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30496179 | PMC6264808 | pmc | 3,252 | {
"abstract": "Speech recognition (SR) has been improved significantly by artificial neural networks (ANNs), but ANNs have the drawbacks of biologically implausibility and excessive power consumption because of the nonlocal transfer of real-valued errors and weights. While spiking neural networks (SNNs) have the potential to solve these drawbacks of ANNs due to their efficient spike communication and their natural way to utilize kinds of synaptic plasticity rules found in brain for weight modification. However, existing SNN models for SR either had bad performance, or were trained in biologically implausible ways. In this paper, we present a biologically inspired convolutional SNN model for SR. The network adopts the time-to-first-spike coding scheme for fast and efficient information processing. A biological learning rule, spike-timing-dependent plasticity (STDP), is used to adjust the synaptic weights of convolutional neurons to form receptive fields in an unsupervised way. In the convolutional structure, the strategy of local weight sharing is introduced and could lead to better feature extraction of speech signals than global weight sharing. We first evaluated the SNN model with a linear support vector machine (SVM) on the TIDIGITS dataset and it got the performance of 97.5%, comparable to the best results of ANNs. Deep analysis on network outputs showed that, not only are the output data more linearly separable, but they also have fewer dimensions and become sparse. To further confirm the validity of our model, we trained it on a more difficult recognition task based on the TIMIT dataset, and it got a high performance of 93.8%. Moreover, a linear spike-based classifier—tempotron—can also achieve high accuracies very close to that of SVM on both the two tasks. These demonstrate that an STDP-based convolutional SNN model equipped with local weight sharing and temporal coding is capable of solving the SR task accurately and efficiently.",
"conclusion": "Conclusion To provide an alternative speech recognition solution to ANNs which is biologically implausible and energy-intense, we proposed an STDP-based SNN model with the time-to-first-spike coding scheme and the local weight sharing strategy. It can achieve high accuracies on two speech recognition tasks. By adopting STDP learning rule and the temporal coding scheme, our SNN is able to learn acoustic features fast and efficiently, and make the speech data low-dimensional, sparse, and more linearly separable. Compared to global weight sharing, the proposed local weight sharing is more suitable for learning the features of speech signals. Moreover, our model can achieve comparable performance to traditional ANN approaches when using SVM as a classifier, and can also work well when using the spike-based classifier—tempotron. Therefore, in practice, due to the spike-based computation, our model with tempotron can be implemented on neuromorphic chips easily as a speech recognition solution with ultra-low power consumption. In summary, our study shows that a biologically plausible SNN model equipped with STDP, local weight sharing, and temporal coding has the ability of solving speech recognition tasks efficiently.",
"introduction": "Introduction Automatic speech recognition is the ability for a machine to recognize and translate spoken language into text. It is a challenging task since the speech signal is high variable due to different speaker characteristics, varying speaking speed, and background noise. In recent years, artificial neural networks (ANNs), especially deep neural networks, have outperformed traditional Gaussian mixture models and became the predominant method in speech recognition area [ 1 ]. ANNs are inspired by features found in brain. They consist of multiple layers of artificial neurons which are able to learn data representations from the input data by gradient descent algorithms [ 2 , 3 ]. In some scenarios, ANNs can reach or surpass human level performance. Despite the biological inspiration and high performance, ANN models are fundamentally different from what are actually observed in biology in two main aspects. Firstly, the artificial neurons in ANNs communicate with each other by sending real numbers which can be seen as their firing rates. In contrast, neurons in biological neural networks communicate via spikes or pulses. Secondly, the standard training method for ANNs is backpropagation [ 4 ], which update weights of neurons calculated from non-local error signals and weights of downstream synapses. However, it seems quite implausible that this process of non-local information propagation would occur in the cortex [ 5 ], in which neurons just communicate with each other based on spikes from direct connections, and the synaptic strengths are generally modified by activities of corresponding pre- and post-synaptic neurons, e.g. spike-timing-dependent plasticity (STDP) [ 6 – 10 ]. STDP was found in experiments in many cortex regions [ 6 , 9 , 10 ] and was believed to be a basic principle for the formation of recognition and memory in human brain. Besides, compared to the brain’s energy efficiency, both training and execution of large-scale ANNs need massive amounts of computational power to perform single tasks. For these reasons, there has been a growing interest in spiking neural networks (SNNs) recently. Like in the brain, a neuron in the SNNs fires only when its membrane potential reaches its threshold. When a neuron fires, its post-synaptic neurons receive the spike and update their potentials. When implemented on neuromorphic platforms like TrueNorth [ 11 ], the SNNs can operate with ultra-low power consumption. Although in both theoretic [ 12 ] and model studies [ 13 – 17 ], SNNs have been shown their powerful ability and advantages in kinds of machine learning tasks, the development on SNN models is still in a primary stage compared with ANNs. For the speech recognition task, several SNN models have been proposed, which have either recurrent connections or feedforward connections. For the recurrent SNN models, a popular approach is the liquid state machine (LSM) [ 18 – 25 ], which is one of two types of reservoir computing [ 26 ]. A typical LSM consists of three layers (input layer, reservoir layer, and readout layer). The reservoir layer is a collection of recurrently and randomly connected spiking neurons, whose connections can be learned by synaptic plasticity rules [ 23 – 25 ]. The reservoir can serve as a function of short-term memory for storing temporal input information in a higher dimension, this makes LSMs suitable for the speech recognition task [ 19 – 22 ]. Nonetheless, in these models, the feature extraction step is very obscure due to the random projection and there is no concept of receptive field when comparing to the sensory system. Moreover, LSMs increase the separability of data by mapping them into a higher dimension, which is not very efficient. For the class of SNN models with feedforward connections, Wade et al. [ 27 ] presented a synaptic weight association training (SWAT) algorithm for SNNs, which merges the Bienenstock–Cooper–Munro (BCM) learning rule with STDP. But an additional training neuron is used to train the synaptic weights of output neurons and removed after training, which is not biologically reasonable. Tavanaei and Maida [ 28 ] proposed a two layer SNN model which learns to convert a speech signal into a distinguishable spike train signature. Their model is trained by switching between Hebbian and anti-Hebbian STDP rule based on the label of current sample. The performance of this model was not good, and their encoding method is inefficient. Another SNN model proposed by Tavanaei and Maida [ 29 ] uses probabilistic STDP to extract discriminative features from speech signals. Their model achieved high performance on the speech recognition task, but the convolutional layer which extracts primary auditory features uses hand-crafted Difference-of-Gaussian (DoG) filters, which is unlikely to happen in biological auditory systems. Therefore, for the purpose of both biological plausibility and energy efficiency, here we proposed a feedforward SNN with STDP and fast temporal encoding scheme for the speech recognition task. Our model was inspired by [ 30 ] and [ 31 ], it consists of a convolutional layer and a pooling layer. In the convolutional layer, the receptive fields of neurons are learned by STDP to extract acoustic features from speech signals. Moreover, the weights in the convolutional layer are shared locally to better capture the features of spoken words. The pooling layer performs a pooling operation to reduce the size of feature maps in the convolutional layer. For a fast and efficient encoding, the time-to-first-spike coding scheme [ 32 ] is adopted in our model. Finally, the output of the pooling layer is used to train a linear classifier. We evaluated our model with a linear classifier on the isolated spoken word recognition task on the TIDIGITS dataset [ 33 ], and achieved an accuracy which outperformed all other SNNs and was comparable to the best result of ANNs. More analysis on network outputs reveal that STDP is able to extract features of speech signals to make speech data more separable. Furthermore, the validity of our model can also be well maintained by changing the classifier to tempotron [ 34 ] and the dataset to the TIMIT dataset [ 35 ].",
"discussion": "Discussion Spiking neural networks had been gradually drawing attention due to its potential of solving ANNs’ problems of biological implausibility and computational intensity. However, it is not easy to train a SNN well for typical pattern recognition tasks, and various training methods have been proposed previously [ 13 ]. Many studies chose to train a traditional ANN instead, and convert it to a SNN by replacing each rate-based neuron with a spiking neuron [ 15 , 16 , 55 – 58 ]. Although they showed good performance on pattern recognition tasks, the problem of training a SNN was actually bypassed. Some researchers used differentiable formulations of SNNs, so they could train them with backpropagation directly [ 14 , 59 ]. With this approach, the training algorithm searches a larger solution space and can achieve better performance. These methods are not biologically plausible since there are no evidence that error backpropagation could happen in the brain. In contrast, our model uses the STDP rule observed in biological synapses to train the SNN. Particularly, since STDP is a local and unsupervised learning rule, the training process doesn’t need any label information. Thus our SNN model is able to utilize the large amount of unlabeled data, which is less expensive and easier to obtain than labeled data. Moreover, a simple linear classifier (linear SVM or spike-based tempotron) can be sufficient to classify the STDP-trained data with high accuracies, this reveals powerful ability of our model for extracting input features in a more biologically realistic way. There were other studies which also use STDP as the learning rule [ 28 – 31 , 40 ]. Masquelier et al. [ 30 ] proposed a SNN which has a similar convolutional architecture to ours. The model has a four-layer hierarchy (S1–C1–S2–C2) where simple cells (S) gain selectivity from a linear sum operation, and complex cells (C) gain invariance from a max pooling operation. The S1 layer uses fixed Gabor filters to detect edges on various scaled versions of the input image. The S2 layer is selective to intermediate-complexity visual features. The C1–S2 synaptic connections are adjusted by STDP, and there is local inhibition between different S2 cells. The main difference between their network and ours is that the weights in their S2 layer are shared globally, while we use local shared weights to extract spatiotemporal features of acoustic signals, and it is more suitable for speech recognition tasks. Besides, we didn’t use various scaled versions of the input like they did, and our network completes the recognition task with only two layers, while they used one more layer with fixed hand-crafted weights. The work of Kheradpisheh et al. [ 31 ] was also inspired by Masquelier et al. [ 30 ], their model consists of multiple convolutional layers and pooling layers, this could benefit the image recognition task, in which all visual features can appear at any location of the input image. Compared to their work, our SNN only uses one convolutional layer and one pooling layer, as well as adopting local weight sharing instead of global weight sharing. Tavanaei et al. [ 29 ] also proposed a convolutional SNN for SR. In their model, the speech signal is converted into spikes trains using a Poisson process, from which the convolutional layer extracts primary acoustic features with shifted DoG filters, the generated feature maps are then pooled and sent to the feature discovery layer, which undergoes learning via a probabilistic STDP rule. The output of the network are used to train a hidden Markov model for evaluation. Our model is different from theirs in two ways. First, we use a more efficient temporal coding scheme instead of the rate-based Poisson process. Second, our model extracts primary acoustic features with STDP-trained receptive fields, while they extracted primary acoustic features by using shifted DoG filters, which are normally adopted to extract visual contrast informations, but there is no evidence of this mechanism in the auditory system. Our model and the studies mentioned above have proven the effectiveness of STDP learning rule, but why STDP can work so well, since the construction of STDP-trained SNN models is often more heuristic than analytic? Actually, the learning process with STDP and lateral inhibition can roughly be seen as the sequential k-means (online k-means) algorithm [ 60 ]. In the sequential k-means algorithm, firstly initial centroids of data are guessed, then the data points are processed in a sequential order, each new data point is assigned to the closest centroid, and the corresponding centroid is moved closer to the data point after the assignment, these two steps are repeated until all data points are processed. With STDP and lateral inhibition, the learning process of the SNN is similar: the samples are fed into the SNN sequentially, for each input the neuron with the most similar receptive field will respond most strongly, and its weights will be updated by STDP to be more similar to its input, while the rest of neurons are laterally inhibited. For the convolutional structure in our model and the model in [ 30 ], the convolutional k-means method in [ 61 ] is comparable. Therefore, the convergence of k-means implies the convergence of STDP-based training. However, k-means algorithm may converge to a local minimum, so the STDP-based learning is likely to suffer from the same weakness. One of the most important features of our SNN is the time-to-first-spike coding, which is faster and more efficient than the traditional rate coding. However, this coding scheme is ideal and highly simplified, since it assumes that all information about the stimulus is contained in the time of the first spike of a neuron, and all the following spikes are neglected. Rolls et al. [ 62 ] compared the information of the presented stimulus in the first spike and in the number of spikes in a given time window, and found that more information is available if all the spikes in the given time window are taken into account. Another weakness of the time-to-first-spike coding scheme is its vulnerability to noise, which means that even a single noise spike could heavily disrupt the information to be transmitted. On the other hand, the rate coding is inefficient but highly robust against noise, which is an essential feature of auditory system. Therefore, in the future research, the temporal coding scheme of utilizing all spikes responded to a stimuli should be considered to improve robustness as well as performance. With regard to the application in industry, our model has the potential to be implemented on neuromorphic chips like TrueNorth [ 11 ] or Loihi, which can offer ultra-low power consumption. Although theoretically all SNNs can run on the neuromorphic chips during their prediction stage to save energy, for those SNNs which are trained by backpropagation directly or indirectly, the learning process still consumes significant power and time. However, with some chips support STDP learning rule [ 63 – 66 ], our SNN, as well as other SNNs trained by STDP, are able to achieve a low energy consumption even in the training stage. Previous experimental studies had shown that there are both feedforward and feedback circuits in the auditory pathway [ 67 ], while our model only takes feedforward connections into consideration. Therefore, in the future, we could add feedback connections between layers into the network. With a recurrent structure, the signal related to supervised information can be sent back to each neuron through spikes for a more precise weight adjustment, thus a better performance may be achieved. It also should be noted that this is much different from that in typical reservoir computing models where recurrent but fixed connections are adopted."
} | 4,315 |
28428313 | PMC5399272 | pmc | 3,253 | {
"abstract": "ABSTRACT Hydrogenogenic carboxydotrophs may provide hydrogen as primary energy for the microbial community via carbon monoxide oxidation. To investigate the genetics of carbon monoxide metabolism, we report here the draft genome sequences of the hydrogenogenic carboxydotrophs Carboxydocella sp. strains JDF658 (2.60 Mbp; G+C content, 49.2%) and ULO1 (2.70 Mbp; G+C content, 48.8%)."
} | 96 |
19399520 | null | s2 | 3,255 | {
"abstract": "Small changes in environmental conditions can unexpectedly tip an ecosystem from one community type to another, and these often irreversible shifts have been observed in semi-arid grasslands, freshwater lakes and ponds, coral reefs, and kelp forests. A commonly accepted explanation is that these ecosystems contain multiple stable points, but experimental tests confirming multiple stable states have proven elusive. Here we present a novel approach and show that mussel beds and rockweed stands are multiple stable states on intertidal shores in the Gulf of Maine, USA. Using broad-scale observational data and long-term data from experimental clearings, we show that the removal of rockweed by winter ice scour can tip persistent rockweed stands to mussel beds. The observational data were analyzed with Anderson's discriminant analysis of principal coordinates, which provided an objective function to separate mussel beds from rockweed stands. The function was then applied to 55 experimental plots, which had been established in rockweed stands in 1996. Based on 2005 data, all uncleared controls and all but one of the small clearings were classified as rockweed stands; 37% of the large clearings were classified as mussel beds. Our results address the establishment of mussels versus rockweeds and complement rather than refute the current paradigm that mussel beds and rockweed stands, once established, are maintained by site-specific differences in strong consumer control."
} | 371 |
19107720 | null | s2 | 3,256 | {
"abstract": "Artificial ECMs that not only closely mimic the hybrid nature of the natural ECM but also provide tunable material properties and enhanced biological functions are attractive candidates for tissue engineering applications. This review summarizes recent advances in developing multicomponent hybrid hydrogels by integrating modular and heterogeneous building blocks into well-defined, multifunctional hydrogel composites. The individual building blocks can be chemically, morphologically, and functionally diverse, and the hybridization can occur at molecular level or microscopic scale. The modular nature of the designs, combined with the potential synergistic effects of the hybrid systems, has resulted in novel hydrogel matrices with robust structure and defined functions."
} | 194 |
31323902 | PMC6680700 | pmc | 3,258 | {
"abstract": "In this study, we used a multifaceted approach to select robust bioaugmentation candidates for enhancing biogas production and to demonstrate the usefulness of a genome-centric approach for strain selection for specific bioaugmentation purposes. We also investigated the influence of the isolation source of bacterial strains on their metabolic potential and their efficiency in enhancing anaerobic digestion. Whole genome sequencing, metabolic pathway reconstruction, and physiological analyses, including phenomics, of phylogenetically diverse strains, Rummeliibacillus sp. POC4, Ochrobactrum sp. POC9 (both isolated from sewage sludge) and Brevundimonas sp. LPMIX5 (isolated from an agricultural biogas plant) showed their diverse enzymatic activities, metabolic versatility and ability to survive under varied growth conditions. All tested strains display proteolytic, lipolytic, cellulolytic, amylolytic, and xylanolytic activities and are able to utilize a wide array of single carbon and energy sources, as well as more complex industrial by-products, such as dairy waste and molasses. The specific enzymatic activity expressed by the three strains studied was related to the type of substrate present in the original isolation source. Bioaugmentation with sewage sludge isolates–POC4 and POC9–was more effective for enhancing biogas production from sewage sludge (22% and 28%, respectively) than an approach based on LPMIX5 strain (biogas production boosted by 7%) that had been isolated from an agricultural biogas plant, where other type of substrate is used.",
"conclusion": "5. Conclusions In this study, we suggested the usefulness of employing genome and metabolic pathway data for strain choice for increasing the hydrolytic activity in biogas reactors. We also investigated the relationship of the isolation source of three bacterial strains and their metabolic potential as well as their contribution to converting sewage sludge substrates into biogas. Genomic and physiological analyses of phylogenetically diverse strains, Rummeliibacillus sp. POC4, Ochrobactrum sp. POC9 (both isolated from sewage sludge) and Brevundimonas sp. LPMIX5 (isolated from an agricultural biogas plant) showed their diverse enzymatic activities and their ability to survive under varied growth conditions. The specific type of the enzymatic activity (proteolytic, lipolytic, cellulolytic or xylanolytic) expressed by the strains was linked to the type of the substrate present in the original isolation source, as the strains were naturally acclimated to a given substrate type. The substrate used in anaerobic digestion also affected the effectiveness of the process carried out with a specific strain. Bioaugmentation with sewage sludge isolates—POC4 and POC9—was more effective for AD of sewage sludge than an approach based on the LPMIX5 strain that had been isolated from an agricultural biogas plant, where other type of substrate is used. Genome-wide analyses such as those employed in this work complement physiological tests. Their implementation in biotechnological processes may facilitate the choice of the most suitable candidate strain for a specific bioaugmentation process. Having genome sequencing data for a large strain collection at hand may speed up the development of effective inoculants and help prevent bioaugmentation failure.",
"introduction": "1. Introduction Anaerobic digestion (AD) of sewage sludge at wastewater treatment plants represents one of the most promising bioenergy production techniques. Its first step—hydrolysis—is usually the rate-limiting step in converting waste substrates into biogas [ 1 ]. Diverse approaches, including mechanical, thermal, chemical and biological treatments, were proposed to enhance the process of hydrolysis, and consequently increase, biogas production [ 2 , 3 ]. Broadly defined environment friendliness, minimal formation of inhibitory by-products, low energy requirement, and mild operating conditions [ 3 , 4 ] are the most important advantages in favor of using biological methods over the physical and chemical ones for hydrolysis enhancement. Common biological approaches include bioaugmentation with hydrolytic microorganisms or the addition of hydrolytic enzymes to the system. Whereas the addition of exogenous enzymes to anaerobic bioreactors may boost the performance of AD systems, enzyme activity is affected by a variety of factors, including substrate type, incubation time, system configuration, and the operating conditions (e.g., temperature and pH) [ 5 ]. Moreover, the enzymes must often be repeatedly added to a working system, which may render the process more expensive than bioaugmentation with microorganisms. Bioaugmentation is the practice of adding specific microorganisms or microbial consortia to a system to enhance the desired activity [ 6 ]. Microorganisms suited to the bioaugmentation process usually tolerate a wide range of environmental conditions, are capable of growing on unique and diverse substrates by synthesizing unique extracellular degrading enzymes, are robust and competitive after their introduction to a system, and can support the solubilization of organic compounds even in the presence of potential inhibitors [ 7 ]. Their ability to produce secondary metabolites, such as vitamins or biosurfactants, may also be exploited in the process. Microorganisms used in bioaugmentation have been isolated from diverse ecological niches, including soil, agricultural residues, manure or animal rumen, where they often form specialized consortia [ 8 ]. While microbial consortia may offer a broader degrading potential, they are less biologically stable and controllable than single microbial strains that are hence more often used [ 9 ]. The role of bioaugmentation in enhancing methane production was demonstrated for various substrates, which can be grouped into four main categories: sewage sludge [ 10 ]; animal manures [ 11 , 12 ]; food industry waste [ 13 , 14 ], and energy crops or agricultural residues [ 15 , 16 ]. These examples are related to studies performed in lab-scale digesters. Bioaugmentation approaches in biogas production could also be grouped according to the metabolic activity (function) that is augmented, i.e., hydrolysis (as addressed in this study), acidogenesis, acetogenesis, or methanogenesis. The type of substrate used in AD is an important factor affecting AD efficiency, as it influences the composition of microbial consortia and their adaptation to the process in a bioreactor [ 17 ]. Sewage sludge in bioreactors is a challenging environment to thrive because it forces the microbes to compete for abundant yet hardly degradable nutrients and to confront various environmental stresses imposed by a working system [ 7 , 18 ]. The survival of microbial strains or consortia introduced to a wastewater treatment plant is the critical factor for the success of any bioaugmentation strategy [ 7 ]. It has been observed that under the conditions of industrial processes the bioaugmentation candidate strains often do not express the abilities displayed in lab-scale tests (including enzymatic activities and competitiveness). As a consequence, their amount often decreases shortly after inoculation of a bioreactor [ 19 ]. Thus, strain choice has far-reaching consequences for the efficiency of a bioaugmentation process. Whereas remarkable effort was devoted into inoculum strain choice to facilitate biodegradation of sewage sludge [ 10 , 20 ], the availability and attractive cost of whole-genome exploration methods have offered new ways to achieve considerable progress in this topic [ 21 ]. Whole-genome sequencing data of environmental isolates provide a valuable groundwork for understanding, predicting and exploiting their metabolic potential in numerous applications, including enhanced biogas production. The aim of this study was to verify whether and how metabolic potential (encoded in genomic content and expressed under specific conditions) of bacterial strains used for bioaugmentation affects the AD performance. We also investigated the influence of the isolation source of bacterial strains (sewage sludge versus an agricultural biogas plant) on their metabolic potential and their efficiency in enhancing biogas production. In our previous study, we explored a novel bacterial bioaugmentation candidate, Ochrobactrum sp. POC9, which had been isolated from a sewage sludge sample [ 22 ]. The strain exhibited lipolytic, proteolytic, cellulolytic, and amylolytic activities (confirmed by qualitative tests only) and substantially improved biogas production during anaerobic digestion of sewage sludge. The analysis of the POC9 genome content revealed its denitrifying, biofilm forming, and toxic compound (e.g., phenol) utilization abilities. The conducted genomic and physiological analyses demonstrated that the POC9 strain is resistant to several heavy metals (As(III), As(V), Cd(II), Co(II), Cr(VI), Cu(II), Ni(II), and Zn(II)) and antibiotics, such as β-lactams (including ampicillin, cefexime, cefotaxime, and ceftriaxone), as well as rifampicin and chloramphenicol [ 22 ]. In this study, we explored the physiological (metabolic) properties and genome content of two novel isolates– Rummeliibacillus sp. POC4 and Brevundimonas sp. LPMIX5. We then evaluated their efficiency, as well as the efficiency of a previously studied Ochrobactrum sp. POC9, in boosting biogas production from sewage sludge through enhancing the hydrolysis step of anaerobic digestion.",
"discussion": "3. Discussion Bioaugmentation with microorganisms may lead to an increase in biomethane output in anaerobic digestion. The literature review shows that, so far, most of the bioaugmentation studies have been carried out on the laboratory scale, yet there is the potential to scale up the process [ 41 ]. Various types of microorganisms are required for effective anaerobic digestion, i.e. those involved in hydrolysis, acidogenesis, acetogenesis, and methanogenesis [ 42 ]. In this study, we specifically focused on enhancing substrate hydrolysis in an anaerobic digester through the addition of microorganisms capable of breaking down complex constituents of sewage sludge (proteins, lipids, and carbohydrates). We explored the physiological (metabolic) properties and genomic potential of three strains with broad hydrolytic capacities, isolated from two different environments (sewage sludge and agricultural biogas plant) to assess their applicability in bioaugmentation of anaerobic digestion for biogas production. The results of the physiological analyses (including the BIOLOG TM assay) revealed the wide metabolic versatility of Rummeliibacillus sp. POC4, Ochrobactrum sp. POC9 and Brevundimonas sp. LPMIX5. The bacterial isolates displayed proteolytic, lipolytic, cellulolytic, amylolytic, and xylanolytic activities and were able to utilize diverse carbon sources (amines, amino acids, carboxylic and ketonic acids, carbohydrates, and polymers), including alternative waste substrates (molasses, dairy waste, malt extract) for growth. The results also showed the wide adaptability of the three strains to various growth conditions (temperature 15–37 °C and pH 5–10) and their resistance to diverse metals (Cd, Cr, Cu, Zn, Ni, Pb). With those information at hand survival rates of specific bioaugmentation candidates in an anaerobic digester fed with a specific substrate may be better predicted, and operation conditions may be tailored for improved activity of hydrolysis. The search for novel microorganisms with exceptional catabolic or survival abilities and potential biotechnology applications is an ongoing pursuit worldwide. Such microorganisms produce specific enzymes in response to the presence of particular substrates in the environment. Many of them are able to utilize peculiar compounds that are not usually preferred by other microorganisms [ 43 ]. Sagar and colleagues [ 44 ] isolated two lipolytic strains, TU-L1 and TU-L2, from domestic waste dumping site and showed that the optimization of growth conditions, including temperature, pH, agitation (rpm), as well as carbon and nitrogen source had a significant effect on lipase activity. Park and colleagues [ 45 ] described morphological and biochemical properties of four proteolytic Bacillus strains isolated from a rotating biological contactor in wastewater treatments plants and suggested that these bacteria play an essential role in the degradation of proteinaceous organic compounds in wastewaters. Bramucci and Nagarajan used a combination of traditional microbiological tools and molecular biology for isolation and characterization of 27 different groups or species of bacteria from industrial wastewater bioreactors. The isolates were able to grow on various commercial media and degraded a variety of aromatic compounds (e.g. benzene, toluene, xylene, phenol, cumene). The authors suggested that the microorganisms from wastewater bioreactors are easier to isolate and potentially more amenable to industrial applications than those inhabiting extreme environments [ 46 ]. In contrast to those studies, we included detailed analyses of the genome content of the isolated candidate strains for biotechnological applications. The genome-wide study of POC4, POC9 and LPMIX5 strains confirmed the presence of specific genes coding for enzymes enabling the utilization of the following compounds: long-chain fatty acids (starting from palmitoyl-CoA (16C) via beta-oxidation, glutathione, proteins (cysteine-, metallo- or serine-type peptidases), (hemi)cellulose, amylose, and xylose. Results of the genomic analysis also indicated the presence of genes linked to diverse resistance mechanisms to a variety of heavy metals (Cd, Cr, Cu, Zn, Ni, Pb) that are frequently present in sewage sludge. All these genome-driven findings could be useful for tailoring and controlling the sewage sludge degradation process during anaerobic digestion by the strain choice. Previous genome-level studies of microbial biogas producers most often included the phylogenetic and functional characterization of the whole microbial communities inhabiting biogas reactors. In their pioneering effort to deeply characterize the AD microbiome, Campanaro and colleagues [ 47 ] identified nearly one million genes and 106 microbial genomes in the biogas microbial community involved in AD. In this work, we first searched for individual, candidate strains for bioaugmentation of AD. We then characterized three such strains through functional assays and genome and metabolic pathway analyses. The genomic data obtained in this study provides a valuable decision tool for developing tailored, site- and substrate-specific bioaugmentation strategies with any of the three strains in any future efforts. Metabolic versatility is based on the activity of enzymes, especially the hydrolytic (proteolytic, lipolytic, cellulolytic, amylolytic, xylanolytic, etc.) ones. In POC4 and POC9 strains that had been isolated from sewage sludge (which usually contains complexes of proteins, lipids, and a small amount of polysaccharides) only protease, lipase and amylase activities were observed. In contrast, the LPMIX5 strain isolated from an agricultural biogas plant in which maize silage (a lignocellulosic material) is the main substrate, exhibited mainly cellulase and xylanase activities. These findings confirmed the results of previous studies, in which enzymatic activities of isolates were related to the strain’s natural environment and–particularly–to the original substrate. Parawira and co-workers [ 48 ] suggested that the nature of a substrate determines the type of the enzymatic activity of the fermentative bacteria present in a digester and observed a higher amylase activity during mesophilic anaerobic digestion of solid potato waste compared to the activities of other hydrolases. Guedon and colleagues [ 49 ] showed that cellulolytic Clostridia were the dominant strains in anaerobic digesters fed with municipal solid waste or agricultural raw materials containing a high percentage of lignocellulosic compounds. The genomic analysis and functional characterization we performed indicated that POC4 and POC9 are strong candidates for usage in bioaugmentation of anaerobic digestion of sewage sludge, while LPMIX5 may be useful in anaerobic digestion of agricultural waste. In our studies, POC4, POC9 and LPMIX5 strains were tested for the ability to enhance sewage sludge hydrolysis. These abilities were next verified in the biogas production process from sewage sludge under batch conditions. Results showed that bioaugmentation with POC4, POC9 or LPMIX5 contributes to enhanced biogas production (an increase by 23, 22, and 7%, respectively, compared to a non-bioaugmented control). We also observed an increase in sCOD (by 5, 7, and 3% for POC4, POC9, and LPMIX5, respectively) and VFAs concentration (by 16, 27, and 11% for POC4, POC9, and LPMIX5, respectively) after three days, compared to the non-bioaugmented control. The increased sCOD and VFAs concentration probably resulted from the high metabolic (enzymatic) activity of the strains used for bioaugmentation. The higher efficiencies of biogas production and degradation of organic compounds by POC4 and POC9 strains were probably fostered by the pre-adaptation of these bacteria to the AD substrate (sewage sludge), which originated from the same environment they were isolated from. In our previous work, we evaluated the effect of the isolation source of microorganisms on the selection of hydrolytic microbial consortia dedicated to anaerobic digestion of lignocellulosic biomass [ 17 ]. The results indicated that substrate input (and not the community origin) was the driving force responsible for the changes in the community structure of the hydrolytic consortia. In this study, we confirmed the vital role of the type of substrate in the efficiency of anaerobic digestion with specific strains. Many studies demonstrated the enhanced anaerobic digestion of lignocellulosic biomass through bioaugmentation with enzymes, microbial consortia, or single strains. However, only a few compared the efficiency of diverse single strains isolated from various environmental sources in the augmentation of sewage sludge anaerobic digestion. Lü and co-workers [ 50 ] showed that the inoculation with Coprothermobacter proteolyticus isolated from a thermophilic digester that was fermenting tannery waste and cattle manure improved the hydrolysis of proteins and polysaccharides and increased methane production by up to 10.7%. Miah and colleagues [ 51 ] found that the addition of an anaerobic thermophilic bacterial culture of Geobacillus sp. AT1, isolated from aerobically and thermophilically acclimatized sludge, could lead to a 2.1-fold increase in methane production at 65 °C, owing to the protease activity of the strain. Cirne and co-workers [ 14 ] showed that bioaugmentation with a Clostridium lundense lipolytic strain, isolated from bovine rumen, increased lipid hydrolysis and methane production by 10–20% during anaerobic digestion of restaurant lipid-rich waste. Despite using the same single strain-based approach and a similar substrate, the biogas yield results of the above-mentioned studies are difficult to rigorously compare with those reported here. However, in spite of the varying experimental designs (e.g. differences in bacterial strains, AD temperature, sludge composition, bioreactor size), the biogas yield data may be informative when related to the controls. As mentioned above, bioaugmentation very often fails. A number of reasons for the failure were suggested, including the growth-limiting conditions due to low substrate concentration; the presence of inhibitory substances (such as antibiotics and heavy metal ions) in the stream to be treated or released by other microorganisms showing antagonistic effects; the presence of bacteriophages; poor biofilm forming ability [ 52 ], or adverse operating conditions, such as low temperatures [ 53 ]. However, the major assumption is that under the conditions of an industrial process the chosen strains fail to express some of the specific abilities that had been observed in the laboratory with the pure strains following isolation [ 19 ]. This variance could be associated with numerous factors, such as the growth rate being lower than the washout rate in reactors, inadequate inoculum size, or insufficient data on the strain ability to use chemical constituents of biomass as sufficient growth substrates. Bioaugmentation failures indicate that lab-scale phenotypical test results are insufficient for making an accurate decision on strain suitability for particular biotechnological application. Another critical factor for the bioaugmentation success is inoculant compatibility with the indigenous microbial consortium (as indicated previously [ 54 ]). Inoculation of a biosystem with a substantial number of cells of a bioaugmentation strain may disturb the system equilibrium affecting the structure and dynamics of the indigenous microbiome (e.g., [ 55 ]). In terms of enhancing a desired biodegradation process, these changes may be either beneficial or disadvantageous as they cause system function alteration and shift the reaction equilibriums of the bioprocess [ 7 ]. In this study, we focused on enhancing substrate hydrolysis. While indigenous consortium dynamics was not monitored in this study, the bioaugmentation effects reflected as the enhanced biogas production were in line with our expectations. Previous reports suggested that the addition of nutrients and surfactants or the application of sufficient acclimatization periods may–to some extent–overcome the limitations of bioaugmentation [ 10 ]. Based on our study, we suggest that data from genome-wide exploration of the candidate strains may also help prevent bioaugmentation failures in biogas production by providing a better understanding of the degradation pathways, substrate ranges, and survival mechanisms of candidate strains, thus laying the groundwork for an optimal strain choice for specific purposes and conditions. Further studies at the level of bacterial transcriptomes and proteomes would broaden the scope of information on the pool of genes that are actually expressed from the genome and on the proteins involved in particular metabolic processes under the specific conditions of an AD process (including the type of the substrate used). Future work on bioaugmentation of AD of sewage sludge with POC4, POC9 and LPMIX5 strains should involve the determination of the inoculum size that would not affect the biodiversity of the entire bioreactor community, and tests on the washout rate of the added strains after several anaerobic cycles. Tests on a pilot and full industrial scales should also be carried out."
} | 5,715 |
35040953 | PMC8793870 | pmc | 3,259 | {
"abstract": "ABSTRACT Cost-effective microbial conversion processes of renewable feedstock into biofuels and biochemicals are of utmost importance for the establishment of a robust bioeconomy. Conventional baker's yeast Saccharomyces cerevisiae , widely employed in biotechnology for decades, lacks many of the desired traits for such bioprocesses like utilization of complex carbon sources or low tolerance towards challenging conditions. Many non-conventional yeasts (NCY) present these capabilities, and they are therefore forecasted to play key roles in future biotechnological production processes. For successful implementation of NCY in biotechnology, several challenges including generation of alternative carbon sources, development of tailored NCY and optimization of the fermentation conditions are crucial for maximizing bioproduct yields and titers. Addressing these challenges requires a multidisciplinary approach that is facilitated through the ‘YEAST4BIO’ COST action. YEAST4BIO fosters integrative investigations aimed at filling knowledge gaps and excelling research and innovation, which can improve biotechnological conversion processes from renewable resources to mitigate climate change and boost transition towards a circular bioeconomy. In this perspective, the main challenges and research efforts within YEAST4BIO are discussed, highlighting the importance of collaboration and knowledge exchange for progression in this research field."
