouling agents with varying characteristics and sizes:\npositively charged lysozyme (14 kDa, pI 9.7) and negatively charged\nBSA (66 kDa, pI 4.5). 41 According to the\nQCM-D data, all zipper brushes successfully suppressed the attachment\nof lysozyme (Δ f ≈ 0), as opposed to\nthe pristine polystyrene substrate ( Figure 8 a). Even though the zwitterionic PMPC chain\nbears both positive and negative charges, the equal number of charges\nmakes it electrically neutral and, therefore, it does not attract\nlysozyme. Interestingly, in the case of BSA, only the PMPC zipper\nbrush was able to convincingly outperform the PS benchmark ( Figure 8 b). These differences\nbecome even more striking when normalizing the frequency shifts with\nregard to the pristine PS-coated substrate and converting the deviations\ninto a bar graph ( Figure 8 c). Even though their grafting densities were lower, both\nthe POEGMA and PMPC brushes have an increased potency against BSA\nadhesion than the PEG brush, presumably due to the enhanced internal\ndensity of the POEGMA brush and the electrostatically induced hydration\nlayer of the zwitterionic PMPC brush. 57 , 59 The superior\nantifouling performance of the PMPC brush can additionally be explained\nby its higher surface coverage and uniformity (evidenced by AFM),\nas well as its high wettability (confirmed by its low CA and high\nΔ D ). Figure 8 QCM-D graphs summarizing the in situ antifouling\nperformance of the adsorbed zipper brush coatings with different antifouling\nblocks against (a) lysozyme and (b) BSA (pH 7, 1 mM). (c) Bar graph\nrepresenting the antifouling efficacy of the zipper brushes with respect\nto the pristine PS-coated substrate. Hence, replacing the antifouling PEG block with\nzwitterionic PMPC\nsignificantly improves the antifouling performance of the resulting\nadsorbed zipper brush."
} | 10,337 |
35604933 | PMC9166356 | pmc | 4,109 | {
"abstract": "Exploiting biological processes to recycle renewable carbon into high value platform chemicals provides a sustainable and greener alternative to current reliance on petrochemicals. In this regard Cupriavidus necator H16 represents a particularly promising microbial chassis due to its ability to grow on a wide range of low-cost feedstocks, including the waste gas carbon dioxide, whilst also naturally producing large quantities of polyhydroxybutyrate (PHB) during nutrient-limited conditions. Understanding the complex metabolic behaviour of this bacterium is a prerequisite for the design of successful engineering strategies for optimising product yields. We present a genome-scale metabolic model (GSM) of C . necator H16 (denoted i CN1361), which is directly constructed from the BioCyc database to improve the readability and reusability of the model. After the initial automated construction, we have performed extensive curation and both theoretical and experimental validation. By carrying out a genome-wide essentiality screening using a Transposon-directed Insertion site Sequencing (TraDIS) approach, we showed that the model could predict gene knockout phenotypes with a high level of accuracy. Importantly, we indicate how experimental and computational predictions can be used to improve model structure and, thus, model accuracy as well as to evaluate potential false positives identified in the experiments. Finally, by integrating transcriptomics data with i CN1361 we create a condition-specific model, which, importantly, better reflects PHB production in C . necator H16. Observed changes in the omics data and in-silico -estimated alterations in fluxes were then used to predict the regulatory control of key cellular processes. The results presented demonstrate that i CN1361 is a valuable tool for unravelling the system-level metabolic behaviour of C . necator H16 and can provide useful insights for designing metabolic engineering strategies.",
"introduction": "Introduction The development of alternative and sustainable routes for producing chemicals and fuels is one of the major challenges of the 21 st century, due to the diminishing supply of fossil fuels and their severe damaging impact on the environment and human health through pollution and global warming [ 1 ]. Exploiting microbes as cellular factories converting renewable feedstocks into biomaterials, biochemicals and biofuels has thus attracted both academic and industrial interest as an alternative to fossil fuels [ 2 ]. Recent advances in metabolic engineering and synthetic biology tools have enabled genetic manipulation of selected microbial chassis to redirect carbon towards native and heterologous pathways for optimising the production and properties of desirable chemicals [ 3 ]. Cupriavidus necator H16 (previously known as Alcaligenes eutrophus and Ralstonia eutropha ) is amongst the most attractive species to engineer as a microbial factory for producing bulk chemicals, due to its highly flexible metabolism, ability to grow to high cell densities and its genetic tractability [ 4 – 6 ]. Interestingly, the bacterium is capable of growing on an extremely wide variety of substrates, including sugars, fatty acids and aromatic compounds [ 7 – 9 ]. Of particular interest, however, is C . necator ’s ability to utilise carbon dioxide (CO 2 ) as its sole carbon source, whilst utilising hydrogen (H 2 ) as its energy and electron source [ 10 ]. CO 2 is highly abundant in waste off-gas from many industrial processes, such as steel and concrete manufacture, as well as energy generation, and is thus a major contributor to air pollution and global warming [ 11 ]. Metabolically engineering C . necator H16 to valorise CO 2 into chemicals and biofuels, thus has become an attractive next generation solution that simultaneously mitigates climate change and reduces our reliance on fossil fuels without competing with food resources [ 4 ], provided ‘green’ hydrogen is used. Of further interest to industry, is the bacterium’s natural ability to produce large quantities of polyhydroxyalkanoates (PHAs) as storage compounds during nutrient-limited conditions, such as nitrogen or oxygen, when carbon is readily available [ 7 , 12 – 15 ]. Importantly, PHAs are being considered as an alternative to the petrol-based thermoplastics due to their comparable material properties and biodegradability [ 16 , 17 ]. The current limitation for commercial use of PHAs, however, is the high cost of their synthesis compared to petrol-based plastics [ 18 , 19 ]. Exploiting C . necator H16 to produce PHAs, whilst also growing on cheap feedstocks, may therefore provide an economically viable and greener solution [ 15 ]. To successfully employ C . necator H16 as a chassis for the production of platform chemicals, however, requires a greater understanding of the bacterium’s metabolic responses to perturbations [ 20 ]. Genome-scale metabolic models (GSMs) representing an organism’s metabolic capabilities are an invaluable computational tool for such an endeavour. With the advent of whole genome sequencing and high-throughput data of all levels of biological organisation, their construction, parametrisation, and validation have been increasingly improved and initiated the development of advanced methods for their application [ 21 , 22 ]. Despite their key role in biotechnological applications, many GSMs, including the previously published model of C . necator H16 (named RehMBEL1391) [ 9 ], are constructed using non-conventional identifiers for reactions and metabolites, which limits their reusability and further development. Manually mapping identifiers in GSMs is extremely time-consuming for large-scale models and applying naive string comparisons can often lead to inconsistencies that invalidate curated models [ 23 ]. Notably, the authors of [ 24 ] have made some significant improvements to the original RehMBEL1391 model in their recent publication, including the addition of identifiers for a subset of metabolites and reactions. Stoichiometric and mass inconsistencies, however, remain in this updated model, which are challenging to correct without the manual curation of metabolite and reaction information due to the incomplete coverage of database-linked identifiers. In this work, we therefore present a GSM that is directly constructed from the BioCyc Pathway Genome DataBase (PGDB) [ 25 ] for C . necator H16 using the ScrumPy software [ 26 ]. The benefits of constructing a GSM using this approach is 3-fold. First, the GSM includes metabolite and reaction identifiers that match the BioCyc database and thus enables accessibility to the plethora of tools available in BioCyc, including visualisation (such as metabolic pathways and metabolite chemical structures), omics data integration and comparisons to other organisms. Additionally, the BioCyc identifiers also provide greater accessibility to additional resources using their links to external databases, such as KEGG [ 27 ] and BRENDA [ 28 ]. Second, the model can be frequently updated as information in BioCyc is updated and improved. Third, unlike the standard SBML models, the ScrumPy model uses a modular approach that enables the capture of changes made during the model’s development lifetime, as well as separately defined metabolic subsystems, improving the model’s readability. Furthermore, we tested the model’s ability to predict gene-knockout phenotypes by employing a genome-wide essentiality screening using a TraDIS approach [ 29 ]. In addition, we used our new GSM to investigate the system-level metabolic changes that occur in C . necator H16 during nitrogen-limited conditions, and importantly, provide new insights into the alterations of metabolic fluxes under these conditions.",
"discussion": "Discussion The natural ability of C . necator H16 to grow on a variety of low-cost feedstocks, including CO 2 , whilst also producing large quantities of PHB during nutrient-limited conditions, make it a particularly attractive host for producing biochemicals and biofuels [ 4 ]. However, identification of genetic modifications and cultivation conditions for its optimal application as a microbial cell factory requires a comprehensive system-level understanding of its metabolism. A curated genome-scale metabolic model is fundamental for such a task. A major challenge in GSM development and analysis, however, is the readability and reusability of models. Often GSMs, including the original GSM of C . necator H16 [ 9 ], are constructed using non-systematic identifiers for metabolites and reactions, which considerably complicates the application of analysis packages, interpretation of results and further improvements of the model. Although a huge effort was recently made to improve the model readability of RehMBEL1391 [ 24 ], the lack of identifiers and chemical formulae for a significant subset of metabolites, makes it difficult to perform theoretical validation, such as stoichiometric and mass balance checks. In this work, we integrated the BioCyc PGDB into the model construction process using the ScrumPy software package to generate i CN1361, a GSM of C . necator H16 that includes the database identifiers for metabolites and reactions, whilst also enabling faster and automated model refinement as the database is updated. Furthermore, the ScrumPy version of our model uses a modular framework, which separates the automated and manually curated reactions, as well as different metabolic subsystems, and thus enhances the readability of the model for future researchers to understand and use. Importantly, unlike the RehMBEL1391 model, we could demonstrate that i CN1361 is stoichiometrically and mass balanced. We tested the performance of our new GSM using a more comprehensive set of experimental data. As part of this validation, we first demonstrated that the model can predict growth phenotypes for a variety of feedstocks. Additional validation, which compared the GSM results to previously published 13 C metabolic flux analysis, demonstrated that i CN1361 is accurately predicting internal fluxes of central carbon metabolism, whilst C . necator H16 is growing on fructose. Notably, accurately predicting internal metabolic fluxes is fundamental to the rational design of metabolic engineering strategies for strain development. Also important in strain development, is the ability of the model to predict metabolic behaviour during targeted engineering. In this work, we have therefore carried out a genome-wide gene essentiality screening using a TraDIS approach to determine in vivo knockout phenotypes for assessing i CN1361’s predictive ability. Importantly, i CN1361 achieved an overall performance of 92%, precision accuracy of 81% and recall accuracy of 62% for predicting gene essentiality phenotypes. Moreover, we could improve the recall performance to 69% by integration of gene expression data to remove inactive isoenzymes. To improve the recall measure, further, incorporation of regulation, enzyme kinetics and/or thermodynamic constraints are likely required to remove alternative flux solutions in the model, which are not feasible in