} | 362 |
31680119 | PMC6976577 | pmc | 3,260 | {
"abstract": "Deep-sea Bathymodiolus mussels and their chemoautotrophic symbionts are well-studied representatives of mutualistic host–microbe associations. However, how host–symbiont interactions vary on the molecular level between related host and symbiont species remains unclear. Therefore, we compared the host and symbiont metaproteomes of Pacific B. thermophilus , hosting a thiotrophic symbiont, and Atlantic B. azoricus , containing two symbionts, a thiotroph and a methanotroph. We identified common strategies of metabolic support between hosts and symbionts, such as the oxidation of sulfide by the host, which provides a thiosulfate reservoir for the thiotrophic symbionts, and a cycling mechanism that could supply the host with symbiont-derived amino acids. However, expression levels of these processes differed substantially between both symbioses. Backed up by genomic comparisons, our results furthermore revealed an exceptionally large repertoire of attachment-related proteins in the B. thermophilus symbiont. These findings imply that host–microbe interactions can be quite variable, even between closely related systems.",
"conclusion": "Conclusion Although B. thermophilus and B. azoricus holobionts are phylogenetically closely related, many of their host–symbiont interactions differ distinctly on the molecular level. Further studies are required to disentangle the respective influence of habitat conditions, biological host parameters (e.g., age, reproductive status), and of individual host–symbiont constellations. However, our results imply that a high degree of variability, even between closely related species, needs to be taken into account when studying host–microbe associations in model systems.",
"introduction": "Introduction Bathymodiolus mussels harbor chemosynthetic bacterial symbionts in their gills and thrive in diverse marine habitats worldwide [ 1 – 3 ]. The intracellular symbionts fix dissolved inorganic carbon into organic compounds using the oxidation of reduced chemicals, such as methane, H 2 S, short-chain alkanes, or hydrogen, as energy source [ 4 – 7 ]. Bathymodiolus symbioses show a high degree of host–symbiont specificity, i.e., each host species harbors one (or several) distinct symbiont phylotype(s) [ 8 ]. B. thermophilus , for example, which colonizes hydrothermal vent fields on the East Pacific Rise (EPR), hosts a thiotrophic (sulfur-oxidizing, SOX) symbiont [ 9 , 10 ]. In contrast, B. azoricus from the Mid-Atlantic Ridge (MAR) contains two symbiont phylotypes, a SOX symbiont (thiotroph) and a methane-oxidizing (MOX) symbiont (methanotroph) [ 5 ]. Despite these differences, B. thermophilus and B. azoricus are phylogenetically closely related [ 1 , 2 ], and their thiotrophic symbionts, too, show close phylogenetic proximity [ 11 , 12 ]. Recently, we reported a number of physiological interactions between host and symbionts in B. azoricus that provide metabolic integrity to the symbiosis as a whole [ 13 ]. However, little is known about these interactions in other Bathymodiolus host–symbiont combinations. Our current study therefore aims to identify similarities and specific differences in metabolic and physical interactions in the two geographically distant Bathymodiolus species B. thermophilus and B. azoricus .",
"discussion": "Results and discussion Our metaproteome analysis of two Bathymodiolus symbioses provided a detailed picture of individual metabolic processes and hitherto unknown interactions between all symbiotic partners (Fig. 1 ). The most prominent similarities and differences observed between B. azoricus and B. thermophilus are outlined below (for an overview of total protein identifications in all sample types see Supplementary Results I ). Fig. 1 Relative abundance of proteins in major metabolic categories in B. thermophilus ( Bth ) and B. azoricus ( Baz ). Bubble size corresponds to protein abundance in %OrgNSAF (average values, for replicate numbers see Supplementary Table S1a ; see Supplementary Tables S2 and S3 for a complete list of all identified proteins). Sample types: we analyzed the soluble proteome of symbiont-containing whole gill tissue (Gill) and symbiont-free foot tissue (Foot). In addition, we selectively enriched symbiont fractions (symbiont cell pellet, Sym) and host proteins (host-enriched supernatant, Host, Baz only) from gill tissue using gradient centrifugation, and analyzed their soluble proteome. For enhanced identification of membrane-associated symbiont proteins, we additionally analyzed the membrane proteome of whole gill tissue samples (gill membrane fraction, GM) and enriched symbionts (symbiont membrane fraction, SM, Baz only). Baz Sym samples were analyzed in an LTQ-Orbitrap Velos (V) mass spectrometer and in an LTQ-Orbitrap Classic (O) mass spectrometer. The heat map in the center shows ratios of symbiont protein abundance in B. thermophilus and B. azoricus Gill and Sym samples (Velos measurements only). Ratios were calculated from CLR-transformed %OrgNSAF values (see Supplementary Methods ). Negative ratios (red cells) indicate higher abundance in B. thermophilus , while positive ratios (blue cells) indicate higher abundance in B. azoricus . Gray cells (NA) indicate proteins that were either not compared, or that lacked the minimum number of valid values for reliable ratio calculations (see also Supplementary Table S4 ). Major metabolic categories are indicated on the right. H hydrogen oxidation, P phage defense (1) Total symbiont biomass was substantially higher in B. thermophilus than in B. azoricus (Fig. 2 ). While the SOX symbiont population of B. thermophilus contributed 60% of total gill biomass, the total symbiont population of B. azoricus contributed only 25.3% (SOX: 16.4%, MOX: 8.9%, calculated based on protein abundance [ 16 ], Supplementary Table S8 ). This suggests that B. thermophilus may acquire a higher proportion of its nutrition through its symbionts than B. azoricus , in which filter-feeding might play a more prominent role. Previous findings based on the degree of convolution in the digestive tract in both mussels [ 17 ] and on the incorporation of dissolved and particulate organic matter in B. azoricus [ 18 ] support this idea. B. thermophilus specimens in our study were sampled in notably greater water depth (2511 m) and thus probably had access to less sinking biomass for filter-feeding than B. azoricus specimens (860 m depth). As thiotrophic and methanotrophic symbionts supposedly contribute equally to B. azoricus ’ nutrition (as suggested for Bathymodiolus sp. [ 19 ]), the presence of the methanotroph likely does not counterbalance the lower total symbiont biomass, indicating that B. azoricus may indeed receive less nutrients from its symbiont population than B. thermophilus . The relative contributions of symbiont-derived nutrition and filter-feeding in B. azoricus appear to vary with season and physiological host factors such as mussel size [ 20 – 22 ]. We can therefore not rule out that dissimilar specimen sizes and sampling dates for B. thermophilus and B. azoricus (see Supplementary Methods ) may have influenced our results, but we assume that this potential effect is negligible. Fig. 2 Biomass contributions of symbionts in B. thermophilus and B. azoricus . Total symbiont biomass was substantially higher in B. thermophilus than in B. azoricus in whole gill tissue as well as in enriched symbiont fractions and in gill membrane fractions. Biomass contributions were calculated from the total number of spectra recorded for each organism during MS/MS analyses [ 16 ]. Error bars indicate standard deviations (all B. thermophilus samples: n = 3; B. azoricus enriched symbiont fraction and whole gill tissue: n = 2; B. azoricus gill membrane fraction: two biological replicates were pooled for MS analysis). SOX sulfur-oxidizing symbiont, MOX methane-oxidizing symbiont (2) Both Bathymodiolus hosts appear to oxidize sulfide and provide a thiosulfate reservoir for their symbionts. We identified a host sulfide:quinone reductase (Sqr) homolog (BAGiLS_015482, 61% sequence identity to mitochondrial sulfide:quinone oxidoreductase of the copepod Eurytemora affinis ) in B. thermophilus , and a host sulfurtransferase (BAGiLS_000284, 53.8% identity to sulfurtransferase of the Pacific oyster Crassostrea gigas ) in B. thermophilus and B. azoricus (Fig. 1 , Supplementary Tables S2 and S3 ). Both are involved in the mitochondrial oxidation of sulfide to thiosulfate (Fig. 3a ). They were enriched or exclusively detected in symbiont-containing samples compared with symbiont-free foot samples, indicating that mitochondrial sulfide oxidation is particularly relevant near the symbionts. As an inhibitor of aerobic respiration, hydrogen sulfide is toxic to aerobic organisms [ 23 ]. Invertebrate hosts of thiotrophic bacteria have therefore developed various strategies to shield their tissues from sulfide toxicity [ 24 , 25 ], including the oxidation of sulfide into less harmful sulfur forms [ 26 ]. Our results strongly support the idea that B. thermophilus turns toxic sulfide into the less toxic thiosulfate by mitochondrial sufide oxidation, which may effectively function as a means of sulfide detoxification. This concept was first described for the thiotrophic symbiont-hosting clam Solemya reidi [ 27 ], but has since been reported for various other symbiotic and nonsymbiotic animals, including Bathymodiolus species [ 28 – 30 ]. Fig. 3 Metabolic interactions in Bathymodiolus mussels. a Thiosulfate generated by mitochondrial sulfide oxidation may accumulate in host tissues and could be used as an energy source by the thiotrophic symbiont. Purple: host mitochondrial membrane-associated enzymes. Green: host mitochondrial matrix enzymes. Gray: thiotrophic symbiont enzymes. Tst thiosulfate sulfurtransferase, Sdo sulfur dioxygenase, Sqr sulfide:quinone reductase, III coenzyme Q complex of respiratory chain, IV cytochrome c oxidase complex, Dsr dissimilatory sulfite reductase complex, Apr adenylylsulfate reductase complex, Sat ATP sulfurylase. Please note that sulfate and thiosulfate transport across host and symbiont membranes involves transporter proteins, which are not shown in this figure, because their identities and exact functions are yet unclear. b Proposed model of amino acid cycling between host and thiotrophic symbionts in Bathymodiolus . The symbiont’s general l -amino acid ABC transporter Aap imports host glutamate and exports aspartate (and presumably other amino acids) synthesized by the symbiont. Red arrows indicate amino acid biosynthetic routes that are shared between host and symbiont, whereas black indicates routes that are exclusive to the host or the symbiont. Arrows with flat ends suggest an inhibitory action. OatA: host ornithine aminotransferase, AgxT: host alanine aminotransferase, AspC: symbiont aspartate transaminase, GltBD: symbiont glutamate synthase, CitT: symbiont citrate transporter, Dct: symbiont tripartite ATP-independent periplasmic transporter. Lys, Thr, Arg, Gln, Asp: lysin, threonine, arginine, glutamine, aspartate; G5S: l -glutamate 5-semialdehyde The thiotrophic symbionts of B. thermophilus and B. azoricus use thiosulfate as an energy source [ 13 , 31 ]. Proteins required for this thiosulfate oxidation process, i.e., the Sox multienzyme complex, showed quite similar total abundances in both thiotrophic symbionts in this study, with 2.03 %OrgNSAF in gill tissue in B. azoricus and 1.98% in B. thermophilus (Fig. 1 , Supplementary Tables S2 – S4 ). This suggests that both symbionts experience comparable thiosulfate levels in their microhabitat, the gill tissue, although their macro-environments differ with respect to host species and geographic location. As previously suggested [ 31 , 32 ], mitochondrial sulfide oxidation in Bathymodiolus gills may thus create a pool of thiosulfate, which provides a stable energy source for the thiotrophic symbionts. (3) We identified several copies of the host enzyme carbonic anhydrase (CA) with significantly higher abundances in symbiont-containing samples than in foot tissue samples in both Bathymodiolus hosts, indicating the involvement of these enzymes in symbiosis-related processes (Fig. 1 , Supplementary Fig. S2 ). CAs interconvert HCO 3 − and CO 2 , turning the diffusible gas CO 2 into a nondiffusible form (and back). The two CA homologs BAGiLS_000922 and BAGiLS_000924 were the most abundant proteins in B. azoricus gill samples (5.2 %OrgNSAF) and host-enriched gill supernatant samples (6.9 %OrgNSAF; Supplementary Table S3 , Fig. 1 ). In contrast, while three CAs were detected in B. thermophilus symbiont-containing samples (BAGiLS_000922, BAGiLS_000924. BAGiLS_003177), their total abundance was about 100-fold lower (0.052 %OrgNSAF in gills, 0.066 %OrgNSAF in enriched symbiont samples, Supplementary Table S2 ) than in B. azoricus . We hypothesize that the high expression of host CA in B. azoricus may be a response to CO 2 released by the methanotrophic symbiont as end-product of methane oxidation. Possibly, CA in gill tissue may convert this methanotroph-derived CO 2 to HCO 3 − , thus immobilizing and concentrating it for efficient fixation by the thiotroph. A function of abundant host CA in providing chemoautotrophic symbionts with inorganic carbon has been suggested for several marine invertebrates, including various Bathymodiolus species, Calyptogena species, and Riftia pachyptila [ 33 – 35 ]. In B. thermophilus , which lacks a methanotrophic symbiont, CO 2 concentrations might be lower, which would require lower CA abundance, compared with B. azoricus . Both hosts thus appear to regulate their enzyme repertoire according to the specific requirements of their respective symbionts (Supplementary Discussion II , Supplementary Fig. S2 ). (4) An amino acid cycling mechanism could provide Bathymodiolus hosts with symbiont-derived amino acids and appears to be particularly relevant in B. thermophilus . We detected a broad specificity l -amino acid ABC transporter (AapJQMP) in both Bathymodiolus SOX symbiont proteomes, which could be involved in selective “leakage” of symbiont amino acids to the host (Fig. 3b ). Aap has a preference for polar amino acids and acts not only as an uptake transporter, but—in the presence of extracellular amino acids—also as an efflux transporter [ 36 , 37 ]. In the well-studied Rhizobium symbiosis, Aap was shown to enable the cycling of amino acids between the plant host and root bacteroids [ 38 , 39 ]. The glutamate-generating host enzymes ornithine aminotransferase (OatA: BAGiLS_006873, BAGiLS_004723) and alanine aminotransferase (AgxT: BAGiLS_022026) were notably more abundant or even exclusively detected in symbiont-containing samples compared with foot tissue in both Bathymodiolus hosts (Supplementary Tables S2 and S3 ). All identified peptides were unique to the host proteins and were not shared with any symbiont proteins. These proteins could produce glutamate in the direct vicinity of the symbionts for uptake by the bacterial Aap transporter. After import through Aap, glutamate could be transaminated in the bacterial cytoplasm by the symbiont's aspartate aminotransferase (AspC: OIR24744.1, SEH69114.1), which we identified in both thiotrophic symbionts, and the resulting aspartate could be recycled into the Bathymodiolus bacteriocyte. A similar amino acid cycling strategy was described in the Buchnera -aphid symbiosis [ 40 ]. Other amino acids besides aspartate and glutamate might also be cycled, as proposed for Rhizobium [ 38 ]. This mechanism would allow the Bathymodiolus host to compensate for its previously proposed inability to synthesize aspartate and many other amino acids autonomously ([ 13 ], Supplementary Table S5 ) by harnessing the symbiont’s biosynthetic machinery (see also Supplementary Discussion III ). Simultaneously, both B. azoricus and B. thermophilus seem to supply their respective thiotrophic symbionts with oxaloacetate, an essential intermediate the bacteria cannot synthesize on their own ([ 13 ], this study; Fig. 3b ). Close metabolic interdependency thus seems to be a typical feature of Bathymodiolus symbioses. Interestingly, Aap was considerably more abundant in the B. thermophilus symbiont (the periplasmic solute-binding subunit AapJ, OIR25769.1, alone contributed ~1% of the entire symbiont proteome, Fig. 1 ), than in the B. azoricus thiotroph (SEH78249.1, <0.1 %OrgNSAF in the symbiont fraction). Possibly, this may be because B. thermophilus obtains a relatively larger part of its nutrition from its symbionts than B. azoricus (see above). (5) Symbiont attachment-related proteins (ARPs) were highly abundant in B. thermophilus and may be involved in interactions with the host. We detected a large set of 129 B. thermophilus symbiont proteins involved in surface-binding and cell-cell adhesion, which together made up 23.9% of the symbiont’s proteome in gill tissue (Supplementary Table S6b ). Most of these proteins (126) are predicted to be either attached to the symbiont cell surface or secreted into the surrounding host vacuole, and 127 were more abundant in gill samples (gill and/or gill membrane) than in symbiont-enriched fractions. The B. azoricus thiotroph, on the other hand, expressed only 16 ARPs, accounting for 3.5 %OrgNSAF in gill samples (Supplementary Table S6c ). To judge whether the high number of ARPs observed in the B. thermophilus thiotroph poses an exception or rather a common feature of thiotrophic Bathymodiolus symbionts, we compared the B. thermophilus symbiont’s genome to the genomes of three other thiotrophic Bathymodiolus symbionts, two thiotrophic clam symbionts, and two free-living thiotrophs. This screening showed that ARP-encoding genes are comparatively rare in the related bacteria, but occur in exceptionally high numbers in the B. thermophilus symbiont (see Supplementary Discussion IV , Supplementary Table S6a, Supplementary Figs. S1 and S5 ). While the exact function of ARPs in Bathymodiolus thiotrophs is unknown, several possible scenarios are conceivable (see Supplementary Discussion V for details): (a) ARPs might be involved in symbiont colonization of host tissue, because most of them were adhesins, invasins, cadherins, integrins, intimins, and other proteins known to play crucial roles in pathogenic bacteria during host colonization and persistence [ 41 – 44 ]. (b) Their extraordinarily high abundance in B. thermophilus may additionally suggest a role in attachment of symbiont cells to each other, i.e., the formation of a biofilm-like structure, or some kind of extracellular proteinaceous matrix around the symbiont cells. This matrix could, for example, serve as proteinaceous substrate that is leaked from the symbionts to the host. As B. thermophilus presumably relies relatively more on its symbiont for nutrition than B. azoricus (see above), higher abundances of leaked symbiont proteins (e.g., ARPs) might be required. (c) Several of the symbiont ARPs contained domains known to bind and interact with phages (e.g., Ig-like, fibronectin Type 3, immunoglobulin superfamily and C-type lectins [ 45 , 46 ]), which may indicate that the proposed ARP matrix could protect the symbionts from phages (Supplementary Fig. S4 , Supplementary Table S7 ). Moreover, as previously suggested for pathogens [ 47 , 48 ], ARPs could enable the symbionts to interact with host phagocytes, potentially enabling them to circumvent host-induced apoptosis (Supplementary Fig. S3 ). Further in-depth studies will be required to verify these hypotheses."
} | 4,952 |
31406671 | PMC6685505 | pmc | 3,262 | {
"abstract": "Abstract Although organic and composite thermoelectric (TE) materials have witnessed explosive developments in the past five years, the research of flexible TE devices is rather limited. In particular, their assembly strategies and device performance reported in the literature cannot be directly compared, due to a variety of deviances including p‐ and n‐type component materials, shape and dimensions of p‐n flexible films, and applied temperature gradient (Δ T ). Here, three types of assembly strategies for flexible TE devices, that is, serial, folding, and stacking, are compared by fixing the corresponding experimental parameters. Furthermore, a convenient and general method to evaluate the flexible device performance (FDP) is put forward, that is, FDP = P max m Δ T N , where the maximum output power ( P \n max ) is divided by product mass ( m ), Δ T , and pair number of p‐n couples ( N ). The FDPs for the present serial, folding, and stacking devices are 11.13, 8.87, and 0.05 nW g −1 K −1 , respectively, confirming that the serial configuration is the best among the three strategies for flexible device fabrication. The preliminary evaluation method proposed herein will pave the way for a design strategy of flexible TE devices and speed up their applications in waste‐heat harvesting, e‐skin, wearable electronics, etc."
} | 337 |
39230277 | PMC11481889 | pmc | 3,264 | {
"abstract": "ABSTRACT During its cell cycle, the bacterium Caulobacter crescentus switches from a motile, free-living state, to a sessile surface-attached cell. During this coordinated process, cells undergo irreversible morphological changes, such as shedding of their polar flagellum and synthesis of an adhesive holdfast at the same pole. In this work, we used genetic screens to identify genes involved in the regulation of the transition from the motile to the sessile lifestyle. We identified a predicted hybrid histidine kinase that inhibits biofilm formation and promotes the motile lifestyle: HmrA ( h oldfast and m otility r egulator A). Genetic screens and genomic localization led to the identification of additional genes that form a putative phosphorelay pathway with HmrA. We postulate that the Hmr pathway acts as a rheostat to control the proportion of cells harboring a flagellum or a holdfast in the population. Further genetic analysis suggests that the Hmr pathway impacts c-di-GMP synthesis through the diguanylate cyclase DgcB pathway. Our results also indicate that the Hmr pathway is involved in the regulation of motile to sessile lifestyle transition as a function of various environmental factors: biofilm formation is repressed when excess copper is present and derepressed under non-optimal temperatures. Finally, we provide evidence that the Hmr pathway regulates motility and adhesion without modulating the transcription of the holdfast synthesis regulator HfiA. IMPORTANCE Complex communities attached to a surface, or biofilms, represent the major lifestyle of bacteria in the environment. Such a sessile state enables the inhabitants to be more resistant to adverse environmental conditions. Thus, having a deeper understanding of the underlying mechanisms that regulate the transition between the motile and the sessile states could help design strategies to improve biofilms when they are beneficial or impede them when they are detrimental. For Caulobacter crescentus motile cells, the transition to the sessile lifestyle is irreversible, and this decision is regulated at several levels. In this work, we describe a putative phosphorelay that promotes the motile lifestyle and inhibits biofilm formation, providing new insights into the control of adhesin production that leads to the formation of biofilms.",
"conclusion": "Conclusion From the above results, we postulate that the hmrABC gene cluster, along with hmrX , encodes different elements of a phosphorelay involved in the regulation of motile versus sessile lifestyles independently of hfiA transcription. This phosphorelay consists of a transmembrane HHK HmrA, two HPTs (HmrB and HmrX), and a membrane protein (HmrC) at the top of the signaling hierarchy, sensing environmental stress ( Fig. 11 ). In this model, excess copper or extreme temperatures are sensed by HmrC, which transmits a signal to HmrA and triggers changes in c-di-GMP levels via HmrX and HmrB. This results in a change in the number of cells bearing a flagellum or a holdfast in the population. We propose that the Hmr pathway detects environmental stresses and acts as a rheostat by promoting cells to disperse (more cells with a flagellum) while discouraging adhesion (less cells with a holdfast). This regulation allows the population to respond to its environment by adjusting the settling/dispersing ratio accordingly. Fig 11 Proposed model for the Hmr pathway. Presence of an environmental stress (such as excess copper or extreme temperature) is detected by the membrane protein HmrC, which transfers the signal to the HHK HmrA. This signal is transduced to the HPT proteins HmrB and HmrX, which results in a change in c-di-GMP levels via the action of DgcB and PdeA. Changes in c-di-GMP levels modify the regulation of flagellum and holdfast synthesis and dictate the switch from the motile to sessile state for each individual cell. Environmental stress affects HmrC and HmrA proteins in a membrane, leading to changes in motility and lifestyle regulation via c-di-GMP, HmrB, and HmrX proteins. Inset depicts detailed interactions at the HmrA RR domain.",
"introduction": "INTRODUCTION In the environment, bacteria live primarily as surface-associated colonies ( 1 – 3 ). Biofilms typically provide strategic advantages to their inhabitants. Indeed, cells in a biofilm can acquire transmissible DNA more easily and can be more resistant not only to xenobiotic compounds and changes in environmental conditions, but also to grazing by some planktonic feeding predators and phagocytosis by the host immune system ( 4 ). While most studied biofilm-forming bacteria rely on a complex extracellular matrix composed of proteins, polysaccharides, DNA, and other macromolecules to tightly adhere to the surface ( 5 ), many Alphaproteobacteria use a strong polar adhesin to irreversibly attach to surfaces and form biofilms ( 6 , 7 ). The most extensively studied example of this type of adhesin is the Caulobacter crescentus holdfast. C. crescentus cells have a dimorphic lifecycle, where each division cycle yields a sessile mother stalked cell and a motile daughter swarmer cell ( Fig. 1A ). Swarmer cells display a flagellum and multiple pili at one pole. During the transition to the sessile form, the flagellum is ejected, the pili are retracted, and cells enter the sessile phase of their life cycle. At the pole that was previously bearing the flagellum and pili, cells first synthesize a holdfast, followed by a cylindrical extension of the cell envelope called the stalk, which pushes the holdfast away from the cell body. The resulting stalked cells are attached to surfaces to form biofilms. Stalked cells eventually elongate, become predivisional cells, and synthesize a new flagellum at the pole opposite the stalk. After cytokinesis, each newborn swarmer cell disperses and must transition from its motile state to a stalked cell prior to the initiation of DNA replication and a new round of cell division. Fig 1 Adhesion enrichment screen for identification of hyperadhesive mutants. ( A ) Asymmetric cell cycle of Caulobacter crescentus. The newborn swarmer cell harbors pili and a flagellum at one pole of the cell. During the motile to sessile transition, this swarmer cell differentiates by retracting pili, ejecting the flagellum, and synthesizing a holdfast and a stalk at the same pole, giving rise to a stalked cell. This non-motile cell progresses through the cell cycle to give an elongated predivisional cell in which a new flagellum is synthesized at the pole opposite the stalked pole. After cell division, the newborn swarmer cell disperses and the stalked cell initiates the next round of replication. ( B ) Schematic of the forward genetic screen to identify mutants with an enhanced adhesion phenotype. A clean glass coverslip (depicted in blue) was added to a culture of pooled Mariner transposon mutants grown in M2X medium. After overnight growth, this coverslip was removed and thoroughly rinsed with sterile M2X, then used to inoculate a new culture. After 3 h of inoculation, the old coverslip (blue) was replaced with a new one (green). The enrichment process was repeated once more before plating. Individual mutants were isolated from single colonies. ( C ) Identity and location of the genes identified in the adhesion enrichment screen. Genes identified in this screen are indicated in red. The locations of the Mariner transposon insertions are indicated by black lollypops. The predicted function of the proteins encoded by the flanking genes is indicated in italics. For more information about the proteins encoded by the genes indicated in red, see Table 1 . Life cycle of a bacterial cell depicts motile and sessile phases, an experimental setup for mutant selection using glass coverslips, and diagrams of operons and genes involved in chemotaxis and type IV secretion systems. The progression of the cell cycle and transition between motile and sessile phases are tightly regulated. Holdfast production is temporally regulated during the cell cycle, with genes involved in holdfast synthesis under the control of key cell cycle regulators ( 8 , 9 ). The intracellular concentration of cyclic di-GMP (c-di-GMP) is the primary developmental regulator of the motile to sessile lifestyle transition ( 10 ) and is involved in both flagellar ejection and holdfast production ( 11 – 13 ). In addition to this internal signal, holdfast production is also controlled by external environmental signals such as nutrient availability, light, and general stress responses ( 14 – 17 ). These signals regulate the h old f ast i nhibitor HfiA, which inhibits the h old f ast s ynthesis protein HfsJ, a predicted glycolipid glycosyltransferase crucial for holdfast formation ( 15 ). Regulation of HfiA is controlled using different mechanisms at the transcriptional and post-translational levels, including by c-di-GMP, enabling proper timing of holdfast synthesis ( 15 , 18 – 20 ). To better understand the underlying mechanisms that govern the motile to sessile lifestyle transition and holdfast regulation, we performed a genetic screen for mutations that enhance biofilm formation. This work reports a putative phosphorelay that inhibits the sessile lifestyle, while promoting motility. Phosphorelays, a sub-class of two-component systems (TCSs), are major regulatory pathways used by bacteria to sense and transduce environmental signals to trigger an adapted phenotypic response. A canonical TCS consists of a histidine kinase (HK)/response regulator (RR) pair. Hybrid histidine kinases (HHKs) are non-canonical TCSs, where the HK and the receiver domain of the RR are fused. HHKs represent less than 20% of bacterial HKs ( 21 ). Signal transduction from the HHK to the final RR typically involves a histidine phosphotransferase (HPT) as a mediator. Sixty-one percent of RR output domains contain a DNA-binding domain and regulate transcription ( 22 ). In addition, some output domains can transduce signals through diguanylate cyclase or phosphodiesterase domains, which produce and degrade c-di-GMP, respectively. This example highlights how regulation through phosphotransfer and c-di-GMP can be intertwined. In this work, we describe a putative phosphorelay centered on the h oldfast m otility r egulator A (HmrA), an HHK encoded by the CCNA_03326 gene, identified in a screen for hyper-adhesive mutants. We show that this gene is involved in the switch from a motile to a sessile lifestyle. By controlling both the proportion of swarmer cells that synthesize a flagellum and the proportion of differentiating swarmer cells that synthesize a holdfast, it enables the fine-tuning of the relative number of cells harboring a flagellum or a holdfast in a mixed population. Our data suggest that HmrA regulation of holdfast production is linked to c-di-GMP production by DgcB. In addition, we identify two putative HPTs involved in the same pathway as HmrA, namely HmrB and HmrX. We also show that holdfast production is regulated by environmental signals such as the presence of excess Cu and different growth temperatures. This regulatory mechanism involves the protein HmrC, which is a predicted transmembrane protein required for sensing environmental stimuli that initiate the Hmr regulation cascade. Finally, our work provides evidence that this mechanism functions without modulating the transcription of the master regulator of holdfast synthesis, HfiA.",
"discussion": "DISCUSSION HmrA (CC3219/CCNA_03326) was first reported in a genome-wide study to identify HHKs in C. crescentus ( 58 ), which reported that a ∆ CC3219 mutant is impaired in swimming through semisolid agar. We show here that, in addition to impacting group swimming, HmrA is also important for adhesion and biofilm formation, by fine-tuning the number of cells producing a holdfast in the population. Future biochemical analysis will be required to confirm that the actors of this putative phosphorelay can indeed directly phosphorylate each other, and in which sequence. We showed that residues H286 and D578 in HmrA are crucial for both inhibiting biofilm formation and promoting swimming dispersal. We could not evaluate whether the loss of activity resulted specifically from amino acid substitutions that eliminated catalytic activity, or from an overall structural destabilization. However, since these mutations have been analyzed multiple times in HK research and typically do not destabilize HK structure, we interpret these phenotypes as good indications that hmrA encodes a functional HHK. In addition, the most downstream element of the phosphorelay is currently unknown and its identification will be required to complete our knowledge of this pathway. It is worth noting that the initial screen that enabled the identification of the Hmr pathway revealed two HHKs: HmrA and CCNA_03265 (CC3162) ( Fig. 1 ; Table 1 ). Interestingly, CCNA_03265 was also shown to impact group motility through semisolid agar ( 58 ). Sequence alignment and structure analysis indicate that the CCNA_03265 HK domain lacks the conserved histidine while the RR domain has retained the aspartate residue (Fig. S3). One possibility would be that the catalytic histidine does not perfectly align with the sequences of other HHKs but is still present in the vicinity. Located a few aa downstream on the same alpha helix, H151 is a reasonable candidate to fulfill this function (Fig. S3 and S12). Another possibility would be that CCNA_03265 has no catalytic histidine and that its RR aspartate is phosphorylated by an HPT, such as HmrB or HmrX, or forms a heterodimer with another HHK, such as HmrA. The model of the canonical isolated, linear phosphorelay has prevailed for a long time, but more recent work has shown that phosphorelays can be more complex. For example, in C. crescentus , several kinases can phosphorylate the single domain response regulator MrrA ( 17 ), which in turn can phosphorylate both the PhyK/PhyR and the LovK/LovR systems known to be involved in general stress response ( 59 ), cell cycle regulation via HfiA ( 15 ), and holdfast production ( 14 ). In P. aeruginosa , the GacS-GacA TCS ( 60 ) interacts with three other HHKs, RetS, LadS, and PA1611, to control the transition between motile and sessile lifestyles depending on the environment ( 61 – 63 ). These examples of regulation cascades involving multiple inputs illustrate the complex molecular mechanisms underlying how bacteria adapt to the different environmental conditions they encounter and how they regulate their lifestyle in response to these changes. Future work could help to decipher if CCNA_03265 (i) is in the same phosphorelay as HmrA; (ii) can interact with HmrA; and (iii) regulates the transition between motile to sessile lifestyles upon different signals. The Hmr pathway is important for tuning biofilm formation in response to environmental stresses Our results suggest that the Hmr pathway is important for adapting the motile to sessile transition in response to environmental cues, as HmrA, HmrB, HmrC, and HmrX are involved in the response to environmental stresses such as the presence of excess metals or non-optimal temperatures ( Fig. 9E and F ; Fig. S9 through S11). hmrC was shown to be upregulated in the presence of metals and is part of the UzcR regulon, which is involved in U, Zn, and Cu sensing ( 56 ). We tested various metals, namely Cu, Zn, Co, Fe, Mn, and Ni. In the tested conditions, only Cu excess produced a significant alteration of the biofilm phenotype in WT cells. While the effect of Cu on biofilm formation is significant and the Hmr pathway is involved, we cannot rule out that this regulation is indirect and results from a general overproduction of biofilm. A recent RNAseq study showed that C. crescentus reacts to Cu excess by overexpressing machineries dealing with Cu detoxification (PcoAB), oxidative stress, protein misfolding/rearrangement, and chelation by cysteine and arginine ( 64 ). In the same study, it stands out that hmrC is the only gene of the hmr set that is consistently upregulated by the addition of Cu (2.4× in stalked cells; 4.1× in swarmer cells). Other hmr genes displayed either no change or a twofold downregulation upon Cu addition. Considering our results, HmrC is an important factor in managing the response to excess copper. We show here that biofilm formation in C. crescentus is decreased by the addition of Cu, while it remains steady in the Hmr mutants, suggesting that this pathway is important to modulate biofilm adhesion under Cu stress. The cell type of C. crescentus (swarmer versus stalked cells, Fig. 1A ) determines the response to Cu excess: while swarmer cells preferentially escape excess copper by negative chemotaxis, stalked cells are seemingly more impacted by Cu stress and rely on detoxification mechanisms (primarily PcoAB) ( 65 ). The different fate for each cell type was postulated to condition a fast bimodal response to Cu stress ( 65 ). Since HmrC, and the Hmr pathway in general, appears to determine the proportion of motile versus sessile cells in a mixed population, we hypothesize that the Hmr pathway, with its response to Cu levels, might be a molecular mechanism underlying this bimodal response by controlling the balance between motile (swarmer cells bearing a flagellum) and sessile (stalked cells lacking a flagellum) lifestyles at the population level. C. crescentus has an optimal growth temperature of 30°C. Our results show that it produces approximately two to three times more biofilm at 15°C, 20°C, and 37°C. This difference depends on all of the Hmr proteins, which repress biofilm formation as a function of temperature with a maximum repression at 30°C and milder repression for non-optimal temperatures ( Fig. 9F ). Interestingly, hmrC is upregulated during cold shock, which affects metal and ion homeostasis ( 57 ). It is not clear at this stage whether HmrC is involved in sensing broad environmental stress, including metal-induced and cold-induced stress, or whether it is involved in sensing environmental metals and its role in cold sensing is a consequence of the disturbance of metal homeostasis. Temperature changes can destabilize the bacterial membrane by changing its fluidity. In the case of cold shock, the main signal that triggers adaptation is the sensing of membrane rigidity by transmembrane histidine kinases, as described in a broad range of organisms such as E. coli , B. subtilis , S. typhimurium , Yersinia pestis, and Synechocystis PCC6803 ( 66 ). Based on our results, we hypothesize that the membrane protein HmrC is required for sensing temperature changes, which conditions the proportion of biofilm-forming cells as a function of the temperature. Interestingly, deletion of hmrC comes at a high fitness cost according to a genome-wide gene essentiality study in C. crescentus ( 67 ). Overall, this could point to HmrC as a crucial element for sensing environmental stresses. Since HmrC and HmrA both reside in the inner membrane and likely function in the same signaling pathway, HmrC may interact with HmrA to facilitate this process, as has been observed for other HK’s with membrane integral accessory proteins ( 68 ). Based on the above considerations, we utilized AF2-multimer as implemented in ColabFold to predict whether a complex between a HmrA dimer and HmrC would be feasible. This generated a set of consistent and confidently predicted models wherein two copies of HmrC were positioned on either side of the HmrA dimer transmembrane region, interacting with one of the two HmrA chains in the dimer ( Fig. 11 ; Fig. S13). Since relatively small changes in the conformation of transmembrane helices can be amplified via adjacent HAMP domains to downstream cytosolic modules ( 34 ), this may represent a mechanism whereby signals linked to HmrC sensing are transmitted into the cell via HmrA ( Fig. 11 ). We can then speculate that HmrA participates in a phosphorelay with HmrB and/or HmrX as intermediaries. Indeed, the alignment of the AF2-predicted structure of HmrX with the P1 domain of E. coli CheA superimposes the substrate histidine of CheA with H81 of HmrX, pointing to a potential site of phosphorylation. Modeling of HmrX with the response regulator domain of HmrA using AF2-multimer ( Fig. 11 ; Fig. S14) positions the predicted catalytic aspartate of HmrA in close proximity to H81 of HmrX ( Fig. 11 ) in an arrangement reminiscent of other response regulator-HPT structures ( 69 , 70 ), supporting the hypothesis that HmrA and HmrX participate in a phosphorelay. HmrX and/or HmrB then eventually modulate the transition from motile to sessile lifestyles and ensure that cells settle in favorable environments. Finally, the phenotypes of ∆ hmrX suggest that other pieces of the relay remain to be discovered. Indeed, the less pronounced phenotype of ∆ hmrX , compared to the mutants related to its presumed upstream partners (∆ hmrC and ∆ hmrA ), indicates that an unknown phosphotransfer may occur in parallel to that mediated by HmrX. Furthermore, the intermediate intensity of the ∆ hmrA ∆ hmrX phenotypes, compared to those of ∆ hmrA and ∆ hmrX , shows that disrupting hmrX mitigates the strong phenotype modification induced by the deletion of hmrA . At this stage, it is not possible to explain these phenotypes, but they clearly reflect the yet to be discovered complexity of the Hmr pathway, which is likely to branch with other pathways. c-di-GMP, produced by DgcB, is involved in the Hmr pathway We show in this work that the Hmr regulatory pathway likely impacts the level of intracellular c-di-GMP, via the diguanylate cyclase DgcB to control both holdfast and flagellum production. Indeed, two different suppressor screens of ∆ hmrA for the gain of swimming through semisolid agar ( Fig. 5 ) identified multiple independent transposon insertions and point mutations in dgcB , suggesting that the Hmr pathway and the level of c-di-GMP are linked. This model is in line with the well-established role of c-di-GMP as an important player in the motile to sessile lifestyle transition in C. crescentus ( 71 ). In addition, our transposon screen for hyper-adhesive mutants ( Fig. 1B ) enriched for five different mutants in the phosphodiesterase encoding gene pdeA ( Fig. 1C ; Table 1 ). PdeA affects motility and biofilm formation through c-di-GMP and the activity of DgcB is counteracted by PdeA ( 13 ). PdeA is degraded during the motile swarmer to sessile stalked cell transition ( 72 ) and DgcB is then able to contribute to increasing c-di-GMP levels in transitioning cells. Stimulation of DgcB activity is achieved by several players at the motile to sessile turning point. First, when swarmer cells encounter a surface in complex medium, pili and the flagellum motor are used as mechanosensors to trigger DgcB to synthesize c-di-GMP, which promotes holdfast synthesis ( 19 , 37 ). In addition, the C heY- l ike c-di-GMP e ffectors proteins CleA and CleD are activated by c-di-GMP and interact with the flagellar motor to promote surface contact-stimulated production of holdfast ( 44 ). Finally, the flagellar stator MotB and the flagellar signaling suppressor proteins FssA and FssB also trigger DgcB-related c-di-GMP production via the mechanical pathway of holdfast synthesis, regardless of the presence of a surface, via modulation of HfiA expression ( 48 ). In those cases, the production of c-di-GMP via DgcB is believed to lead to the activation of the holdfast synthesis protein HfsJ, which binds to c-di-GMP. Our work on the Hmr pathway provides insights into a different regulation mechanism because: (i) we performed our experiments in M2X minimal medium where surface contact stimulation of holdfast synthesis is not active ( 38 ); and (ii) we showed that HfiA is not involved in the Hmr pathway. Future work could provide more insight into whether HfsJ is the final player in the Hmr regulation cascade. The Hmr pathway regulates motile to sessile lifestyle transition independently of hfiA trancription Several TCS have been shown to regulate holdfast production in C. crescentus . For example, the general stress-response PhyR/NepR ( 17 ), the LOV (light, oxygen, and voltage) blue light photoreceptor proteins LovK/LovR ( 59 ), and the RegB/RegA homologs SpdS/SpdR ( 73 ) all control holdfast synthesis. They act by regulating the transcription of hfiA , the major regulator of holdfast synthesis, itself regulated via a multilayered network ( 15 , 20 ). Interestingly, our work shows that the Hmr pathway regulates holdfast production without modulating hfiA transcription ( Fig. 10 ), revealing a novel facet of the highly complex network dedicated to holdfast regulation. However, we cannot rule out potential post-transcriptional regulation of HfiA by the Hmr pathway, as is the case with the chaperone DnaK ( 18 ). A previous ChiP-Seq analysis reported that the cell cycle regulator GcrA, which was shown to bind to the hfiA promoter ( 15 ), can also interact with the hmrB promoter ( 74 ). Thus, the connection between GcrA and the Hmr pathway appears as another interesting future direction to investigate how this cell cycle regulator impacts holdfast production via both the Hmr and HfiA pathways."
} | 6,332 |
38049915 | PMC10696704 | pmc | 3,266 | {
"abstract": "Background Active hydrothermal vents create extreme conditions characterized by high temperatures, low pH levels, and elevated concentrations of heavy metals and other trace elements. These conditions support unique ecosystems where chemolithoautotrophs serve as primary producers. The steep temperature and pH gradients from the vent mouth to its periphery provide a wide range of microhabitats for these specialized microorganisms. However, their metabolic functions, adaptations in response to these gradients, and coping mechanisms under extreme conditions remain areas of limited knowledge. In this study, we conducted temperature gradient incubations of hydrothermal fluids from moderate (pH = 5.6) and extremely (pH = 2.2) acidic vents. Combining the DNA-stable isotope probing technique and subsequent metagenomics, we identified active chemolithoautotrophs under different temperature and pH conditions and analyzed their specific metabolic mechanisms. Results We found that the carbon fixation activities of Nautiliales in vent fluids were significantly increased from 45 to 65 °C under moderately acidic condition, while their heat tolerance was reduced under extremely acidic conditions. In contrast, Campylobacterales actively fixed carbon under both moderately and extremely acidic conditions under 30 − 45 °C. Compared to Campylobacterales , Nautiliales were found to lack the Sox sulfur oxidation system and instead use NAD(H)-linked glutamate dehydrogenase to boost the reverse tricarboxylic acid (rTCA) cycle. Additionally, they exhibit a high genetic potential for high activity of cytochrome bd ubiquinol oxidase in oxygen respiration and hydrogen oxidation at high temperatures. In terms of high-temperature adaption, the rgy gene plays a critical role in Nautiliales by maintaining DNA stability at high temperature. Genes encoding proteins involved in proton export, including the membrane arm subunits of proton-pumping NADH: ubiquinone oxidoreductase, K + accumulation, selective transport of charged molecules, permease regulation, and formation of the permeability barrier of bacterial outer membranes, play essential roles in enabling Campylobacterales to adapt to extremely acidic conditions. Conclusions Our study provides in-depth insights into how high temperature and low pH impact the metabolic processes of energy and main elements in chemolithoautotrophs living in hydrothermal ecosystems, as well as the mechanisms they use to adapt to the extreme hydrothermal conditions. \n Video Abstract Supplementary Information The online version contains supplementary material available at 10.1186/s40168-023-01712-w.",
"conclusion": "Conclusions DNA-SIP, combined with 16S rRNA gene and metagenomic high-throughput sequencing, revealed that Nautiliales (mainly Lebetimonas ) were the dominant active chemolithoautotrophs at WV 65 °C, while Campylobacterales (mainly Sulfurimonas and Sulfurovum ) actively assimilated DIC under 30 − 45 °C in WV and YV mouths. Thiotrichales (mainly Thiomicrospira ), which was the most abundant taxa in the two vent mouths, did not show significant carbon fixation activity at any of the temperatures tested. The thermophilic Nautiliales and mesophilic/psychrophilic Campylobacterales , as the two mainly active chemolithoautotrophs in the Kueishantao vents at different temperatures, exhibited unique or preferential pathways in sulfur oxidation, nitrogen acquisition, oxygen utilization, and nitrogen utilization. Compared to Campylobacterales , Nautiliales that bloomed at WV 65 °C were found to lack the Sox sulfur oxidation system and instead use NAD(H)- rather than NADP(H)-linked glutamate dehydrogenase to catalyze the assimilation of ammonium. They cannot utilize oxygen via the cytochrome c oxidase cbb3-type but have a much higher genetic potential for the activity of cytochrome bd ubiquinol oxidase in oxygen respiration. Additionally, they exhibit a higher genetic potential for increased hydrogen oxidation activity at high temperatures. For high-temperature adaption, Nautiliales rely on the gene rgy to maintain DNA stability at high temperature, while the gene splB is important for maintaining UV resistance of spores in shallow-sea hydrothermal ecosystems by lysing photoproducts. The main strategies utilized by Campylobacterales to survive under low pH conditions include (1) exporting protons using proton pumps, (2) reducing proton influx by maintaining a positive membrane potential via electrostatic repulsion, and (3) forming an impermeable cell membrane to restrict proton influx into the cytoplasm. Additionally, notably, the membrane arm subunits of complex I may play a role in regulating cellular pH homeostasis at low pH. In summary, our investigation demonstrates the significant impact of high temperature and low pH on the chemolithoautotrophic microbial compositions and their metabolism of energy and main elements in the hydrothermal vent ecosystem. Moreover, we have identified functional genes that contribute to the adaptation of these microorganisms to such extreme conditions. These findings shed light on the mechanisms and strategies employed by chemolithoautotrophs to survive and thrive in high-temperature and extremely acidic environments.",
"discussion": "Discussion The taxonomy and metabolic capabilities of chemolithoautotrophs inhabiting hydrothermal sulfide chimneys are largely influenced by the local geochemical conditions, particularly temperature and pH [ 7 , 11 ]. Members in order Nautiliales , Campylobacterales , and Thiotrichales have frequently been found to be the major active bacterial groups in the hydrothermal systems of Kueishantao Island [ 3 , 11 , 22 ]. Our work for the first time showed that Nautiliales exhibited high carbon fixation activity at high temperature (65 °C) and moderate acidity (pH = 5.6) conditions, and Campylobacterales were adapted to moderate temperature (45 − 30 °C) and moderate and extreme acidity (pH = 2.2) conditions in the hydrothermal systems of Kueishantao Island by using DNA-SIP analysis. However, the Thiotrichales did not show carbon fixation activities in any of the samples. In addition, we found that extremely acidic condition (specifically at pH 2.2) restrained the high-temperature tolerances of Nautiliales . A previous study has shown that high-temperature tolerances of hyperthermophilic archaea were not greatly affected by pH within the range of 4.5–7.5 [ 54 ]. In the present study, we found the archaeal abundance was stimulated under moderately acidic conditions (pH = 5.6), but inhibited under extremely acidic conditions (pH = 2.2) at high temperatures (Fig. S 3 ). These results indicate that varying acidic conditions have distinct impacts on chemolithoautotrophs at different temperatures. Here, DNA-SIP combined with metagenomic analysis provides genomic insights into the impact of temperature and pH on the metabolic functions of the primary chemolithoautotrophs living in the hydrothermal ecosystem. High temperature and low pH-induced difference in microbial metabolism Previous studies conducted in sulfur-rich hydrothermal ecosystems have found that chemolithoautotrophs typically utilize reduced sulfur and H 2 as energy sources, and inorganic nitrogen as electron acceptors and nitrogen sources to reduce CO 2 to organic carbon [ 11 , 55 ]. The transcriptional activities of the Epsilonproteobacteria and Aquificae rTCA pathways, as well as the Gammaproteobacteria CBB pathway for carbon fixation, were frequently detected in marine and terrestial hydrothermal ecosystems [ 11 , 56 – 59 ]. Our study found that the rTCA carbon fixation pathway was active in all of our incubation conditions, whereas the Thiotrichales CBB pathway was inactive. The Chromatiales and Cyanobacteria CBB pathways were active at YV and WV, respectively (Fig. 4 ). These results suggest that temperature and pH might not be the determining factors in the activity of rTCA and CBB cycles. Given the high concentration of S 2− observed in WV and YV (Fig. 1 ), sulfur oxidation may be a primary energy source for carbon fixation mediated by chemolithoautotrophs in these regions. Our study detected several sulfur-oxidizing genes, including soxABCXYZ , sqr , and fccB . Among these, sqr was the only gene that was abundant at WV 65 °C (Fig. 4 ). SQR is an enzyme frequently observed in hyperthermophiles. For example, the SQR isolated from thermoacidophilic Acidianus ambivalens demonstrated maximum activity at 70 °C and was almost inactive at room temperature (25 °C) [ 60 ]. The Campylobacterales group contained both sox genes and sqr , while Nautiliales only contained sqr (Figs. 4 and 6 ). Notably, we found that all Nautiliales and hyperthermophilic Aquificae genomes (Table S 2 ) lacked sox genes but contained sqr . According to many scientific proposals [ 61 , 62 ], life on Earth may have originated from high-temperature hydrothermal vents, and SQR is considered a phylogenetically ancient enzyme that was acquired early in the evolution of life [ 63 ]. The absence of sox genes in thermophilic or mesophilic Nautiliales may be due to the limited availability of thiosulfate under 65 °C, as thiosulfate can easily hydrolyze into sulfur and sulfur dioxide under acidic condition when the temperature exceeds 45 °C. Thus, it is possible that temperature played an important role in the acquisition of sox genes by chemolithoautotrophs during their evolution to adapt to lower temperatures from their high-temperature environments. Although Fcc provides less energy through sulfide oxidation than SQR [ 64 ], it has a higher affinity for sulfide [ 65 ]. Hydrogen is another important reducing agent present in hydrothermal systems, and its oxidation can yield higher catabolic energy than sulfur oxidation [ 5 ]. Therefore, hydrogen was also a significant energy source for chemolithoautotrophs inhabiting hydrothermal vents [ 11 , 55 ]. In the present study, we found that Epsilonproteobacteria exhibit a higher genetic potential for increased activity of Hyd1 and Hyd5, responsible for hydrogen oxidation, under high temperature of 65 °C. However, this potential is inhibited by extremely acidic conditions [ 66 , 67 ]. Unlike Hyd1 and Hyd5, Hyd4 catalyzes the production of H 2 depending on electrochemical proton gradient (Δμ H + ) [ 68 – 70 ], of which the membrane subunits HyfDEF are involved in proton-translocating [ 71 ]. The high abundance of hyfBEF (mainly hyfEF ) genes in the WV 65 °C and 45 °C samples, as well as in the YV samples (Fig. 4 ), suggests that Nautiliales and Campylobacterales could use HyfEF for proton translocation to adapt to acidic environments. Carbon fixation requires the coupling of nitrogen assimilation with growth [ 72 ]. Nautiliales and Campylobacterales have the potential to utilize both GDH and GS-GOGAT pathway for NH 4 + assimilation (Fig. 4 ). In the GDH pathway of ammonium assimilation, Nautiliales utilize NAD(H)-GDHs while Campylobacterales utilize NADP(H)-GDHs (Fig. 4 ). NADP(H)-GDHs are typically involved in ammonia assimilation [ 73 ], whereas NAD(H)-GDHs can generate 2-oxoglutarate from glutamate, an important intermediate in the rTCA cycle [ 74 ] that may enhance the cycle. This is consistent with our observation that Nautiliales Lebetimonas -dominated chemolithoautotrophs at WV 65 °C exhibit higher carbon fixation activity (Figs. 2 and 4 ). The presence of high relative abundances of narB , nasA , and nirA genes in all samples suggests that both Nautiliales and Campylobacterales may utilize the assimilatory nitrate reduction pathway to obtain NH 4 + (Fig. 4 ). Although napA/B genes, which are involved in dissimilatory nitrate reduction, were present in both Nautiliales and Campylobacterales , they were only abundant in WV 65 °C (Fig. 4 ). This observation may be attributed to the fact that higher temperatures, such as in WV 65 °C, are often accompanied by lower oxygen content [ 1 ], and nitrate can serve as an alternative electron acceptor in place of oxygen [ 11 ]. The absence of genes encoding for dissimilatory nitrite reductase (e.g., nirBD , nrfAH , nirS , nirK ) but the presence of abundant napA/B genes at WV 65 °C (Fig. 4 ) suggests assimilatory nitrite reduction may be involved in detoxifying nitrite produced by dissimilatory nitrate reductase within cells [ 75 ]. Campylobacterales could also obtain nitrogen via nitrogen fixation at WV 45 °C and 30 °C (Fig. 4 ). Overall, the chemoautotrophic members of Epsilonproteobacteria employed flexible strategies to acquire inorganic nitrogen for growth in hydrothermal ecosystems characterized by varying physicochemical conditions, including temperature, pH, oxygen levels, and inorganic nitrogen concentrations [ 76 , 77 ]. Temperature is a crucial factor that influences the oxygen content of water [ 1 ]. Indeed, there was a significant decrease in the oxygen content from the reference sites to the interiors of the vents (Fig. 1 ). Furthermore, particles in vent fluids may contain niches with lower oxygen content because microbes attached to their surfaces can create micro-zones of depleted oxygen through respiration [ 78 , 79 ]. In this study, we detected three oxidases: cytochrome bd ubiquinol oxidase (Cyd), cytochrome c oxidase cbb3-type (Cco), and aa3-type (Cox) (Fig. 4 ). Cyd and Cco are expressed in microaerobic conditions, whereas Cox is expressed under aerobic conditions [ 80 , 81 ]. The Cyd and Cco assigned to Nautiliales and Campylobacterales were more abundant in the UH fraction, while Cox was much more abundant in the L fraction (Fig. 4 ), suggesting the Nautiliales and Campylobacterales experienced microaerobic/anaerobic conditions. One key difference between Nautiliales and Campylobacterales in terms of oxygen respiration is that Nautiliales contain only Cyd, while Campylobacterales contain both Cyd and Cco (Fig. 4 ). We also detected that Cyd is the only oxidase present in all genomes of hyperthermophilic Aquificae (Fig. 6 ). In addition to low oxygen stress, Cco is also capable of oxygen respiration under aerobic conditions [ 82 , 83 ], while Cyd is involved in the bacterial response to a wide variety of stress conditions, including high temperature and gasotransmitters like H 2 S [ 84 – 86 ]. The highest enrichment and abundance of cydA/B genes assigned to Nautiliales in the UH fraction of WV 65 °C sample compared to other key genes (Fig. 4 ) suggest Cyd might play a critical role in enabling Nautiliales to thrive in microaerobic/anaerobic conditions induced by high temperature. A previous study also found cydB was helpful for Brucella suis to grow by utilizing nitrate and detoxifying nitrite [ 87 ], which coincides with our findings that Nautiliales at WV 65 °C had higher potential to produce nitrite by reducing nitrate compared to the Campylobacterales at WV 45 °C and 30 °C. We were intrigued by the observation that the most abundant KO group enriched at WV 30 °C (Fig. 5 a) corresponded to the TC.FEV.OM protein, which is an iron (Fe) complex outer-membrane receptor protein. Under oxic conditions, iron (Fe) is primarily present in an oxidized ferric form (Fe 3+ ) that is insoluble at neutral pH [ 88 ]. To import Fe 3+ , bacteria secrete ferric chelators known as siderophores, which have an intimate relationship with iron complex outer-membrane receptor protein. Thus, the product encoded by the TC.FEV.OM gene appeared to play an important role in importing insoluble Fe 3+ complexes at normal temperatures (e.g. 30 °C). At acidic pH or under anaerobic conditions, iron is predominantly present in a soluble ferrous form (Fe 2+ ), which can be directly taken up into the cell via Fe 2+ transporters like FeoB [ 89 ]. A previous study found that Fe 2+ concentration was much higher in the shallow-sea hydrothermal vent center, and decreased dramatically as the distance from the vent center increased [ 90 ]. Since the pH at WV was acidic (Fig. 1 ) and high temperature usually accompanies low oxygen conditions [ 1 ], it is likely that Fe 2+ served as the primary source of iron for microorganisms at WV 65 °C. Consistent with this hypothesis, the feoB gene was found to be one of the most abundant genes, with the highest abundance at WV 65 °C and lowest at WV 30 °C (Fig. 5 a). The TC.FEV.OM and feoB were both relatively abundant at WV 45 °C, indicating both Fe 2+ and Fe 3+ were the main iron sources, as Fe 2+ oxidized to Fe 3+ when oxygen increased with the decrease in temperature. Our temperature gradient incubation demonstrated that temperature could determine the forms of iron (Fe 2+ or Fe 3+ ) that are available to microbes by affecting oxygen content. Microbial adaption strategies of high temperature and low pH The discussion above reveals the differences in chemolithoautotrophic metabolism of key elements under different temperature and pH conditions. In this session, we further focus on the potential essential functions for chemolithoautotrophs adapting to high temperature and low pH. The comparison of metagenomes from the UH fraction revealed that member transport, signal transduction, and some genes of unknown functions may play important roles for chemolithoautotrophs to adapt to extreme environments (Figs. S 7 and S 8 ). For high-temperature adaptation, the gene rgy , which is involved in positive supercoiling in closed circular DNA for DNA stability at high temperature [ 13 , 91 , 92 ], was found to be one of the most abundant genes at WV 65 °C, but not detected at WV 30 °C (Fig. 5 a). It exists in almost all genomes of Nautiliales and Aquificae (Fig. 6 ). Therefore, it is likely to be a key gene for Nautiliales living under high temperature. The other genes that facilitated the boom of Nautiliales at high temperature may include proA , which is involved in the biosynthesis of proline, an amino acid used by thermophiles to keep protein thermostabilization [ 19 ], pepF , which participates in the regulation of sporulation [ 93 – 95 ], splB , which is involved in the repair of UV light-induced DNA damage in spores [ 96 ], and mrcA , murG, and mltC , which are involved in biosynthesis of peptidoglycan, the major component of gram-negative cell walls (Fig. 5 a). PepF only existed in all Nautiliales and splB only existed in the MAG (WV45 °C bin6) of our study (Fig. 6 ), indicating sporulation is a special strategy for Nautiliales to cope with heat stress, and maintaining UV resistance of spore is a unique strategy for Nautiliales inhabiting shallow-sea hydrothermal ecosystem. Heat shock is a widespread protective mechanism in bacteria that enables them to adapt and survive under adverse conditions. Transcriptional regulation of heat-shock genes can be positive or negative, and mediated by dedicated regulatory proteins. In our study, the genes encoding for dedicated regulatory proteins include hrcA , hspR , and rpoH (Fig. 4 ), of which hrcA and hspR are negative regulators, while rpoH is a positive regulator [ 97 ]. The products of hrcA and hspR are DNA-binding repressors that can bind specific operators and repress transcription of heat-shock genes under normal conditions and rapidly derepress transcription of these genes upon heat stress [ 97 ], while the rpoH gene product was able to confer specificity to RNA polymerase in recognizing heat-shock promoters and promote transcription initiation at heat-shock promoters upon heat stress [ 98 ]. In our study, hrcA was most abundant in WV 65 °C sample, while hspR was abundant in all samples (Fig. 4 ). The activity of HrcA in Helicobacter pylori has been proven to be temperature-dependent and become essentially inactive when temperature increased above 37 °C [ 97 ]. In this study, we observed that hrcA assigned to Nautiliales has higher relative abundance in L fraction than in UH/H fractions compared to other key genes assigned to Nautiliales at WV 65 °C, which were more abundant in the UH/H fraction (Fig. 4 ). These results indicate HrcA might be an important thermosensor [ 99 ]. The HrcA in Nautiliales probably is directly regulated by the master regulator HspR, just like those in Helicobacter pylori [ 97 ]. For low pH adaption, several genes may play a role in maintaining the cells’ pH homeostasis, including those encoding for the monovalent cation/H + antiporter, Ca 2 + /H + antiporter, trk system K + uptake protein, Cu 2+ exporting ATPase, ABC-2 type transport system permease protein ABC-2.P, which is related to osmotic pressure [ 100 ], O-antigen ligase, which catalyzes a key step in the synthesis of lipopolysaccharide (LPS), a matter contributes to the effective permeability barrier of the bacterial outer membrane [ 101 ], porin TC.OOP , a member of OmpA-OmpF porin that has been suggested to play an important role in acid tolerance [ 102 ]. These genes were found to be more abundant at YV 45 °C and 30 °C than at WV 30 °C (Fig. 5 c). Notably, the present study identified genes encoding all subunits of proton-pumping NADH: ubiquinone oxidoreductase, also called complex I. The membrane arm subunits of complex I ( nuoA/H/J/K/L/M/N ) were marked as core functions at WV (Fig. S 9 a). However, these subunits were more abundant at YV 30 °C and 45 °C than at WV 30 °C (Fig. S 9 b). Especially the nuoL/M/N subunits, which are homologous to the Na + or K + /H + antiporter family and likely participate in proton translocation [ 103 ], were the three most abundant subunits of complex I at YV 30 °C or 45 °C. These results suggest that the membrane arm subunits of complex I may also participate in maintaining cellular pH homeostasis under low pH conditions. In conclusion, the strategies used by Campylobacterales at YV to maintain a near-neutral intracellular pH include actively exporting protons with proton pumps, reducing proton influx through electrostatic repulsion by maintaining a positive membrane potential, and forming an impermeable cell membrane to restrict proton influx into the cytoplasm [ 104 ]. In addition, genes encoding for the twin-arginine translocation proteins ( tatBC ), which can translocate tightly folded proteins across biological membranes using only a pH gradient independently of ATP [ 105 , 106 ], were found to be enriched at YV 45 °C and 30 °C (Fig. 5 c). This suggests that Campylobacterales may take advantage of the extremely acidic condition to conserve energy for metabolism."
} | 5,656 |
31844294 | PMC7008030 | pmc | 3,267 | {
"abstract": "The methylotrophic yeast Pichia pastoris is widely used in the manufacture of industrial enzymes and pharmaceuticals. Like most biotechnological production hosts, P. pastoris is heterotrophic and grows on organic feedstocks that have competing uses in the production of food and animal feed. In a step toward more sustainable industrial processes, we describe the conversion of P. pastoris into an autotroph that grows on CO 2 . By addition of eight heterologous genes and deletion of three native genes, we engineer the peroxisomal methanol-assimilation pathway of P. pastoris into a CO 2 fixation pathway resembling the Calvin-Benson-Bassham cycle, the predominant natural CO 2 fixation pathway. The resulting strain can grow continuously with CO 2 as a sole carbon source at a µ max of 0.008 h -1 . The specific growth rate was further improved to 0.018 h -1 by adaptive laboratory evolution. This engineered P. pastoris strain may promote sustainability by sequestering the greenhouse gas CO 2 and by avoiding consumption of an organic feedstock with alternative uses in food production.",
"introduction": "Introduction Industrial biotech production of proteins and chemicals relies on heterotrophic host cells, which grow on feedstocks, such as glucose, sucrose or glycerol, that have competing uses in the production of food and animal feed. Biotech manufacturing would become more sustainable if it could use CO 2 as a carbon feedstock, as this would not consume organic feedstocks and would deplete atmospheric CO 2 . CO 2 is converted into biomass by autotrophic organisms such as plants and algae. Channeling CO 2 into the central carbon metabolism of industrial microbes could generate autotrophic or mixotrophic organisms with the potential for increased carbon efficiency (e.g. mixed-substrate production of succinic or acetic acid from CO 2 and methanol) 1 . The Calvin-Benson-Bassham (CBB) cycle 2 is one of six naturally occurring CO 2 fixation pathways 3 , 4 and includes ribulose-1,5-bisphosphate carboxylase/oxygenase (RuBisCO), which is the most abundant enzyme in the biosphere and fixes around 90% of the inorganic carbon converted into biomass 5 . Previously, metabolic engineers have endeavored to equip the heterotrophic model organisms Escherichia coli , Methylobacterium extorquens and Saccharomyces cerevisiae with CBB cycle genes. Expressing RuBisCO and phosphoribulokinase (PRK) genes in E. coli led to decreased release of CO 2 when growing on arabinose 6 . Antonosky et al. enabled “hemiautotrophic” growth of E. coli with a modularized carbon metabolism, utilizing pyruvate as an energy source for a heterologous CBB cycle 7 . Hemiautotrophic means that only part of the carbon assimilated originated from CO 2 , with the rest derived from pyruvate. In a follow-up study the mutations that stabilized the non-native CBB cycle in E. coli \n 8 were identified. Parts of the CBB cycle have also been introduced into the yeast species S. cerevisiae \n 9 – 12 ; ethanol yields were increased by using CO 2 as an additional electron acceptor to reoxidize NADH. More recently, the assimilatory pathway of Methylobacterium extorquens AM1 was blocked and RuBisCO and PRK were overexpressed, resulting in a strain that can incorporate CO 2 into biomass using methanol as energy source. However, this engineered methylobacterium was unable to grow continuously on CO 2 as a sole carbon source 13 . Engineering of a synthetic autotrophic microorganism able to grow with CO 2 as the sole carbon source has not been reported to our knowledge. Pichia pastoris (syn.: Komagataella phaffii ) 14 , 15 is widely used to produce heterologous proteins for the biopharmaceutical 16 and enzyme markets 17 . P. pastoris is a chassis host for metabolic engineering 18 and a model for peroxisome biogenesis 19 , 20 . This industrial yeast has a methylotrophic lifestyle and uses C1 compound methanol as its sole energy and carbon source. Methanol is oxidized to formaldehyde, which then enters either a dissimilatory or assimilatory metabolic branch. In the assimilatory branch formaldehyde is converted to phosphosugars needed for biomass, whereas in the dissimilatory branch formaldehyde is oxidized to CO 2 , yielding NADH. Steps of the dissimilatory branch are carried out both in the peroxisome and in the cytosol, but the assimilatory branch is localized entirely in peroxisomes 21 . During growth on methanol, peroxisomes are highly abundant in the cell and methanol utilization enzymes are highly expressed e.g. alcohol oxidase 1 (Aox1). A suite of molecular biology tools including CRISPR/Cas9 methods are available for P. pastoris \n 18 , 22 – 24 that allow entire metabolic pathways to be integrated without a need for selection markers. We report de novo engineering of a CBB cycle into P. pastoris and analysis of the capability of engineered strains to grow using CO 2 as a sole carbon source.",
"discussion": "Discussion We reengineered yeast metabolism to enable a synthetic chemoorganoautotrophic lifestyle by introducing a heterologous CBB cycle into the methylotrophic yeast P. pastoris. This enables the cells to utilize CO 2 as their sole carbon source, and to grow as an autotrophic organism. The heterologous CBB cycle is localized to peroxisomes by targeting the enzymes via PTS1 signals. The peroxisomal pathway enables superior growth on CO 2 compared to a cytosolic version, highlighting the importance of cellular compartmentalization, which likely facilitated functional CO 2 fixation in our set-up compared to other approaches 13 . The spatial separation can have a beneficial impact on the operation of other pathways like the pentose phosphate pathway, enabling different concentrations of key intermediates like ribose-5-phosphate or sedoheptulose-1,7-bisphosphate. In addition, a channeling effect by the close proximity of CBB cycle enzymes in the dense peroxisomal environment may improve flux rates 30 , 31 . P. pastoris may serve as a promising chassis cell to also test synthetic CO 2 fixation pathways in vivo such as the malonyl-CoA-oxaloacetate-glyoxylate (MOG) pathway 32 or the crotonyl–coenzyme A (CoA)/ethylmalonyl-CoA/hydroxybutyryl-CoA (CETCH) cycle 33 . One needs to consider however whether the intermediate metabolites of such pathways are available in the peroxisome. Adaptive evolution was employed to increase the maximum specific growth rate on\nCO 2 more than twofold, from 0.008 h -1 to 0.018\nh -1 . After evolution for 30 generations single isolates were analyzed\nand three independent isolates (clone 5, 6 and 9) were sequenced showing in total 6,\n5 or 3 mutations compared to the CBBp+RuBisCO parental strain ( Supplementary Table 6 ).\nNotably, two isolates have a mutation in the heterologous PRK gene\nleading to an amino acid exchange (Ala2Gly or Thr5Ala), while the third isolate\ncarries a mutation in NMA1 (Thr358Ile), encoding for nicotinic acid\nmononucleotide adenylyltransferase. In addition clone 5 shows three mutations in\nrRNA loci with a frequency of 70 %. Both altered coding sequences give rise to\nfurther engineering targets. PRK catalyzes the ATP dependent phosphorylation of\nD-ribulose-5-phosphate and thus a key step of the CBB cycle. ATP and NADH balancing\nis crucial for a functional integration of a heterologous CBB cycle into the central\ncarbon metabolism 7 , 8 , 12 , 34 . Nma1 is involved in maintaining\nhigh NAD levels upon growth on methanol 21 , 35 and mutations\nleading to activity changes could alter both NADH and ATP levels. In addition to its\nimpact on ATP consumption, an altered PRK activity would affect the availability of\nD-ribulose-5-phosphate for various biosynthetic routes 36 . P. pastoris has been demonstrated to be a suitable chassis for the production of enzymes and chemicals 18 , 37 , making pathway engineering toward varied products straightforward. Implementation of CO 2 as a carbon source in industrial processes raises several considerations. Any CO 2 assimilation pathway requires energy and reducing power, provided by light or a chemical electron donor such as hydrogen, formate or methanol. While light and hydrogen require specific bioreactor equipment, a water-soluble, potentially renewable chemical energy source like methanol or formate can be directly applied in standard setups and in large-scale bioreactors 38 . More oxidized products, like organic acids, require less reducing power. Combined with a reduced co-substrate, a net CO 2 fixation can be obtained when producing organic acids such as succinic, lactic, acetic or itaconic acid from methanol and CO 2 . Theoretically, up to 62 kg CO 2 are fixed when producing 100 kg succinic acid with a methanol co-feed 1 . For cost-efficient production of bulk chemicals, volumetric productivity must achieve a range of at least 2 g L -1 h -1 \n 39 . P. pastoris is well established to produce at biomass concentrations of 100 g L -1 or more 40 . The current best specific CO 2 assimilation rate reported here of 0.03 g g -1 h -1 (calculated on specific growth rate) would correspond to a potential volumetric productivity of about 2 g L -1 h -1 succinate, as an example. This indicates that production rates would already be close to existing processes. We have demonstrated that conversion of a heterotroph to a synthetic autotroph is possible. Rational re-engineering of metabolism led to growth on CO 2 as the only carbon source. Adaptive evolution more than doubled growth rates, likely through adjustments in the CO 2 assimilation pathway and cofactor availability. The resulting yeast strains may form the basis of a system for producing bulk chemicals and enzymes based on CO 2 and may support mitigation of atmospheric CO 2 ."