vivo . Comparing the discrepancies to Tn-Seq gene essentiality predictions available from a recent study [ 24 ], showed that 70% of the false negatives agreed with the TraDIS results, further suggesting additional constraints are required to correct these gene knockout phenotypes in i CN1361. To address the discrepancies between the GSM and TraDIS gene essentiality predictions defined as false positives, a classical genetics approach was carried out to test the fitness of C . necator H16 mutants, carrying the in-frame deletions of 6 genes that were predicted to be essential by i CN1361 but not by TraDIS (or by the Tn-Seq predictions for 3 out of the 6 genes), during growth in FMM. None of these mutants grew under these experimental conditions, thus confirming the in silico predictions. The ambiguity of gene essentiality for genes that lie close to the determined threshold, as well as intrinsic limitations of the TraDIS-based approaches are likely responsible for these misclassified genes. Overall, our results clearly indicate that GSM and TraDIS present complementary advantages and limitations in predicting gene essentiality. We therefore propose a new “gold standard” pipeline for the identification of conditionally essential genes in bacteria that is based on the integration of in silico (GSM) and in vivo (TraDIS and/or Tn-Seq) system-level approaches. Wherever feasible, additional data derived from transcriptomic and classical genetics analysis should also be incorporated in this pipeline to minimise the points of conflict between the in silico and in vivo genotype-phenotype relationship predictions. Notably, useful insights from a metabolic engineering point of view can be extracted from the results. Indeed, the identification of the essential core genome of a given bacterial species represents the first step towards the construction of streamlined strains that only retain the minimal set of essential genetic functions. The use of these strains as microbial chassis for biotechnological applications should improve yields and economics of these bioprocesses since the inactivation of non-essential cellular functions is likely to result in a more efficient utilisation of resources, with respect to wild-type strains. Moreover, because of their decreased metabolic complexity, genome streamlined bacterial strains can serve as powerful tools to improve GSM predictions and, in turn, facilitate further strain development processes. Furthermore, such information can also be useful when considering suitable growth-coupling strategies, which rely on the inactivation of an essential function to force flux towards heterologous pathways for restoring growth. Additionally, we used i CN1361 to investigate the metabolic changes occurring during nitrogen-limited conditions to provide insights for designing strains with improved production of PHB or, more generally, PHAs, which are co-polymers generated by the combination of 3HB with other hydroxy-alkanoates and have improved chemical and mechanical properties, as compared to PHB. We found that performing standard FBA under conditions simulating nitrogen depletion resulted in pyruvate production, as previously demonstrated in vivo using a PHB-negative strain [ 43 ]. Using the iMAT method, we generated a condition-specific model to represent C . necator H16 during nitrogen-limitation, which correctly predicted PHB production as the sole product (other than CO 2 ). Further insights from the predicted internal fluxes suggested metabolic rewiring that interestingly included the up-regulation of the CBB cycle, which balances excess electrons whilst simultaneously avoiding carbon loss via CO 2 . Importantly, an active CBB cycle for growth on fructose has previously been observed experimentally but could not be predicted using the i CN1361 base model, due to the high level of redundancy in the model that prevented the results from converging in our analysis. Both results demonstrate the importance of solution space reduction by experimental data for a reliable analysis of biological properties using GSMs. Notably, the iMAT algorithm can also be integrated with proteomics data, and thus it would be interesting to investigate whether a proteomics-based iMAT model produces similar results. Currently, however, only transcriptomics data are available for C . necator H16 growing in batch culture. For continuous culture see [ 24 ]. Additionally, we predict whether metabolic activity is transcriptionally or post-translationally controlled for several important metabolic pathways, including amino acid biosynthesis and PHB metabolism. This provided valuable information that can be used for determining potential overexpression candidates to redirect metabolic fluxes towards production of a target chemical. As future work, it would be interesting to carry out dynamic modelling at the pathway level, to validate any candidates proposed from our analysis. Whilst we have shown that i CN1361 can predict metabolic behaviour with a high degree of accuracy, there are many ways in which the model can be improved and developed further, which could reduce the number of discrepancies with in vivo results. The current model is a simplified representation of metabolism, lacking information regarding enzyme kinetics, thermodynamic feasibility, and gene expression regulation, and thus can sometimes lead to solutions that are not possible in vivo . Approaches such as iMAT are useful for constraining the model according to gene expression or proteomics data for a given environmental condition, however, the approach is based on the assumption that gene expression or protein abundance is highly correlated to reaction flux, and thus still ignore the effect of kinetic and thermodynamic regulation. More advanced techniques, such as Resource Balance Analysis [ 24 ], GECKO [ 58 ] and matTFA [ 59 ], overcome these limitations by incorporating enzyme turnover rates and metabolite concentrations, to reduce the solution space. As data availability improves for C . necator H16, these tools can be applied to i CN1361 to improve the predictive accuracy of the model. To summarise, we have presented a new GSM of C . necator H16, named i CN1361, that allows for easier reusability by other researchers, which should benefit the greater scientific community by facilitating the further development of the model as future experimental data become available. Importantly, we demonstrated that combining i CN1361 and TraDIS data provides an accurate platform for predicting gene knockout phenotypes in C . necator H16. Additionally, we showed that incorporation of omics data to overcome the lack of regulatory, kinetics and thermodynamic information in i CN1361, improves predictions and provides useful metabolic insights. More broadly, we expect that the model, as well as the results presented, will provide useful information for guiding engineering efforts for facilitating the implementation of C . necator H16 as a microbial chassis for biotechnological applications."
} | 4,581 |
19788541 | null | s2 | 4,111 | {
"abstract": "Matrix production during biofilm formation by Bacillus subtilis is governed by a gene control circuit at the heart of which are three dedicated regulatory proteins, the antirepressor SinI, the repressor SinR and the downstream regulator SlrR. Matrix production is triggered by the synthesis of SinI, which binds to and inactivates SinR, thereby derepressing genes for matrix production as well as the gene for SlrR. Recently, two additional regulators of matrix genes were identified: SlrA, which was reported to be an activator of SlrR, and YwcC, a repressor of SlrA synthesis (Kobayashi, 2008). We present evidence indicating that SlrA, which is a paralogue of SinI, is like SinI, an antirepressor that binds to, and inactivates, SinR. We also show that SlrA does not activate SlrR for expression of matrix genes. Instead, SlrR binds to, and inhibits the activity of, SlrA. Thus, the YwcC-SlrA-SinR-SlrR pathway is a negative feedback loop in which SlrA indirectly stimulates the synthesis of SlrR, and SlrR, in turn, inhibits the activity of SlrA. Finally, we report that under standard laboratory conditions SlrA makes only a small contribution to the expression of genes for matrix production. We propose that in response to an unknown signal recognized by the YwcC repressor, SlrA transiently boosts matrix production."
} | 331 |
24044876 | PMC3848690 | pmc | 4,112 | {
"abstract": "Background Succinic acid (SA) has become a prominent biobased platform chemical with global production quantities increasing annually. Numerous genetically modified E. coli strains have been developed with the main aim of increasing the SA yield of the organic carbon source. In this study, a promising SA-producing strain, E. coli KJ134 [Biotechnol. Bioeng. 101:881–893, 2008], from the Department of Microbiology and Cell Science of the University of Florida was evaluated under continuous and batch conditions using D-glucose and CO 2 in a mineral salt medium. Production characteristics entailing growth and maintenance rates, growth termination points and metabolic flux distributions under growth and non-growth conditions were determined. Results The culture remained stable for weeks under continuous conditions. Under growth conditions the redox requirements of the reductive tricarboxylic acid (TCA) cycle was solely balanced by acetic acid (AcA) production via the pyruvate dehydrogenase route resulting in a molar ratio of SA:AcA of two. A maximum growth rate of 0.22 h -1 was obtained, while complete growth inhibition occurred at a SA concentration of 18 g L -1 . Batch culture revealed that high-yield succinate production (via oxidative TCA or glyoxylate redox balancing) occurred under non-growth conditions where a SA:AcA molar ratio of up to five was attained, with a final SA yield of 0.94 g g -1 . Growth termination of the batch culture was in agreement with that of the continuous culture. The maximum maintenance production rate of SA under batch conditions was found to be 0.6 g g -1 h -1 . This is twice the maintenance rate observed in the continuous runs. Conclusions The study revealed that the metabolic flux of E. coli KJ134 differs significantly for growth and non-growth conditions, with non-growth conditions resulting in higher SA:AcA ratios and SA yields. Bioreaction characteristics entailing growth and maintenance rates, as well as growth termination markers will guide future fermentor designs and improvements.",
"conclusion": "Conclusions Tests on the modified E. coli KJ134 revealed that the flux distribution of the cell is not constant: higher SA fluxes were obtained under non-growth conditions, and SA yields in excess of 0.9 g g -1 are possible. Results from the continuous culture fermentations suggest that the optimal SA-producing pathway is absent during growth, with AcA production supplying the reduction requirements, similar to those of the wild SA producers. The intended metabolic pathway, where the TCA oxidative branch (or the glyoxylate shunt) supplies the reduction requirements, mainly functions under non-growth conditions, as observed from the batch fermentation. Growth termination occurred close to a SA concentration of 18 g L -1 – the amount of AcA from the batch and chemostat fermentations was similar. This indicated that high titre (as well as high yield) production is only possible with non-growing cells. The maximum maintenance rate with SA production in the batch reactor was found to be twice that of the chemostat estimate.",