} | 2,445 |
35572762 | PMC9089743 | pmc | 3,268 | {
"abstract": "The demand for self-healing\nelastomers is increasing due to the\npotential opportunities such materials offer in reducing down-time\nand cost through extended product lifetimes and reduction of waste.\nHowever, further understanding of self-healing mechanisms and processes\nis required in order to develop a wider range of commercially applicable\nmaterials with self-healing properties. Epoxidized natural rubber\n(ENR) is a derivative of polyisoprene. ENR25 and ENR50 are commercially\navailable materials with 25 and 50 mol % epoxidation, respectively.\nRecently, reports of the use of ENR in self-healing materials have\nbegun to emerge. However, to date, there has been limited analysis\nof the self-healing mechanism at the molecular level. The aim of this\nwork is to gain understanding of the relevant self-healing mechanisms\nthrough systematic characterization and analysis of the effect of\ncross-linking on the self-healing performance of ENR and natural rubber\n(NR). In our study, cross-linking of ENR and NR with dicumyl peroxide\nand sulfur to provide realistic models of commercial rubber formulations\nis described, and a cross-linking density of 5 × 10 –5 mol cm –3 in sulfur-cured ENR is demonstrated to\nachieve a healing efficiency of 143% for the tensile strength. This\nwork provides the foundation for further modification of ENR, with\nthe goal of understanding and controlling ENR’s self-healing\nability for future applications.",
"conclusion": "Conclusions This\nwork compared the self-healing of dynamic cross-links (sulfur-cured)\nand static cross-links (DCP-cured) in ENR and NR. Materials were prepared\nwith a range of cross-linking densities, leading to the demonstration\nof a direct relationship between cross-link density and self-healing\nperformance. Thus, the ability to directly influence self-healing\nperformance through variation of the cross-link density was demonstrated.\nThis is a rare example of control of self-healing properties in elastomers.\nComparison of the dynamic and static cure systems over the same cross-link\ndensity range revealed an enhancement of self-healing due to dynamic\ncross-linking and enabled the contribution of this effect to self-healing\nperformance to be estimated. Sulfur-cured ENR was also shown to have\nsuperior self-healing performance relative to sulfur-cured NR under\nthe conditions tested. Although the focus of this work has been\non NR, we highlight the\nimportance of control over cross-linking density in achieving the\noptimal balance between mechanical properties and self-healing performance\nof cross-linked polymers in general. These results contribute to the\ngrowing understanding of self-healing processes for future application\nof sustainable materials in both academic and industrial contexts.",
"introduction": "Introduction Natural rubber (NR),\na renewable resource derived from Hevea brasiliensis , has mechanical properties that\nare generally superior to those of synthetic rubber. The material\nhas high elasticity, high tensile strength, and low heat build-up;\nhowever, it also has low oil resistance and gas permeability. 1 , 2 Epoxidation of NR to create epoxidized natural rubber (ENR) improves\nthese disadvantageous properties while retaining many of the positive\nproperties of NR. 1 , 3 ENR exists commercially in two\nforms, ENR25 and ENR50, which contain 25 and 50 mol %, respectively,\nof epoxy groups on the cis -1,4-isoprene backbone.\nDue to the presence of these epoxy groups, ENR is also more polar\nthan NR, which increases its compatibility with more polar components\nsuch as silica, with the additional benefit of enabling a variety\nof secondary modifications. 2 , 3 In this context,\nENR has a range of applications from adhesives\nto tires and other automotive parts. 2 , 4 While its chemical\nand mechanical properties have been examined for more than 40 years, 5 − 7 it has yet to realize its full potential as a commercial elastomer.\nHowever, recently there has been an increasing interest in ENR for\ntires in electric vehicles as it has much potential for low rolling\nresistance materials 8 , 9 and for self-healing applications. 10 − 15 Self-healing of polymeric materials is a highly desirable property\nand is defined as the capability of a material to recover from physical\ndamage. 16 , 17 ENR can be cured using the same established\nchemistries as NR and\nother rubbers, typically sulfur or dicumyl peroxide (DCP) cures. 4 The poor ageing characteristics of ENR cured\nwith sulfur, due to acid-catalyzed ring-opening of the epoxides to\nform ether cross-links, can be offset with the addition of a suitable\nbase. 18 , 19 In addition to these curing methods in common\nwith NR, it has also been demonstrated that ENR can be cured with\ndicarboxylic acids 20 − 23 or with zinc acrylate via an oxa-Michael reaction. 24 These curing methods avoid the drawback of the\nsulfur cure and also afford the possibility of introducing different\nchemical functionalities via the structure of the\ncross-linker. As an example, Imbernon et al. incorporated a\ndisulfide bond using dithiodibutyric acid as a cross-linker. 23 This allowed the material to regain most of\nits mechanical properties after reprocessing, creating an ENR with\nthe ability to be partially recycled. Cheng et al. took this further by employing a mixture of diamine and dicarboxylic\ncuring agents that contained disulfide bridges, thus producing a self-healing\nENR that could achieve a self-healing efficiency of 98%. 12 Self-healing was achieved through dynamic disulfide\nbridges which have a low bond dissociation energy that promotes a\ndisulfide metathesis reaction. Self-healing can also be achieved\nwith sulfur cure systems. The\nratio of dynamic disulfidic/polysulfidic cross-links was investigated\nin sulfur-cured NR by Hernández et al. , and\nit was concluded that while the ratio was important to the self-healing\nperformance, the main limiting factor was the sulfur content as the\nsamples with lower sulfur content reached higher self-healing performance\ndespite similar ratios as other samples. 25 It is established that ENR has self-healing properties. For\nexample,\nRahman et al. determined by ballistic testing that\nself-healing could occur autonomically in ENR that was lightly cross-linked\nwith DCP. 10 This was proposed to be due\nto the synergistic effect of chain interdiffusion and polar interactions.\nConsequently, ENR50 was found to self-heal at a higher wt % DCP than\nENR25 as it has a greater amount of polar interactions. It was observed\nthat once the cross-linking density increases above a certain value,\nthe material can no longer self-heal. Thus, to develop useful materials,\na compromise must be achieved between maintaining good mechanical\nproperties (that requires a high cross-linking density) and imparting\nself-healing ability (which is limited by the cross-linking density). These literature examples all compare the self-healing performance\nagainst the cure system or cure ingredient content. However, to our\nknowledge, the direct relationship between the cross-linking density\nand self-healing performance has not been examined in elastomers.\nHere, we examine self-healing in ENR and NR compounded with different\ncuring systems in a range of cross-linking densities to determine\nwhether there is a relationship between self-healing performance and\ncross-link density and to estimate the extent of this interaction\nrelative to the autonomic self-healing behavior of ENR.",
"discussion": "Results and Discussion Cross-linked ENR Two master batches of ENR with 0.8\nwt % sulfur and 2.0 wt % DCP were manufactured. Dumbbells cut out\nof these materials were then subjected to self-healing testing at\ndifferent temperatures and times with a minimum of three samples for\neach test. The conditions selected to enable comparison of self-healing\nacross a range of materials and cross-linkers were as follows: 1,\n2, and 24 h at room temperature and 1, 2 and 24 h at 120 °C.\nThe results of these initial self-healing tests, together with dynamic\nmechanical analysis (DMA) and IR data, can be seen in Figure 1 and Tables S1 and S2 (see Supporting Information ). Samples are indicated\nby curative/self-healing time (hours)/self-healing temperature (°C),\nfor example, S/2/120 represents a sulfur cure for 2 h at 120 °C.\nThese results reveal that there is no significant self-healing at\nroom temperature for either curing system, even after 24 h. The tensile\nstrength is recovered in the S-cured ENR by only approximately 30%\nat room temperature and in DCP-cured ENR by approximately 10%. Meanwhile,\nelongation at break recovery is very low at about 5% in both systems. Figure 1 Sulfur-cured\nENR: (a) tensile properties; inset—magnified\ninitial region; (b) tan δ curves; (c) IR spectra. DCP-cured\nENR: (d) tensile properties; inset—magnified initial region;\n(e) tan δ curves; (f) IR spectra. Key: curative/SH time (hours)/SH\ntemperature (°C) ( e.g. S/2/120 represents a\nsulfur cure for 2 h at 120 °C). See the Supporting Information for tensile data for 24/120. However, heating at 120 °C has a dramatic effect on the self-healing\nability. At this temperature both, the hydrogen bonding and dynamic\ndisulfide bridges should be disrupted, and the polymer chains are\nfree to flow past each other, allowing for chain interdiffusion and\nbond reformation. 30 − 34 The S-cured samples show that the self-healing after 1 h is markedly\nimproved, with a tensile strength recovery of 93% and elongation at\nbreak recovery of 88%. Increases for DCP-cured ENR can also be observed\nbut to a lesser extent. Although the high-temperature method has positive\neffects over 1 and 2 h, the samples exposed for 24 h suffer deleterious\neffects similar to those seen in thermal oxidation studies of ENR. 35 It has been reported that at 120 °C acid-catalyzed\nring-opening of the epoxides results in the ENR becoming more brittle\nand stiff through introduction of ether, carboxylate, and hydroxyl\nfunctionalities. 35 This is most clearly\nreflected in the broad tan δ peak shifted to high temperatures\nin Figure 1 b, which\nsupports a large increase in the cross-link density due to the formation\nof new ether bonds. Ether peaks are present in the IR spectrum in Figure 1 c at 1050 cm –1 , as well as a carboxyl peak at 1700 and 3400 cm –1 for hydroxyl groups. These peaks are also present\nin the IR spectrum of DCP-cured ENR for 24 h ( Figure 1 f). Consistent with this interpretation,\nbroadening and shifting of the tan δ peak is also observed in Figure 1 e. From these\ndata, self-healing for 1 h at 120 °C was examined\nto further probe the self-healing mechanism. A range of sulfur-cured\nENR samples were prepared with varying sulfur contents (ENR S1–S5, Table 1 ). The cross-linking\ndensity was calculated using the Flory–Rehner equation ( via swelling in toluene), resulting in values from 1.1 ×\n10 –5 to 6.2 × 10 –5 mol cm –3 . Self-healing performance remains high for all samples\n(>76%, see Table S4 ) as revealed by\ntensile\ntesting ( Figure 2 a),\nwhich indicates that chain interdiffusion efficiently occurs within\n1 h of healing at 120 °C, facilitating recovery of the entanglements. Figure 2 (a) Tensile\nproperties and (b) self-healing vs cross-link density\nof ENR S1–S5 compounds after 1 h at 120\n°C. Key = virgin (solid line) and self-healed (SH) (dashed line). Figure 2 b highlights\nthat a maximum in self-healing performance occurs at a cross-link\ndensity of approximately 5 × 10 –5 mol cm –3 , suggesting that good material properties do not\nalways need to be compromised to achieve high levels of self-healing\nperformance. Self-healing values greater than 100% are reported because\nof the introduction of monosulfidic bonds during heating in the self-healing\nprocess. This was confirmed by reductive swelling experiments which\nwill be discussed later in this work. The relationship between cross-linking\ndensity and self-healing performance has been discussed previously, 10 , 12 , 25 , 36 but to our knowledge, the direct control of cross-link density to\nmaximize self-healing performance has not been explored explicitly\nfor elastomers. Self-healing efficiency is affected by the ability\nof polymer chains (and therefore broken cross-links) to diffuse across\na cut and also by the availability of broken cross-links to enable\na cross-link to reform. These two factors are competing: as cross-link\ndensity increases, chain diffusion decreases, whereas the availability\nof broken cross-links increases. Therefore, a maximum self-healing\nefficiency is observed for a level of cross-link density at which\nthese two competing factors balance ( Figure 3 ). The level of cross-linking required for\noptimum self-healing efficiency will depend on the nature of the elastomer\nand the dynamic bond as well as on the conditions of self-healing. Figure 3 Qualitative\nrepresentation of the competing factors that produce\na maximum in the self-healing performance of rubbers cured with dynamic\ncross-links. To further clarify the role of\ndynamic cross-links in the self-healing\nof rubbers, a range of DCP-cured ENR samples were prepared ( Table 2 ) in which the carbon–carbon\ncross-links are not dynamic and cannot, therefore, reform ( Figure 4 ). This should demonstrate\nthe autonomic behavior of cross-linked ENR, thereby allowing the additional\ncontribution of dynamic sulfur cross-links to be estimated. As expected,\nthe DCP-cured ENR shows a steady decrease in self-healing performance\nwith increasing cross-link density with no significant maximum observed\nat intermediate cross-link density ( Figure 5 a); this is in contrast to the behavior described\nabove for sulfur-cured ENR ( Figure 2 b). This indicates that chain diffusion, which decreases\nas the cross-link density increases, is the only contribution to self-healing\n(black line, Figure 3 ). Figure 5 b highlights\nthe different behavior between these two cross-linking systems and\nprovides an estimate of the underlying self-healing ability (red line)\nand therefore the contribution to self-healing of dynamic cross-links\nin the sulfur system (shaded region). This supports the relationship\ndescribed in Figure 3 , highlighting that it is possible to optimize self-healing through\ncross-link density to achieve better materials. Figure 4 Dynamic and static cross-links\ninvestigated in this work. Figure 5 (a) Self-healing\nof tensile properties in DCP-cured ENR D1–D7\ncompounds after 1 h at 120 °C; (b) isolation of the contribution\nto self-healing from dynamic cross-links in sulfur-cured ENR. The maximum for self-healing in sulfur-cured ENR\nwas observed at\na lower cross-linking density in this work than in the study by Cheng et al. ( 12 ) After reductive swelling\nexperiments, a sulfur-cured ENR sample partially dissolved, but the\nmajority was retained as a gel suggesting the presence of monosulfidic\ncross-links (Table S11, Supporting Information ) which are known to hinder chain diffusion. 26 − 29 As Cheng et al. employed disulfide cross-linkers in their work, these monosulfidic\ncross-links could explain the difference in cross-link density for\nthe peak of maximum self-healing between these works. They also explain\nwhy self-healing values >100% are reported ( Figure 2 b) as the presence of these cross-links results\nin higher tensile strengths than in the virgin samples. Further\ncharacterization of the systems described was carried out\nby DMA and FT-IR spectroscopy. It is interesting to note that while\nthe self-healing performance is dependent upon the cross-link density,\nthere is little variation in the viscoelastic properties across the\nrange of samples investigated ( Figure 6 ). This suggests that tan δ is not a useful parameter\nfor predicting the self-healing performance, and techniques that reveal\nthe cross-link density of a sample more directly, such as double-quantum\nNMR spectroscopy or swelling as in this analysis, are more appropriate\npredictors of self-healing performance. Similarly, little variation\nin FT-IR spectra across the range of sample studies suggests that\nthe self-healing performance is not influenced by changes in hydrogen-bonding\ncharacteristics of the system ( Figure 7 ). Figure 6 Tan δ data from DMA for ENR samples. (a) S1–S5\nand\n(b) D1–D7. Figure 7 FT-IR spectra of ENR\nsamples. (a) S1–S5 and (b) D1–D7.\nSpectra cut to show regions of polar groups: 3500–3200 cm –1 (hydroxyl), 1750–1600 cm –1 (carboxyl), 1100–1000 cm –1 (ether), and\n900–800 cm –1 (epoxide). Cross-linked NR Samples were prepared with NR to explore\nthe generality of the relationship between the cross-link density\nand self-healing performance. As for ENR, two sets of samples were\nprepared; sulfur-cured NR (S1–S9, Table 3 ) and DCP-cured NR (D1–D7, Table 4 ). Figure 8 shows a decrease in self-healing\nperformance for sulfur-cured NR as well as for DCP-cured NR across\nthe range of cross-link densities examined. Indeed, the DCP-cured\nNR shows little discernible self-healing ability across a wide range\nof cross-linking densities. Self-healing in DCP-cured NR can only\noccur via chain diffusion, and this is limited to\nlow cross-link densities. As highlighted in Figure 9 a, the decrease for the sulfur-cured NR samples\nis in contrast to the results for S-cured ENR, for which a distinct\nmaximum in self-healing performance was apparent. The lack of a maximum\nis proposed to be due to reduced chain diffusion dominating the self-healing\nperformance in NR ( Figure 3 ). Despite there being no obvious maximum in the self-healing\nperformance, a plot comparing S- and DCP-cured NR does reveal an enhancement\nin self-healing performance due to the dynamic cross-linking of the\nformer ( Figure 9 b).\nAlthough at very low and very high cross-link densities, the two systems\nare similar, at intermediate values, a significant contribution to\nself-healing performance due to the dynamic sulfur cross-links can\nbe discerned. Figure 8 Self-healing of tensile properties after 1 h at 120 °C\nin\n(a) sulfur-cured NR (S1–S9); (b) DCP-cured NR (D1–D7). Figure 9 (a) Comparison of the self-healing performance for sulfur-cured\nENR and sulfur-cured NR; (b) isolation of the contribution to self-healing\nfrom dynamic cross-links in sulfur-cured NR. Reductive swelling experiments were carried out on a sulfur-cured\nNR sample (Table S11, Supporting Information ). This sample fully dissolved after treatment with 1-hexanethiol,\nsuggesting that it only contained polysulfidic and disulfidic linkages.\nAs no monosulfidic cross-links are present, this suggests that the\nself-healing performance seen in Figure 8 a is the best that can be achieved with sulfur-cured\nNR under these conditions. However, Hernández et al. achieved self-healing of 80% with sulfur-cured NR at higher cross-link\ndensity values than that reported in this work by using conditions\nof 70 °C for 7 h. 25 This highlights\nthat different conditions yield different absolute values of self-healing\nand that this should be taken into account when assessing the application\nof a self-healing rubber product."
} | 4,754 |
33877964 | PMC8057819 | pmc | 3,269 | {
"abstract": "A major open question in microbial community ecology is whether we can predict how the components of a diet collectively determine the taxonomic composition of microbial communities. Motivated by this challenge, we investigate whether communities assembled in pairs of nutrients can be predicted from those assembled in every single nutrient alone. We find that although the null, naturally additive model generally predicts well the family-level community composition, there exist systematic deviations from the additive predictions that reflect generic patterns of nutrient dominance at the family level. Pairs of more-similar nutrients (e.g. two sugars) are on average more additive than pairs of more dissimilar nutrients (one sugar–one organic acid). Furthermore, sugar–acid communities are generally more similar to the sugar than the acid community, which may be explained by family-level asymmetries in nutrient benefits. Overall, our results suggest that regularities in how nutrients interact may help predict community responses to dietary changes.",
"introduction": "Introduction Understanding how the components of a complex biological system combine to produce the system’s properties and functions is a fundamental question in biology. Answering this question is central to solving many fundamental and applied problems, such as how multiple genes combine to give rise to complex traits ( Phillips, 2008 ; Mackay, 2014 ), how multiple drugs affect the evolution of resistance in bacteria and cancer cells ( Michel et al., 2008 ; Wood et al., 2014 ), how multiple environmental stressors affect bacterial physiology ( Cruz-Loya et al., 2019 ), or how multiple species affect the function of a microbial consortium ( Sanchez-Gorostiaga et al., 2019 ; Gould et al., 2018 ; Guo and Boedicker, 2016 ). In microbial population biology, a major related open question is whether we can predict how the components of a diet collectively determine the taxonomic and functional composition of microbial communities. Faith and co-workers tackled this question using a defined gut microbial community and a host diet with varying combinations of four macronutrients ( Faith et al., 2011 ). This study found that community composition in combinatorial diets could be predicted from communities assembled in separate nutrients using an additive linear model. Given the presence of a host and its own possible interactions with the nutrients and resident species, it is not immediately clear whether such additivity is directly mediated by interactions between the community members and the supplied nutrients or whether it is mediated by the host, for instance by producing additional nutrients, or through potential interactions between its immune system and the community members. More recently, Enke et al., 2019 found evidence that marine communities assembled in mixes of two different polysaccharides could be explained as a linear combination of the communities assembled in each polysaccharide in isolation. Despite the important insights provided by both of these studies, we do not yet have a general quantitative understanding of how specific nutrients combine together to shape the composition of self-assembled communities ( Pacheco and Segrè, 2020 ). Motivated by this challenge, here we use an enrichment community approach (i.e. where natural microbial communities are grown in a defined growth medium under well-controlled lab conditions) to systematically investigate whether the assembly of enrichment microbial communities in a collection of defined nutrient mixes could be predicted from the communities that assembled in each of the single nutrients in isolation.",
"discussion": "Discussion Our analysis indicates that our empirical observations regarding the assembly of microbial communities in nutrient mixes are consistent with generic behavior of consumer-resource models. Based on this finding, we cautiously suggest that family-level asymmetries in nutrient uptake rates may be a possible mechanism for the general nutrient dominance patterns we have observed, and that a null additive model is in general a good first approximation for the assembly of microbial communities in simple nutrient mixtures (a pattern that is consistent with previous work [ Faith et al., 2011 ; Enke et al., 2019 ]). It is important to recognize, however, that other explanations and mechanisms of dominance may be at play too. Generally, these can be split into two main categories: asymmetries in how species respond to the provided nutrient and asymmetries that emerge as a result of the constructed environment. Below, we discuss several specific mechanisms that may contribute to each of these. Our null model (and consumer-resource simulations) assumes, by definition, that the growth of a single species on a mixture of nutrients (in terms of growth rate and yield) will be the aggregate sum of the growth on each nutrient alone. Multiple mechanisms, however, could lead to violations of this assumption. Firstly, a species might not consume both nutrients simultaneously but may instead consume them sequentially, or diauxically, resulting in fluctuations in the effective resource specialization of each species ( Monod, 1942 ; Lendenmann et al., 2000 ; Erickson et al., 2017 ; Pacciani-Mori et al., 2020 ). Secondly, even if a species is co-utilizing both nutrients, the biomass yields may not be additive, due to synergistic effects of using different nutrients for different cellular functions (such as energy versus biomass or for synthesis of different biomass precursors) ( Lendenmann et al., 1996 ; Pacheco et al., 2019 ; Wang et al., 2019 ). Thirdly, a molecule that can be used as a nutrient by one species may have an inhibitory effect on another species, for example benzoate is known to have antimicrobial activities against some bacteria (which may explain why benzoate dominates sugars for some families in Figure 3C ; Stanojevic et al., 2009 ). The growth dynamics on mixtures of carbon sources have been extensively characterized in simple sugars for a few model organisms (such as Escherichia coli , Bacillus subtilis , and Pseudomonas aeruginosa ), but we still lack a systematic understanding of mixed-substrate growth across taxa and environment ( Harder and Dijkhuizen, 1982 ; Görke and Stülke, 2008 ; Bajic and Sanchez, 2020 ). Systematically mapping mixed-resource utilization strategies represents an exciting direction for future work and would allow us to better predict the effects of environmental complexity on the emergent properties of complex microbial communities. Importantly, even if species respond to the supplied pair of nutrients in an additive manner, niche construction (and thus the interactions between species) may not be additive. For example, species may secrete secondary metabolites or antimicrobial agents on nutrient mixtures, which may interact with each other ( Sánchez et al., 2010 ; Mendonca et al., 2020 ; Fujiwara et al., 2020 ). Moreover, cellular growth can change other physico-chemical properties of the environment aside from carbon source availability, such as by changing the pH, the accessibility of non-carbon source nutrients leading to co-limitation, or oxygen availability ( Harpole et al., 2011 ; Cremer et al., 2017 ; Sánchez-Clemente et al., 2020 ). The wealth of independent mechanisms that may contribute to nutrient dominance illustrates the potential importance of this phenomenon. Quantitatively elucidating the specific mechanisms that may explain the individual patterns of nutrient interactions (or lack thereof) for each family and in each pair of nutrients would require us to measure the amounts of all nutrients secreted by every species in each environment over time (i.e. in each nutrient and in each pair) and then characterize the growth curves of all species in those nutrients. Although such monumental effort is beyond the scope of this paper, we hope that our findings and methodology will be a stepping stone towards elucidating how microbial communities assemble in complex nutrient mixtures and that they will stimulate further theoretical and empirical work. We propose that top-down community assembly in combinatorially reconstructed nutrient environments can be a helpful approach not only to understand the origins of microbial biodiversity, but also to learn how to manipulate existing microbiomes by rationally modulating nutrient availability."
} | 2,111 |
36909290 | PMC9995662 | pmc | 3,270 | {
"abstract": "Abstract Emerging neuromorphic hardware promises to solve certain problems faster and with higher energy efficiency than traditional computing by using physical processes that take place at the device level as the computational primitives in neural networks. While initial results in photonic neuromorphic hardware are very promising, such hardware requires programming or “training” that is often power-hungry and time-consuming. In this article, we examine the online learning paradigm, where the machinery for training is built deeply into the hardware itself. We argue that some form of online learning will be necessary if photonic neuromorphic hardware is to achieve its true potential.",
"introduction": "1 Introduction Neuromorphic engineering aims to implement neural networks in hardware by combining neurophysiological principles with engineered device physics [ 1 ]. Neuromorphic hardware could break the limitation of conventional digital computers in terms of speed and energy efficiency [ 2 ] for implementing artificial intelligence (AI) applications enabled by machine learning. A wide variety of devices have been proposed for this new paradigm, including analog, digital, and hybrid analog–digital CMOS technology [ 3 , 4 ], memristive devices [ 5 ], magnetic tunnel junctions [ 6 ], superconducting devices [ 7 ], and indeed a variety of photonic platforms. Neuromorphic photonics [ 8 ]—combining photonic device physics with distributed processing models—has resulted in a new class of ultrafast information processors [ 9 ]. Free space optical neural networks were first demonstrated in the 1980s and 1990s [ 10 – 12 ] while more recent neuromorphic photonic demonstrations range from free-space [ 13 , 14 ] to integrated [ 15 , 16 ] implementations, spiking neural networks [ 17 – 19 ] and artificial and deep neural networks [ 20 , 21 ], to reservoir computing [ 22 – 24 ]. However, the training of neuromorphic hardware is still primarily performed on conventional computers. Referred to as offline learning, in this paradigm, network parameters (e.g., weights and biases) are determined in software based on a computational model of the physical system, and then these parameters are mapped to the physical device which is used for inference. Offline learning has proven to be a valuable tool in neuromorphic engineering, well-suited to mass production, where the results of a single simulation can be mapped to large numbers of devices. For offline learning to be effective, very accurate models of the individual network devices must be developed. One significant body of ongoing work in photonic neuromorphic engineering is optimizing the reliability of the design, fabrication, and manufacture of optical devices such that offline training leads to reproducible results. However, offline training may rule out various devices that cannot be easily modeled and simulated in this way – for example analog devices, or non-standard architectures such as highly recurrent or nonlinear networks. Offline learning is also very power-hungry for applications that often need retraining, resulting in a static model that is hard to adapt to new data and adjust for different scenarios [ 25 ]. An alternative approach is needed for these cases. Online learning may be just this alternative, allowing new classes of devices and architectures to be developed and providing other new capabilities that cannot be provided with offline training alone. In fact, many large-scale neuromorphic demonstrations in both photonics [ 13 , 26 ], [ 27 ], [ 28 ] and other platforms [ 29 – 32 ] have leveraged some form of online learning. Online learning refers to training that takes place on the same hardware that is used for inference. Online learning can be either supervised or unsupervised; the critical feature is that it is done without requiring an external model of the device being trained. This article will focus on supervised learning, as it is the most common type of training used on photonic hardware. While reliable digital platforms such as very large-scale integration (VLSI) devices may be effectively simulated and do not necessarily require online learning [ 33 ], online learning is already a topic of significant investigation in analog VLSI systems [ 34 ], memristive crossbar arrays [ 29 , 30 , 35 , 36 ] and a variety of other novel architectures with complex, recurrent or nonlinear interactions that cannot be easily modeled or described mathematically [ 32 , 37 ], [ 38 ], [ 39 ]. At the device level, variability can lead to degradation in the measured inference accuracy compared to the expected, offline-simulated inference accuracy. This is an endemic, historically significant issue for many types of emerging hardware. In Section 2 , we will discuss how recent approaches have addressed variability for photonic devices. Ultimately, many of these offline training solutions require sacrificing some of the inference capabilities of the device to make it more “trainable” or adding models that include individual device data to the training simulation. At the system level, new architectures could have significant computational power [ 40 ] if a feasible training technique could be identified, and nonlinear effects and crosstalk could be harnessed rather than compensated. In Section 3 , we discuss the experimental progress on implementing different online training techniques and how they have already enabled improved performance at certain tasks. From a hardware perspective, the complexity of the devices used for online learning will need to be increased compared to inference-only devices. The exact nature of these new devices and components will depend on the specific learning algorithm and the degree of autonomy required. However, this complexity would also bring a great deal of flexibility to these systems; allowing them to compensate for variability and noise, ultimately leading to much larger networks and enabling us to take full advantage of its information processing capabilities. In Section 4 , we make the argument that photonics, in particular, is a good candidate for online learning and that many successful experimental demonstrations of photonic neuromorphic systems, from the 1980s to the present day, have involved some form of online training. Although the problem of training optical neuromorphic hardware has been considered since the 1980s [ 11 ] and likely earlier, a one size fits all solution has not been found. The further development of online algorithms and the associated physical implementations will greatly enable the scaling of photonic neuromorphic systems and enhance their performance. Online learning could allow photonic neuromorphic systems to entirely avoid issues with imperfect modeling and thermal and electrical cross-talk, and could help foster the next generation of photonic neuromorphic systems that are competitive with digital electronic systems at AI tasks."