"discussion": "Discussion Succinic acid yield considerations In order to interpret the measured product distributions and yields, proper analysis of the possible metabolic pathways is required. From an overall perspective the optimum stoichiometry is given by the following balanced reaction where glucose (Glu) reacts with carbon dioxide to form succinic acid (SA): (1) Glu + 6 7 C O 2 → 12 7 SA + 6 7 H 2 O The above equation ignores the formation of biomass and gives the maximum possible yield of SA based on one mol of glucose. When expressed in mass units the above equation results in a SA yield of 1.12 g g -1 . In order to understand metabolic pathways for high-yield SA production, it is useful to consider the pathways of the naturally producing organisms such as Actinobacillus succinogenes , Mannheimia succiniciproducens and Anaerobiospirillum succiniciproducens . All of these organisms produce SA anaerobically via the reverse TCA (tricarboxylic acid) cycle starting with a PEP (phosphoenolpyruvate) carboxylation step. The net stoichiometry from glucose to SA requires NADH (see red arrows in Figure 4 ) and the pathway is therefore referred to as the reductive pathway. In order to balance the redox an oxidative pathway is required (also starting at glucose as indicated by the blue arrows in Figure 4 ). All the wild SA producers use AcA as a product to generate the required NADH. Pyruvate can be oxidised via the pyruvate dehydrogenase (PDH) pathway or the formate lyase pathway (FL). In the PDH pathway NADH is released and accordingly the oxidative pathway in Figure 4 (B) supplies more reduction power. When balancing the NADH of the two pathways the net oxidative and reductive flux can be determined. The combined overall pathway can then be used to determine the maximum possible yield. For the FL route in Figure 4 (A) an equal amount of oxidative and reductive flux occur, implying a 1:1 split of carbon at the PEP node. The maximum mass-based yield for this scenario is 0.66 g g -1 . For the PFL pathway (Figure 4 (B)) the additional NADH formed causes a ratio of 2:1 between the reductive and oxidative paths, thus allowing for more flux to SA where the maximum mass-based yield increases to 0.87 g g -1 . For this scenario each mol of AcA formed will result in 2 mol of SA formed. Figure 4 Metabolic pathways of native SA producers. A) Pyruvate oxidation via pyruvate formate lyase, B) Pyruvate oxidation via pyruvate dehydrogenase. Glu – glucose; PEP – phosphoenolpyruvate; OXA – oxaloacetate; Mal – malate; Fum – fumarate; SA – succinate; Pyr – pyruvate; AcCoA – acetyl coenzyme A; AcA – acetate. It is possible to improve the metabolic pathways of the natural organisms to further enhance SA yields by using an oxidative pathway with SA as the final product. The simplest of these is the oxidative branch of the TCA cycle where reduction power or NADH is generated en route to SA (see Figure 5 (A)). The TCA cycle can function in the absence of oxygen, although no NADH can be converted to ATP via oxidative phosphorylation. The major generation of NADH in the oxidative side of the TCA cycle (see Figure 5 (A)) causes most of the flux to flow through the reductive part of the cycle (fraction of 5/7 of total flux). It is important to note that the combined stoichiometry is exactly the same as Equation 1. The representation in Figure 5 (A) does not dictate termination of the oxidative TCA section at SA. It is also possible to operate the full TCA cycle as the oxidative pathway. In this case the reductive pathway flux will increase while the overall stoichiometry will remain the same as that of Equation 1. The glyoxylate shunt can be employed in a similar manner to achieve the exact same result. The overall oxidative route will share sections of the reductive route. The smaller amount of NADH generated in the oxidative glyoxylate path causes more oxidative flux (fraction of 3/7 of total flux), as indicated in Figure 5 (B). Figure 5 Metabolic pathway with SA as the only excretion product. A) Reductive and oxidative TCA sections, B) Glyoxylate shunt. Glu – glucose; PEP – phosphoenolpyruvate; OXA – oxaloacetate; Mal – malate; Fum – fumarate; SA – succinate; Pyr – pyruvate; AcCoA – acetyl coenzyme A; Cit – citric acid; AcA – acetate. Analysis of production capabilities and limitations It is evident that high-yield production of SA by E. coli KJ134 occurs under non-growth conditions where AcA production is small. The amount of AcA produced under growth conditions, especially for continuous cultures, resembles that of a native SA producer employing pyruvate dehydrogenase for the oxidation of pyruvate. This is clear for the SA:AcA ratios reported in Table 2 . All values are close to the theoretical value of two (see Figure 4 (B)) while formic acid production is limited. The chemostat yield values all lie below the theoretical maximum yield of 0.87 g g -1 due to biomass formation. The mechanism by which the AcA is produced is unknown, but it is unlikely that it is due to genetic regression. This is because the chemostat fermentations exhibited good repeatability between initial and final steady states after extended operation. For the development of E. coli KJ134, numerous minor acetate-forming pathways were deleted [ 14 ], with minimal AcA formation reported in the test fermentations. Product distributions under non-growth or maintenance conditions differ substantially from growth conditions as observed in the batch results. It appears that the metabolic modifications only function after cell growth has terminated, although SA:AcA ratios slightly higher than two were obtained in the growth phase of the batch reactor. The highest SA:AcA ratio of five was obtained in the maintenance phase of the batch reactor, as seen from the instantaneous production ratios in Table 3 . It is therefore evident that the ‘ideal’ metabolic pathway represented in Figure 5 is partially utilised under maintenance conditions, where reduction power is generated via the oxidative TCA (or glyoxylate shunt) pathway. When comparing the batch runs of this study to that of the original [ 1 ], the major difference lies in the inorganic carbon source. Jantama et al. [ 14 ] employed a mixture of K 2 CO 3 and KOH for neutralisation and carbonate supply, while continuous CO 2 (g) sparging was used in this study. Despite a major difference in the initial DCW (0.07 g L -1 for this study compared to 0.003 g L -1 previously reported), the SA concentration after 96 hours was much higher (71.5 g L -1 ) than in this work (approximately 43 g L -1 ). The SA to AcA ratio was also significantly higher (16) than in this study (4). The growth inhibition characteristics of the chemostat and batch fermentations agree, where a SA concentration of 18 g L -1 (with the associated AcA) can be used as a marker. High-titre production of SA will accordingly only be possible with non-growing cells. The classical fed-batch system is therefore suited for the process. High-titre continuous production will only be viable with a cell recycle system where a separate growth fermentor supplies cells to a cell recycle fermentor. For the proposed scheme AcA production under growth conditions can be bypassed by operating the growth fermentor aerobically. The high SA titre from the non-growing cells will be associated with high SA yields. Maintenance production rates were quantified for both the chemostat and batch fermentations. The analysis of the continuous fermentations is given in Figure 6 where the cell-based production rate of SA (r SA ) is plotted against the dilution rate. The y-axis intersection on this graph gives the maintenance production rate, which was determined to be 0.3 g SA g -1 cells h -1 . The maintenance production rate for the batch fermentation can be obtained by dividing the slope of the SA profile (Figure 3 ) by the DCW (once there is no further increase in the DCW). It is evident that the slope of the SA profile decreases towards the end of the fermentation. The maximum slope (and maximum maintenance production rate) was obtained right after growth termination, and was determined to be 0.6 g SA g -1 cells h -1 . This is twice the rate of the chemostat estimate. The consequent decrease in SA production could not be attributed to the decrease in the DCW, implying that the r SA decreases towards the end of the fermentation. Cell death might be a possible explanation for the observation. Figure 6 r SA vs. D for the determination of the maintenance production rate of SA. Glucose feed concentrations of 20 and 50 g L -1 are indicated. Glu – glucose; SA – succinic acid."
} | 2,943 |
40244660 | PMC12037064 | pmc | 4,115 | {
"abstract": "Significance Microbial ecosystems in nature exhibit dynamic lifecycles, cycling through distinct physiological states for the microbes as they switch between active growth, stressed states, and dormancy. Constructing mechanistic bottom–up models that incorporate these changes is challenging because experimental data do not sufficiently constrain the many parameters. Consequently, current models typically assume constant exponential growth and fixed pairwise interactions, missing the critical link between physiology and ecology. Instead, we present a phenomenological model, the Community State Model, that emphasizes the changing physiological state of community members rather than individual interactions. Our model provides testable predictions about the emergent structure of microbial communities with dynamic lifecycles.",
"discussion": "Discussion In this work, we investigated models of microbial growth and survival in communities undergoing repeated cycles of environmental fluctuations with prolonged periods between nutrient replenishments, as seen in the wild ( 36 , 65 ) and in serial-dilution lab experiments ( 12 , 39 , 66 ). Under these conditions, exponential steady-state growth is unsustainable due to resource consumption, waste accumulation, and other processes that speed up exponentially in time. Predicting dynamics in such cyclic systems from bottom–up models is challenging, given our limited understanding of microbial behaviors beyond exponential growth ( 65 , 67 ). Here, we developed a top–down CS Model, by assuming that the cyclic dynamics are low dimensional; we exploited the simplest closure of equations, namely that total biomass is the low dimensional eco-coordinate. We discussed the justifications for these assumptions, using a recent experimental investigation ( 16 ) as a case study. We derived quantitative self-consistency conditions on dynamical behaviors of community members after repeated serial-dilution cycles, requiring the input of only several experimentally measurable quantities: the instantaneous growth rates of community members { r α ( t ) } and the total biomass ρ tot ( t ) . In theoretical ecology, it is common to “coarse-grain” or ignore dynamics seen in real systems for the sake of “simplicity” ( 68 , 69 ). However, the work here shows such coarse-graining a) destroys the link between physiology and ecology and b) overlooks an important source of niches. For (a), we note that the classic work on seasonal resources by Stewart and Levin ( 58 ) was dismissed as a mathematical observation without broad physiological relevance, but our work argues that their mechanism of dynamic coexistence is the essential link between physiology and ecology. We find that dynamic niches are more relevant given the complex physiology and nonlinear growth dependencies in real microbial ecosystems ( 12 , 16 , 17 ). For (b), we have quantified how physiological states can serve as dynamic niches. One major finding here is that community states differ from resource niches where many species can coexist by specializing on different resources, almost indifferent to the presence of other species: the dynamic nature of community states implies that the growth of one species strongly affects the growth of another. Our self-consistency criteria (Eq. 7 ) quantify dynamic niche overlap, with their explicit dependence on growth rate ratios serving as a fitness-like measure in dynamic contexts. Our main results on physiological states as niches are as follows: 1) Community stability through coordinated staggering of growth dominance: Coordinating to stagger the fast growth phases of different species across distinct community states—rather than growing simultaneously—ensures stable coexistence. 2) Tolerance to growth dominance: increasing the growth rate of an individual species in its favored state does not necessarily eliminate other species and does not impact community diversity. 3) Increased requirement on growth dominance for late-growers: species growing in late community states must grow (exponentially) faster or grow for (exponentially) larger biomass intervals than species in early states. A key strength of our model is its anchoring on experimentally accessible quantities rather than inaccessible interaction parameters. Instantaneous growth rates of individual species can be obtained from transient changes in species abundances (via e.g., 16S sequence as proxy), and the total community biomass can be obtained by measuring total protein or total RNA as proxies, or simply by the optical density if the culture does not aggregate. This allows the investigation of community dynamics to go beyond taxonomic characterization, and without invoking numerous fitted “interaction” parameters such as those employed in Lotka–Volterra or CR models, but based directly on the quantitative analysis of the dynamic data. For example, suppose a community is observed to exhibit a certain dynamical sequence { r α ( t ) } for one cycle, can this sequence persist after repeated serial dilution cycles? For a community that settles down to a stable cycle with { r α sc ( t ) } , do the data capture all the major species? And, might data from some important time intervals be missing? Concrete predictions of the CS Model, e.g. late species require increased dominance to survive, can be tested experimentally by acquiring dynamic growth data. In this sense, the CS Model is a phenomenological model that can be updated directly from data. Our approach shares common elements with other top–down approaches like the Stochastic Logistic Model ( 70 , 71 ) and recent data-driven models ( 72 , 73 ) without explicit interspecies interactions. However, unlike these other models which attribute growth rate fluctuations to external factors, our model focuses on endogenously driven changes. Our model can be extended to incorporate external fluctuations perturbing growth niches across hosts or cycles, predicting abundance distributions as in ref. 70 . A key distinction is that our approach imposes closure conditions on cycle-to-cycle growth rate variations to ensure stable but dynamic coexistence. We also distinguish our findings from the well-known Storage Effect ( 43 ). While both the CS Model and the Storage Effect provide mechanisms for stable coexistence through negative frequency-dependent selection arising due to differential responses to the environment, the Storage Effect concerns exogenous temporal fluctuations near an equilibrium community while the CS Model concerns deterministic and endogenous temporal variations. The CS Model is in fact more similar to “classical coexistence mechanisms” such as resource partitioning or differential predator pressures ( 74 ), as it implicitly admits different environmental limiting factors such as nutrient supply, pH change, signaling molecules, etc. in the form of different community states. As such, the Storage Effect and the CS Model are not mutually exclusive either. A key notion in our work is the existence of global community states with a low dimensional parameterization, the eco-coordinate η ( t ) , that can be sensed by microbes in that community. Our results suggest that it would be advantageous for organisms to use this information to adjust their behavior and grow in specific community states since such regulation would increase their chance of survival in the community. For example, organisms occupying early phases of the cycle may benefit from limiting their own growth there, so as not to eliminate other species active later in the cycle, those which could help the survival of all species in later phases of the cycle—as is the case for acid-induced stress relief ( 16 ), the early blooming acid-producing sugar eater is rescued from death by the late-blooming acid consumer which removes the excreted acid and detoxifies the environment. In this light, the acid consumer can be viewed as “public good” for the community, and the puzzle of species coexistence can be viewed as a problem of coordination around a public good. A possible future direction employing the CS Model would be to explore how diverse communities are robust to cheater strains that seek to maximize growth while impacting community diversity. Our findings already present possible explanations such as the tolerance of community diversity to growth dominance and greater stability through coordinated dominance, which suggest that species seeking optimal growth within their dynamic niche do not affect community diversity, and species seeking long-term survival instead benefit from specializing in their niche. However, these explanations currently lack physiological justifications constraining the ability of species to grow quickly in multiple dynamic niches. We believe this eco-coordinate-based regulation hypothesis is biologically plausible: first, a number of key physiological parameters, e.g., pH, oxygen content, waste products, and iron availability, change with the accumulation of community biomass ( 75 ), and the values of these parameters to cause transitions in the physiological states of individual organisms are known. Second, it is known that several autoinducers are produced and sensed by a wide range of both gram-positive and gram-negative bacteria ( 76 – 78 ). In fact, AI-2 has been proposed to serve as a “universal signal” for interspecies communication ( 79 – 81 ). Third, it is common for microbes to develop sensors to detect important features of their environment ( 82 – 85 ); as total community biomass is clearly an important dynamical variable that can be used to forecast the fate of the community (e.g., how close to the carrying capacity), it would not be surprising if organisms have evolved schemes to sense the total biomass. Various bacterial species may detect additional features of the community state, possibly in species-specific manner, and integrate the available information through regulatory mechanisms. In fact, in the case of bacterial toxicity, it has been shown that regulation of toxin production is associated with local biomass using experimental data ( 86 ), an optimal strategy according to evolutionary simulations ( 87 – 90 ), and a strategy found to afford fitness benefits experimentally ( 91 ). Thus we can speculate, inspired by the CS Model, that organisms might actively regulate their own physiology by sensing low-dimensional, community-wide signals and thus organize stable ecosystems despite lacking an obvious central organizer for the community. Indeed, the existence of a group of organisms that can sense and respond to common low-dimensional features in the environment may be taken as a key characteristic that defines a “community.”"
} | 2,691 |
30674830 | PMC6209286 | pmc | 4,116 | {
"abstract": "One strategy that has gained much attention in the last decades is the understanding and further mimicking of structures and behaviours found in nature, as inspiration to develop materials with additional functionalities. This review presents recent advances in stimuli-responsive gels with emphasis on functional hydrogels and microgels. The first part of the review highlights the high impact of stimuli-responsive hydrogels in materials science. From macro to micro scale, the review also collects the most recent studies on the preparation of hybrid polymeric microgels composed of a nanoparticle (able to respond to external stimuli), encapsulated or grown into a stimuli-responsive matrix (microgel). This combination gave rise to interesting multi-responsive functional microgels and paved a new path for the preparation of multi-stimuli “smart” systems. Finally, special attention is focused on a new generation of functional stimuli-responsive polymer hydrogels able to self-shape (shape-memory) and/or self-repair. This last functionality could be considered as the closing loop for smart polymeric gels.",
"conclusion": "5. Conclusions In the field of materials science and engineering, the design, research and development of new and improved smart structures and systems is currently a hot topic. In this context, functional stimuli-responsive gels are of great interest due to their versatility and possible application in fields as diverse as biomedicine, catalysis, or even biosensors. The relevance of the subject dealt in this review is clearly reflected in the considerable number of relevant publications. In this review, we intended to cover the most recent and high-impact publications using functional stimuli-responsive gels. The review started from macro to micro, i.e., from hydrogels to microgels, ending with a new generation of functional gels. Stimuli-responsive functional hydrogels and microgels are used for a broad range of applications, and several publications can be found in literature. PNIPAAm is the most used thermoresponsive polymer. In many cases, PNIPAAm is combined with another polymer to add a new functionality to the hydrogel. In microgels, PNIPAAm is most commonly combined with an inorganic component, ranging from metallic nanoparticles to carbonaceous particles. In the last part of the review, the new generation of functional stimuli-responsive gels, able to self-repair or/and possess shape memory property, are described. Among others, PAAm, PVA and PEG are the commonly used polymers in this new generation of functional gels. The development of Shape Memory Polymers suitable for biological media in a living system is a still a challenge today. In this regard, shape memory hydrogels that are predominantly water stand out as alternative candidates for biomedical applications due to the use of water as a driving force for the desired shape memory effect. The advantages and attributes of functional gels (macro and micro) have been highlighted throughout the entire review, but the most promising is the ability to self-heal, expected in almost all industries in the near future. Self-healable hydrogels go through improvements in their mechanical properties without affecting their intrinsic properties, and importantly, their responsiveness to external stimuli. In summary, this review demonstrates the prominent role of smart functional gels in materials science; its versatility and tunable properties allows usage in a wide range of applications.",
"introduction": "1. Introduction Gels have pervaded our everyday life in a variety of forms. The wet soft solids that we encounter in the form of commercial products such as soap, shampoo, toothpaste, hair gel and other cosmetics, as well as contact lenses and gel pens, etc., are all gels derived from polymeric compounds. Polymer gels have been known for centuries and used for application in fields as diverse as food, medicine, materials science, cosmetics, pharmacology, and sanitation, among others. In general, gels are viscoelastic solid-like materials comprised of an elastic cross-linked network and a solvent, which is the major component. The solid-like appearance of a gel is a result of the entrapment and adhesion of the liquid in the large surface area solid three-dimensional (3D) matrix [ 1 ]. Pierre-Gilles de Gennes during his Nobel lecture in 1991 recognized the place of gels among the broad category of ‘‘soft matter’’. Focusing on the phenomenological characteristics, polymer gels are 3D networks swollen by a large amount of solvent. Solid-like gels are characterized by: (i) the absence of an equilibrium modulus; (ii) the presence of a storage modulus, G’(u), which exhibits a pronounced plateau extending to times at least of the order of seconds; and (iii) the presence of a loss modulus, G’’(u), which is considerably smaller than the storage modulus in the plateau region. The presence of liquid-like behavior on molecular length scales combined with solid-like macroscopic properties makes them very unique systems. Polymer gels are classified as chemical and physical gels, depending on the nature of crosslinks ( Figure 1 ) [ 2 ]. Considering the current needs in the field of materials science, the strategy that has gained attention in the last decades is the understanding and further mimicking of structures and behaviours found in nature in order to develop materials with additional functionalities. These materials will have the ability to respond to several stimuli and could be used for biomedical purposes or in everyday life applications. In this context, the so-called “smart” or responsive polymers are becoming increasingly important. This kind of polymer is able to transform external stimuli into shape change or movement by taking advantage of the surrounding environment. The interest in the stimuli-responsive polymers has continued over many decades and it is still a hot topic in materials science. Indeed, researchers’ interest in the ability that this kind of gels present when subjected to external stimuli can be seen in the literature since the early 1990’s ( Figure 2 a) and is transversal to several scientific subjects ( Figure 2 b). In this regard, polymer gels have a special place in the field of stimuli responsive systems, and have attracted much attention due to their composition, versatility, and wide variety of potential applications, in particular in the biomedical field. However, we can also find its use within fields as catalysis, mechanical, chemical or optical sensors, or actuators, among others. The nature of the stimulus can be classified as physical, chemical or biological [ 3 ]. Physical stimuli influence the systems molecular interactions, while the last two types of stimuli directly affect the interactions between the polymer chains (intramolecular) or with other constituents of the system. However, in both cases, a phase transition is observed. Gels can be divided into macrogels, microgels and nanogels and can be assembled to give rise to thin-films, brushes, membranes, colloidal particles, foams, among others, as is well explained by Stuart et al. [ 4 ]. In this review, we focus attention on recent advances found within the field of stimuli responsive functional polymeric gels. In the first section of the review, we will devote our attention to earlier (last year) developments on stimuli-responsive polymer hydrogels. Some examples are presented where stimuli as temperature, pH, light and redox, or analyte-responsive hydrogels and 3D printing applications are highlighted. The second section of the review will focus on the most recent studies regarding multifunctional stimuli-responsive microgels, in particular hybrid microgels systems. Special attention will be paid to (multi)responsiveness induced by inorganic nanoparticles incorporated within the microgel matrix, such as, metallic, magnetic, or carbonaceus particles. Finally, the last part of this review aims to highlight the new generation of functional stimuli-responsive polymer hydrogels—self-shape (shape memory) or self-healing hydrogels, as a step-forward in the field of “smart” materials."