} | 1,739 |
34123311 | PMC8150096 | pmc | 3,271 | {
"abstract": "Herein, we report a three-dimensional (3D) DNA walking nanomachine innovatively constructed from a functionalized 3D DNA track, which runs in an orderly manner with favorable directionality to allow for programming certain pathways of information transduction for some target tasks. The nanomachine was constructed using a departure station of walker (U B + W) and a functionalized 3D track, which was made up of a rolling circle amplification (RCA)-generated backbone chain and numerous triangular rung units with stators (U A + S) assembled into a repeating array along the backbone. A specific domain (SD) was designed at the 5′-end of the backbone to capture the U B + W, and stators with specific RNA substrates were immobilized at the three U A corners for the DNA walker to travel on. Powered by 10–23 DNAzyme, the DNA walker started moving from the SD end to the other end of the track by the autonomous cleavage of RNA substrates. Significantly, the homogeneous distribution of stators in the longitudinal and horizontal extensions paved a specific path for each walker to move along the 3D track. This resulted in random and inactive self-avoiding walking; thus, the nanomachine exhibited good executive ability. These properties allowed the DNA walking nanomachine to program the certain pathways of information transduction for the stepwise and programmed execution of some target tasks, such as the synthesis of specific polyorganics and cargo delivery. We believe that such a 3D DNA walking nanomachine could enrich the concept in the field of dynamic DNA nanotechnology, and may improve the development of novel DNA nanomachines in cargo delivery and composite product synthesis.",
"conclusion": "Conclusions Unlike the existing 3D DNA walking nanomachine whose direction of each moving step is random, our 3D DNA track-based nanomachine has a relatively high level of controllability and directionality. The track is well designed to have a departure station for the walker at one end, and the stators are orderly and homogeneously arranged along the track, which ensure a certain pathway for DNA walking. The new concept of integrating the directionality from the 1D DNA walking nanomachine and processivity from the 3D nanomachine is beneficial to extending the functionality of the DNA walking machine, such as specific polyorganic synthesis and cargo delivery. This protocol exhibited the promising application of the DNA nanostructure on improving the locomotion performance of the DNA walking machine, which may pave a significant avenue to the development of artificial DNA nanotechnology. Reagents and materials Phi29 DNA polymerase, 10× phi29 DNA polymerase buffer, and deoxyribonucleoside triphosphate (dNTPs) solution were obtained from Sangon Inc. (Shanghai, China). T4 DNA ligase and T4 DNA ligase buffer were purchased from TaKaRa (Dalian, China). DNA oligonucleotides (as shown in Table S1 † ) utilized in this work were synthesized by Sangon Inc. (Shanghai, China). TAE/Mg 2+ buffer system: 40 mM Tris, 10.0 mM Mg(OAc) 2 and 2 mM EDTA with the pH value adjusted to 8.0 using glacial acetic acid. Instrumentation The polyacrylamide gel electrophoresis (PAGE) analysis was carried out with a BG-verMIDI standard vertical electrophoresis apparatus (Baygene, Beijing, China). The gel imaging was implemented using a Bio-Rad Gel Doc XR+ System (Bio-Rad, Hercules, CA). The morphologies of the designed DNA nanotube were characterized by atomic force microscopy (AFM, Bruker, Germany) with a Dimension ICON system. In addition, the fluorescence responses were acquired from an FL-7000 fluorescence spectrophotometer (Hitachi, Tokyo, Japan). The nanomachines were imaged using an LSM780 confocal microscope (Carl Zeiss), which was equipped with ZEN 2010 software. Preparation of the DNA backbone based on rolling circle amplification (RCA) The long DNA backbone was prepared by a modified method. 32 The details are as follows: a volume of 2 μL of 10× T4 DNA ligase buffer, 9 μL of linker (4 μM) and 9 μL of the padlock probe (2 μM) were mixed together, and then subsequently annealed at 95 °C for 5 min and cooled down to 20 °C over 75 min. After the successful hybridization of linker and the padlock probe, 5 U of T4 DNA ligase was added to combine its 5′-end with the 3′-end of the padlock probe, and then the mixture was incubated at 16 °C for 12 h and thermally treated at 65 °C for 15 min. After that, 1 μL 10× phi29 DNA polymerase buffer, 0.5 U phi29 DNA polymerase and 2.5 μL dNTPs (2.5 mM) were reacted with every 6 μL of the prepared mixture at 37 °C for 2 h to generate the long DNA backbone. Then, the phi29 DNA polymerase was inactivated by thermal treatment at 65 °C for 15 min to stop the reaction. The assembling of the designed 3D DNA walking nanomachine The proposed DNA nanomachine consisted of the DNA backbone, a departure station of the walker (U B + W), and an abundant triangular rung unit with stators (U A + S). In brief, U B + W and U A + S were separately generated by the annealed product of V1′, C1′, C2′, R1′, R2′, h-S and the walker with an equal concentration and V1, C1, C2, R1, R2 with the stator at 3 times the concentration in TAE/Mg 2+ buffer. Then, 10 μL of the prepared U A + S with a final concentration of 1.77 μM was combined with 5 μL DNA backbone by annealing the mixture from 44 °C to 20 °C over 75 min. This nanomachine was activated by adding 10 μL U B + W solution (final concentration of 0.24 μM) to the above solution mixture.",
"introduction": "Introduction The DNA walking nanomachine, as one of the DNA nanomachines, has attracted intense attention with its remarkable performance of automaticity and controllability through converting chemical energy to walking locomotion. 1–4 In terms of the track of the DNA walking machine, the majority of the emerging DNA walking machines utilized the track of a one-dimensional (1D) DNA footpath with the highest level of controllability and directionality. 5–8 These travel distances of each DNA walker, however, were well confined at only a few walking steps, 9 so that the 1D DNA walkers were of very limited processivity, 10 which restricted the executive ability of such DNA walking nanomachines. By bringing in a second plane, two-dimensional (2D) DNA origami was designed to serve as the track, 11–14 which increased the number of walking steps and degrees of freedom, but the travel space was still confined, 15 as well as the processivity of the walker. To address these issues, researchers recently exploited particle-based three-dimensional (3D) DNA walking nanomachines, which enabled a broad moving space with abundant steps for each DNA walker, 15–19 thus performing a high processivity compared to the 1D and 2D ones. Despite the prominent increase in the amount of DNA stators for such 3D DNA nanomachines, the attachment of the stators to the particles via coordination bond was stochastic; thus, the stators were at a heterogeneous and locally disordered surface. 20,21 The disordered surface environments disturbed the movement of each walker. When the walker traveled to the sparse locations of the stators, the locomotion was terminated once the distance between two stators was too far for the walker to move forward. 22 In this way, the other stators of the whole machine would be wasted to restrict the good execution extent and performance ability of each walker, eventually limiting the executive ability of this machine. Further, the disordered stators would guide these walkers to chaotically walk on a spherical surface without a certain direction, 15–19 which was not beneficial to programming certain pathways for information transduction. In consequence, although the 3D DNA walking nanomachine has overcame the low processivity from 1D and introduced the third plane from 2D, it lost the high level of directionality and controllability from 1D and did not maximumly utilize the executive ability of each walker. There are many challenges to overcome in order to integrate the superiorities of the 1D and 3D walking nanomachines and develop a novel DNA nanomachine, which has not only a high executive ability, but also a relatively good controllability and directionality. Herein, by directly using Watson–Crick base pairs, a 3D DNA walking nanomachine that can run in an orderly manner was constructed by designing a specific departure site and homogeneous steps for the DNA walker, which could pave a certain pathway for information transduction. The principle of this design is shown in Scheme 1 . The 3D track of the walking machine was formed by numerous triangular rung units with payload-labeled stators (U A + S) assembled into a repeating array along an extremely long rolling circle amplification (RCA)-generated backbone with a specific domain (SD) at the 5′-end. Each triangular rung units (U A ) had a foothold at every corner to immobilize three stators with specific RNA substrates for the DNA walker to move on, and the SD was especially designed to capture a departure station of the walker (U B + W). Fueled by the 10–23 DNAzyme, 23–25 one DNA walker was able to move from the SD end to the other end of the track by cleaving the RNA substrates of stators at every step with the release of the payload. Since every side of U A + S had 20 invariable nt sequences and every layer between each U A + S contained constant sequences (40 nt), the DNA walker was programmed to follow a certain pathway. It would first move along the triangle, and then go to the next U A + S with a random and inactive self-avoiding walking. In this design, the departure position of each DNA walker was well-designed. The programmed 3D track provided a definite direction and invariable distance between each step for each DNA walker to travel with controllability. In principle, our design is beneficial to the stepwise and programmed execution of target tasks (by performing a series of multistep reactions), such as specific composite production synthesis and cargo delivery. Scheme 1 Schematic illustration of the principle of the 3D DNA walking nanomachine.",
"discussion": "Results and discussion Characterization of the designed nanomachine To verify the construction of the 3D DNA nanomachine, we evaluated the assembly products by polyacrylamide gel electrophoresis (PAGE, 8%). As exhibited in Fig. 1A , the number of chains hybridized together was increased stepwise and ascribed to lines 1 to 5, so that those products showed a stepwise slow mobility with stepwise higher molecular weight. In addition, line 6 demonstrated that U A (line 5) hybridized with the stator chains, indicating the formation of the proposed DNA construction of U A + S. Meanwhile, lines 7–9 (shown in Fig. 1B ) showed the process of the rolling circle amplification (RCA). The RCA products, with extremely low mobility, exhibited a bright band in line 9, indicating that we obtained a long proposed DNA chain. Because of the low concentration of polyacrylamide and relatively long electrophoresis experimental time, the linker DNA in line 7 and padlock probe DNA in line 8 with low molecular weights both moved out from the bottom of the polyacrylamide gel. The result of the PAGE experiment of U B + W is exhibited in Fig. 1C . Lines 10 through 16 showed a stepwise slow mobility in the same manner as the PAGE images of U A + S, revealing the successful formation of the proposed U B + W construction. Sequence information of all DNA oligonucleotides used in our work are exhibited in Table S1 of the ESI. † Moreover, to investigate the morphology of our designed 3D nanomachine, atomic force microscopy (AFM) was performed in air. Single DNA nanomachines were observed and are shown in Fig. S6. † The AFM image indicated that the DNA nanomachines successfully formed with an approximate length of 0.30 μm. Fig. 1 (A) Native PAGE (8%) images of U A + S: lane 1, V (0.3 μM); lane 2, V + C1 (0.3 μM); lane 3, V + C1 + R1 (0.3 μM); lane 4, V + C1 + C2 + R1 (0.3 μM); lane 5, V + C1 + C2 + R1 + R2 (0.3 μM); lane 6, V + C1 + C2 + R1 + R2 + Cy5/3-S (0.3 μM); (B) native PAGE (8%) images of DNA backbone: lane 7, linker (1 μM), lane 8, padlock probe (1 μM), lane 9, DNA backbone. (C) Native PAGE (8%) images of U B + W: lane 10, V′ + C1′ + C2′ + R1′ + R2′ + h-S + walker (0.3 μM); lane 11, V′ + C1′ + C2′ + R1′ + R2′ + h-S; lane 12, V′ + C1′ + C2′ + R1′ + R2′ (0.3 μM); lane 13, V′ + C1′ + C2′ + R1′ (0.3 μM); lane 14, V′ + C1′ + C2′ (0.3 μM); lane 15, V′ + C1′ (0.3 μM); lane 16, V′ (0.3 μM). To verify the feasibility of the movement of the walker and the sequence specificity of the 10–23 DNAzyme, we employed PAGE to analyze whether the walker could successfully move from U B + W to the next layer (U A + S). The backbone is a long chain produced by RCA with a high molecular weight (approximately thousands of bases), which makes it difficult to observe and analyze such related products. Thus, to replace the long backbone chain, we introduced a short-backbone that only had one complementary region for U B + W and another one for U A + S. Although this structure was simplified to two layers by the introduction of the short-backbone, the triangle unit still had approximately 1200 nt from assembly by the short-backbone, U B + W and U A + S. Thus it required further simplification. Herein, we still assembled two layers to implement the experiment, but this was a simple two-layer combination with relatively low molecular weight. The two-layer combination was composed of a short-backbone, V′′ and V, which would not affect the proposed analysis due to no changes in the distance between the two new layers. As shown in Fig. 2 , the lines from 1–5 exhibited the PAGE results of the successful assembly process. More importantly, the status of line 6 showed the reaction result of the walker walking, which is the same as that of line 5. This indicated the successful cleavage and release of the DNA substrate, and eventually the successful movement of the walker between the two layers. Fig. 2 Native PAGE (8%) images: lane 1, short-backbone (0.3 μM); lane 2, short-backbone + V′′ (0.3 μM); lane 3, short-backbone + V′′ + V (0.3 μM); lane 4, short-backbone + V′′ + V + h-S (0.3 μM); lane 5, short-backbone + V′′ + V + h-S + walker (0.3 μM); lane 6, short-backbone + V′′ + V + Cy5/3-S + walker (0.3 μM). Construction of a fluorometric 3D DNA walking nanomachine As shown in Fig. 3A , as a proof of principle, we first designed a 3D DNA walking nanomachine in which the fluorescence dye Cy5 labeled at the 5′-end of a stator served as the payload. Another fluorescence dye Cy3 was labeled at a position 17 nt away from Cy5, and the stator was denoted as Cy5/3-S. Initially, the distance between Cy3 and Cy5 was roughly 5 nm. Thus, a red fluorescence from Cy5 was observed due to the generation of fluorescence resonance energy transfer (FRET) 26–28 between Cy3 (donor) and Cy5 (acceptor) with the excitation wavelength at 550 nm. Once this machine worked, each walker driven by 10–23 DNAzyme would achieve autonomous motion along the 3D DNA track with the release of the Cy5 payload, causing an apparent quenching of the Cy5 fluorescence and increasing of the Cy3 fluorescence owing to the far distance between the two fluorescent dyes, which is not beneficial for FRET. Fig. 3 (A) Schematic illustrating the locomotion mechanism of the elaborate 3D DNA walking machine. (B and C) The fluorescence increases of Cy3 and the fluorescence quenching of Cy5 as a function of time from the fluorescent 3D DNA walking machine (0.12 μM). (D) Monitoring the initial moving rate of each walker by linear fit for continuous fluorescence increases in the first 4000 s. To quantitatively characterize the performance of this machine, the fluorescence increases of Cy3 and quenching of Cy5 in real time were studied ( Fig. 3B and C , respectively). After the 0.24 μM U B + W was added to the 0.12 μM Cy5/3-S 3D DNA track, an obvious increase in the fluorescence intensity of Cy3 occurred due to the disappearance of FRET for the release of Cy5, which approached a saturation state after about 4 h. The initial locomotion rate of this DNA walking nanomachine was roughly estimated to be 1.80 × 10 −11 M s −1 . This rate was determined by the fluorescence changes for the first 4000 s ( Fig. 3D ). Moreover, we also examined the fluorescence emission of the Cy5/Cy3 system before and after walking to further check the operation of this machine. The images represented two typical peaks for Cy3 and Cy5 located at around 564 nm and 668 nm, respectively, in which the fluorescence intensity of Cy3 was increased and that of Cy5 was quenched after walking compared to the initial state (before walking) (Fig. S1 † ). Simultaneously, we employed a confocal microscope to synchronously monitor the results of the DNA walking at three channels in green, red and colocalization ( Fig. 4 ). The images (A–C) were the results of fluorescence before walking and the images (D–F) were the results after walking. Comparing the results in images (A and B) with those of (D and E), the fluorescence intensity of the green spots in image (D) were more enhanced than that in (A), and the fluorescence intensity of the red spots in image (E) were apparently more quenched than that in (B). Meanwhile, the corresponding colocalized spots were shown in images (C and F). Moreover, the respective confocal fluorescence intensities of Cy3 and Cy5 before and after walking were plotted as histograms (Fig. S2 † ). Collectively, these results indicate the successful operation of the designed 3D DNA walking machine. Fig. 4 Fluorescence comparison diagrams. (A–C) Confocal images of the DNA nanomachine before walker moving. (D–F) Confocal images of the DNA nanomachine after walker moving. The scale bar is 10 μm. Feasibility investigation of the nanomachine To verify that each DNA walker traveled along the 3D track rather than moving between the scattered U A + S, we designed a control experiment by hybridizing U A with three times the amount of Cy5/3-S, but without the backbone ( Fig. 5A ), to construct an unassembled nanomachine. For contrasting with the correct nanomachine in Fig. 3A , we also monitored the fluorescence changes of Cy3 and Cy5 in real time under the same analysis condition ( Fig. 5B and C ), and linear fitting was also performed for the first 4000 s. As shown in Fig. 5B and D , the total efficiency of this reaction was relatively slow. The saturation point did not occur after a reaction time of 5 h with an initial rate of 3.68 × 10 −12 M s −1 . We think the collision theory could be employed to explain this phenomenon. The reactants have to collide to make contact with each other, and then they may react. The collision frequency is proportional to the concentration of the walker and U A in this work. 29,30 In the scattered situation, the local concentrations of the walker and U A + S were lower than that of being assembled together based on the backbone, 31 resulting in a low collision efficiency and further giving rise to a depressed reaction efficiency between them. This result indicates that the construction of the 3D DNA track is a key component for improving the executive ability of this machine. The relevant fluorescence changes could be read out from the fluorescence spectra in Fig. S3. † Fig. 5 (A) Schematic illustrating the locomotion mechanism of the unassembled 3D DNA walking nanomachine. (B and C) The respective fluorescence changes of Cy3 and Cy5 as a function of time. (D) Linear fit for the continuous increase in fluorescence during the first 4000 s. To check the influence of U B + W at one end of the track for realizing the directional movement of the walker, we also explored a second control experiment by adding only the walker to Cy3/5-track ( Fig. 6 ). This enabled the construction of a walker-unset nanomachine, in which each walker was not involved in assembling U B + W, but could randomly hybridize with any Cy5/3-S. In this way, both the initial moving position for each walker and the number of walkers hybridized on one Cy3/5-track were uncertain; thus, an unquantifiable walker could start moving from anywhere on one Cy3/5-track to an uncertain direction. As shown in Fig. 6B and C , the completion time for the walker-unset nanomachine was about 1.1 h (roughly v = 1.33 × 10 −11 M s −1 ), which was 3.6 times shorter than that of the correct nanomachine with a lower saturated fluorescence intensity. We think that the chaotic hybridization of the walkers and stators would make the walker start moving from the uncertain position towards one end of the track, while the Cy5 on the other end would not be released due to a lack of the nearest neighbors for the walker to move back to this end. In addition, some walker-unset nanomachines might be left that were not hybridized with any walker, so these machines would not work. Owing to the mentioned speculations above, a saturation state was approached earlier with a lower fluorescence intensity than that of the correct 3D DNA walking nanomachine. Therefore, such a departure station is a key point for the DNA walker to move along the track with a certain direction; thus, each walker could move in an orderly manner with controllability to exhibit the good execution extent and performance ability. Similarly, the relevant fluorescence spectra are shown in Fig. S4. † Fig. 6 (A) Schematic illustrating the locomotion mechanism of the walker-unset 3D DNA walking nanomachine. (B and C) The respective fluorescence changes of Cy3 and Cy5 as a function of time from the walker-unset 3D DNA walking nanomachine (0.12 μM). (D) Linear fit for the continuous increase in fluorescence during the first 4000 s. Furthermore, we designed another control experiment, in which the walker did not appear to move along the track, to check whether the changes of the fluorescence intensity occur because of the operation of this designed DNA nanomachine ( Fig. 7 ). As shown in Fig. 7B and C , in the no-walker nanomachine system, the fluorescence intensities of both Cy3 and Cy5 showed almost no change during a continuous reaction time of 5 h compared with that of the correct walking nanomachine in Fig. 3B and C . These results confirm that the walker is the necessary factor to the successful release of the payload. The relevant fluorescence spectra in Fig. S5 † also exhibited the same results. Fig. 7 (A) Schematic illustrating the mechanism of the no-walker 3D DNA walking nanomachine. (B and C) The respective fluorescence changes of Cy3 and Cy5 as a function of time from the no-walker 3D DNA walking nanomachine (0.12 μM)."
} | 5,670 |
35539192 | PMC9082177 | pmc | 3,272 | {
"abstract": "Oil/water separation has become an increasingly important field due to frequent industrial oily wastewater emission and crude oil spill accidents. Herein, we fabricate a robust superhydrophobic loofah sponge via a versatile, environmentally friendly, and low-cost dip coating strategy, which involves the modification of commercial loofah sponge with waterborne polyurea and fused SiO 2 nanoparticles without the modification of any toxic low-surface-energy compound. The as-prepared loofah sponge showed excellent superhydrophobic/superoleophilic properties and exhibited robustness for effective oil–water separation in extremely harsh environments (such as 1 M HCl, 1 M NaOH, saturated NaCl solution and hot water higher than 95 °C) due to the remarkably high chemical stability. In addition, the as-prepared loofah sponge was capable of excellent anti-fouling, has self-cleaning ability and could act as the absorber for effective separation of surfactant-free oil-in-water emulsions. More importantly, the as-prepared loofah sponge demonstrated remarkable robustness against strong sandpaper abrasion and finger wipes, while retaining its superhydrophobicity and efficient oil/water separation efficiency even after more than 50 abrasion cycles. This facile and green synthesis approach presented here has the advantage of large-scale fabrication of a multifunctional biomass-based adsorbent material as a promising candidate in anti-fouling, self-cleaning, and versatile water–oil separation.",
"conclusion": "Conclusions In summary, we developed a facile, versatile and environmentally friendly strategy for construction of superhydrophobic loofah sponge coated with WPU/SiO 2 by the dip-coating method. The as-prepared loofah sponge exhibits excellent superhydrophobicity and efficient oil/water separation ability under a series of harsh conditions (such as 1 M HCl, 1 M NaOH, saturated NaCl solution and hot water higher than 95 °C) due to the remarkably high chemical-stability. And the as-prepared loofah sponge also can effectively separate surfactant-free oil-in-water emulsions and possesses excellent antifouling and self-cleaning properties against dirty contaminants. Moreover, the as-prepared loofah sponge has robust mechanical abrasion resistance, and shows excellent superhydrophobicity and oil/water separation ability under strong abrasion using sandpaper and the finger-wipe test for more than 50 cycles. In addition, the whole process without involving poisonous chemically volatile reagents or expensive materials or sophisticated equipment can be easily scaled up. Therefore, the attractive features of the loofah sponge could make it an ideal adsorbent material for a range of applications including anti-fouling, self-cleaning, massive oil spill cleanup, and industrial oily wastewater purification.",
"introduction": "Introduction An oil spill is the release of a liquid petroleum hydrocarbon into the environment, especially marine oils and industrial wastewater. 1 Oil spills have occurred throughout the world and are currently ongoing. Due to the increasing occurrence of industrial oily wastewater emission and crude oil leakage accidents, oil–water separation has become an increasingly important and urgent research issue to solve the severe ecological problems. 2–8 Generally, traditional methods such as gravity separation, ultrasonic separation, centrifugation, flotation, coagulation, and biological and electrochemical treatments are all widely used for oil/water separation. 9–12 Nevertheless, complex separation instruments, low separation efficiency and high cost have caused difficulty in the use of most of these oil/water separation systems. 13 Recently, a variety of functional materials for oil/water separation were fabricated through the rational control of surface structures and chemical compositions to possess the property of superhydrophobicity/superoleophilicity, 14–21 since Jiang 22 et al. first discovered the oil/water separation materials inspired by special wettability in 2004. Li et al. 23 demonstrated a superhydrophobic polyurethane sponge fabricated by coating TiO 2 nanoparticles and a low-surface-energy compound (octadecanoic acid) onto its skeleton surface. The coated PU sponges via the ultrasonic-assisted dip coating (UADC) method showed excellent oil–water separation ability in extremely high acidic and alkaline environments as well as the extremely high salt concentration of seawater. Zhang et al. 24 demonstrated a facile salt-induced phase-inversion method to fabricated superhydrophilic and underwater superoleophobic PAA-g PVDF membranes for separation of oil-in-water emulsions with high separation efficiency and much higher fluxes. Li et al. 25 developed a facile approach to fabricate superhydrophobic bags filled with pristine PU sponges for highly efficient oil/water separation in harsh environments. For super-wetting materials, the fragile micro–nano surface roughness structure is so vulnerable that it can fail easily under the influence of external mechanical forces or friction. This is becoming the biggest bottleneck that limits large-scale industrial application in the area of oil–water separation. 26 In order to solve this problem and improve the mechanical properties of the surface of superhydrophobic materials, many methods have been proposed. 27–38 Lu et al. 27 used a perfluorosilane-coated titanium dioxide nanoparticles ethanolic suspension as a paint to fabricate micro–nano multi-level structure, with commercial adhesives as a binding layer to improve the robustness and abrasion resistance, to construct robust superhydrophobic surfaces on several substrates, which maintained excellent superhydrophobicity even after finger-wipe, knife-scratch, and sandpaper abrasion. Chen et al. 30 successfully fabricated superhydrophobic surfaces with remarkable robustness against knife scratch and sandpaper abrasion on various substrates in a similar method called “Paint + Adhesive”. Tricoli et al. 32 reported a novel synthesis method to construct ultradurable superhydrophobic surfaces by using a PU-PMMA colloidal suspension and fluoro-functionalized nanostructured silica (F-SiO 2 ). After curing, the highly transparent and excellent superhydrophobic surfaces with hierarchical micro–nano structure and ultralow surface energy were formed, which presented outstanding mechanical, chemical, and photo durability, and retained their water repellency even after 250 rotary abrasion cycles. However, the fluorocarbon reagents used were expensive and environmentally incompatible, which largely limited their applications. Consequently, robust and environmentally friendly approaches for construction of fluorine-free, green superhydrophobic absorbent materials are highly desirable. With improving environmental protection and a growing shortage of oil resources, the use of renewable natural materials is becoming increasingly attractive because of their high absorption capacities as well as renewability and biodegradability. 39–54 Yang et al. 39 prepared a novel diisocyanate-modified lignin xerogel using renewable lignin as the precursor via a sol–gel process and ambient pressure drying method. The as-prepared xerogel showed high performance in self-cleaning and superhydrophobicity without further hydrophobic modification. Zhou et al. 46 fabricated superhydrophobic microfibrillated cellulose aerogels with high lipophilicity, ultralow density, superior porosity as well as extremely high mechanical stability. The aerogels exhibited excellent oil/water selective absorption capacity and superior reusability. However, the relatively complicated operation procedures and low structural stability have limited the actual applications for oil/water separation. Loofah sponges are available at very low cost and are popular in China and Southeast Asia. The loofah sponge possesses a continuous 3D macroporous surface with a strong rigid structure that is similar to those of polymer-based sponges. Loofah sponge has many applications in life, such as a filter material for filtration and purification, kitchen cleaning supplies and decorative materials, due to its good water absorption capacity and stable structure. Meanwhile, it can also be used as a kind of fuel for cooking in remote rural areas. In this study, we fabricated a 3D macroporous oil-absorbing material prepared from a fibrous loofah sponge via a facile and efficient dip coating process. The fumed nano silica and waterborne polyurea adhesive were first dispersed into ethanol, then the loofah sponge was introduced into the above solution. After curing at 60 °C, the superhydrophobic/superoleophilic biomass-based loofah sponges have been obtained. The as-prepared loofah sponges showed excellent superhydrophobic/superoleophilic properties and exhibited robustness for effective oil–water separation. In this work, the fumed SiO 2 nanoparticles not only enhance the surface roughness of the loofah sponge but also act as a low-surface-energy compound material, which endow the sponge with excellent superhydrophobic properties. Most importantly, due to the excellent adhesion of the polyurea adhesive, it can tightly bond SiO 2 nanoparticles to the loofah sponge and endow the sponge with superior chemical stability and robustness for oil–water separation under harsh environments, including strong acidic, alkaline, and saturated salt aqueous solutions, hot water, mechanical abrasion and finger abrasion. These extraordinary properties suggest that the as-prepared loofah sponge will be a promising candidate for large-scale oil–water separation.",
"discussion": "Results and discussion The one-step, rapid and cost-effective fabrication process for the superhydrophobic/superoleophilic loofah sponge is illustrated in Scheme 1 . The fused nano-SiO 2 and waterborne polyurea adhesive were added in an absolute ethanol solution under ultrasonication for 2 h to obtain a homogeneous paint-like suspension. An economical and biodegradable loofah sponge with a three-dimensional hierarchical porous structure was used as the frame for coating. After pre-treatment with 1 M NaOH solution to remove the existence of the natural plant wax layer and the lignin, the cleaned pristine loofah sponge was dipped into the above homogeneous suspension for 2 h under vigorous mechanical stirring. Then, the as-prepared loofah sponge was dried at 60 °C for 12 h to obtain the stable water-repellent loofah sponge. Taking advantage of the powerful stirring effects, the polyurea molecules and SiO 2 nanoparticles diffused quickly into the loofah sponge frame. The urethane bond in the polyurea molecules formed van der Waals force interactions with the hydroxyl groups on the loofah fibers. After curing, the polyurea and the fumed nano silica were tightly attached onto the loofah sponge, which provide the loofah sponge with excellent superhydrophobicity and chemical stability for use as an adsorbent in practical oil–water separation applications in harsh environments. Scheme 1 Schematic illustration of the fabrication of the superhydrophobic loofah sponge. The surface chemical compositions of pristine loofah sponge, WPU modified loofah sponge and silica@WPU modified loofah sponge were determined by Fourier transform infrared spectroscopy (FTIR). As shown in Fig. 1a , comparing with the spectrum of pristine loofah, the C \n \n\n<svg xmlns=\"http://www.w3.org/2000/svg\" version=\"1.0\" width=\"13.200000pt\" height=\"16.000000pt\" viewBox=\"0 0 13.200000 16.000000\" preserveAspectRatio=\"xMidYMid meet\"><metadata>\nCreated by potrace 1.16, written by Peter Selinger 2001-2019\n</metadata><g transform=\"translate(1.000000,15.000000) scale(0.017500,-0.017500)\" fill=\"currentColor\" stroke=\"none\"><path d=\"M0 440 l0 -40 320 0 320 0 0 40 0 40 -320 0 -320 0 0 -40z M0 280 l0 -40 320 0 320 0 0 40 0 40 -320 0 -320 0 0 -40z\"/></g></svg>\n\n O stretching vibration peak at about 1732 cm −1 showed a noticeable increase in intensity on the surface of WPU modified loofah, indicating that a considerable number of urethane groups were introduced after WPU modification. The peak at about 1509 cm −1 was attributed to the deformation vibration of N–H in urethane, which was a little weaker than that of C O of 1732 cm −1 due to the stretching vibration of N–H. The stretching vibration near the 1066 cm −1 absorption peak was attributed to the ether bond and ammonia ester bond of C–O–C. The infrared spectra analysis proved that polyurea adhesive was successfully grafted onto the loofah fiber surface. In addition, the characteristic peak at 465 cm −1 belonged to the bending vibration peak of Si–O–Si. These observations indicated that fumed nano silica and WPU were included on the loofah sponge surface, which confirmed successful synthesis of SiO 2 @WPU modified loofah sponge. Fig. 1 FT-IR spectra (a) and XPS spectra (b) of pristine loofah, WPU modified loofah, and SiO 2 @WPU modified loofah. To further prove the above results, X-ray photoelectron spectroscopy (XPS) and X-ray energy dispersive spectroscopy (EDS) were employed to determine the surface elemental compositions of the pristine loofah sponge and the as-prepared loofah sponge. The values for the concentration of the loofah surface chemical elements can be estimated (demonstrated in Table S1 of the ESI † ). As depicted in Fig. 1b , the XPS spectrum of original loofah was composed of the elements carbon (286.5 eV) and oxygen (533.0 eV), which can be inferred due to the lignocellulosic characteristic of vegetable materials. In the WPU modified loofah sponge, the relative atomic concentration of carbon increased from 59.75% to 77.24%, the relative atomic concentration of oxygen decreased from 40.25% to 18.78%, a new peak with binding energy of 407.3 eV (N 1s) appeared, strongly confirming that polyurea was successfully attached onto the loofah surface. For the as-prepared loofah sponge, two new peaks with binding energies of 154.23 eV (Si 2s) and 102.14 eV (Si 2p) appeared, which strongly demonstrated the loofah sponge was fully covered by fumed silica particles and WPU adhesive. In addition, elemental mapping analysis based on X-ray energy dispersive spectroscopy as shown in Fig. 2 also confirmed that the as-prepared loofah sponge was successfully coated with polyurea and fused SiO 2 nanoparticles. Fig. 2 EDS elemental mapping images of the as-prepared loofah sponge. The typical scanning electron microscopy (SEM) images of the pristine loofah sponge and as-prepared loofah sponge with different magnifications, which were used to obtain the surface morphological changes in the loofah sponge after dip casting, are shown in Fig. 3 . As shown in Fig. 3a1 , the pristine loofah sponge had a three-dimensional hierarchical porous structure. The magnified SEM images ( Fig. 3a2 and a3 ) revealed that the loofah skeleton surface was slightly rough with several shallow channels and small folds. This unique structure of loofah sponge provided a larger surface area which could be beneficial to load more fused silica nanoparticles on the surface of the loofah fibers. As depicted in Fig. 3b , after dip casting with a homogeneous ethanol suspension composed of fused nano-SiO 2 and WPU adhesive, the surface of as-prepared loofah sponge was covered with coralloid silica nanoparticles to provide hierarchical nanoscale rough surfaces, which facilitated the construction of super-wettability. In this system, the fused nano-SiO 2 not only enhanced the surface roughness of the loofah sponge to construct 3D hierarchical rough surfaces, but also acted as a low surface energy material to replace the use of toxic low surface energy fluorocarbon substances, which endow the sponge with excellent superhydrophobic properties in an environmentally friendly approach. Fig. 3 FESEM images of the original loofah sponge (a) and the as-prepared SiO 2 @WPU modified loofah sponge (b). The wettability of the as-prepared loofah sponge was investigated by water contact angle (WCA) measurements. As displayed in Fig. 4a , the as-prepared loofah sponge showed superhydrophobicity and superoleophilicity. When the oil droplet (oily red dyed chloroform) dropped onto the loofah sponge surface, it was absorbed quickly and disappeared completely, while the methylene blue dyed water droplets were repelled on the loofah surface and maintained their spherical shapes, exhibiting a water contact angle of 151.8° ( Fig. 4b ). When being placed into water, the original loofah sponge rapidly absorbed water to expand and sank into water immediately (see Movie S1 of the ESI † ), while the as-prepared loofah sponge floated on the surface of the water due to its superhydrophobicity ( Fig. 4c ). Moreover, the prepared loofah sponge appeared to have silver mirror-like surfaces when it was immersed into water by an external force ( Fig. 4d ). This non-wetting Cassie–Baxter behavior was due to a continuous air layer between the loofah sponge and water. 55 The as-prepared loofah sponge also displayed a low adhesion to water. The water droplet (dyed with methylene blue) bounced and rolled off quickly from the loofah surface the moment it dropped on the surface (Fig. S1, see Movie S2 of the ESI † ). Fig. 4 Optical photos of (a) methylene blue dyed water and red oil dyed oil droplets on the as-prepared loofah surface, (b) the water contact angle in air, (c) original and as-prepared loofah after being placed in water, and (d) the as-prepared loofah immersed in water by an external force. The as-prepared loofah sponge showed excellent superhydrophobicity and superoleophilicity, which made it very promising as a versatile absorber material for removal of oil from water. As illustrated in Fig. 5a , the modified loofah sponge showed highly efficient selection to remove oil from water. Oily red dyed n -hexane spread on the water was rapidly and completely absorbed in a few seconds, leaving a transparent and clean region on the water surface due to the superhydrophobicity/superoleophilicity of the as-prepared loofah sponge (see Movie S3 of the ESI † ). The prepared sponge also showed excellent absorption selectivity toward organic solvents with higher densities than water by selectively absorbing the oily red dyed chloroform from under the water ( Fig. 5b , see Movie S4 of the ESI † ). The rapid and complete absorption of organic solvents from water demonstrated the excellent oil/water separation capability of the as-prepared sponge. Fig. 5 Optical photos demonstrating the processes for oil–water separation of the as-prepared loofah: (a) sequential snapshots of removing a layer of oily red dyed n -hexane on top of water and (b) sequential snapshots of removing oily red dyed chloroform under water. Moreover, the as-prepared loofah sponge can separate oil microdroplets from a surfactant-free oil-in-water emulsion, which was prepared by mixing n -hexane in water (v/v, 1/49) as shown in Fig. 6 . Under intensive stirring for 0.5 h, the as-prepared loofah sponge was placed into the emulsion. Once touching the loofah sponge, emulsion droplets demulsified. The red oil droplets in the emulsion were immediately trapped and quickly absorbed by the loofah sponge. During the separation process, the loofah sponge slowly turned red and the emulsion gradually faded to transparent and clean in 1 min, which suggests a highly efficient selective absorptive capacity of the as-prepared loofah sponge ( Fig. 6a–d , see Movie S5 of the ESI † ). Fig. 6b and c show an obvious bright silver mirror layer on the loofah surface when it was immersed into water, due to the reflectance of light at a continuous air layer between the loofah sponge and water. This suggested the loofah was in the non-wetting Cassie–Baxter state and still maintained excellent superhydrophobic properties. In addition, optical images of the n -hexane-in-water emulsion before and after oil separation further confirmed that the residual water was free of oil droplets ( Fig. 6e–g ), revealing a high separation efficiency for the separation of oil from surfactant-free oil-in-water emulsions. Fig. 6 Photographs of the selective collection of oil with a stirring process (a–d) and optical microscope images and digital photo of the separation results of the oil-in-water emulsion before and after oil–water separation (e–g). The as-prepared loofah sponge also exhibited robust superhydrophobicity and excellent oil/water separation efficiency in harsh environments, such as immersed into 1 M HCl, 1 M NaOH, and saturated NaCl solutions, and hot water, respectively. The oil–water separation efficiency of the as-prepared loofah sponge for corrosive water/oil mixtures is depicted in Fig. 7 . When directly immersed in a mixture of oily red dyed chloroform/n-hexane and 1 M HCl solution, the loofah sponge absorbed the oil and turned red rapidly due to the robust superhydrophobic/superoleophilic properties. The HCl water solution became clean and transparent with the volume nearly unchanged ( Fig. 7a ; Movie S6 in the ESI † ). Moreover, the loofah sponge also showed excellent oil/water separation ability in chloroform/n-hexane/1 M NaOH ( Fig. 7b ; Movie S7 in the ESI † ), chloroform/n-hexane/saturated NaCl ( Fig. 7c ; Movie S8 in the ESI † ), and hot water at higher than 95 °C ( Fig. 7d ; Movie S9 in the ESI † ) using the same method. And the loofah sponge still retained superhydrophobicity after 5 cycles as shown in Fig. S2. † These results demonstrated that the as-prepared loofah sponge maintained robust superhydrophobicity in harsh environments, which exhibited great potential in practical applications such as with ocean oily spills and wastewater from chemical industry. Fig. 7 The absorption process of the as-prepared loofah under harsh conditions by taking oily red dyed chloroform/n-hexane in corrosive solution mixtures as examples. (a) 1 M HCl solution, (b) 1 M NaOH solution, (c) saturated NaCl solution, and (d) oily red dyed kerosene in 95 °C hot water. As we all know, the construction of a superhydrophobic interface requires two elements: on the one hand was to construct a rough interface with hierarchical micro–nano structure on the hydrophobic surface, and the other hand was to modify the low surface energy material on the rough interface. 56,57 In this work, the hydrophobic fused nano-SiO 2 was introduced not only to provide a hierarchical micro–nano rough surface on the loofah sponge but also to act as a low-surface-energy compound material to endow the sponge with excellent superhydrophobic properties, which avoided the use of toxic, expensive fluorocarbon reagents. However, the fragile rough micro–nano structures of conventional superhydrophobic surfaces can be easily damaged under external mechanical forces or friction, which limits its large-scale application in practical industry. To solve this problem, the waterborne polyurea adhesive with 100% solid content was used as an adhesive to provide excellent adhesion, which can tightly bond SiO 2 nanoparticles to the loofah sponge, and endow the sponge with superior chemical stability, abrasion resistance and robustness for oil–water separation in harsh environments. In order to further check the robustness of the sponge against mechanical forces, the sandpaper-abrasion test and finger-wipe test were performed as shown in Fig. 8 and 9 , respectively. In Fig. 8a , the as-prepared loofah sponge was placed on the sandpaper under a weight of 100 g and moved back and forth with abrasion length of about 15 cm. After a certain number of friction cycles, the sponge still preserved a good water repellency. Fig. 8b describes the water static contact angles after every tenth abrasion cycle and it can be seen that the water static contact angles were all higher than 150°, indicating that the loofah sponge possessed excellent superhydrophobicity and abrasion resistance (see Movie S10 in the ESI † ). The insets in Fig. 8b are the SEM image and water static contact angle after 50 sandpaper-abrasion cycles for the loofah sponge surface. After 50 abrasion cycles, the loofah sponge surface still had a large amount of silica and the water contact angle was about 152°, which strongly indicated that the as-prepared sponge retained robust superhydrophobicity due to the strong adhesion of the polyurea resin. Fig. 8 Sandpaper-abrasion tests. (a1 and a2) One cycle of the sandpaper-abrasion test. (b) The variation of water CAs of the as-prepared sponge versus the number of abrasion cycles. Fig. 9 Schematic illustration of the method of the finger-wipe test (a1 to a4). (b) The variation of water CAs and separation efficiency of the as-prepared sponge versus the number of finger-wipe cycles. \n Fig. 9 demonstrates the finger-wipe test of loofah sponge. After several finger-wipes, the paint still remained on the sponge surface with no visible paint loss. The blue dyed water quickly fell off the surface of the sponge, which demonstrated the sponge surface retained superhydrophobicity ( Fig. 9a1–a4 , and see Movie S11 in the ESI † ). Fig. 9b depicts the water contact angle and oil/water separation efficiency of the as-prepared sponge during the 50 times finger-wipe test. As can be seen, the water contact angle of the sponge surface was still above 150° after 50 abrasion cycles, which demonstrated the excellent mechanical abrasion resistance of the as-prepared superhydrophobic sponge. Meanwhile, the separation efficiency of the as-prepared sponge still remained above 95% after 50 finger-wipes taking the n -hexane–water mixture as an example. These results indicated that the as-prepared superhydrophobic loofah sponge has excellent separation efficiency for the oil–water mixture against finger-wipe abrasion. The as-prepared superhydrophobic loofah sponge with strong abrasion resistance has great potential in practical industrial oil/water separation applications. To our surprise, the superhydrophobic loofah sponge possessed antifouling and self-cleaning properties which were vital in practical oil/water separation applications since the fouling issues can seriously affect the absorption efficiency and cycle usage times of the absorbers. 58 To observe the anti-fouling and self-cleaning properties, an abundant amount of manganese dioxide powder dispersed in water was used as a model contaminant. When the black sewage dripped onto the surface of the loofah sponge, the water droplets immediately rolled off the surface leaving a clean superhydrophobic surface ( Fig. 10a1–a3 ). Moreover, after immersion in the black dirty solution, the surface of the as-prepared loofah sponge was almost free of black sewage indicating the excellent anti-fouling and self-cleaning performances ( Fig. 10b1–b3 and see Movie S12 in the ESI † ). However, for the pristine loofah sponge there was a lot of black dirt accumulation on the pristine loofah sponge as shown in Fig. S3 and Movie S12 in the ESI. † Fig. 10 Photographs of the self-cleaning property of the as-prepared sponge."
} | 6,761 |
23143043 | null | s2 | 3,274 | {
"abstract": "Non-Watson-Crick base pairing provides an in situ approach for actuation of DNA nanostructures through responses to solution conditions. Here we demonstrate this concept by using physiologically-relevant changes in pH to regulate DNA pyramid assembly/disassembly and to control the release of protein cargo."