} | 2,035 |
22018401 | PMC3333776 | pmc | 4,117 | {
"abstract": "Background The rhizosphere is the microbe-rich zone around plant roots and is a key determinant of the biosphere's productivity. Comparative transcriptomics was used to investigate general and plant-specific adaptations during rhizosphere colonization. Rhizobium leguminosarum biovar viciae was grown in the rhizospheres of pea (its legume nodulation host), alfalfa (a non-host legume) and sugar beet (non-legume). Gene expression data were compared to metabolic and transportome maps to understand adaptation to the rhizosphere. Results Carbon metabolism was dominated by organic acids, with a strong bias towards aromatic amino acids, C1 and C2 compounds. This was confirmed by induction of the glyoxylate cycle required for C2 metabolism and gluconeogenesis in all rhizospheres. Gluconeogenesis is repressed in R. leguminosarum by sugars, suggesting that although numerous sugar and putative complex carbohydrate transport systems are induced in the rhizosphere, they are less important carbon sources than organic acids. A common core of rhizosphere-induced genes was identified, of which 66% are of unknown function. Many genes were induced in the rhizosphere of the legumes, but not sugar beet, and several were plant specific. The plasmid pRL8 can be considered pea rhizosphere specific, enabling adaptation of R. leguminosarum to its host. Mutation of many of the up-regulated genes reduced competitiveness for pea rhizosphere colonization, while two genes specifically up-regulated in the pea rhizosphere reduced colonization of the pea but not alfalfa rhizosphere. Conclusions Comparative transcriptome analysis has enabled differentiation between factors conserved across plants for rhizosphere colonization as well as identification of exquisite specific adaptation to host plants.",
"conclusion": "Conclusions Overall, the comparative transcriptome approach used here has revealed bacterial responses common to different plant rhizospheres, as well as mapping key general responses such as organic acid, C1-C2 and aromatic amino acid metabolism. In addition, it has highlighted specific bacterial adaptations to individual plants species and enabled identification of specific detoxification systems, such as that for canavanine in the alfalfa rhizosphere. Mutation of two genes (RL0680 and pRL80021) specifically induced in the pea rhizosphere only reduced competitiveness in the pea and not the alfalfa rhizosphere. A dramatic observation is the large number of genes located on plasmid pRL8 that are specifically induced in the pea rhizosphere. This is particularly exciting and suggests there may be a wealth of plant rhizosphere-specific plasmids or chromosomal islands to be revealed by emerging high-throughput sequencing projects.",
"discussion": "Results and discussion Rhizobia provide a special advantage when studying the plant rhizosphere as bacterial responses can be investigated during colonization of the rhizosphere of a specific host legume (for example, pea), a non-host legume (alfalfa) and a non-legume (sugar beet). In addition, we are able to chart metabolic activity in the rhizosphere by comparison to the Sinorhizobium meliloti transportome, which comprises a large induction map for 76 identified ATP-binding cassette (ABC) and tripartite ATP-independent periplasmic (TRAP) transport systems in rhizobia [ 5 ]. This induction map was extended in this study with a series of microarrays of free-living cultures grown on a variety of metabolites (Table 1 ). Table 1 Microarray experiments performed with R.leguminosarum biovar viciae Rlv3841 Array Express accession number a Condition 1 Condition 2 Biological replicates Results shown E-MEXP-2844 Pyruvate/NH 4 + /hesperetin (1 μM) Pyruvate/NH 4 + 3 Additional file 6 E-MEXP-2846 Pea root exudate Pyruvate/NH 4 + 3 Additional file 6 E-MEXP-2845 21 day pea rhizosphere 1 dpi Glucose/NH 4 + 4 Additional file 6 E-MEXP-2845 14 day pea rhizosphere 1 dpi Glucose/NH 4 + 4 Additional file 6 E-MEXP-2845, E-MEXP-2848 7 day pea rhizosphere 1 dpi Glucose/NH 4 + 5 Additional file 6 E-MEXP-2848 7 day pea rhizosphere 3 dpi Glucose/NH 4 + 5 Additional file 6 E-MEXP-2848, E-MEXP-2852, E-MEXP-2854 7 day pea rhizosphere 7 dpi Glucose/NH 4 + 5 Additional file 7 E-MEXP-2852 7 day alfalfa rhizosphere 7 dpi Glucose/NH 4 + 3 Additional file 7 E-MEXP-2852 7 day sugar beet rhizosphere 7 dpi Glucose/NH 4 + 3 Additional file 7 E-MEXP-2849 7 day pea rhizosphere 7 dpi 7 day alfalfa rhizosphere 7 dpi 4 Additional file 6 E-MEXP-2849 7 day pea rhizosphere 7 dpi 7 day sugar beet rhizosphere 7 dpi 4 Additional file 6 E-MEXP-2849 7 day alfalfa rhizosphere 7 dpi 7 day sugar beet rhizosphere 7 dpi 4 Additional file 6 E-MEXP-2854 7 day pea rhizosphere 7 dpi inoculated with 10 3 CFU Glucose/NH 4 + 3 Additional file 6 E-MEXP-2857 Formate/pyruvate Pyruvate/NH 4 + 1 Additional file 9 E-MEXP-2857 Protocatechuate Pyruvate/NH 4 + 1 Additional file 9 E-MEXP-2857 4-Hydroxybenzoate Pyruvate/NH 4 + 1 Additional file 9 E-MEXP-2857 Phenylalanine/pyruvate/NH 4 + Pyruvate/NH 4 + 1 Additional file 9 E-MEXP-2857 Proline/pyruvate Pyruvate/NH 4 + 1 Additional file 9 E-MEXP-2857 N-limited (glucose/1 mM NH 4 + ) Glucose/10 mM NH 4 + 1 Additional file 9 E-MEXP-2857 L-Arabinose/NH 4 + Glucose/NH 4 + 1 Additional file 9 E-MEXP-2857 Galactose/NH 4 + Glucose/NH 4 + 1 Additional file 9 E-MEXP-2857 Arabinogalactan/pyruvate/NH 4 + Pyruvate/NH 4 + 1 Additional file 9 Microarrays comparing growth on acetate, acetoacetate, inositol, succinate, glucose and pyruvate as carbon sources have been published previously [ 8 ]. All carbon sources were 10 mM, except pyruvate (30 mM), protocatechuate (3 mM), 4-hydroxybenzoate (3 mM), phenylalanine (5 mM), formate (40 mM) and arabinogalactan (10 mg/ml). a Where two or more accession numbers are given they form part of different time courses. Inoculation of all rhizospheres was performed with 10 8 CFU unless otherwise stated. At the start of this study three variables were compared: (i) length of incubation of bacteria in the rhizosphere (bacteria harvested at 1, 3 and 7 days post-inoculation (dpi) of 7-day-old pea plants (Table 1 ; Additional file 1 )); (ii) age of the plant (bacteria harvested at 1 dpi of 7-, 14- and 21-day-old pea plants (Table 1 ; Additional file 2 )); (iii) level of bacterial inoculum (10 3 or 10 8 colony forming units (CFU; 7 dpi of 7-day-old peas); Table 1 ; Additional file 3 ). Incubating bacteria in the pea rhizosphere for 7 dpi was chosen as the standard incubation because it gave the highest number of three-fold or more differentially regulated genes (7 dpi (764) > 3 dpi (682) > 1 dpi (638); Additional file 1 ). Seven-day-old plants were chosen because this gave the largest number of three-fold or more differentially regulated genes (7-day-old plants (635) > 21-day-old (441) > 14-day-old (171); Additional file 2 ). In addition, 138 genes were specifically up-regulated in 7-day-old pea plants (Additional file 2 ), including many genes of interest (for example, rhi genes pRL10169-171, cinI (RL3378) and nod genes pRL100180, pRL100183, pRL100186-188), which we assume are induced by young, fast growing roots but not by those of older plants. An inoculum of 10 8 CFU rhizobia was chosen because it resulted in more differentially expressed genes (Additional file 3 ) and RNA recovery was more reliable. With the standard conditions established R. leguminosarum bv. viciae Rlv3841 was inoculated at 10 8 CFU into the rhizosphere of 7-day-old pea, alfalfa or sugar beet plants and bacteria harvested 7 dpi. The gene induction pattern was compared against glucose-grown laboratory cultures, leading to an indirect comparison of rhizospheres (Table 1 ; Additional file 4 ). By contrast, relative levels of gene induction were also directly compared from bacteria isolated from the rhizospheres of two different plants (that is, pea:alfalfa, pea:sugar beet and alfalfa:sugar beet; Table 1 ; Additional files 4 and 5 ). Thus, the results of two independent methods could be compared. Increased gene expression was classified as general (that is, elevated in all plant rhizospheres) or specific, either for the rhizospheres of legumes or individual plant species (Additional files 4 and 6 ). Seventy of the 106 genes up-regulated in all rhizospheres tested compared to glucose-grown bacteria (Additional files 4 and 7 ) are annotated as hypothetical (compared to 27% of the genome); even permitting for a degree of mis-annotation, this suggests synthesis of proteins of novel function. A similar observation has been made for Pseudomonas [ 6 ]. As our purpose was to integrate information about metabolism and cellular function in the rhizosphere, we have avoided a tedious list of genes and instead distilled key features of bacterial life in the rhizosphere into diagrams for membrane transport (Figure 1 ), metabolism (Figure 2 ) and cellular activities (Figure 3 ) (data in Additional file 8 ). Figure 1 Rhizosphere-induced genes in the Rlv3841 transportome . Genes induced (by three-fold or more, P ≤ 0.05) are color coded: black, all rhizospheres; green, pea-specific; red, alfalfa-specific; orange, sugar beet-specific; blue, legume-specific; purple, alfalfa and sugar beet; gold, pea and sugar beet. Genes are scored as elevated in more than one rhizosphere if they are up-regulated by three-fold or more in one and two-fold or more in one or two other rhizospheres (Additional file 8 ). Identified transported solutes are shown. Uncharacterized ABC uptake systems are classified according to Saier [ 12 ]. For uptake ABC transporter family: CUT1, carbohydrate uptake transporter 1; CUT2, carbohydrate uptake transporter 2; HAAT, hydrophobic amino acid transporter; MolT, molybdate transporter; NitT, nitrate/nitrite/cyanate transporter; PAAT, polar amino acid transporter; PepT, peptide/opine/nickel transporter; POPT, polyamine/opine/phosphonate transporter; QAT, quaternary amine transporter. Classification of ABC transporters is as follows: MolT, RL3040; CUT1, RL2418 (MtlE); CUT2, RL4655 (IntA), RL3840 and RL2720; PepT, pRL110281 and pRL110243; PAAT, pRL80060 and pRL80064; POPT, pRL100248; NitT, RL3721. Asterisks indicate a compound metabolized by an enzyme whose expression is elevated (Figure 2) or, in the case of Nod factor, synthesized for export (Figure 3). Abbreviations: ABC, ATP-binding cassette; MATE, multidrug and toxic compounds extrusion; MDR, multi-drug resistance; MFS, multi-facilitator superfamily; MscS, mechanosensitive channel small; RND, resistance-nodulation-cell division; TRAP, tripartite ATP-independent periplasmic. Genes underlined have been mutated and results of their competitiveness in the rhizosphere are shown in Additional file 8 . Figure 2 Rhizosphere-induced genes in Rlv3841 metabolic pathways . Bold lines show reactions encoded by genes induced (by three-fold or more, P ≤ 0.05) and are color coded for the rhizospheres: black, all; green, pea-specific; red, alfalfa-specific; blue, legume-specific; purple, alfalfa and sugar beet. An induced gene is also considered to be elevated in further rhizospheres where expression was elevated by two-fold or more (Additional file 8 ). Where more than one enzyme carries out a reaction the color reflects the gene elevated in most rhizospheres. Asterisks indicate compounds imported by a transport system whose expression was elevated (Figure 1). a Genes are part of an induced operon and elevated ≥ 1.3-fold; b genes induced ≥ 3-fold, P ≤ 0.11; c genes elevated ≥ 2.2-fold, P ≤ 0.05. Dotted lines and boxed genes show those down-regulated (≤ 0.3-fold, P ≤ 0.05) relative to glucose-grown cells. Expression is considered to be down-regulated in all rhizospheres if ≤ 0.5-fold. Reactions carried out by genes slightly down-regulated (0.4- to 0.8-fold; Additional file 8 ) are shown by a thin grey line. The dichloroethane pathway shown in italics is speculative. Genes underlined have been mutated and results of their competitiveness in the rhizosphere are shown in Additional file 8 . DHAP, dihydroxyacetone phosphate; ED, Entner-Doudoroff; TCA, tricarboxylic acid. Figure 3 Rhizosphere-induced genes for cellular functions in Rlv3841 . Genes elevated by three-fold or more ( P ≤ 0.05) are color coded for the rhizospheres: black, all; green, pea-specific; blue, legume-specific; purple, alfalfa and sugar beet; gold, pea and sugar beet. An induced gene is considered to be also elevated in further rhizospheres where expression was elevated by two-fold or more (Additional file 8 ). Asterisks indicate Nod factor is exported by a specific transport system whose expression was elevated (Figure 1). a Genes are part of an induced operon and elevated ≥ 1.7-fold; b genes induced ≥ 3-fold, P ≤ 0.08; c gene considered up-regulated in the pea rhizosphere (1.8-fold elevated). Genes underlined have been mutated and results of their competitiveness in the rhizosphere are shown in Additional file 8 . In order to determine the importance of bacterial genes up-regulated in the rhizosphere, competition assays were performed in the pea rhizosphere between wild-type Rlv3841 and 46 strains, each mutated in one of these up-regulated genes (Additional file 8 ). These genes were chosen after the initial screen of genes up-regulated in the pea rhizosphere versus glucose grown laboratory cultures. Pea was used because it is the host plant for R. leguminosarum . However, two mutants were also tested in both pea and alfalfa rhizospheres because subsequent gene expression analysis showed they are specifically up-regulated in the pea rhizosphere. In these mutants it would be expected that any impairment in competition would be restricted to the pea rhizosphere. Mutants were scored with a rhizosphere colonization index (RCI); as described in Materials and methods, a RCI of 1 indicates equal competitiveness with Rlv3841, and the lower the RCI (down to 0.35), the less able the strain is to compete with Rlv3841 (Additional file 8 ). Thus, a low RCI indicates that the mutation is in a gene that is important for the strain to colonize the rhizosphere. General adaptation to the rhizosphere: cellular factors Genes induced in all three plant rhizospheres reflect general life in the rhizosphere and we consider these before examining responses specific to one plant (Additional file 7 ). They include elevated expression of rhiABC (pRL100169-171) and rhiI (pRL100164), previously described as rhizosphere-induced genes [ 7 ], and the gene for autoinducer synthesis protein CinI (RL3378), which is involved in coordinating quorum-sensing regulation and biofilm formation (Figure 3 ). Quorum sensing is likely to be important in rhizosphere biology, where bacterial attachment is a key step in root colonization [ 7 ]. Expression of genes encoding an alternative aa 3 -type cytochrome c oxidase complex (RL3041-45) and a possibly associated cytochrome c (RL3046) were induced in the rhizosphere (Figure 3 ). This rhizosphere-induced cytochrome pathway, which is distinct from both the normal cytochrome aa 3 complex found in laboratory cultured bacteria and the high affinity cytochrome cbb 3 complex found in the N 2 -fixing nodule form of rhizobia [ 8 ], suggests a distinct redox environment in the rhizosphere. It may be that in the rhizosphere the level of available oxygen is lower than in shaken laboratory culture but higher than in the microaerophilic conditions found inside legume nodules. General adaptation to the rhizosphere: metabolism and transport Up-regulation of genes encoding C4-dicarboxylate transport protein, DctA (RL3424; Figure 1 ), and PEP carboxykinase, PckA (RL0037; Figure 2 ), reveals increased organic acid metabolism in the rhizosphere. Induction of pckA is required for gluconeogenesis and indicates sugar synthesis. R. leguminosarum represses pckA when grown on organic acids with added sugar [ 9 ] so while sugars are present in the rhizosphere (that is, based on induction of sugar transporters), central metabolism is almost certainly dominated by catabolism of organic acids. Soils are rich in organic acids and they are the main carbon sources in the tomato rhizosphere [ 10 ]. Mutations in both dctA (RL3424) and pckA (RL0037) decreased the ability of R. leguminosarum to compete in the pea rhizosphere as shown by RCIs of 0.65 and 0.57, respectively (Additional file 8 ). The glyoxylate cycle was induced showing that short chain (C2) organic acids are catabolized (Figure 2 ). C1 metabolism is important based on the induction of NAD + -dependent formate dehydrogenase (RL4391-3) in all rhizospheres (Figure 2 ). Formate induced this operon in a laboratory culture of Rlv3841 (Additional file 9 ) and is a carbon source for autotrophic growth of S. meliloti [ 11 ]. Formate dehydrogenase (RL4391-3) requires a Mo cofactor and the gene encoding MoaA2 (RL2711), involved in molybdenum cofactor biosynthesis, showed elevated expression (Figure 2 ). Mutation of moaA2 (RL2711) resulted in a RCI of 0.73 in the pea rhizosphere (Additional file 8 ). In addition, in all the rhizospheres tested there was induction of an ABC transporter solute binding protein (SBP; RL3040) from the MolT (molybdate transporter) family (ABC families are according to Saier [ 12 ]), which is likely to be part of an uptake system for molybdate (Figure 1 ; Additional file 10 ). Aromatic compounds are important precursors or breakdown products of many plant compounds and can be used as a source of carbon by rhizosphere bacteria. Their presence in the rhizosphere is illustrated by induction of genes encoding transport systems for uptake of shikimate and protocatechuate. Shikimate is taken up by a multi-facilitator super-family (MFS) transporter (RL4709). Protocatechuate is imported by a TRAP transporter (pRL120499-pRL120500; Figure 1 ), which was identified by high level induction of pRL120498-500 in microarrays of cells grown in the presence of protocatechuate (Additional files 2 and 5 ). In the pea rhizosphere, mutation of pRL120500 led to a RCI of 0.72 (Additional file 8 ). Catabolism of aromatic compounds has also been shown to be important for Pseudomonas putida in the rhizosphere of Zea mays [ 13 ]. One of the strongest general metabolic responses in the rhizosphere was induction of genes encoding proteins involved in catabolism of phenylalanine and tyrosine (RL1860-6; Figure 2 ). These genes were also induced in free-living cells grown on phenylalanine (Additional file 9 ). The presence of phenylalanine in the rhizosphere probably results from its important role as a precursor for lignin synthesis by roots. Mutation of two genes encoding enzymes on this phenylalanine breakdown pathway (RL1860 and RL1863; Figure 2 ) led to two of the largest reductions in pea rhizosphere competitiveness (RCIs of 0.42 and 0.45, respectively; Additional file 8 ). Common to all rhizospheres was induction of genes for uptake systems for inositol (IntA, RL4655) [ 8 , 14 ] and sorbitol/mannitol/dulcitol (MtlE, RL4218). Also elevated were genes encoding components of two previously uncharacterized systems. The first, RL3840, encodes a CUT1 (carbohydrate uptake transporter 1) family SBP likely to transport raffinose, melibiose and lactose based on 91% identity to SMb20931 from S. meliloti , whose expression was induced by these sugars [ 5 ]. The second, pRL110281, which encodes a PepT (peptide/opine/nickel transporter) family SBP, is clearly important in the pea rhizosphere since mutation of the gene led to a RCI of 0.44 (Additional file 8 ). The contiguous gene, pRL110282, encodes a product with putative α-N-arabinofuranosidase activity that could be responsible for removing arabinose subunits from arabinan. Based on this proximity, pRL110281 may import the arabinose polymer arabinan, or an oligosaccharide derived from it. Indeed, pRL110281 is unlikely to transport arabinose as its gene was not induced in laboratory cultures grown on arabinose (Additional file 9 ). Growth on arabinose did cause induction of genes encoding components of CUT2-family transporters, RL3615-6 and RL2377-8 (Additional files 9 and 10 ), neither of which was elevated in the rhizospheres tested. Co-induction of transport systems and metabolic pathways provides additional evidence of the presence of a compound in the rhizosphere. The gene encoding mannitol dehydrogenase (MalK, RL4214), which converts mannitol to fructose, was elevated (Figure 2 ) along with those of a mannitol uptake system (MtlE, RL4218; Figure 1 ). Although intA (RL4655), encoding the myo -inositol transporter, was induced, genes for inositol catabolism were not. Induction of uptake genes may occur at lower substrate concentrations than for catabolic genes, and there are many examples in our data where catabolic genes were less induced than corresponding transport genes. The genes encoding a CUT1 family ABC system (RL3860-2) were induced in all rhizospheres and although the solute specificity of this system is unknown, it clearly has a role in the pea rhizosphere as a mutation in RL3860 led to a RCI of 0.58 (Additional file 8 ). The transporter genes are surrounded by genes encoding predicted mandelate racemase/muconate lactonising proteins (RL3858, RL3864-66), a family of enzymes involved in breakdown of lignin-derived aromatic compounds, protocatechuate and catechol to intermediates of the citric acid cycle via the β-ketoadipate pathway. Although the transport genes were induced in all rhizospheres, of the genes encoding lignin breakdown enzymes only RL3864 was slightly elevated in the alfalfa rhizosphere (1.5-fold, P ≤ 0.05) and RL3866 in the pea rhizosphere (1.4-fold, P ≤ 0.05). Examination of ABC transporters with unknown solute-specificity shows that 11 genes encoding CUT1 transporters were induced in plant rhizospheres (Figure 1 ). An increase of expression of CUT1 systems, which usually import oligosaccharides and their derivatives, is consistent with the presence in the rhizosphere of many different poly- and oligosaccharides. In addition, some members of the PepT class also transport oligosaccharides - for example, the α-galactoside (Agp) transporter (pRL110243; Figure 1 ) [ 15 ]. Genes for five PepT transporters were induced in these rhizospheres, with three of unknown solute-specificity induced only in the alfalfa rhizosphere (pRL90101, pRL120243 and pRL120609-10; Figure 1 ). This work supports the hypothesis that the large increase in the number of high-affinity ABC systems in rhizobia (and other α-proteobacteria) results from selective adaptation to the oligotrophic nature of soil and the rhizosphere. General adaptation to the rhizosphere: dealing with adversity Plants produce antimicrobial agents (for example, phytoalexins) that bacteria