} | 76 |
22880069 | PMC3413654 | pmc | 3,275 | {
"abstract": "Background History drives community assembly through differences both in density (density effects) and in the sequence in which species arrive (sequence effects). Density effects arise from predictable population dynamics, which are free of history, but sequence effects are due to a density-free mechanism, arising solely from the order and timing of immigration events. Few studies have determined how components of immigration history (timing, number of individuals, frequency) alter local dynamics to determine community assembly, beyond addressing when immigration history produces historically contingent assembly. Methods/Findings We varied density and sequence effects independently in a two-way factorial design to follow community assembly in a three-species aquatic protozoan community. A superior competitor, Colpoda steinii, mediated alternative community states; early arrival or high introduction density allowed this species to outcompete or suppress the other competitors ( Poterioochromonas malhamensis and Eimeriidae gen. sp.). Multivariate analysis showed that density effects caused greater variation in community states, whereas sequence effects altered the mean community composition. Conclusions A significant interaction between density and sequence effects suggests that we should refine our understanding of priority effects. These results highlight a practical need to understand not only the “ingredients” (species) in ecological communities but their “recipes” as well.",
"introduction": "Introduction Community assembly has been a prominent concept in ecology; a variety of sometimes divergent views have reflected different assumptions and a confusing array of terminology. At one extreme, communities have been viewed as the product of random dispersal events, after which deterministic species sorting overrides immigration history. For example, Diamond [1] outlined a set of “assembly rules” of limited membership for the local fauna of bird communities in New Guinea that set limits on which species from the regional source pool could coexist. At the other extreme, the final community structure can be viewed as a historical artifact of the precise order of species' arrival. Although not supporting such an extreme role for historical contingency, Drake [2] , used aquatic microcosms to show that community assembly depends in potentially complex ways on the identities and sequence of arrival of species as communities develop. Empirical efforts to understand historical forces driving community assembly have included observational comparisons of natural communities at different localities at various disturbance levels (see, e.g., Urban [3] , Weslien et al. [4] ) and experimental perturbations of naturally recovering communities [5] – [7] ; these empirical studies complement theoretical investigations into alternative stable states (e.g., Shurin et al. [8] ) and transient states [9] . Communities from a wide range of habitats have been shown to be affected by the direct manipulation of immigration history (e.g., acacia ants, by Palmer et al. [10] ; amphibians by Wilbur and Alford [11] ; aquatic protists by Robinson and Dickerson [12] and Fukami [13] ; ectomycorrhizal fungi by Kennedy et al. [14] ; drosophilids by Shorrocks and Bingley [15] ; wood-decaying fungi by Fukami et al. [16] ). Along with empirical insights, theoretical work suggests that the context in which communities assemble can be altered by regional factors (e.g., large regional species pools, low rates of connectivity) and local factors (e.g., high productivity and low disturbance) [17] . These studies have explored aspects of the effects of immigration history on historically contingent assembly, but do not separate how various components of immigration history (timing, number of individuals, frequency) alter local dynamics to determine community assembly. No empirical studies have rigorously identified mechanisms by which local dynamics interact with immigration history. History drives community assembly by two potentially independent mechanisms, density effects and sequence effects. Density effects are predictable dynamics that follow directly from different initial abundances of competitors and the time for unimpeded growth between colonizing events. For example, simple Lotka-Volterra models predict that, when conditions for a stable two-species equilibrium occur, communities will reach the same final equilibrium state regardless of the initial abundances of species, but when parameters create an unstable equilibrium, differences in species' abundances at the time when later colonists arrive determine which species outcompetes the other [18] . Density effects are independent of the history of other species and are firmly anchored in population-dynamics principles. In contrast, sequence effects occur through differences that are unrelated to density but are due purely to the order in which species arrive. Possible mechanisms of sequence effects would include delayed life-history effects [19] and ecosystem engineering that alters fitness landscapes of competing species [20] . Note that, by our definitions, the widely used term “priority effects” (sensu Wilbur and Alford [11] , Young et al. [21] ) confounds density and sequence effects, even though theory gives reason to suspect that density and sequence effects on community assembly can differ (cf. Lotka [18] , Connell and Slatyer [22] ). Our separation of density and sequence effects is therefore essentially a claim that we should refine interpretations of priority effects. Previous experimental studies (e.g., Drake [2] , Fukami [9] , Robinson and Dickerson [12] , Kennedy et al. [14] , Collinge and Ray [23] ,) have shuffled the sequence of species introduction, but because they did not factorially vary the intensity of immigration (density of species) crossed with sequence of arrival, the underlying mechanisms leading to historically contingent community structure remain undetermined. We varied density and sequence effects independently in a two-way factorial design to follow community assembly of an inquiline protozoan community in experimental microcosms. The community originates from the water-filled leaves of the purple pitcher plant, Sarracenia purpurea ; in this ecosystem, energy is derived from allochthonous material in the form of insects that fall into the water-filled leaves and drown [24] . Bacteria make up the bottom trophic level as communities develop through immigration of protozoans, rotifers, and top predators [25] . This well-studied community has rapid dynamics and is ideal for studying assembly. We specifically tested the hypothesis that density and sequence effects interact to determine the mean and the variation (i.e., beta diversity) in community structure of protozoans in experimental microcosms.",
"discussion": "Discussion Our experiment and analyses demonstrated that density and sequence effects were distinct ecological mechanisms that differed qualitatively in their impacts on assembly of a three-species protozoan community and, most importantly, that density and sequence effects on assembly interacted. Density effects caused greater dispersion in the protozoan community structure without substantially changing the average community states, whereas sequence effects often altered the community states, possibly through changing the locations of the community attractors themselves ( Fig. 4 ). Historical contingency in the protozoan community therefore arises from three sources: (1) whether or not initial densities differ sufficiently to cause density effects when the immigration sequence and times of arrival are fixed, (2) whether sequence effects determine community structure even when initial densities do not differ substantially, and (3) effects of assembly history that arise from interactions between density and sequence effects. Although most of our experimental protozoan communities appeared to have stabilized after 72 hours (approximately 9 generations), we cannot be certain that they do not actually represent transient community states. We suggest that the durations of our experiments were generally sufficient, on the basis of the criteria presented by Grover and Lawton [33] —the intervals between invasions was longer than the generation times, the invasion interval was shorter than the time necessary for maximum population densities to develop, and the total duration of the experiment was much longer than the generation times. However, even if our final communities did not represent stable or near-stable states, theoretical work suggests that historical contingency can be important for understanding transient dynamics as well [9] . In prior studies, priority effects have often been invoked as a post hoc explanation for the observed community changes, as the investigator looked back to initial conditions to interpret current conditions [see, e.g., Robinson and Dickerson [12] , Kennedy et al. [14] ]. However, because early-arriving species in these studies are likely to be more abundant by the time later species arrive, the effects of sequence and density are confounded. Our work not only suggests a refined interpretation of priority effects in principle but also provides a wider framework that might be useful in decision making in practical restoration projects. For restoration ecologists, the vague concept of priority effects does not reveal when, or how many individuals of, a particular species should be introduced, because most previous studies of priority effects inherently confounded density and timing. We propose that a theory of assembly history could better guide restoration efforts if density and timing are considered separately and interactively. Sequence effects may be characteristic of particular types of systems—they may lead us forcefully to dissect purely historical processes into trait-based mechanisms (see, e.g., Beckerman et al. [19] ) for the practical purpose of gaining specific predictions about the target systems. Separating density and sequence effects can thus contribute theoretical guidance to harnessing contingency behind community assembly or at least clarifying the information demands in previous studies that have relied heavily on purely empirical, case-by-case approaches. Sequence effects may less important in other systems, however, especially over the long term: for example, Collinge and Ray [23] used a restoration project in vernal plant communities to test for historically contingent assembly but found that the order and intensity of seeding influenced plant communities only transiently, within a decade of early community formation. An important future challenge will be to determine whether such historical forces scale up to more complex situations. Natural experiments often involve many uncontrolled variables and may require using multiple sources of information to rule out alternative hypotheses of assembly-history dynamics. Reconstructing population-genetic structure by analyzing current populations, for example, may allow us to use proxies for density effects and sequence effects of the unwitnessed past. Accumulating quantitative facts about the components of immigration history (timing, number, frequency, etc.) in island restoration, biocontrol management, and biological invasion continues to be important for understanding a large-scale imprint of assembly-history dynamics. Although our study was of a competitive community, further mechanistic lines of inquiry into assembly-history dynamics for predator-prey interactions, mutualisms, and multitrophic food webs will enrich our understanding not only of the ingredients (the species) but also of the recipes (timing and numbers of individuals) for ecological communities in an invasion-driven world."
} | 2,964 |
27359217 | null | s2 | 3,276 | {
"abstract": "The ability of bacteria to recognize kin provides a means to form social groups. In turn these groups can lead to cooperative behaviors that surpass the ability of the individual. Kin recognition involves specific biochemical interactions between a receptor(s) and an identification molecule(s). Recognition specificity, ensuring that nonkin are excluded and kin are included, is critical and depends on the number of loci and polymorphisms involved. After recognition and biochemical perception, the common ensuing cooperative behaviors include biofilm formation, quorum responses, development, and swarming motility. Although kin recognition is a fundamental mechanism through which cells might interact, microbiologists are only beginning to explore the topic. This review considers both molecular and theoretical aspects of bacterial kin recognition. Consideration is also given to bacterial diversity, genetic relatedness, kin selection theory, and mechanisms of recognition."
} | 245 |
31667368 | PMC6807065 | pmc | 3,278 | {
"abstract": "One-carbon compounds, such as methanol, are becoming potential alternatives to sugars as feedstocks for the biological production of chemicals, fuels, foods, and pharmaceuticals. Efficient biological production often requires extensive genetic manipulation of a microbial host strain, making well-characterised and genetically-tractable model organisms like the yeast Saccharomyces cerevisiae attractive targets for the engineering of methylotrophic metabolism. S. cerevisiae strains S288C and CEN.PK are the two best-characterised and most widely used hosts for yeast synthetic biology and metabolic engineering, yet they have unpredictable metabolic phenotypes related to their many genomic differences. We therefore sought to benchmark these two strains as potential hosts for engineered methylotrophic metabolism by comparing their growth and transcriptomic responses to methanol. CEN.PK had improved growth in the presence of methanol relative to the S288C derivative BY4741. The CEN.PK transcriptome also had a specific and relevant response to methanol that was either absent or less pronounced in the BY4741 strain. This response included up-regulation of genes associated with mitochondrial and peroxisomal metabolism, alcohol and formate dehydrogenation, glutathione metabolism, and the global transcriptional regulator of metabolism MIG3 . Over-expression of MIG3 enabled improved growth in the presence of methanol, suggesting that MIG3 is a mediator of the superior CEN.PK strain growth. CEN.PK was therefore identified as a superior strain for the future development of synthetic methylotrophy in S. cerevisiae.",
"conclusion": "5 Conclusions Due to inherent and unpredictable differences in the S288C and CEN.PK laboratory yeast strains and the need to identify a host strain for the development of synthetic methylotrophy, we compared the methanol-specific growth and transcriptomic responses of the commonly used yeast strains BY4741 and CEN.PK113-5D. We found that the CEN.PK strain had dramatically improved growth on solid media supplemented with methanol relative to the S288C strain (BY4741), and slightly improved growth in liquid yeast extract medium containing methanol compared to yeast extract only medium. In contrast, the S288C derivative had no growth response to methanol in liquid medium. Consistent with this improved methanol-specific growth, the CEN.PK strain had a distinct transcriptomic response to methanol that included up-regulation of mitochondrial genes, peroxisome biogenesis, glutathione metabolism, the alcohol dehydrogenase ADH2 , the formate dehydrogenase FDH1 , and the global carbon-source specific transcriptional regulator MIG3 . Reverse engineering of the CEN.PK phenotype by expressing MIG3 in the BY4741 strain to improve growth in the presence of methanol also suggested that MIG3 is a mediator of the improved growth phenotype and distinct transcriptome in CEN.PK. We conclude that CEN.PK is a superior host strain for future studies on methylotrophic processes in S. cerevisiae , and for the development of synthetic methylotrophy.",
"introduction": "1 Introduction The yeast, Saccharomyces cerevisiae , is one of the most intensely studied model eukaryotic microorganisms. This single-celled fungus has a well-characterised genetic system amenable to a large variety of advanced genetic manipulation tools, and robust industrial growth. Thanks to its long history in the food, beverage and bioethanol industries, its safety record, and ability to grow robustly at an industrial scale, S. cerevisiae has been widely engineered and deployed as a “cell factory” for the production of chemicals, fuels, foods, materials, and pharmaceuticals [ 1 ]. With the eventual decline of global oil reserves and mounting environmental concerns over fossil-resource use, renewable methods of biological chemical production are becoming increasingly important. One limitation to the use of cell factories, such as yeast, to achieve this is the fact that they rely on sugars as a carbon source for growth and production. The sugarcane and maize that is commonly used as a bioprocess feedstock relies on arable land, water, and fertiliser that competes with the human food supply. Moreover, the complete transfer of petrochemical production processes to sugar-fed biological production would have a significant impact on food supplies. An emerging alternative to sugar as a bioprocess feedstock is to use substrates such as carbon dioxide, methane, and methanol as carbon sources for microbial production processes. Compared to the gases carbon dioxide and methane, methanol is a relatively safe and stable liquid at room temperature and therefore does not require alternative infrastructure for transportation, storage and fermentation. Methanol can be derived from the gasification of biomass to synthesis gas with subsequent reduction to methane, followed by oxidation to methanol. This can be achieved chemically or biologically via a variety of emerging technologies [ 2 , 3 ]. These processes would enable the use of biomass, municipal waste, or natural gas as feedstocks for bio-production via methanol, enabling independence from arable land and sugar production. For these reasons, methanol has become an attractive carbon source for the metabolic engineering of sustainable chemical production [ 4 ]. There are many microorganisms that naturally grow using methanol, yet they usually do not have the depth of characterisation and genetic tools of model organisms such as Escherichia coli and S. cerevisiae . Native methylotrophic metabolism is also optimised for growth, making metabolite production from methanol a challenge. Synthetic methylotrophy in model organisms has therefore become a focus in the fields of synthetic biology and metabolic engineering with recent demonstrations in E. coli [ [5] , [6] , [7] , [8] ]. Engineering methylotrophy in yeast is also an attractive option since it would enable production of compounds that require the functional expression of eukaryotic proteins, and could be coupled to a multitude of optimised metabolite production pathways [ 9 ]. Laboratory strains of S. cerevisiae, such as the S288C derivatives and semi-industrial CEN.PK series, are commonly used for synthetic biology and metabolic engineering projects due to their depth of characterisation and genetic tools. However, significant variation exists in their physiology and genetics with roughly 22,000 point mutations and 83 genes absent in the CEN.PK strains relative to S288C [ 10 , 11 ]. There is an enrichment of single nucleotide polymorphisms (SNPs) in genes and regulatory regions that encode enzymes involved in metabolism, and these two popular laboratory strains of S. cerevisiae have inherently different capacities for different engineered functions. For example, S288C was shown to produce 10-fold more vanillin from an engineered pathway than a CEN.PK strain in continuous culture [ 11 ]. In contrast, a CEN.PK strain engineered for p -coumaric acid production made between 20 and 50% more than its S288C counterpart [ 12 ]. Given these fundamental and unpredictable metabolic differences in S. cerevisiae strain backgrounds, we sought to benchmark and compare the S288C derivative BY4741 and the CEN.PK derivative CEN.PK113-5D strains for their potential as hosts for synthetic methylotrophy, and understand any differences using RNA-seq mediated transcriptomics.",
"discussion": "4 Discussion We have compared the two commonly used laboratory strains of S. cerevisiae , BY4741 and CEN.PK113-5D, for growth and transcriptional response to methanol. We found that the CEN.PK strain grows better in the presence of methanol than the BY4741 strain on both solid and liquid medium, but that yeast extract is required to support growth in liquid medium. These differences are important for determining which strain could best serve as a host for the engineering of methylotrophic metabolism. Synthetic methylotrophy has become an active area of research in the field of synthetic biology due to the potential attractiveness and sustainability of methanol as a bioprocess feedstock, and the genetic plasticity of model organisms, such as S. cerevisiae and E. coli . We therefore used transcriptomics to gain insight into differences in genes expression that might explain the methanol-specific growth differences between these two laboratory yeast strains. In contrast to a previous transcriptome study on methanol toxicity in S. cerevisiae S288C where growth medium with yeast extract, peptone, dextrose, and 5% methanol was used [ 24 ], we used a lower concentration of methanol (2%), included the semi-industrial CEN.PK113-5D strain, and focused on both strain- and medium-specific differences in transcription. Despite these differences, we found some similar trends to this previous study. For example, we also observed up-regulated aryl alcohol dehydrogenases, alcohol dehydrogenases, aldehyde dehydrogenase, and enzymes involved in glutathione metabolism. These genes are likely involved in the detoxification of methanol and formaldehyde and their up-regulation suggests that S. cerevisiae has a native metabolic response to methanol, potentially via promiscuous alcohol dehydrogenase activity followed by formaldehyde detoxification ( Fig. 5 B). For example, a study by Grey et al. (1996) found that over-expression of ADH1 lead to hyper-resistance to formaldehyde via possible reduction to methanol, this reaction could also be occurring in the reverse direction oxidising methanol to formaldehyde [ 25 ]. We also found that the CEN.PK strain has a specific response to methanol that differs to that of BY4741, and has some similarities to methylotrophic yeasts such as Pichia pastoris ( Fig. 5 A). This response included up-regulation of genes that are specific to the ethanol responsive ADR1 transcription factor [ 22 ], such as peroxisome biogenesis genes, alcohol dehydrogenase ( ADH2 ), and glutathione enzymes. The CEN.PK strain also had significant up-regulation of genes involved in mitochondrial respiration, suggesting a more active metabolism involved in ATP synthesis. In theory, NADH would be derived from formaldehyde and formate detoxification by the CO 2 forming formate dehydrogenase ( FDH1 ), which was the most highly up-regulated gene in both strains. The NADH generated from Fdh1p-mediated formate oxidation could then be oxidised via the mitochondrial electron transport chain, as long as the tricarboxylic acid cycle (TCA) was active. Despite FDH1 being up-regulated in both strains under methanol exposure, FDH1 was still significantly up-regulated by 9.6-fold in CEN.PK grown on YEM relative to BY4741 grown on YEM. Another interesting finding was the CEN.PK-specific up-regulation of the MIG3 transcription factor. MIG1 and MIG2 are well-characterised glucose-responsive regulators of metabolism [ [26] , [27] , [28] ], yet the role of MIG3 is less well-characterised. Recent work has suggested that MIG3 is involved in responding to ethanol, and is non-functional in S288C strains [ 21 ]. Given the observed up-regulation of MIG3 in methanol-treated CEN.PK cultures, which was absent in the equivalent BY4741 cultures, and the fact that we were able to improve the growth of both strains by increasing the expression of MIG3 , it is possible that this transcription factor mediates the observed CEN.PK-specific transcriptional differences in the presence of methanol. MIG3 represses SIR2 expression [ 29 ], and decreased SIR2 expression has been shown to improve growth on non-fermentable carbon sources such as ethanol [ 21 ]. It is therefore possible that MIG3 improves growth on non-fermentable carbon sources in general, rather than methanol specifically, which is supported by our observation that the MIG3 over-expressing CEN.PK strain also has improved growth on YNB-only medium, without methanol present ( Fig. 6 ). However, this does not rule out the possibility that MIG3 mediates the differences in growth and global transcription patterns that we observed between methanol-treated BY4741 and CEN.PK ( Fig. 1 , Fig. 2 ). This is supported by the fact that MIG3 expression in BY4741 enabled an increase in growth under methanol exposure on solid minimal media ( Fig. 6 ). Both synthetic and native methylotrophy are becoming attractive targets for metabolic engineering due to the potential of methanol as an industrial bioprocess feedstock. Our results, alongside some recent studies, suggest that S. cerevisiae is a promising host for the engineering of either native or synthetic methylotrophy. For example, a synthetic methylotrophic pathway involving four genes from P. pastoris , including an alcohol oxidase and dihydroxyacetone synthase, was recently expressed in S. cerevisiae with a subsequent increase in growth in the presence of methanol [ 30 ]. However, this study did not demonstrate methanol assimilation using 13 C-methanol labelling. The potential for formate assimilation to glycine by redirecting fluxes in the native glycine cleavage complex in S. cerevisiae was also recently demonstrated [ 31 ], and it is not inconceivable that this pathway contributes to the small boost in growth that we observed in the CEN.PK strain grown in liquid culture supplemented with methanol. Alternatively, the NADH generated from the detoxification of methanol and formaldehyde to CO 2 by the Fdh1p enzyme could also boost growth via subsequent ATP generation. Previous work has shown that over-expression of the native formaldehyde dehydrogenase ( SFA1 ) can enable the use of formaldehyde as an auxiliary substrate in S. cerevisiae [ 32 ], demonstrating the potential for C1 metabolism in yeast."
} | 3,437 |
37110511 | PMC10146397 | pmc | 3,279 | {
"abstract": "Rhizosheric bacteria with several abilities related to plant growth and health have been denominated Plant Growth-Promoting Rhizobacteria (PGPR). PGPR promote plant growth through several modes of action, be it directly or indirectly. The benefits provided by these bacteria can include increased nutrient availability, phytohormone production, shoot and root development, protection against several phytopathogens, and reduced diseases. Additionally, PGPR can help plants to withstand abiotic stresses such as salinity and drought and produce enzymes that detoxify plants from heavy metals. PGPR have become an important strategy in sustainable agriculture due to the possibility of reducing synthetic fertilizers and pesticides, promoting plant growth and health, and enhancing soil quality. There are many studies related to PGPR in the literature. However, this review highlights the studies that used PGPR for sustainable production in a practical way, making it possible to reduce the use of fertilizers such as phosphorus and nitrogen and fungicides, and to improve nutrient uptake. This review addresses topics such as unconventional fertilizers, seed microbiome for rhizospheric colonization, rhizospheric microorganisms, nitrogen fixation for reducing chemical fertilizers, phosphorus solubilizing and mineralizing, and siderophore and phytohormone production for reducing the use of fungicides and pesticides for sustainable agriculture.",
"conclusion": "8. Conclusions This review emphasizes the potential of biologically dependent instruments, specifically PGPR, to assist in addressing global food production issues. Before these tools can be applied to real-world situations, it is evident that there are significant knowledge deficits that must be filled. PGPR could be the key to sustainable crop productivity and efficient nutrient management.",
"introduction": "1. Introduction Plant growth-promoting rhizobacteria (PGPR) are free-living bacteria that colonize plant roots and promote plant growth. PGPR may promote plant growth by using their own metabolism (solubilizing phosphates, producing hormones, or fixing nitrogen), by directly affecting the plant metabolism (increasing the uptake of water and minerals), enhancing root development, increasing the enzymatic activity of the plant, by “helping” other beneficial microorganisms to enhance their action on the plant, or by suppressing plant pathogens [ 1 , 2 , 3 ]. They protect plants indirectly by competing with pathogens for scarce nutrients, biocontrolling pathogens by producing aseptic-activity compounds, synthesising fungal cell wall lysing enzymes, and inducing systemic responses in host plants. PGPR may help plants to thrive under abiotic stress by improving the plant fitness, stress tolerance, and pollution remediation. Additional data and greater knowledge of bacterial features driving plant-growth promotion might motivate and stir the development of creative solutions utilizing PGPR in highly changeable environmental and climatological settings [ 4 ]."
} | 752 |
40037293 | PMC11931723 | pmc | 3,281 | {
"abstract": "Abstract Drylands cover one-third of the Earth’s surface and are one of the largest terrestrial sinks for methane. Understanding the structure–function interplay between members of arid biomes can provide critical insights into mechanisms of resilience toward anthropogenic and climate-change-driven environmental stressors—water scarcity, heatwaves, and increased atmospheric greenhouse gases. This study integrates in situ measurements with culture-independent and enrichment-based investigations of methane-consuming microbiomes inhabiting soil in the Anza-Borrego Desert, a model arid ecosystem in Southern California, United States. The atmospheric methane consumption ranged between 2.26 and 12.73 μmol m 2 h −1 , peaking during the daytime at vegetated sites. Metagenomic studies revealed similar soil-microbiome compositions at vegetated and unvegetated sites, with Methylocaldum being the major methanotrophic clade. Eighty-four metagenome-assembled genomes were recovered, six represented by methanotrophic bacteria (three Methylocaldum , two Methylobacter, and uncultivated Methylococcaceae ). The prevalence of copper-containing methane monooxygenases in metagenomic datasets suggests a diverse potential for methane oxidation in canonical methanotrophs and uncultivated Gammaproteobacteria. Five pure cultures of methanotrophic bacteria were obtained, including four Methylocaldum . Genomic analysis of Methylocaldum isolates and metagenome-assembled genomes revealed the presence of multiple stand-alone methane monooxygenase subunit C paralogs, which may have functions beyond methane oxidation. Furthermore, these methanotrophs have genetic signatures typically linked to symbiotic interactions with plants, including tryptophan synthesis and indole-3-acetic acid production. Based on in situ fluxes and soil microbiome compositions, we propose the existence of arid-soil reverse chimneys, an empowered methane sink represented by yet-to-be-defined cooperation between desert vegetation and methane-consuming microbiomes.",
"conclusion": "Conclusions This study was inspired by a high methane sink observed in arid ecosystems via in situ measurements almost three decades ago [ 19 ] and a more recent remote-sensor-based demonstration of arid ecosystems as “black holes” of methane, i.e., environments with methane levels significantly below the average [ 102 ]. Here, we aimed to better understand the underlying biological means of arid methane sinks. We investigated methane cycling in the Anza-Borrego State Park, starting with enrichments in 2016, followed by additional sampling sets in 2018, 2020, and 2023. Each time, we isolated microbes from vegetated sites, which inspired a deeper investigation of methanotrophic biome structure via metagenomic studies and in situ methane flux measurements. Integrated, the data highlights the importance of interaction among arid biomes, especially soil microbes and arid vegetation, for atmospheric methane consumption. Plant-supported methane flux shows daily dynamics, suggesting yet-to-be-determined links with the plant’s photosynthetic activity. This observation became the foundation for the reverse chimney hypothesis proposed here ( Fig. 1D ), which could partially explain why deserts constitute natural CH 4 sinks. This hypothesis was coined as the opposite of the chimney effect [ 70–73 ], in which plants transport CH 4 from the anoxic soil layers from their roots through their vascular system to their leaves and release it into the atmosphere ( Fig. 1C ). The reverse chimney hypothesis proposes that in dryland ecosystems (i.e., low organic matter and limited water availability) plants transport CH 4 and oxygen from the atmosphere through their vascular system down to the soil, where it is consumed and converted by methanotrophic microbiota ( Fig. 1D ). It is tempting to speculate that plants accelerate desert methane sinks by providing unique ecosystem support for methanotrophic microbes. Research on how plants contribute to the modulation of CH 4 fluxes has only recently started to be explored. The results presented here encourage future studies aimed at understanding how the CH 4 concentration, macronutrients (i.e., N, S, or P), and moisture levels of the soil determine whether a system functions as a sink or source of CH 4 . The plant-promoting properties of the desert Methylocaldum species will be described in a separate study. The Methylocaldum clade is the most prominent methanotroph in the studied ecosystem, and is the most likely contributes to the observed atmospheric methane consumption. Up to date, none of the Methylocaldum spp. were reported as high-affinity methane oxidizers [ 103 , 104 ]. Thus, their role in the soil methane cycling needs to be re-evaluated. Genomic analysis of Methylocaldum isolates provides insights into the unique metabolic features of the dominant methanotroph in Anza-Borrego soil, contributing to the understanding of microbial adaptation in arid environments. These adaptations include the presence of multiple stand-alone pmoC paralogs in Methylocaldum , which may have functions beyond methane oxidation or contribute to high-affinity methane oxidation. The TRAP found in Anza-Borrego Methylocaldum isolates might play an important role in supporting substrate transport under reduced water availability. Genomic evidence suggests that Methylocaldum may rely on a symbiotic relationship with Bradyrhizobium for cobalamin (vitamin B 12 ) due to its lack of de novo synthesis genes. Additionally, both Methylocaldum and Bradyrhizobium possess the necessary genes for tryptophan synthesis and IAA production, indicating a potential interaction that benefits plant growth and bacterial adaptation in arid environments. Establishing beneficial rhizosphere microbiomes in drylands could enhance soil stability by producing an extracellular matrix [ 105 ], promoting vascular plant growth, or generating a positive feedback loop that supports the proposed reverse chimney effect. These findings are the starting point for further research on how CH 4 concentrations, macronutrients, and soil moisture levels influence the role of plant-microbiome biomes in modulating CH 4 fluxes at different scales across seasons in arid ecosystems. Further research is needed to explore the impact of different vegetation types, environmental conditions, and soil microbiomes on terrestrial CH 4 fluxes.",
"introduction": "Introduction Greenhouse gases (GHGs) are the chemical footprint of natural and anthropogenic activities that accelerate climate change. Methane (CH 4 ) is the second most abundant GHG, after carbon dioxide (CO 2 ), constituting the most abundant reduced compound [ 1 ] and hydrocarbon [ 2 ] in our atmosphere. The global warming potential of CH 4 is 84 times higher than CO 2 over a period of 20 years [ 3 ]. Approximately 500–600 Tg (1Tg = 10 12 g) of CH 4 are emitted globally into the atmosphere every year from different natural and anthropogenic processes [ 4–9 ], posing an urgent need for worldwide mitigation efforts [ 10 ]. Biological CH 4 emissions are driven by the interplay of two groups of organisms: CH 4 producers (mostly methanogens) and CH 4 consumers (often described as methanotrophs). The metabolic activities of these two functional microbial groups determine the net methane flux of ecosystems as a CH 4 source (presenting net emissions) or sink (presenting a net uptake from the atmosphere) [ 4 ]. Soils are the major sinks of atmospheric CH 4, consuming 30–42 Tg per year through the activity of methanotrophic bacteria [ 11–15 ]. CH 4 uptake rates in soils—which vary significantly depending on the ecosystem—have declined in the past decades, mostly due to anthropogenic disturbances [ 16–18 ]. The CH 4 consumption rates in dryland areas (which include semiarid, arid, and hyper-arid regions) have average annual consumption rates as high as 0.66 mg CH 4 m −2 d −1 [ 19 ], which is comparable to that of grassland and forest soils (0.65 mg CH 4 m −2 d −1 and 0.74–1.26 mg CH 4 m −2 d −1 , respectively) [ 20 , 21 ]. The fact that dryland environments comprise roughly one-third of the land surface on Earth [ 22 , 23 ] denotes the importance of studying these regions for correct modeling of the global CH 4 budget. As dryland microbes contribute to global climate regulation through CO 2 , reactive N, and CH 4 emissions, these processes will also likely alter the rate of GHG release and impact the rate of climate change [ 24 ]. Considering that dryland ecosystems are predicted to expand due to climate change and land-use shifts [ 25 ], characterization of soil microbial communities, or microbiota, responsible for biogeochemical fluxes from pristine arid soils is essential for understanding the community dynamics across organizational scales and its effects on global carbon fluxes. Globally, dryland microbiomes are dominated by bacteria members of the phylum Actinomycetota (Actinobacteria), Chloroflexota (Chloroflexi), and the Pseudomonadota (Proteobacteria) [ 24 ]. Less is known about microbial groups that control the local flux of CH 4 , including CH 4 -oxidizing bacteria, anaerobic methanotrophic archaea, and methanogenic archaea [ 26 ]. Different microbial groups, including members of the genera Methylocapsa , Methylococcus, and the family Methylocystaceae have been identified as possible players in methane cycling in these environments [ 27 ]. A study assessing >3400 metagenomes to examine the global patterns of CH 4 metabolism marker gene abundances in soil (a proxy for the distribution of CH 4 -metabolizing microorganisms), has revealed the existence of latitudinal trends in the global abundances of these microbes [ 28 ]. The variations in global abundances of CH 4 -metabolizing microorganisms have been primarily governed by vegetation cover [ 28 ], with no clear patterns in the structure and composition of methanotrophic communities [ 27 ]. This study investigated the role of soil microbiota in modulating CH 4 fluxes for comprehending deserts as CH 4 sinks. The Anza-Borrego Desert State Park (mentioned hereafter as “Anza-Borrego”) was selected as a model system for investigating the methanotrophic soil communities, including those inhabiting plant rhizosphere. The Anza-Borrego Desert ecosystem lies within the Colorado Desert of southern California, United States. Once a tropical forest, then a wetland and savanna, and finally one of the hottest deserts in the western United States, this area was assessed to determine the impact of microbiota from semiarid regions on the methane cycle. This study integrates in situ CH 4 fluxes measurements, microbial metagenomics, and the metabolic potential of methanotrophic bacteria isolates, thus providing insights into how the soil microbiota, with and without vegetation, consumes CH 4 .",