must degrade or export. Plant-made antimicrobials such as halogenated hydrocarbons (for example, dichloroethane) could be dealt with by induction of RL4047 and RL4267, whose products may catalyze conversion of dichloroethane via chloroacetic acid to glycolate, with further degradation by the glyoxylate cycle (Figure 2 ). RL4267 shows 84% identity to a Xanthobacter autotropicus enzyme involved in 1,2-dichloroethane degradation [ 16 ]. Mutation of RL4267 resulted in a strain with reduced competitiveness in the pea rhizosphere (RCI = 0.47; Additional file 8 ). There have been descriptions of other haloalkanoate dehalogenases in Rhizobium sp. [ 17 ], suggesting halogenated hydrocarbons may act as antimicrobials around roots. In addition to metabolic detoxification, expression of the multi-drug resistance (MDR) family efflux pump encoded by rmrA (pRL90059) was elevated (Figure 1 ). RmrA is a membrane fusion protein whose role is typically to dock an inner membrane exporter to a TolC-like protein that spans the periplasm and outer membrane. An R. etli rmrA mutant produced 40% less nodules on bean roots and had increased sensitivity to phytoalexins, flavonoids and salicylic acid [ 18 ]. Another membrane fusion protein elevated in all rhizospheres is encoded by RL4274, a RND (resistance-nodulation-cell division) multi-drug exporter (Figure 1 ). The importance of this system in the pea rhizosphere is demonstrated by a mutant of RL4274 having a RCI of 0.57 (Additional file 8 ). Maintaining the correct osmotic environment is important for bacteria in any situation. In all rhizospheres there was elevated expression of ndvA (RL4640). NdvA is responsible for export of cyclic β-1-2-glucan to the bacterial periplasm and important in rhizobia for hypoosmotic regulation [ 19 ] (Figure 1 ). Expression of RL1908, encoding a small-conductance mechanosensitive ion channel (MscS), was also elevated in the rhizospheres examined (Figure 1 ) and is important in osmotic homeostasis. This suggests that the test microcosm was mildly hypoosmotic. Elevation of expression of genes involved in response to stress occurred in all rhizospheres (Figure 3 ). Mutation of RL3982 and RL4265 ( msrB ), which encode general- and oxidative-stress proteins, reduced pea rhizosphere competitiveness (RCIs of 0.52 and 0.55, respectively; Additional file 8 ). Some of the largest effects on ability to compete in rhizospheres were shown by mutation of genes encoding proteins of unknown function; the photo reaction centre (PRC) family protein RL0913 and flavoprotein RL3366 had RCIs of 0.42 and 0.43, respectively, in the pea rhizosphere (Additional file 8 ). Mutation of RL2946, encoding part of a two-component sensor regulator (Figure 3 ), led to a RCI of 0.59 in the pea rhizosphere (Additional file 8 ). Specific adaptation to legume rhizospheres The largest class of genes induced only in legume rhizospheres were the nod genes ( nodABCEFIJLMNO ), required for synthesis and export of nodulation factors (Figure 3 ). This acts as an exquisite internal control since nodulation factors are specifically induced in response to secretion of flavonoids by legumes [ 3 ]. There is also a legume rhizosphere-specific transporter encoded by pRL90085 (Figure 1 ) shown to be important in the pea rhizosphere as mutation led to a RCI of 0.52 (Additional file 8 ). Although the solute is unknown, it is probably a monosaccharide, as pRL90085 is in the CUT2 family. Specific adaptation to the pea rhizosphere Increased expression of genes encoding enzymes of the glyoxylate cycle (RL0054, RL0866) only occurred in the pea rhizosphere. RL0054 (malate synthase) forms malate from glyoxylate and acetyl CoA while GlcF (RL0866) probably converts glycolate to glyoxylate (Figure 2 ). Thus, while C2 metabolism is elevated in all rhizospheres, it is particularly important in that of pea. Curiously, although the gene for isocitrate lyase (RL0761, aceA ) was up-regulated in both alfalfa and sugar beet rhizospheres, indicating elevated C2 metabolism, expression of RL0054, encoding malate synthase, was only elevated in that of pea (Figure 2 ). The gene for MFS transporter of tartrate (RL0996) was induced by three-fold or more in the pea rhizosphere (Figure 1 ; Additional file 7 ) while that for tartrate dehydrogenase (RL0995), which converts tartrate to oxaloglycolate for metabolism by the glyoxylate cycle, was only induced by legumes [ 20 ] (Figure 2 ). Mutation of RL0996, encoding the tartrate transporter, led to the largest effect on ability to compete in the pea rhizosphere (RCI = 0.35; Additional file 8 ). RL0996 was also induced 1.5-fold in the alfalfa rhizosphere, so although this falls below our two-fold cutoff, it suggests tartrate utilization may be important in legume rhizospheres (Additional file 8 ). However, tartrate may be more generally important as in Agrobacterium vitis the ability to utilize tartrate offered a selective advantage for growth on grapevine [ 21 ]. The importance of pRL8 in the pea rhizosphere R. leguminosarum Rlv3841 has a chromosome and six plasmids designated pRL7-pRL12, with pRL10 containing most nodulation and nitrogen fixation genes [ 22 ]. Although pea rhizosphere-induced genes from different parts of the genome have been discussed above, many genes on pRL8 are specifically up-regulated in the pea rhizosphere (Figure 4 ; Additional file 6 ). Indeed, 37% (11 genes) of the 30 genes elevated by three-fold or more specifically in the pea rhizosphere (using both direct and indirect comparisons (Additional file 7 )) are encoded on pRL8. With a threshold of up-regulation of two-fold or more ( P ≤ 0.05), then 21 genes on pRL8 are pea rhizosphere-specific (15% of all genes on pRL8). By comparison, only three and two genes on pRL8 were up-regulated in alfalfa and sugar beet rhizospheres, respectively, and two genes were up-regulated in the legume rhizosphere. Since plasmid pRL8 is conjugative [ 22 ], it can easily transfer between rhizobia. Consistent with its heavy bias to genes important in the pea rhizosphere, pRL8 shows little colinearity (< 5%) with other sequenced rhizobial genomes [ 23 ]. BLAST analysis shows that of its 142 genes, 25% are found only in R. leguminosarum bv viciae and a further 42% are specific to rhizobia or related α-proteobacteria. Figure 4 Expression pattern of a pea rhizosphere specific region of pRL8 . Abbreviations: Pea rh, bacteria grown in the pea rhizosphere; FL, free-living bacteria; alf rh, bacteria grown in the alfalfa rhizosphere; SB rh, bacteria grown in the sugar beet rhizosphere. Genes on pRL8 that are pea rhizosphere-specific include a molybdenum-containing xanthine dehydrogenase-like carbon monoxide dehydrogenase, CoxMSL (pRL80023-25), together with accessory protein CoxG (pRL80021). Nearby are genes for proteins that may be involved in maturation of this complex: proteins involved in molybdopterin biosynthesis (pRL80034 and pRL80033 encode MoaA and MoeA-like proteins, respectively) and CoxI (pRL80038), which is needed for insertion of a molydopterin cofactor into a xanthine dehydrogenase. However, while CoxMSL (pRL80023-25) may be able to catalyze CO conversion to CO 2 (Figure 2 ), in phylogenetic clustering these proteins form a separate clade from the biochemically characterized CO dehydrogenases, including one from Bradyrhizobium japonicum [ 24 ]. Mutation of pRL80021 ( coxG ) and pRL80023 ( coxM ) resulted in reduced competitiveness in the pea rhizosphere (RCIs of 0.44 and 0.73, respectively; Additional file 8 ). Since pRL80021 is up-regulated only in the pea rhizosphere, its mutation did not result in reduced competitiveness in the alfalfa rhizosphere (RCI = 0.97; Additional file 8 ). Homoserine is abundant in pea root mucilage and can be utilized as a carbon source by R. leguminosarum [ 25 ]. Although the genes involved in catabolism of homoserine are uncharacterized in Rlv3841, pRL80071, which encodes a putative homoserine dehydrogenase (which catalyses conversion of homoserine to L-aspartate-semialdehyde), was specifically up-regulated in the pea rhizosphere (Figure 2 ). Tryptophan is probably available in the rhizosphere [ 26 ]. The gene encoding N-formylkynurenine formidase (pRL80036) was six- to ten-fold elevated in the pea rhizosphere (Figure 4 ). It catalyzes release of formate and kynurenine from N-formylkynurenine, formed after the first step in tryptophan catabolism. The formate produced might be further metabolized to CO 2 by a NAD + -containing short-chain dehydrogenase encoded by pRL80037, whose expression is 2.5- to 3.5-fold elevated (Figure 4 ). Mimosine (β-3-hydroxy-4 pyridone amino acid), a toxic amino acid related to tyrosine, is produced by the tree-legume leucaena, which is nodulated by Rhizobium sp. TAL1145. Rhizobium sp. TAL1145 has a specific ABC importer for mimosine (MidABC) and an aminotransferase responsible for its degradation (MidD) [ 27 ]. An ABC importer (encoded by pRL80060/pRL80063-4; Figure 1 ), which shows 44 to 79% identity to MidABC [ 27 ], was induced in the pea rhizosphere. However, there is no protein in Rlv3841 with > 27% identity to the aminotransferase required for mimosine degradation. While the transporter encoded by pRL80060/pRL80063-4 is unlikely to transport mimosine, it may transport a similar amino acid. Expression of this system was also elevated in 7-day-old pea bacteroids [ 8 ]; thus, it may have a role in the symbiotic interaction between Rlv3841 and pea. Also elevated specifically in pea rhizospheres were pRL80026-30, which encode proteins belonging to the HAAT (hydrophobic amino acid transporter) ABC family (Figure 1 ). Despite the fact that this transporter has been annotated as a LIV (leucine, isoleucine, valine) system, it could transport one or more aromatic amino acid(s) or homoserine. Mutation of pRL80026 resulted in a RCI of 0.69 in the pea rhizosphere (Additional file 8 ). Dealing with adversity in the pea rhizosphere Export of plant toxins is likely to be important for successful growth in the rhizosphere. The gene encoding the RND family exporter RL4274 was induced 3.5- to 2.8-fold in the rhizospheres of alfalfa and sugar beet and 135-fold ( P ≤ 0.05) in pea (Figure 1 ). In addition, secDF2 (RL0680) encodes a membrane protein specifically induced to a very high level only in the pea rhizosphere (> 100-fold, P ≤ 0.05; Figure 1 ). SecDF homologues belong to the RND exporter superfamily and RL0680 may participate in metabolite rather than protein export. It is clear that SecDF2 has a key role affecting competitiveness in the pea rhizosphere since a mutant in this gene had a RCI of 0.45 (Additional file 8 ). In contrast, in the alfalfa rhizosphere the same mutant had a RCI of 0.97 (Additional file 8 ), showing that mutation of secDF2 has no significant effect on its ability to compete with Rlv3841in the alfalfa rhizosphere. The mildly hypoosmotic nature of the general rhizosphere microcosm was revealed by the induction of genes encoding cyclic β-1-2-glucan exporter (NdvA, RL4640) and a mechanosensitive ion channel (MscS, RL1908) (Figure 1 ). In addition, the gene for a second MscS (RL1522) was specifically induced in the pea rhizosphere (Figure 1 ), presumably fine-tuning the osmotic response. Specific adaptation to the alfalfa rhizosphere A dicarboxylate may be a key carbon source in the alfalfa rhizosphere since genes for the malonate transporter (MatC, RL0992; Figure 1 ) and enzymes for malonate metabolism to acetyl CoA (MatA, RL0990, and MatB, RL0991; Figure 2 ) were induced. Alternatively, the malonate present in the alfalfa rhizosphere may need to be detoxified as it can act as an inhibitor of succinate dehydrogenase. Canavanine is a toxic amino acid analogue of arginine found in seeds and exudates of leguminous plants [ 28 ]. The canavanine exporter MsiA from Mesorhizobium tianshanense shows 97% identity with RL2856. In Rlv3841, expression of RL2856 was specifically elevated in the alfalfa rhizosphere (Figure 1 ). Canavanine comprises 0.6 to 1.6% of the dry weight of alfalfa seeds and restricts growth of bacteria [ 28 ]. MsiA (RL2856) was slightly induced in vetch bacteroids (3.2-fold, P = 0.07) [ 8 ], suggesting that vetch releases some canavanine. MsiA is important for attachment to root hairs and survival in rhizospheres of canavanine-producing legumes [ 29 ]. The ability to deal with toxic canavanine may enable selection of MsiA-producing bacteria by these leguminous plants. RL2720 encodes a CUT2 family SBP specifically induced in the alfalfa rhizosphere (Figure 1 ). From the up-regulation of expression of RL2720-2 (4- to 25-fold) in microarrays of cells grown in the presence of arabinogalactan (Additional file 9 ), this cluster of genes may encode an arabinogalactan transporter (Additional file 10 ). In addition, this gene cluster encodes two transketolases (RL2718-19). Expression of RL2719 was elevated (12-fold) in the alfalfa rhizosphere (Additional file 7 ), as was that of a short chain dehydrogenase (RL2725). The proteins encoded by these genes may have a role in arabinogalactan metabolism. These genes were not elevated in microarrays of cells grown on galactose or arabinose (Additional file 9 ), indicating a response only to the polysaccharide or to oligosaccharide break-down products (and not the monosaccharide constituents) of arabinogalactan. Specific adaptation to the sugar beet rhizosphere Comparative analysis reveals that the sugar beet rhizosphere is N-limited. Expression of genes encoding glutamine synthetase II (GlnII, RL3549), the NH 4 + transporter AmtB (RL4564) (Figure 1 ) and PAAT (polar amino acid transporter) family importer pRL120079 (Figure 1 ) was elevated, as they were in all N-limited microarrays (Additional files 7 and 9 ). As these experiments were deliberately conducted in N-free plant growth medium, it is not surprising that the sugar beet rhizosphere was N-limited. However, legume rhizospheres were not N-limited, indicating release of nitrogen into the rhizosphere, possibly specifically because rhizobia were present. Response to root secretions compared with growth in the rhizosphere As useful information about how micro-organisms respond to the rhizosphere can be obtained by incubating bacteria in root secretions [ 6 ], bacterial responses to constituent components were measured (Table 1 ). Pea root exudate was added to liquid-grown cells and microarray analysis showed 21 genes elevated by ≥ 3-fold ( P ≤ 0.05), 18 of which were also elevated by growth in medium containing the flavonoid hesperetin (27 genes elevated ≥ 3-fold, P ≤ 0.05) (Additional file 6 ). Common induced genes, in addition to the nod and rhi gene clusters on pRL10 ( nodABCEFIJLMNO and rhiIABC ), include RL2418, encoding a CUT1 ABC transporter (and also induced three-fold or more in all rhizospheres and in the presence of acetoacetate, hydroxybenzoate and protocatechuate) (Additional files 6 and 9 ). Expression of RL2418 is clearly important for pea rhizosphere growth as a mutant showed much reduced competitiveness with Rlv3841 in the pea rhizosphere (RCI 0.43; Additional file 8 ). Genes elevated under these two conditions (root exudate and hesperetin) form only a small proportion of those elevated in plant rhizospheres. One reason is that root secretions are very dilute and only induce genes responsive to low concentrations of bioactive compounds (for example, nod genes). Furthermore, growth in the rhizosphere involves a far more complex series of interactions, including attachment to roots, biofilm formation, contact with a complex array of plant macromolecules and cell-cell competition."
} | 9,658 |
38013927 | PMC10566253 | pmc | 4,120 | {
"abstract": "Biohybrid photosynthesis systems, which combine biological and non-biological materials, have attracted recent interest in solar-to-chemical energy conversion. However, the solar efficiencies of such systems remain low, despite advances in both artificial photosynthesis and synthetic biology. Here we discuss the potential of conjugated organic materials as photosensitisers for biological hybrid systems compared to traditional inorganic semiconductors. Organic materials offer the ability to tune both photophysical properties and the specific physicochemical interactions between the photosensitiser and biological cells, thus improving stability and charge transfer. We highlight the state-of-the-art and opportunities for new approaches in designing new biohybrid systems. This perspective also summarises the current understanding of the underlying electron transport process and highlights the research areas that need to be pursued to underpin the development of hybrid photosynthesis systems.",
"introduction": "1. Introduction Increasing global energy demands force us to seek environmentally sustainable alternatives to fossil fuels. 1 Solar energy is a renewable energy source that could address this need over the next century. 2 The use of solar energy requires solar capture/conversion and storage; chemical fuels are one sustainable solution to energy storage. 3 A wide range of potential fuels can potentially be generated including hydrocarbons, nitrogen-based fuels, and hydrogen. 4 Beyond the direct use as fuels, new solar-derived chemical building blocks can also play an important role in the chemical industry, which is still heavily dependent on non-renewable feedstocks. 5 Over billions of years of evolution, photosynthetic organisms have developed the photosynthetic machinery to capture sunlight and convert it into organic molecules ( i.e. , biomass) to store solar energy in the form of chemical bonds. 6–8 Natural photosynthesis is relatively inefficient compared to the potential thermodynamic limit; a maximum photosynthetic efficiency of about 4.5% has been calculated by Thorndike. 9 It has been a long-standing challenge to develop practical artificial photosynthetic systems and many different approaches have been used such as photoelectrochemical systems, 10 photovoltaic cells, 11 and photocatalyst materials. 12,13 Artificial photosynthesis mimics these biological systems by using solar energy to drive a thermodynamically uphill reaction to generate fuels. 14 Photogenerated charge carriers are used for hydrogen production from water or to produce other organic molecules, such as methanol via CO 2 reduction. 2 Typically, the solar-to-hydrogen efficiency is much lower than those of photosynthetic organisms, 6 even though solar light absorption process can be more efficient in artificial semiconductors. Biological systems also have numerous advantages of over artificial photosynthesis, including the ability to continually and selectively generate active multi-complex macromolecules and to facilitate electron transfer, as well as sustainable repair and physiological regulation. 28 Hence, to enhance solar-fuel conversion efficiencies, different strategies have been employed to interface synthetic and biological components. This has prompted researchers to explore artificial photosynthetic systems that are inspired by natural photosynthetic machinery, with the aim of combining the advantages of biological systems with carefully designed semiconductors. This relatively new approach is often termed semi-artificial photosynthesis or biological-chemical hybrid photosynthesis. 28 In these hybrid systems an irradiated material captures solar energy, generates individual charges and transfers photoexcited electrons to biocatalysts, including enzymes and microbes, to produce hydrogen or other products. Progress has been made in this field since the early 1980s when scientists began to combine inorganic semiconductors with microorganisms to increase hydrogen production, 29 but semi-artificial photosynthesis has only been studied more extensively since the beginning of this century. A range of systems that capture sunlight can be coupled with biological systems such as photovoltaics, 30 photoelectrodes, 31 and photocatalysts, 32 thus allowing the construction of diverse hybrid photosynthetic systems. Most studies report either hydrogen or acetate as their product ( Table 1 ). The crucial goal of biohybrid photosynthetic systems is to transform essentially inexhaustible atmospheric CO 2 , N 2 , or even wastewater into high-value chemicals with high yield and selectivities, 31,33 and in the longer term, with high catalyst stability. Summary of selected cell/photosensitizer-based biohybrid systems for semi-artificial photosynthesis Material Size and morphology Microorganism Product and activity Ref. CdS <10 nm; NPs \n M. thermoacetica \n Acetate, 0.48 mM day −1 , QE: 2.14 ± 0.16% \n 15 \n CdS, TiO 2 –MnPc <10 nm; NPs \n M. thermoacetica \n Acetate, 1.2 mM day −1 \n 16 \n TiO 2 Anatase powder Engineered E. coli Hydrogen, 0.72 μmol min −1 (mg wet cell) −1 \n 17 \n Water-soluble dyes, inorganic complexes n.d. \n S. oneidensis \n Activity for several processes: H 2 production, fumarate and pyruvate reduction, CO 2 reduction \n 18 \n CdS 15–20 nm; NPs \n E. coli \n Hydrogen, >1.8 mmol over 3 hours \n 19 \n CdS <50 nm; NPs Engineered E. coli Hydrogen, 13.4 μmol after 6 hours, 81.8 μmol after 24 hours (10 8 cells) \n 20 \n AuNCs Nanocluster \n M. thermoacetica \n Hydrogen, after 24 hours overall QE: 2.86 ± 0.38% \n 21 \n PFP/PDI n.d. \n M. thermoacetica \n Acetic acid, 0.63 mM accumulated over a 3 day experiment, QE: 1.6% \n 22 \n CdS 4.1 ± 1.4 nm; NPs \n S. oneidensis MR-1 \n Hydrogen, 362.44 ± 119.69 μmol mg −1 produced over a total of 72 hours \n 23 \n CdS/CsgA A7 Nanofibers Engineered E. coli Formic acid, 0.84 mM within 8 hours, QE: 0.13% \n 24 \n PFTP–PSMA D–A CPNs@threonine deaminase 93.2 ± 8.2 nm; NPs Engineered E. coli 2-Oxobutyrate, 6.0 ± 0.15 mM cumulative over 72 hours \n 25 \n La/Rh co-doped SrTiO 3 , Mo-doped BiVO 4 Monolithic photocatalyst sheets \n Sporomusa ovata \n Acetate, solar-to-fuel conversion efficiency of 0.7% at ambient conditions (298 K, 1 atm) \n 26 \n PFODTBT polymer dots Average size 70 nm; polymer dots \n Ralstonia eutropha H16 \n Poly-3-hydroxybutyrate, a yield of 21.3 ± 3.78 mg L −1 \n 27 \n Although research programmes in artificial photosynthesis and synthetic biology are moving the field of semi-artificial photosynthesis forward, many of the fundamentals are still under investigation. In particular, the design principles underpinning the construction of functional hybrid systems, and an in-depth understanding of the extracellular/intracellular electron transfer pathways has not been achieved, even though both are crucial steps in these hybrid systems. A central problem here is that the interfaces between the biological and synthetic materials are often not well understood."
} | 1,744 |
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