"discussion": "Results and discussion Reverse chimney of arid soils unfolds: In situ methane consumption rates are accelerated by vegetation and linked to daylight intensity Positive correlations between soil cover (vegetation) and methane consumption rates were observed in all field studies conducted in 2016, 2018, 2020, and 2023. The results discussed below are from 2020 and 2023, as they include the most comprehensive set of metadata, such as the type of vegetation—we collected gas fluxes only over A. villosa (desert verbena) and the sunlight phase during the measurements. CH 4 fluxes of Anza-Borrego soil from vegetated sites were observed to vary during the day, reaching their consumption peak during the hours of most intense sunlight with up to 12.73 μmol m −2 h −1 at noon ( Fig. 1A ). The average CH 4 consumption rate in vegetated sites between 10:00 a.m. (i.e., 3 h after sunrise) and 2:00 p.m. (9.07 μmol m −2 h −1 +/− 2.2) was 2.4 times higher than the rates measured 3 h before sunset (3.78 μmol m −2 h −1 +/− 0.81; Fig. 1B ). In contrast, unvegetated sites from the immediate vicinity constantly consumed CH 4 at a rate between 2.26 to 3.74 μmol m −2 h −1 +/− 0.46 ( Fig. 1A ). Moreover, the peak CH 4 consumption rates in vegetated sites between 10:00 a.m. and 2:00 p.m. were 3.17 times higher and significantly different than the average rates for unvegetated sites ( P value <0.0001; Fig. 1B ). This serendipitous observation suggests that Anza-Borrego soil CH 4 consumption rates at vegetated sites are linked to sunlight intensity, while the consumption rates of unvegetated patches are constant during the day ( Fig. 1A ). Many terrestrial plants can accelerate methane transfer from soil to atmosphere, a phenomenon often described chimneys of methane ( Fig. 1C ) [ 70–73 ]. Our evidence suggests that arid plants can reverse the methane flow and accelerate atmospheric methane sink. Hence, arid plants and plant biomes will be referred to here as reverse chimneys ( Fig. 1D ). Figure 1 The methane flux (consumption) comparing vegetated and unvegetated patches in the Anza Borrego Desert State Park. (A) the presence of vegetation and methanotrophs correlated positively with an increased consumption rate of methane. (B) Comparison of methane consumption between morning and afternoon. Significance with P value <0.0001 ( **** ) and 0.0229 ( * ) obtained with unpaired parametric t-test. (C) Graphical summary of the chimney effect. The ribbons in (C) and (D) represent soil moisture (WATER) and organic content (ORG.MATTER). (D) Graphical summary of the proposed reverse chimney effect in arid ecosystems. Reverse chimneys of arid soils empowered by vegetation rather than methanotrophic community structure The taxonomic assignment of the Anza-Borrego metagenomic reads (microbiome) from 2023 to a (non-viral) family using Kaiju resulted in <45% of the total sequences being assigned, which is within the output range reported for this approach with similar sample types [ 43 ]. This assessment revealed that the most abundant members of these microbiomes were similarly distributed among both vegetated and unvegetated sites ( Fig. 2A and Supplementary Fig. S2 ). The most abundant bacteria in these microbiomes belonged to the phyla Actinomycetota (12%–19%), Pseudomonadota (7%–12%), and Acidobacteriota (2%–3%); and to a lesser extent Chloroflexota (1.8%–2.5%), Planctomycetota (1.0%–1.2%), Bacilliota (0.5%–1.1%), Gemmatimonadota (0.8%–1.2%), Bacteroidota (0.5%–2.0%), and Nitrososphaerota (0.4–0.9%). The families Methylobacteriaceae (0.3%–2.4%) and Bradyrhizobiaceae (0.3%–0.5%) were the most abundant Pseudomonadota in these microbiomes ( Fig. 2A ). Reads assigned to known methanotroph families were found in all vegetated and unvegetated Anza-Borrego 2023 samples. Methylococcaceae had the highest relative abundance of all the methanotrophs detected (representing between 0.06% and 0.3% of all the taxonomically assigned reads), followed by Methylocystaceae (with 0.04%–0.06%), and Methylophilaceae (with 0.01–0.04%). Methylothermaceae and Methylacidiphilaceae were the less abundant ranging between 0.002% and 0.006% ( Fig. 2B ). Taxonomic assignation at genus level revealed Methylocaldum (Methylococcaceae) as the most abundant methanotroph in both vegetated and unvegetated samples, between 0.01–0.04% followed by Methylocystis (Methylocystaceae), Methylocapsa (Beijerinckiaceae) and Methylobacter (Methylococcaceae) with abundances of 0.03–0.09% ( Fig. 2C ). Reads assigned to methanotrophs were also found in Anza-Borrego 2016 metagenomes, with an average of 0.5% of relative abundance of Methylococcaceae, 0.3% Methylophilaceae, 0.09% of Methylocystaceae, 0.007% Methylothermaceae, and 0.003% Methylacidiphilaceae. Figure 2 (A) Relative abundance of reads taxonomically assigned groups at a family level. Only abundant families are listed on the legend (>0.5% of assigned reads). (B) Relative abundance of reads taxonomically assigned to methanotrophic groups at family level. (C) Relative abundance of reads taxonomically assigned to methanotrophic genera. (D) Alpha diversity of all normalized taxonomically assignable metagenomic reads of samples with and without vegetation. Non-significant differences were found for Shannon (paired t-test P value = 0.184) and Simpson (paired t-test P value = 0.2354) indexes. Normalized data was randomly rarefied to 1 721 047 reads. (E) Beta diversity was visualized through a NMDS plot of the Bray–Curtis dissimilarity distances between all the taxonomically assignable metagenomic reads. Both normalized and non-normalized approaches, using the taxonomically assignable metagenomic reads, showed no significant differences between the alpha diversity among the Anza-Borrego samples with and without vegetation ( Fig. 2D , Supplementary Fig. S2 ). This trend was also confirmed through pairwise comparison between vegetated and unvegetated when assessing the beta diversity using their normalized taxonomically assignable metagenomic read counts ( Fig. 2E ) [ 27 ]. The similarities between assigned microbial communities do not follow the initial assumption that vegetation, including plant litter and root exudates, serves as a source of organic matter for microbes and leads to distinctive shifts in soil microbial diversity [ 24 ]. Since this study investigated the rhizosphere of the seasonal vascular plant A. villosa (desert verbena), which has a lifespan of only 2 to 3 months between late autumn and early spring, and samples were collected during the first month of plant growth, it might not produce sufficient exudates to change its rhizosphere microbiota to detectable levels and only influence root epibionts. On the other hand, in nutrient-poor and arid environments, plants do not waste resources on supporting a broader microbiome community but rather tend to control nutrient exchange directly with microbes that colonize roots [ 74–76 ]. The results presented here agree with a previous study reporting no significant changes in the total abundance and richness of key marker genes for methanotrophic microbes when assessing different vegetation and climate types from 80 dryland ecosystems [ 27 ]. Based on the recovered soil microbiome structures from unvegetated and vegetated sites, we conclude that the observed enhancement of the methane flux is plant-driven and might be achieved in two ways: close colonization of plant roots by Methylocaldum spp. or enhanced activity of yet-to-be-discovered methanotrophic functions or organisms. Numerous CuMOs are identified in the Anza-Borrego soil metagenomes Considering the low representation of genomes for dryland soil methanotrophs in current databases and its consequent limitations for their identification in metagenomic datasets, the prevalence of methanotrophs in Anza-Borrego was further assessed using functional metabolic marker genes, such as those coding for the key enzymes for CH 4 oxidation: methane monooxygenases (MMO). This enzyme has two types: a soluble MMO (sMMO) and pMMO. Only one sMMO sequence was recovered from all Anza-Borrego 2023 metagenomes. The search for pMMO using KEGG and TIGR databases additionally retrieved genes for other CuMOs, representing ammonia and alkane monooxygenases. The phylogenetic relationship of CuMOs retrieved in this functional screening was generated to distinguish which taxa had each of the three possible CuMOs. A total of 148 CuMOs A, 166 CuMOs B, and 146 CuMOs C gene sequences were recovered from the assembled Anza-Borrego 2023 metagenomes ( Fig. 3 ). Thirty-seven and forty-three CuMO sequences associated with canonical methanotrophic taxa (putative methanotrophs) were recovered from vegetated and unvegetated sites, respectively, with the majority corresponding to pmoB subunits (25 in vegetated and 27 in unvegetated metagenomes). In addition, CuMOs from ammonia oxidizers were retrieved from both vegetated and unvegetated sites (97 and 116 genes, respectively), as well as CuMOs related to putative hydrocarbon (alkane) oxidizers (58 from vegetated sites and 66 from unvegetated). These results denote the extensive diversity of potential CH 4 oxidizers in the Anza-Borrego soil microbiomes and suggest that the prevalence of all three types of CuMOs may be independent of the presence of vegetation ( Fig. 3 ). Figure 3 Maximum likelihood trees representing the phylogenetic relationship between CuMOs across bacteria and archaea retrieved from the metagenomes and publicly available genomes. The functional richness of the different subunits from the Anza-Borrego metagenomes is represented by green (vegetated) and yellow (unvegetated) lines at the tips of their corresponding leaves. The outside color-coded ring guides the function of CuMOs, which was assigned based on the taxon at the corresponding leaf. The phylogenetic trees do not show the branch length to facilitate the visualization of clade topology. MAGs and isolate genomes indicate methanotrophy potential in the Anza-Borrego soil microbiome beyond canonical species The 2016 and 2023 Anza-Borrego soil metagenomes were used to generate 84 MAGs, of which 10 were high-quality and 53 medium-quality drafts [ 77 ] ( Supplementary Fig. S3 ). Among them, eight MAGs had methane monooxygenase and methanol dehydrogenase genes. These included three Methylocaldum , two Methylobacter , one Methylococcaceae , and two that could only be assigned to the class Gammaproteobacteria, with their pmoB subunits having a 36% coverage with 74% identity to pmoB of Methylococcus and the other a 36% coverage with 75% identity to Methylocaldum pmoB ( Fig. 4 ). Figure 4 Comparison of the metabolic potential of isolates and relevant MAGs obtained from Anza-Borrego (2016 and 2023). The analysis indicates the presence of key genes involved in relevant pathways for this study. Also, other 12 MAGs had at least one of the three CuMO subunit genes ( Fig.4 ): 10 Nitrososphaeraceae (ammonia-oxidizing), ( Fig. 4 ), one Acidimicrobiia, and one Pedosphaerales ( Supplementary Fig. S3 ) with CuMO subunits with high identity to recovered pmoA sequences from Anza-Borrego that formed part of the putative alkane-oxidizer clade and Methylocaldum stand-alone pmoC Types 4 and 5, respectively. Five pure cultures of methanotrophic bacteria were obtained from the Anza-Borrego cultivation efforts ( Fig. 4 , Supplementary Table S1 ). Among these isolates, four corresponded to Methylocaldum (strains 0917, S3V3, YM2, and RMAD-M, all with a genome size of 5.2 to 5.4 Mbp), and one corresponded to Methylosinus sp. Sav-2 (4.7 Mbp). All isolated Methylocaldum grew only when supplemented with methane between 0.04% to 20% (for enrichments and routinary culture, respectively) and did not grow when supplemented with methanol or organic acids as carbon sources. The growth of Methylosinus sp. Sav-2 can be supported by methane and methanol. Ten isolates corresponded to non-methanotrophic bacteria, including Bradyrhizobium (strains W, R2.2-H, BM-T, Y-H1, all with a genome size of 8.0 Mb), Neorhizobium sp. R1-B (5.5 Mb) and S3V5DH (5.8 Mb), Caulobacter sp. H1 (3.7 Mb) and the methylotroph Methylobacterium sp. R2–1 (5.8 Mb). The growth of methylotrophic cultures can be supported by methanol and organic acids (pyruvate, succinate). All expected metabolic functions in Methylocaldum MAGs were reproduced in at least one of the genomes of isolated strains obtained in this study ( Fig. 4 , Supplementary Fig. S3 ). Therefore, since the genus Methylocaldum (from the family Methylococcaceae) was the most dominant methanotrophic bacterial group detected in the Anza-Borrego metagenomes ( Fig. 2C ), further analysis focused on the metabolic potential of the Methylocaldum isolates. A genomic comparison between the Anza-Borrego Methylocaldum and the 10 Methylocaldum genomes ( Supplementary Table S3 , Supplementary Fig. S4 ) that were publicly available at the time of the analysis was performed to assess the distinguishing metabolic features of the dryland isolates. For example, all the Methylocaldum genomes had the metabolic potential for nitrogen fixation, and both the large (K01601) and small (K01602) subunit of a Type-IA/B ribulose 1,5-bisphosphate carboxylase (Supplementary Information and Supplementary Fig. S5 ). The Anza-Borrego Methylocaldum isolates presented more lanthanide-dependent xoxF 3-type methanol dehydrogenase paralogs compared to the genomes of isolates from other environments following previous xoxF assignations [ 78–80 ] ( Supplementary Fig. S6 ). Further details on key features of the Anza-Borrego genomes, as unveiled by assessing the distribution of the 8668 groups of orthologous genes comprising the Methylocaldum pangenome, are described below (and in Supplementary Tables S4 and S5 ). \n Methylocaldum has four pmoC paralogs in addition to the canonical gene involved in methane oxidation The Methylocaldum pangenome revealed the presence of several paralogs among the 39 pmoC retrieved (K10946), of which only nine formed parts of the canonical pMMO gene cluster ( Fig. 5 ). The remaining stand-alone pmoC paralogs (that included neither pmoA nor pmoB ) could be grouped into four distinctive gene contexts that were conserved even among representatives isolated from different continents ( Fig. 5A and Supplementary Fig. S4 ). These stand-alone pmoC genes clades were named “Type 2 to 5” considering their conserved genomic context and phylogenetic placement to the canonical “Type 1” pMMO gene cluster ( Fig. 5B and Supplementary Material). The immediate vicinity of the conserved genomic context of Type 2 Methylocaldum pmoC had genes involved with nucleoside modification or the biosynthesis of GMP and the generation of radical species by reductive cleavage of S-adenosylmethionine. The genes located near Type 3 pmoC s encode the degradation of polyhydroxybutyrate, an energy and carbon storage polymer [ 81 ], and the Na-translocating NADH-quinone reductase respiratory complex operon [ 82 ]. All Type 4 pmoC are located between two genes, one of which has a fumarate/nitrate reduction transcriptional regulator domain, and both contain helix-turn-helix domains. Thus, these genes likely have a role in either transcriptional regulation or DNA-binding processes [ 83 ], that in Escherichia coli have been linked to an oxygen-responsive transcriptional regulation to switch from aerobic to anaerobic metabolism [ 84 ]. The Type 5 pmoC clusters the rsbU gene, which has been shown to contribute to general stress sensing and response, as well as oxygen starvation [ 85 , 86 ], and a putative nucleoside deaminase, followed by the GCN5-Related (GNAT-family) N -Acetyltransferases, are known to contribute to a broad spectrum of cellular metabolic and regulatory functions [ 87 ]. Figure 5 (A) Maximum likelihood tree representing the phylogenetic relationship of Methylocaldum particulate methane monooxygenase, based on the amino acid sequences of the pmoC gene. Next to each branch, the projection has a color-coded representation of the predicted functions for the genes in the vicinity of each pmoC . Next to each clade, brackets indicate with a number the type of pmoC corresponding to each clade. Type 1 PmoC is part of the canonical pMMO, whereas Types 2 to 5 correspond to the different stand-alone PmoC. Predicted AlphaFold models were based on the prediction obtained from the CryoEM structure of Methylococcus capsulatus (bath) pMMO in a native lipid nanodisc at 2.16 Angstrom resolution (ID 7S4J). Predicted structures are color-coded according to the confidence percentage in the model accuracy. (B) Gene function prediction for genes in the vicinity of each of the five types of pmoC from Methylocaldum strains. The canonical pmoC from 0917 was recovered from a metatranscriptome. To further investigate the stand-alone pmoC function, the in-silico simulations of the predicted tertiary structure of Methylocaldum PmoC types were carried out. The analyses showed a differential tertiary structure for all stand-alone PmoC, whereas still preserving their transmembrane domains ( Supplementary Fig. S7 and Supplementary videos). Additionally, the search for the presence of the key amino acid residues forming the Cu D binding site, which recent structural studies had indicated as the methane oxidation catalytic center in PmoC [ 88 ] was conserved across all Methylocaldum PmoC types ( Supplementary Fig. S8 ). Types 2 and 3 PmoCs differ from Type 1 only slightly in structure, suggesting that these stand-alone PmoC likely perform similar membrane anchoring and/or metabolite binding functions. Individual differences in residues compared to Type 1 might reflect lessened evolutionary pressure for folding outside of catalytic regions when the structure is not restricted by a multi-protein complex. Type 4 differs in the structure of the N-terminal signal peptide, suggesting that these proteins differ in their subcellular localization compared to the other PmoC types. Type 5 PmoC contains an ~40 residue region that extends the largest cytoplasmic domain. This additional catalytic region might reflect additional substrate specificities, substrate preferences, or new binding sites. Additional experimental work will be needed to confirm functional differences between these pmoC types. Overall, the functional diversity of the genes in the immediate vicinity and the same orientation as the stand-alone pmoC , added to their differential tertiary structure, suggests that in Methylocaldum these paralogs are likely involved in other functions not related to CH 4 -oxidation ( Fig. 5B and Supplementary Material ). TRAP transporter system A tripartite ATP-independent Periplasmic (TRAP)-type periplasmic transport system [ 89 ] was found exclusively in the Anza-Borrego Methylocaldum isolates and not in other Methylocaldum isolates ( Fig. 4 ). TRAP transporters are one of the three known solute binding-protein-dependent systems which are characterized by their high-affinity for the uptake of substrates (the other two are the well-studied ATP-binding cassette and the more recently studied tripartite tricarboxylate transporters [ 90 ]). TRAP transporters do not require ATP hydrolysis and instead use transmembrane electrochemical gradients (usually sodium or other cations) to transport various molecules, including C4-dicarboxylates, sulfonate, and carboxyl-containing substrates [ 90 , 91 ]. The putative TRAP-type transport system in the Anza-Borrego Methylocaldum isolates was found to be encoded by three genes—a TRAP transporter component, a periplasmic component, and the fused version of the large and small permease component. The putative TRAP-type gene cluster in the Anza-Borrego Methylocaldum isolates resembles an evolved variant of the TRAP transporters from Treponema pallidum [ 90 , 92 ], which has been predicted to transport hydrophobic nutrients through the periplasm [ 93–95 ]. The involvement of this system in transporting substrates in response to reduced water availability has been suggested in a metaproteomic study reporting that the TRAP-type protein abundances produced by populations of Pseudomonadota (from the genus Acidithrix, Aureimonas, Niastella , and Pedobacter ) and Actinomycetota (from the genus Jiangella ) were higher in soils subjected to a regulated irrigation-deficit [ 96 ] . Considering that the methanotrophic bacteria have very limited ability to utilize extracellular organic carbon, the role of the TRAP transport mechanisms in Methylocaldum deserves a thorough investigation. Interaction among methanotrophic microbiome members \n Methylocaldum strains were co-isolated with Bradyrhizobium, and the challenges for their separation suggested some level of dependency for the methanotrophs. A genomic comparison revealed that Methylocaldum possesses only the genes necessary for salvaging cobalamin (vitamin B 12 ). In contrast, Bradyrhizobium has all the necessary genes for the de novo synthesis of the essential cofactor ( Fig. 6 ). Methylocaldum has two methionine synthesis pathways, dependent and independent of vitamin B 12 . However, considering that the association with Bradyrhizobium is advantageous for Methylocaldum growth (data not shown), we speculated that the B 12 exchange supports the symbiotic interactions between the species. It has been previously demonstrated that rhizobia can stimulate the growth of methanotrophs via excreted cobalamin [ 97 ]. Our finding provides genetic evidence for such dependencies. It should be mentioned that the B 12 exchange is perhaps the most common interaction between microbes in complex soil or aquatic communities. Several carbon and nitrogen catabolism pathways can also rely on cobalamin [ 98 ], and metagenomic studies indicate that only <10% of soil prokaryotes encode the genetic potential for de novo synthesis [ 99 ]. Figure 6 Genomic potential for cobalamin (vitamin B 12 ) de novo synthesis and salvaging by Anza-Borrego isolates of Bradyrhizobium and Methylocaldum, respectively. The required genes for de novo cobalamin synthesis are present in the Bradyrhizobium genome. The absence of the initial required genes for de novo synthesis and the presence of two paralogs of the cobalamin outer membrane cobalamin receptor and transporter gene, btu B, indicates that Methylocaldum relies on a salvaging pathway of cobalamin. Both rhizobia and methanotrophs have been shown as key microbial partners for N 2 fixation in non-leguminous plants [ 100 ]. Even though expected for Bradyrhizobium , additionally, all Anza-Borrego Methylocaldum strains have the genetic potential for dinitrogen (N 2 ) fixation, including nifH (K02588) and nifK (K02591), in addition to nifB (K02585), nifD (K02586), nifQ (K15790), nifU (K04488), and nifZ (K02597) ( Supplementary Fig. S9 ). Therefore, Methylocaldum has the enzymatic inventory to fix nitrogen, providing an advantage for both bacteria and its host plant in the low-nutrient desert environment. Searches for metabolisms favoring the interaction of the Methylocaldum-Bradyrhizobium consortia with plants pointed to the different pathways for tryptophan synthesis and its subsequent metabolization to indole-3-acetic acid (IAA) production as relevant. Methylocaldum and Bradyrhizobium both have the necessary genomic potential for tryptophan synthesis ( Fig. 7 ). IAA is an important auxin in plants, which acts as a phytohormone regulating plant growth and also mediates bacterial physiology [ 101 ]. Methylocaldum and Bradyrhizobium have the complete gene set necessary for IAA production via tryptamine and indole-3-acetaldehyde. Moreover, Bradyrhizobium can also potentially produce IAA via indole-3-acetamide, whereas Methylocaldum could also produce it via indole pyruvate ( Fig. 7B ). Production of IAA had been found in a majority of plant-interacting bacteria and had been shown to confer benefits to the host plant, and also an advantage under environmental stress for bacteria [ 101 ]. Figure 7 Genomic potential for tryptophan and indole-3-acetic acid (IAA) synthesis in Anza-Borrego isolates of Bradyrhizobium and Methylocaldum. (A) Comparison of metabolic potential for the synthesis of IAA by Anza-Borrego isolates. (B) The major difference in their tryptophan synthesis pathway relies on the gene encoding the initial step enzymes; Bradyrhizobium has the fused version of the anthranilate synthase TrpEG, and Methylocaldum has its two components separately."
} | 8,897 |
27376307 | PMC4962014 | pmc | 3,282 | {
"abstract": "Astaxanthin, a red C40 carotenoid, is one of the most abundant marine carotenoids. It is currently used as a food and feed additive in a hundred-ton scale and is furthermore an attractive component for pharmaceutical and cosmetic applications with antioxidant activities. Corynebacterium glutamicum , which naturally synthesizes the yellow C50 carotenoid decaprenoxanthin, is an industrially relevant microorganism used in the million-ton amino acid production. In this work, engineering of a genome-reduced C. glutamicum with optimized precursor supply for astaxanthin production is described. This involved expression of heterologous genes encoding for lycopene cyclase CrtY, β-carotene ketolase CrtW, and hydroxylase CrtZ. For balanced expression of crtW and crtZ their translation initiation rates were varied in a systematic approach using different ribosome binding sites, spacing, and translational start codons. Furthermore, β-carotene ketolases and hydroxylases from different marine bacteria were tested with regard to efficient astaxanthin production in C. glutamicum . In shaking flasks, the C. glutamicum strains developed here overproduced astaxanthin with volumetric productivities up to 0.4 mg·L −1 ·h −1 which are competitive with current algae-based production. Since C. glutamicum can grow to high cell densities of up to 100 g cell dry weight (CDW)·L −1 , the recombinant strains developed here are a starting point for astaxanthin production by C. glutamicum .",
"introduction": "1. Introduction Carotenoids are natural pigments with yellow-to-red coloring properties, found ubiquitously in plants, algae, fungi, and bacteria. These pigments form a subfamily of the large and diverse group of terpenoids with more than 55,000 different structures. Terpenoids are natural secondary metabolites composed of isoprene units, which typically exhibit flavoring, fragrance and coloring properties. Carotenoids and their derivatives have become more and more important for the health care industry due to their beneficial effects on human and animal health and their possible pharmaceutical, medical, and nutraceutical applications. For example, carotenoids are suggested to have beneficial effects on the human immune system and to protect against degenerative diseases and cancer [ 1 , 2 , 3 ]. Astaxanthin is a marine, red, cyclic C40 carotenoid and the third most important carotenoid on the global market after β-carotene and lutein, with a predicted sales volume of 670 metric tons valued at 1.1 billion US$ in 2020 [ 4 ]. Currently, astaxanthin is primarily used as a food and beverage colorant, in animal feed and in nutraceuticals [ 5 ] with e.g., an annual demand of 130 tons for coloration of poultry, salmon, lobster and fish [ 6 ]. Astaxanthin shows the strongest hitherto demonstrated anti-oxidant effect due to its keto and hydroxy groups at 4,4'- and 3,3'-beta-ionone ring positions, respectively. Those functional groups result in a more polar nature of astaxanthin and explain its unique antioxidative properties [ 7 ]. Furthermore, astaxanthin can be esterified which leads to increased stability [ 8 ]. Therefore, the demand for astaxanthin is particularly rising in the health sector [ 5 ]. Astaxanthin has been described to promote skin health and to have potential anti-aging effect [ 9 ]. Moreover, it alleviates the fatigue, inflammation, and aging of the eye [ 10 , 11 , 12 ]. Astaxanthin has a positive effect on blood rheology and potential antihypertensive properties, which makes it interesting for therapy of cardiovascular diseases [ 13 , 14 ]. Its wide potential for the reduction of inflammation also promotes the immune system functions [ 15 ]. In addition, astaxanthin was reported to have a positive impact on muscle recovery when used as a nutritional supplement [ 16 ]. Although the chemical synthesis of astaxanthin from petrochemical precursors is so far more cost-efficient and therefore dominates the market [ 17 ], consumer demand for naturally produced carotenoids is increasing [ 18 ]. Synthetic astaxanthin is often a mixture of R - and S -enantiomers and, thus, inferior to natural-based astaxanthin [ 19 ] and not suitable as a neutraceutical supplement without further complex and cost-intensive purification steps before application. Consequently, the demand for an efficient, environmentally friendly production of natural astaxanthin, and carotenoids in general, by microbial hosts is on the rise [ 20 , 21 , 22 ]. C. glutamicum is a Gram-positive soil bacterium with a long biotechnological history: its relevance goes back to the 1950s when it was first discovered as a natural glutamate producer [ 23 ]. Over centuries it has been used for the million-ton scale production of different amino acids for the feed and food industry. Moreover, its potential for biotechnological application has been further exploited [ 24 ]: besides amino acids, e.g., diamines [ 25 ], alcohols [ 26 ], and terpenoids [ 27 , 28 ] can be produced by engineered C. glutamicum . This bacterium has the ability to grow aerobically on a variety of carbon sources like glucose, fructose, sucrose, mannitol, propionate, and acetate [ 29 , 30 ]. In addition, it has been engineered to grow with alternative carbon sources such as glycerol [ 31 ], pentoses [ 32 ], amino sugars [ 33 , 34 ], β-glucans [ 35 ], and starch [ 36 ]. C . glutamicum is pigmented due to synthesis of the C50 carotenoid decaprenoxanthin and its glucosides. Its potential to produce carotenoids has been explored over recent years [ 28 , 37 , 38 , 39 ]. The carotenogenic pathway of C . glutamicum was identified [ 40 ] and several metabolic engineering strategies were applied to convert this biotechnologically established bacterium into a carotenoid producer [ 41 , 42 ]. In order to enable C40 carotenoid production by C. glutamicum , the conversion of lycopene to decaprenoxanthin needs to be prevented by deletion of the genes encoding lycopene elongase and ε-cyclase. As consequence of deletion of the lycopene elongase encoding gene crtEb , the cells exhibited a slight red color due to accumulation of the intermediate lycopene [ 37 ]. Additional overexpression of the endogenous genes crtE , crtB , and crtI in C. glutamicum Δ crtEb intensified the red phenotype as conversion of GGPP to the red chromophore lycopene was improved. Thereby, the lycopene content could be increased 80 fold with 2.4 ± 0.3 mg·(g·CDW) −1 and showed for the first time enhanced C40 carotenoid production in C. glutamicum [ 37 ]. Heterologous expression of crtY from Pantoea ananatis ( crtY Pa ) in a lycopene accumulating platform strain led to the production of the orange pigment β-carotene. Zeaxanthin was accumulated when crtZ from P. ananatis ( crtZ Pa ) was expressed in addition [ 38 ]. Furthermore, carotenoid biosynthesis was improved by enhancing the precursor supply, which was accomplished by overexpression of the dxs gene encoding the enzyme for the initial condensation of pyruvate and GAP in the MEP-pathway [ 42 ]. In this study production of the marine carotenoid astaxanthin by C. glutamicum was developed using a β-carotene producing strain ( Figure 1 ). Two strategies were followed: (i) the implementation of a combinatorial gene assembly for crtW Ba and crtZ Pa to optimize the ratio of enzyme quantities (ketolase and hydroxylase) by variation of translation initiation rates (TIR) based on different ribosome binding sites, spacing lengths, and translation start codons and (ii) the use of alternative crtW and crtZ genes from marine and non-marine prokaryotes in a two-vector system in order to find enzymes with higher activities or affinities for the intermediates of the astaxanthin biosynthesis pathway ( Figure 1 ). Combined expression of crtW and crtZ from the marine bacterium Fulvimarina pelagi yielded a C. glutamicum strain producing astaxanthin as the major carotenoid in shaking flasks with productivities of up to 0.35 mg·L −1 ·h −1 .",
"discussion": "3. Discussion In this study, Corynebacterium glutamicum was engineered for the production of the marine carotenoid astaxanthin. C. glutamicum grows fast to high cell densities [ 54 ] and, thus, is suitable for production of carotenoids and other compounds that are stored within the cell. Here, C. glutamicum was shown to produce β-carotene to about 12 mg·(g·CDW) −1 within 24 h at a volumetric productivity of about 3.4 mg·L −1 ·h −1 . Growth and production of carotenoids by C. glutamicum is monophasic and strains BETA4 and ASTA1 showed growth rates of 0.32 ± 0.01 h −1 and 0.29 ± 0.05 h −1 , respectively. This is in contrast to biphasic growth/production of carotenoids e.g., by the alga Haematococcus pluvialis [ 55 ]. As a consequence, the volumetric productivity for β-carotene exceeds that reported for the industrially used microalga Dunaliella bardawil [ 56 ] or the yeast Saccharomyces cerevisiae [ 57 ] by about a factor of three. Combined expression of the genes coding for β-carotene ketolase and hydroxylase from microorganisms that do not synthesize astaxanthin ( B. aurantiaca and P. ananatis ) in a β-carotene producing C. glutamicum led to astaxanthin production. However, astaxanthin was not the main carotenoid being produced. Since a balanced expression of the β-carotene ketolase and hydroxylase genes are essential for an efficient astaxanthin production [ 48 , 58 ] we assumed that the activities of the respective enzymes in the tested recombinants were not matched. Therefore, translation initiation rates of the respective genes, crtW and crtZ , were varied in a combinatorial approach. However, a strict correlation between TIR and production titers was not observed. As tendencies, the lower the TIRs of both crtW and crtZ the lower were the canthaxanthin and astaxanthin titers, and the higher the TIR of crtW the higher were astaxanthin titers ( Figure 4 ). In E. coli astaxanthin biosynthesis from β-carotene was reported to proceed more efficiently via zeaxanthin rather than canthaxanthin since ketolated intermediates did not accumulate [ 48 , 58 ]. Both ketolase and hydroxylase compete for their substrates and accept β-carotene as well as canthaxanthin and zeaxanthin, respectively, as substrates [ 59 , 60 ]. Independently induced expression of crtZ from P. ananatis and crtW148 of Nostoc puntiforme PC73102 revealed that hydroxylation occurred fast with β-carotene, echinenone, adonirubin, and canthaxanthin [ 58 ]. In their system, CrtW148 was identified as the limiting step in conversion of zeaxanthin to astaxanthin [ 58 ]. Expression of crtZ from P. ananatis in β-carotene producing C. glutamicum also yielded zeaxanthin [ 38 ] as did expression of crtZ from F. pelagi in this study (data not shown). Varying expression levels of crtW Ba and crtZ Pa led to accumulation of zeaxanthin only if TIR for crtW Ba was low ( Figure 4 ). On the other hand, canthaxanthin accumulated as intermediate typically if TIR of crtW Ba was medium to high ( Figure 4 ). Canthaxanthin accumulation may be explained best by the assumption that β-carotene ketolase CrtW from B. aurantiaca did not accept the non-natural substrate zeaxanthin well. It is likely that astaxanthin production by this approach was not only limited by an imperfect match between expression levels of the β-carotene ketolase and hydroxylase genes, but rather by imperfect compatibility of the substrate spectra of the chosen β-carotene ketolase and hydroxylase enzymes. Consequently, crtW and crtZ genes from marine and non-marine bacteria known to synthesize astaxanthin were examined in the second approach. Astaxanthin was produced in combinations of CrtZ from the marine bacterium F. pelagi and CrtW from either F. pelagi , S. astaxanthinifaciens or B. aurantiaca . F. pelagi was isolated from ocean surface water, an aerated environment at least transiently exposed to high solar radiation [ 45 ]. It is hypothesized that carotenoids play an important role as antioxidants for survival of F. pelagi under these conditions [ 50 ]. Analysis of the codon usage of crtW and crtZ from F. pelagi revealed a good fit to the codon usage of C. glutamicum , which is in compliance with the achieved astaxanthin titers of the recombinants. Co-expression of crtW from B. aurantiaca and crtZ from F. pelagi led to comparable astaxanthin titers, but considerable β-carotene amounts accumulated as side-product ( Table 3 ), co-expression of crtW and crtZ from F. pelagi , instead, yielded astaxanthin as major carotenoid (80%; Table 3 ). As compared to β-carotene production of about 12 mg·(g·CDW) −1 by the parent strain BETA4, the astaxanthin titers were at least seven fold lower ( Table 3 ). Thus, conversion of β-carotene to astaxanthin is incomplete; however, other carotenoids besides canthaxanthin and residual β-carotene did not accumulate to significant titers (data not shown and Table 3 ). The partial conversion of β-carotene to astaxanthin may, thus, indicate that astaxanthin and/or intermediate(s) of its biosynthesis are inhibitory. This is in line with our finding that overexpression of only crtW from F. pelagi resulted in 0.5 mg·(g·CDW) −1 canthaxanthin and 1.7 mg·(g·CDW) −1 remaining β-carotene. Similarly, overexpression of only crtZ yielded 1.1 mg·(g·CDW) −1 zeaxanthin and 5.6 mg·(g·CDW) −1 β-carotene remained. Similarly, heterologous expression of crtW148 and crtZ in the β-carotene-producing E. coli strain reduced the overall formation of carotenoids, indicating that the formation of the carotenoid precursors were affected [ 58 ]. High product purities and titers are beneficial for downstream processing. The astaxanthin producing C. glutamicum strain overexpressing crtW and crtZ from F. pelagi accumulated astaxanthin (about 1.6 mg·(g·CDW) −1 ) as major (about 80%) carotenoid. The fact that little β-carotene and canthaxanthin accumulated (about 0.3 and 0.1 mg·(g·CDW) −1 , respectively) may be an important advantage for downstream processing. Nevertheless, higher product purities can be obtained by algae with 95% of total carotenoids being astaxanthin [ 58 ]. Purification of astaxanthin from the cell walls of algae and red yeasts is challenging since algae like H. pluvialis accumulate astaxanthin in response to stress and heavily walled cysts are formed in the red stage [ 55 ]. Extraction of carotenoids from microalgae does not only require the removal of chlorophyll [ 61 ], but also efficient cell breakage technology [ 55 ]. Ethoxyquin or other antioxidants are added to the cells in order to minimize oxidation of the carotenoids during drying and cracking [ 58 ]. Because of laborious and time-consuming extraction processes of astaxanthin from algal systems, its production by a prokaryotic host, Escherichia coli , has emerged for substitution [ 62 ]. It has to be noted that H. pluvialis produces esterified astaxanthin, which is more stable than the free form astaxanthin as it does not cross react with proteins and e.g., lipoproteins [ 8 ], and which is incorporated easier by marine animals [ 63 ]. But hydrolysis of the ester narrows the bioavailability of astaxanthin e.g., to salmon [ 64 ]. The rigid cell walls of the red yeast X. dendrorhous also requires cell breakage prior to astaxanthin extraction [ 65 , 66 ]. In contrast to that, a simple methanol-acetone extraction was sufficient to recover astaxanthin from C. glutamicum cells at lab scale. The volumetric productivities of up to about 0.4 mg·L −1 ·h −1 obtained in simple shaking flask cultures by the recombinant C. glutamicum strains compare favorably with those reported for the commercially used production hosts such as the green microalgae H. pluvialis [ 55 , 67 ] and the red yeast Xanthophyllomyces dendrorhous (formerly Pfaffia rhodozyma ) [ 6 , 68 ] under similar conditions as well as recombinant E. coli [ 58 ]. Under optimal conditions, astaxanthin titers obtained e.g., with H. pluvialis are very high (up to about 40 mg·(g·CDW) −1 ), but slow growth, biphasic growth (green stage) and production (red stage) properties and the low final biomass concentrations reduce the maximal volumetric productivity [ 55 ]. After the non-productive green phase (about 4 days), the volumetric productivity for astaxanthin in the red stage is about 1 mg·L −1 ·h −1 and can be maintained for extended periods [ 55 ]. Although astaxanthin product titers from red yeasts such as X. dendrorhous are generally lower than from algae [ 69 ], higher growth rates and easier cultivation conditions argue in favor of these yeasts [ 70 ]. After optimization of a glucose-based fed-batch process a volumetric productivity of about 5 mg·L −1 ·h −1 was achieved [ 65 , 71 ]. Can it be envisioned that comparably high volumetric productivities can be obtained using the recombinant C. glutamicum strains described here? In pressurized high-cell-density fed-batch cultivations C. glutamicum grows to biomass concentrations of about 220 g·CDW·L −1 within 24 h [ 54 ]. If this growth could be achieved with the C. glutamicum strains accumulating astaxanthin to titers of about 1.6 mg·(g·CDW) −1 , theoretically volumetric productivities of about 14 mg·L −1 ·h −1 may be achieved. Future work focused on process intensification, however, needs to be performed in order to evaluate if scale-up to such high astaxanthin volumetric productivities can be realized with C. glutamicum ."
} | 4,386 |
35158314 | null | s2 | 3,283 | {
"abstract": "Microbes can convert inexpensive renewable substrates to valuable metabolites by their natural metabolic pathways. To maximize the productivity, the pathways yet require further optimization, which remains challenging for our limited knowledge of complex biology. Genetically encoded biosensors are able to detect metabolite concentrations or environmental changes and transfer these inputs to measurable or actionable outputs, thus providing enabling regulation and monitoring tools for complicated pathway optimization. Here, we review recent advances in biosensor-mediated dynamic regulation and strain screening for the highest microbial production of diverse desirable products."
} | 170 |
19178139 | null | s2 | 3,284 | {
"abstract": "The topology of metabolic networks can provide insight not only into the metabolic processes that occur within each species, but also into interactions between different species. Here, we introduce a novel pair-wise, topology-based measure of biosynthetic support, reflecting the extent to which the nutritional requirements of one species could be satisfied by the biosynthetic capacity of another. To evaluate the biosynthetic support for a given pair of species, we use a graph-based algorithm to identify the set of exogenously acquired compounds in the metabolic network of the first species, and calculate the fraction of this set that occurs in the metabolic network of the second species. Reconstructing the metabolic network of 569 bacterial species and several eukaryotes, and calculating the biosynthetic support score for all bacterial-eukaryotic pairs, we show that this measure indeed reflects host-parasite interactions and facilitates a successful prediction of such interactions on a large-scale. Integrating this method with phylogenetic analysis and calculating the biosynthetic support of ancestral species in the Firmicutes division (as well as other bacterial divisions) further reveals a large-scale evolutionary trend of biosynthetic capacity loss in parasites. The inference of ecological features from genomic-based data presented here lays the foundations for an exciting \"reverse ecology\" framework for studying the complex web of interactions characterizing various ecosystems."
} | 376 |
27607553 | null | s2 | 3,286 | {
"abstract": "The ancient phylum Actinobacteria is composed of phylogenetically and physiologically diverse bacteria that help Earth's ecosystems function. As free-living organisms and symbionts of herbivorous animals, Actinobacteria contribute to the global carbon cycle through the breakdown of plant biomass. In addition, they mediate community dynamics as producers of small molecules with diverse biological activities. Together, the evolution of high cellulolytic ability and diverse chemistry, shaped by their ecological roles in nature, make Actinobacteria a promising group for the bioenergy industry. Specifically, their enzymes can contribute to industrial-scale breakdown of cellulosic plant biomass into simple sugars that can then be converted into biofuels. Furthermore, harnessing their ability to biosynthesize a range of small molecules has potential for the production of specialty biofuels."
} | 224 |
32900963 | PMC7519342 | pmc | 3,287 | {
"abstract": "Significance Although various creatures possess different structural gradients to gather water from fog, such as spider silk and cactus cluster, their gradient surfaces can only drive the motion of harvested water droplets over only a limited drop-sized distance and afford a slow speed, limiting the practical usage. The peristome of the pitcher plant presented here is a superior fog harvestor that capitalizes on the combined effects of ratchet, concavity, and arch structures to collect water from humid air and transport condensate water directionally along the curved peristome at a recording speed. Biomimetic approaches apply this multiscaled curvatures design to the construction of water fog and organic vapor harvestor, making it a versatile solution for a broad range of applications.",
"conclusion": "Conclusion In summary, in view of the environmental importance of water collecting and oil fogs harvesting, we have demonstrated the water-harvest mechanism of the peristome of the Nepenthes plant and harnessed multicurvatures-based biomimetic structures to harvest water and oil fogs. In this work, we have introduced several key elements including: 1) The unique water collection system is composed of ratchet teeth, concavities, and arch channels on the peristome surface; each contains integrated curvatures that play different roles in the fog harvesting and transport process. 2) The surface-gradient–induced Laplace pressure at the ratchet and concavity endows the peristome with an efficient water condensation and transportation system. 3) The formation of the condensate water layer on the surface can enhance the subsequent water harvesting with a recording speed. Investigations of the structure–function relationship in this system may help us in designing novel materials and devices for collecting water from fog and in transporting condensate water with high efficiencies. We envision the multicurvature design could be customized to the shape of the specific collection devices by the 3D printing process to provide the required harvesting efficiency during the individual usage.",
"discussion": "Discussion Fog Harvesting and Transport Processes along Peristome Surface. Environmental scanning electron microscopy (ESEM), high-speed cameras, and X-ray imaging techniques are used to investigate the water condensation–transport phenomena ( Fig. 2 ). The time-sequence images shown in Fig. 2 are divided into three magnifications that focus on the action of the ratchet teeth ( Fig. 2 A ), concavities ( Fig. 2 B ), and arch channels ( Fig. 2 F ). ESEM is used to monitor the water condensation state on the ratchet teeth ( Fig. 2 A ). When the peristome is exposed to water fog, water condenses on the teeth. The cone structure ( 14 ) can facilitate condensate water transport away from that location to refresh the interface. The condensate water drops 1 and 2 merge into 1 + 2 and grow in size ( 32 ) and climb the dry structures at a speed of 1.36 × 10 −1 mm s −1 . Continuous condensate water can wet the cone structure. Comparing with dry structures, the wet structures can wick the merged water drop 3 from the cone to the teeth base at a faster speed of 2.25 mm s −1 . The wet cone structure can accelerate the transport speed at 16.5 times. Besides water condensation, the ratchet teeth capture all available water droplets, such as raindrops ( SI Appendix , Fig. S1 ). Fig. 2. Water condensation and transport processes on natural peristome. ( A ) Water droplets are first condensed on the dry ratchet teeth and collected together to form larger droplets. After water droplets merge or climb up, the ratchet teeth surface becomes wet. Droplets at the dry–wet boundary slide into the wet region quickly. The tip is refreshed, with the water being transported upward. ( B ) Droplets climb the ratchet teeth and merge into a larger drop at the concavity. The pump of water from state I to state II and back to state III forces water to climb upward successively. The red arrows indicate the transport direction of the water droplets and the blue dotted line marks the wet–dry dividend line. ( C ) Schematic image of the pump mechanism. Laplace pressure forces condensate water to flow upward. ( D ) Plots of the water meniscus distance ( x ) from the concavity tip measured in B as a function of time ( t ). Water gathered in the concavity reduces as the dry peristome becomes wet. ( E ) The experimental setup for the X-ray observation. The stage rotation facilitates the observation from orthogonal views. A high-sensitivity balance system records the water-gathering weight during the condensation process. ( F ) The transport of water condensation eventually results in the development of a thin water film that covers the arch-shaped peristome surface. To help locate the positions of the dry–wet boundary line, the red arrows and white dashed lines indicate the parts of the surface that are eventually filled with water. ( G ) Individual condensate droplet weight with corresponding transport speed as a function of the condensation surface particular length on the dry and wet peristome surfaces. Condensate water transport on the wet peristome surface has a 300 times higher speed than that of water transport on the dry surface. High-speed camera records the water transport dynamics. When the dry peristome surface is just placed in fog at a relative humidity of 95%, condensate droplets on the neighboring ratchet teeth generally do not coalesce with each other but simply move individually to the base, as the liquid front indicated by the arrows in Fig. 2 B . As the condensate droplets grows in size, the neighboring droplets then combine into a large droplet at the concavity. A capillary bridge connects either side of the cone structures. The meniscus grows as the deposition proceeds, from state I to state II in Fig. 2 B , introducing a more significant pressure gradient across the wetting pattern ( 33 , 34 ). Considering water menisci pins at a distance of x from the center with the menisci radius, r m , in the cross-sectioning ( Fig. 2 C and SI Appendix , Fig. S2 ), the Laplace pressure is regarded as Eq. 1: Δ P = γ ( 1 r m − cos θ α x ) , [1] where γ is the water surface tension, θ is the water contact angle, and α is the opening angle of the concavity, respectively. As the wetting states change from II to III, the expulsive force induced by the capillary effect can cause the gathered water to flow upward in a pulsed fashion. A new cycle with transitions from III to V “pumps” the water along the peristome surface repeatedly. The variation of x decreases as water covers the whole peristome surface, indicating a low pump force is needed to overcome the resistance ( Fig. 2 D ). In addition, the maximum water-climbing height, H max , supported by the concavity can be regarded as Eq. 2: H max = l c 2 ( 1 r m − cos θ α x ) , [2] where l c is the capillary length and equals ( γ / ρg ) 1/2 . H max is ∼60 mm. Considering the radius of the peristome is only 2.3 mm, the H max is enough for water to cover the whole peristome surface ( 13 , 20 , 25 ). The covering water film can steadily remain on the peristome without leakage ( Movie S2 ). The whole water-harvesting process over a long duration is recorded by X-ray imaging and high-sensitivity balance system. Fig. 2 E provides in-line projection images of the system. The rotation of the sample stage enables the system to record the process from the front- and cross-sectioning views, respectively. The weight change of 5.0 × 10 −2 g, recorded by the balance, requires 10 s in a dry state, whereas it requires only 2 s when the peristome is wet ( Fig. 2 F ). As the water film forms on the peristome after condensation, the subsequent droplets can wick along the wet surface from one side to the other with a lower resistance. The correlation between the timescale and the length scale of the water film on the peristome surface is shown in SI Appendix , Fig. S3 . The transport velocity, v , can be deduced from Stokes equation ( 35 ) as Eq. 3 : v ∝ e 2 γ μ l ( 1 r m − cos θ α x ) , [3] where e is the liquid film thickness, μ is the liquid dynamic viscosity, and l is the length of the peristome from the outer side to the inner side. According to Eq. 3 , water transport on the dry peristome surface with a contact angle of 30° scales as 0.4–0.7 mm s −1 which is in accordance with the experimental results ( Fig. 2 B and G ). The r m and x of gathered water in the concavity reduces as the dry peristome becomes wet, as the data shown in Fig. 2 D and the red curve shown in Fig. 2 F . A much higher water transport velocity, several millimeters per second in calculation, is thus achieved on the wet peristome surface. We statistically analyze the spreading speed, transport length, and condensation weight of 100 condensate droplets at 10 positions around the whole circle of the peristome and find the maximum spreading speeds, ranging from several millimeters per second on the wet ratchet teeth and concavities to hundreds of millimeters per second on wetted arch channels, as revealed by the blue distributions in Fig. 2 G , respectively. Significantly, the average transport speed for the whole process increases by 300 times as the peristome surface switches from the dry state to the wet state, as the red arrow indicates in Fig. 2 G . Typically, water achieves an ultrafast motion speed of centimeters per seconds when drop rolls on a super–water-repellent surface or superhydrophobic surface ( 36 ), particularly because the entrapped air layer inside superhydrophobic structures can reduce the liquid solid friction. Comparing with such a fast speed without hysteresis, the condensate water can transport on the superhydrophilic peristome surface at a similar or even higher speed. The synergistic effect among ratchet, concavity, and arch structures works together to accelerate the water transport speed and achieve efficiently transporting water. The fog-harvesting ability of the peristome facilitates the formation of water on the surface to slippery interface after the drying ( SI Appendix , Fig. S4 ). Pitcher plants harness this synergistic effect to effectively construct slippery surface and survive in the harsh environment. Inspired by this water-harvest strategy, we can innovate the construction of water and organic vapor harvestor and expand the scope of application. Artificial Multicurvature Water Harvestor. After understanding the water harvesting and transport mechanism on the natural peristome, we use a three-dimensional (3D) printing method ( 25 , 26 ) to construct an artificial peristome harvestor and use PVA as the replica. The surface morphology of the artificial multicurvature water harvestor is shown in SI Appendix , Fig. S5 . As Fig. 3 A reveals, the artificial peristome with a single arch channel is coated onto a cup with the cone structures facing downward. The water fog is set at an upward velocity of 1.0 g s −1 . The rising fog deposited onto the ratchet teeth overflows the arch-shaped channel and is transferred to the container at the other end. It takes 100 s to turn the artificial peristome surface from the dry state to the wet state ( Fig. 3 B ). In the dry state, the average water collection speed per arch is 3.5 × 10 −3 g cm −2 ⋅s −1 , and the water transport speed is 4.6 mm s −1 . After 100 s, the collected water that covers the curved surface acts as communicating vessels that connect the collecting point and the gathering point ( SI Appendix , Fig. S6 ). The water channel speeds up the water-harvesting efficiency, where a water amount of 5.4 × 10 −1 g is gathered through a wet channel during the same period of 20 s ( Fig. 3 B ). There is an average water collection of 6.8 × 10 −2 g cm −2 ⋅s −1 , almost 20 times faster than that on the dry surface. The condensate water can slide on the water-covered surface in a high speed. The maximum water transport speed on the wet surface reaches 1.2 × 10 3 mm s −1 which is about 260 times larger than that on the dry surface. Fig. 3. Artificial peristome water harvestor. ( A ) Schematic diagram of the artificial peristome harvestor. ( B ) Time-sequence images of the water condensation and transport process on the artificial peristome harvestor. ( C ) The mechanism for enhancing water transport speed. The water droplet with a diameter d 1 condensate at the cone side transports along the wet surface to the container side. The energy release induced by the surface energy of the droplets converts to the kinetic energy for water to overflow the arch. ( D ) Water-harvest weight ( w ) versus time ( t ) for the water fog collected on the artificial peristome harvestor. ( E ) The water-harvest weight ( w ) versus time ( t ) during the initial water condensation state. To demonstrate the role of multiscaled curvatures, peristome-mimetic half-tubes without ratchet teeth and smooth half-tubes are fabricated for comparison. As SI Appendix , Fig. S7 reveals, water drips down from the bare half-tube at ∼3.6 s and drips down from the peristome tube without ratchet teeth or concavity with a harvest volume of 1.9 × 10 −1 g at ∼4.7 s. No water drips from the peristome tube with ratchet teeth. In addition, if condensate water cannot form on the surface on time, a delay in water transport occurs at the precursor side on the dry surface ( 19 ), which slows the condensate efficiency and forces condensate water to drip down. For the peristome tube with ratchet, a water-harvest volume of 2.3 × 10 −1 g is achieved within the shortest time of 3.6 s (1.6 × 10 −1 g cm −2 ⋅s −1 ). As a result, introducing the conical ratchet or concavity structures at the bottom edge of the peristome tube, we can increase both the water-harvesting amount and the water-harvesting speed. The artificial peristome harvestor with an opening angle of 45° for the concavity, a radius of curvature of 1.5 cm for the arch channel, and a bending angle of 180° for the channel shows the best water-harvest ability ( SI Appendix , Figs. S8–S10 ). The synergistic effect of feature structures, ratchet teeth, concavities, and peristome structures plays a vital role in water harvesting. Although the wind can influence the harvest efficiency ( SI Appendix , Figs. S11–S13 ), the peristome surface is a unique surface model that integrates several advantages to achieve high efficiency. The acceleration of water transport speed is not only induced by the Laplace pressure imbalance ( 37 ) at the concavity but accelerated by the energy release, ∆ E , of the droplets at the cone side ( Fig. 3 C ). Comparing with the water motion process driven by the Laplace pressure at the concavity, the water velocity achieved by the release of surface tension of condensate droplet is 10 times higher. As Fig. 3 C reveals, the release of surface energy at the cone side, ∆ E ∼ γd 1 2 , converts into the kinetic energy of the liquid. Considering the drop size of d 2 is much larger than d 1 , the transport velocity, v , of the condensate water can be deduced as Eq. 4: v ∝ 3 γ ρ d 1 . [4] Droplets with an average diameter d 1 of 20 μm can trigger the condensate water to move from the inner side to the outer side with a typical velocity of ∼1.0 m s −1 . The harvest speed for the water fog increases as the artificial fog harvestor turns into the wet state ( Fig. 3 D ). The harvest area will increase if we pattern the single arch channel into an array. Therefore, we can further accelerate the liquid harvest amount. Multifunctional Liquid Harvestor. Natural pitcher plants can gather water fog from a pitcher tank with a circular shape ( 13 , 22 ). The multicurvatures facilitate water condensation and transport from the inner side to the outer side to form a stable slippery surface ( Fig. 4 A ). For practical usage, we reverse the collar direction, with the ratchet teeth facing downward on the outer side, where liquid fog can be transported from the outer side to the inner side to fill the tank ( Fig. 4 B ). The biomimetic system would benefit water collection in a cooling tower and the collection of oil or organic fog ( 37 – 41 ) in a chemical plant, laboratory, or kitchen. In the proof-of-concept experiment, digital light procession 3D printing was used to construct peristome-mimetic substrate with invert structures. The PVA hydrogel and the PDMS oleogel replica are fabricated for the artificial water harvestor and oil harvestor by replicating the surface morphology of 3D printed substrate. Fig. 4. Multifunctional liquid harvestor device. ( A ) The natural peristome has a corolla shape, with the ratchet teeth facing downward on the inner side. Condensate water can be transported from the inner to the outer side, forming a slippery surface. ( B ) Reversal of the corolla, with the ratchet teeth facing downward on the outer side, could benefit the transport of water condensation from the atmosphere into the inner tank. ( C – E ) Both water and oil fogs are gathered and stored in the artificial peristome harvestor. ( C ) The performance of an artificial hydrogel harvestor when gathering water fog at a flow volume rate of 200 mL h −1 . ( D ) The long-term usage of artificial water harvestor and artificial oleogel harvestor. The water-harvestor gathers can collect water fog at high temperatures. ( E ) The artificial oleogel harvestor gathers the isopropanol, kerosene, gasoline, and glycol fogs. ( F ) Transport and harvest velocity of liquid condensation on different artificial structures. See SI Appendix , Fig. S14 and Table S3 for details. Mounting the artificial peristome along the circle of glass cylinder achieves the fog harvestor. The harvesting device is stored in a sealed glass box. A commercial Venturi atomizer is used to produce liquid fog. The fog flow is set at an upward velocity of 5.6 × 10 −2 g s −1 (200 mL h −1 ). Considering the perimeter of artificial peristome circling the glass cylinder is 90 mm, the artificial peristome harvestor can gather 40.1 mL water within 2 h at an average velocity of ∼6.1 × 10 −3 g cm −2 ⋅s −1 for water fog at room temperature ( Fig. 4 C ). In addition, the artificial water harvestor can collect water fog at high temperature ranging from 40 to 80 °C without reducing the harvesting efficiency ( Fig. 4 D ). Comparing with water-harvesting devices, the multifunctional PDMS oleogel harvestor can harvest organic vapor at a high speed ( Fig. 4 D and E ). The artificial liquid harvestor can harvest organic vapor at a rate of ∼4.2 × 10 −3 g cm −2 ⋅s −1 for isopropanol, ∼3.7 × 10 −3 g cm −2⋅ s −1 for kerosene, ∼3.4 × 10 −3 g cm −2⋅ s −1 for gasoline, and ∼2.5 × 10 −3 g cm −2⋅ s −1 for glycol ( Fig. 4 E , and see SI Appendix , Table S2 for physical and chemical properties of the liquids). These values were relatively consistent during the long-term experiments, ∼120 h ( Fig. 4 D ). Traditional fog harvestor can only collect water fog. Our proposed biomimetic approach is beneficial to the construction of water and organic vapor harvestor. Significantly, our method achieves the much higher harvesting speed and transport speed than artificial harvestor inspired by spider silk, spine, and slippery pitcher surfaces ( Fig. 4 F )."
} | 4,831 |
28939889 | PMC5610245 | pmc | 3,289 | {
"abstract": "Pretreatment of biomass with dilute acid requires high temperatures of >160 °C to remove xylan and does not remove lignin. Here we report that the addition of peracetic acid, a strong oxidant, to mild dilute acid pretreatment reduces the temperature requirement to only 120 °C. Pretreatment of yellow poplar with peracetic acid (300 mM, 2.3 wt%) and dilute sulfuric acid (100 mM, 1.0 wt%) at 120 °C for 5 min removed 85.7% of the xylan and 90.4% of the lignin leaving a solid consisting of 75.6% glucan, 6.0% xylan and 4.7% lignin. Low enzyme loadings of 5 FPU/g glucan and 10 p NPGU/g glucan converted this solid to glucose with an 84.0% yield. This amount of glucose was 2.5 times higher than with dilute acid-pretreated solid and 13.8 times higher than with untreated yellow poplar. Thus, the addition of peracetic acid, easily generated from acetic acid and hydrogen peroxide, dramatically increases the effectiveness of dilute acid pretreatment of biomass.",
"conclusion": "Conclusions A short (5 min) one-step pretreatment at 120 °C with 300 mM PAA and 100 mM H 2 SO 4 removed both xylan and lignin from yellow poplar biomass in contrast to dilute acid pretreatment, which removed mainly xylan under same conditions. Enzymatic hydrolysis of solid from this one-step pretreatment released ~80% of the glucose, which was 2.5 and 13.8 times higher than from solids from DA-pretreatment and raw YP, respectively. The difference between one-step and DA pretreatment was high lignin removal, which dramatically enhanced enzymatic hydrolysis at low enzyme loadings. In addition, one-step pretreatment decreased the formation of fermentation inhibitors. This novel one-step pretreatment under mild conditions is a promising method for more efficient in biofuel production.",
"introduction": "Introduction Lignocellulosic biomass is a sustainable, abundant and low-cost resource. Conversion of biomass to biofuels reduces the society’s dependence on petroleum-based fuels and reduces net greenhouse gas emissions 1 , 2 . Pretreatment of lignocellulosic biomass is key step in the conversion of biomass to biofuels. Lignocellulosic biomass is composed of cellulose, hemicellulose and lignin in an interwoven matrix. Conversion of biomass into biofuels requires enzymatic hydrolysis of cellulose to glucose followed by the microbial fermentation of this glucose to biofuels 3 . The complex structure of biomass makes it recalcitrant to enzymes making the hydrolysis of cellulose slow and inefficient. This recalcitrance is the major economic obstacle to conversion of biomass to sugar 4 . Pretreatment of biomass enhances the accessibility of cellulose to enzymes, thereby overcoming biomass recalcitrance 5 . Effective pretreatments should be energy efficient, not degrade the cellulose and yield a cellulose fraction that is easily hydrolyzed with low enzyme loadings 3 , 6 . The most effective pretreatments – dilute acid and organosolv – still require high temperatures of >150 °C. Dilute acid pretreatment at high temperatures (>160 °C) removes most of the hemicellulose with minimal degradation of cellulose and lignin 7 , 8 . The remaining lignin hinders access of the enzymes to cellulose both by blocking access and by adsorbing the enzymes 9 , 10 . Organosolv pretreatments using ethanol or THF remove both the hemicellulose and lignin 11 – 13 , but still require high temperature (>150 °C) and additional steps to recover the organic solvents. Lower temperature pretreatments are desirable because they reduce energy requirements and capital costs of equipment because the pressures generated during pretreatment are lower. In particular, autoclaves conveniently and inexpensively generate temperatures of 121 °C using steam, so pretreatments that work at or below this temperature are desirable. Peracetic acid is strong oxidant that effectively removes lignin from biomass 14 . Pretreatment with peracetic acid at 80 °C improved the cellulose digestibility of sugarcane bagasse 15 and pretreatment with hydrogen peroxide-acetic acid mixtures, which generate peracetic acid in situ , at 80 °C was also increased the enzymatic digestibility of rice straw, pine wood and oak wood as compared to dilute acid pretreatment 16 . Two-step pretreatment with alkali followed by peracetic acid increased the enzymatic digestibility and reduced the amount of peracetic acid needed 17 . Enhanced enzymatic digestibility of the solid after peracetic acid pretreatment is due to delignification and increased surface area of cellulose 13 . However, pretreatment with only peracetic acid removed mainly lignin leaving most of the hemicellulose. This remaining hemicellulose hindered cellulase access to the cellulose. Removal of both lignin and xylan allows efficient enzymatic hydrolysis of the cellulose 18 . Yellow poplar ( Liriodendron tulipifera ) grows quickly even in poor soil and sequesters higher amounts of carbon dioxide than other biomass crops due to its extensive root structure. The Korea Forest Service recommended yellow poplar as a biomass crop and it is a major planting species in Korea 19 . In this study, we increased the effectiveness of dilute acid pretreatment by adding peracetic acid. This single step procedure simultaneously removes both hemicellulose and lignin from yellow poplar biomass under comparably milder conditions. As compared to dilute acid under same conditions, this process reduces pretreatment time, pretreatment temperature and cellulase enzyme loading while providing high yields of glucose.",
"discussion": "Results and Discussion Optimization of one-step pretreatment The four major pretreatment variables are the concentrations of peracetic acid (PAA) and H 2 SO 4 , the temperature and the time of pretreatment. These variables were optimized stepwise for xylan and lignin removal by measuring the effect of one variable, while the other variables were fixed at the harsh condition. A PAA concentration of 300 mM gave the highest xylan and lignin removal with minimal loss of glucan. The ratio of PAA solution to water was varied from 1:9, 2:8 and 3:7 (v/v), which corresponded to 200, 300 and 400 mM PAA, respectively. Caution: PAA decomposes at high temperatures. Solutions with >600 mM PAA rapidly evolved gas over 100 °C so were not used. The other pretreatment conditions were 120 °C, 100 mM H 2 SO 4 and 2 h pretreatment time. As the concentration of PAA increased, the amount of lignin removed increased from 63.1% in 200 mM, 85.4% in 300 mM, to 96.2% in 400 mM, but the amount of xylan removed remained similar (84.1, 79.4, 85.2%, respectively) (Fig. 1a ). In the pretreatment, PAA reacted with the lignin 14 , while the acidic conditions were responsible for xylan hydrolysis. With increasing PAA concentration, the losses of glucan also increased to 17.0, 20.8 and 33.6%, respectively. The optimal PAA concentration was 300 mM because it gave a high xylan and lignin removal and acceptable loss of glucan. Figure 1 Optimization of one-step pretreatment. Increasing PAA concentration, pretreatment temperature and H 2 SO 4 concentration increased xylan and lignin removal. The pretreatment time of 5 min was sufficient for the removal of xylan and lignin. Composition analysis of pretreated solid with ( a ) different PAA concentrations at 120 °C with 100 mM H 2 SO 4 for 2 h, ( b ) different pretreatment temperatures with 300 mM PAA and 100 mM H 2 SO 4 for 2 h, ( c ) different H 2 SO 4 concentrations with 300 mM PAA at 120 °C for 2 h, ( d ) different pretreatment times with 300 mM PAA and 100 mM H 2 SO 4 at 120 °C. Error bars correspond to the standard deviation for three measurements. \n The optimal temperature for removal of xylan and lignin was 120 °C (Fig. 1b ). Pretreatment at 100 or 110 °C with 300 mM PAA for 2 h only partially removed xylan and lignin, but pretreatment at 120 °C effectively removed both. The higher acid concentration of 100 mM removed xylan more effectively, but had no effect on lignin removal (Fig. 1c ). High acid concentration (100 mM H 2 SO 4 ), removed more xylan (79.4%) than at the low acid concentrations (25 mM H 2 SO 4 : 60.7%, 50 mM H 2 SO 4 : 71.0%), indicating that H 2 SO 4 catalyzes xylan hydrolysis. When combined with PAA, more effective xylan removal leads to more effective lignin removal. PAA with added H 2 SO 4 removed lignin more effectively than PAA only 20 , but the amount of lignin removal did not correlate with increasing concentration of H 2 SO 4 at 120 °C. Therefore, optimal concentration of 100 mM H 2 SO 4 was selected to optimize the xylan hydrolysis. Surprisingly, pretreating for only 5 min was as effective as pretreating for 2 h (Fig. 1d ). Heating the sample to 120 °C and cooling required approximately 3 min, so it was not practical to reduce the pretreatment time below 5 min. Xylan and lignin removal were complete within 5 min and extending the pretreatment time had little further effect on xylan hydrolysis or delignification. Separate experiments revealed that the concentration of PAA decreased from 300 mM to ~30 mM after 5 min at the pretreatment conditions. Longer pretreatment times also had the disadvantage of removing some of the glucan due to acid hydrolysis. For example, ~12, ~15 and ~20% of glucan was lost after a 5, 30 and 120-min pretreatment (Fig. 1d ). The enzymatic digestibilities of the solids from different pretreatment times were similar (Fig. 2 ). At an enzyme loading of 5 FPU/g glucan and 72 h digestion, the glucose yield increased slightly with increasing pretreatment time (75.5, 76.2, 78.1 and 84.3%). Samples pretreated for 30 min yielded ~10% more glucose than those pretreated for only 5 min. At the higher enzyme loading of 30 FPU/g glucan, the glucose yield increased and the differences between the different pretreatment times decreased: 87.5, 86.1, 88.2 and 93.9%. These similar glucose yields from 5, 10 and 20 min pretreated solids suggests that the pretreatment removed similar amounts of xylan and lignin. The 10% higher glucose yield after 30 min pretreatment comes at the energy cost of longer pretreatment. We selected 5 min as the optimal pretreatment time, but others could choose a longer pretreatment to increase the glucose yield. Figure 2 Effect of pretreatment time on enzymatic digestibilities of pretreated solid. The solid pretreated for 5 min released slightly lower amounts of glucose than the solids pretreated for 10, 20 and 30 min. Yellow poplar was pretreated with 300 mM PAA and 100 mM H 2 SO 4 at 120 °C. Enzymatic hydrolysis was conducted using enzyme loadings of ( a ) 5 FPU/g glucan and ( b ) 30 FPU/g glucan. Both solutions contained 30 p NPGU/g glucan. Error bars correspond to the standard deviation for three measurements. \n Negligible amounts of sugar degradation products, furfural or HMF, formed under the selected pretreatment conditions. These degradation products, which can also inhibit subsequent fermentation, often form under hasher conditions 10 . Finally, optimal conditions were selected to minimize loss of glucan and formation of byproducts, and enhance xylan and lignin removal. Therefore, the optimal conditions for one-step pretreatment were 300 mM PAA (~2.3 wt%), 100 mM H 2 SO 4 (~1 wt%), 120 °C and 5 min. These optimal conditions are milder than those for the standard acid hydrolysis of biomass (4 wt% sulfuric acid at 120 °C for 1 h) 21 . Comparison with dilute acid pretreatment under same conditions The effectiveness of the one-step pretreatment was compared to the standard dilute acid pretreatment under the same conditions of 120 °C for 5 min. Chemical composition Raw yellow poplar biomass contains 39.3 g glucan, 18.4 g xylan, 21.4 g lignin and 20.9 g other components per 100 g. Dilute acid (DA) pretreatment selectively solubilized and hydrolyzed xylan, thereby increasing the relative amounts of glucan and lignin in the remaining solid. The DA-pretreated solid contained 38.2 g glucan, 4.4 g xylan and 17.0 g lignin per 100 g of raw YP, which corresponds to removal of 75.8% of the original xylan and 20.8% of the lignin. DA pretreatment at higher temperatures removes 90 to 100% of the xylan 3 , 13 , but at the moderate temperature of 120 °C DA pretreatment removed only 75.8% of the xylan. The DA/PAA pretreatment removed both xylan and lignin leaving a glucan-rich solid (Fig. 3 ). The DA/PAA-pretreated solid contained 33.2 g glucan, 2.6 g xylan and 2.1 g lignin per 100 g of raw YP, which corresponds to removal of 85% of the original xylan and 90% of the lignin under moderate temperature. The relative amount of glucan in the solid fraction increased from 39.3% in the raw biomass to 75.6% in the pretreated biomass. Only 15.4% of the glucan was lost during this one-step pretreatment. The one-step DA/PAA pretreatment dramatically improved the lignin removal and also increased the xylan removal as compared to DA pretreatment under same conditions. Figure 3 Composition of pretreated solid by DA and one-step DA/PAA pretreatment under same conditions. While DA pretreatment mainly hydrolyzed the xylan, one-step pretreatment solubilized both xylan and lignin. The values are based on the content of each component in 100 g of yellow poplar before pretreatment. Pretreatment conditions: DA: 100 mM H 2 SO 4 , 120 °C, 5 min; One-step: 300 mM PAA, 100 mM H 2 SO 4 , 120 °C, 5 min. Error bars correspond to the standard deviation for three measurements. \n Enzymatic hydrolysis Cellulase mixtures digested the one-step pretreated solid more effectively than the raw YP or the DA-pretreated solid (Fig. 4 ). The enzymatic hydrolysis released only 5.9 and 30.0% of the glucose in raw YP and DA-pretreated solids, respectively, but released 81.7% of the glucose from the one-step pretreated solid after 72 h at low enzyme loadings. The one-step pretreated solid had 13.8 and 2.5 times higher enzymatic digestibility than raw YP and DA-pretreated solid, respectively. In the DA-pretreated solid, the residual lignin or pseudo-lignin (re-deposited lignin) during DA pretreatment likely blocked access of the enzymes to cellulose and non-productively adsorbed the cellulases thereby preventing them from acting on the cellulose 22 , 23 . The higher rate of removal of xylan and especially lignin in the one-step pretreated biomass enhanced its enzymatic digestibility by increasing the accessibility of cellulase to cellulose and by reducing inhibition by residual lignin, thereby reducing the enzyme requirements. Figure 4 Comparison of glucose yield from enzymatic hydrolysis of solid from DA and one-step pretreatment of yellow poplar using 5 FPU/g glucan and 10 p NPGU/g glcuan. Glucose yield of raw YP and DA-pretreated solid was 5.9 and 30.0%, but increased up to 81.7% with one-step pretreatment at 72 h. Delignification in biomass increased the accessibility of cellulase to cellulose and reduced the inhibitory effect of lignin to cellulase compared as DA pretreatment. \n The optimal conditions for one-step pretreatment (120 °C, 5 min) are milder than those for various organosolv pretreatments, Table 1 . Organosolv pretreatment use organic solvents and catalysts to simultaneously remove xylan and lignin from lignocellulosic biomass resulting in a cellulose-rich fraction. To remove comparable amounts of xylan and lignin, organosolv pretreatment required substantial amounts of organic solvent and higher temperatures or longer times than the one-step pretreatment. In addition, pretreatment with PAA did not require subsequent incubation to enhance the cellulose digestibility as compared to pretreatment with formic acid or γ-valerolactone. Table 1 Organosolv biomass pretreatment for saccharification. Biomass Solvent Catalyst Temp. (°C) Time (min) Cellulose yield (%) Hemicellulose removal (%) Delignification (%) Cellulose digestibility (%) Ref. Lodgepole pine Ethanol 65% (v/v) 1.1% H 2 SO 4 \n 170 60 74.8 93.0 69.5 ~100 \n 29 \n Wheat straw Ethanol 60% (w/w) 0.29% H 2 SO 4 \n 190 60 91.1 95.3 75.8 89.4 \n 30 \n Sugarcane bagasse Glycerol 80% (w/w) 0.94% H 2 SO 4 \n 190 60 89.3 96.6 53.5 >90 \n 31 \n Sugarcane bagasse FA a 88% (w/w) — 107 60 87.5 90.7 74.5 53.2 (95.7 b ) \n 32 \n Sugarcane bagasse PAA c 50% (on biomass) — 80 120 — — 82.0 82.1 \n 33 \n Parairie cordgrass MIBK d 9% (w/w) 0.69% H 2 SO 4 \n 154 39 — — 87.0 84.0 \n 34 \n Switchgrass EA e 37%, ethanol 25% (w/w) 0.46% H 2 SO 4 \n 140 20 — — — 84.9 \n 35 \n Beech wood 2-MTHF f 50% (v/v) 0.1 M oxalic acid 140 180 — — — — \n 36 \n Corn stover THF g 50% (v/v) 0.5% H 2 SO 4 \n 150 25 75.0 94.8 76.6 95.0 \n 11 \n Beech wood GVL h 80% (w/w) 0.75% H 2 SO 4 \n 120 60 95.0 78.5 77.0 55.0 (99.0 i ) \n 37 \n Yellow poplar PAA 2.3% (w/v) 1% H 2 SO 4 \n 120 5 75.6 85.0 90.0 81.7 This study \n a Formic acid. b Deformylation with NaOH incubation at 120 °C for 1 h. c Peracetic acid. d Methyl isobutyl ketone. e Ethyl acetate. f 2-Methyltetrahydrofuran. g Tetrahydrofuran. h γ-Valerolactone. i NaOH incubation at 50 °C for 1 h and neutralization with acetic acid. \n The one-step pretreatment yields a lower quality xylose fraction than DA pretreatment. The xylose fraction is a mixture of xylose, xylose degradation products, lignin and acetic acid, while the DA pretreatment yields mainly an acidic xylose fraction. In addition, HPLC analysis revealed three sugar oxidation products, likely due to reaction with the PAA. These products were not further characterized. These products could also be fermentation inhibitors, but HMF, furfural and these products were removed in the washing step before enzymatic hydrolysis. Recently engineered microbes can convert not only glucose, but also xylose and arabinose, to fuels. The loss of the xylose/arabinose fraction is a disadvantage of the one-step pretreatment, which must be balanced by the short pretreatment time, higher quality of the glucose fraction, and high yield of glucose at low enzyme loadings. Structural characterization The structural changes in crystallinity, functional group distribution and surface morphology are consistent with removal of xylan and lignin using the one-step pretreatment. The crystallinity index (CrI) of one-step pretreated solid increased from 49.9% for raw YP to 66.9% for DA-pretreated solid and to 75.1% for the one-step pretreated solid (Fig. 5 ). The CrI indicates the relative amount of crystalline cellulose in the solid. This increase is consistent with the removal of the amorphous xylan and lignin fractions during pretreatment. Figure 5 Crystallinity changes after DA pretreatment and one-step pretreatment. The crystallinity of one-step pretreated solid increased due to high removal of xylan and lignin. I 002 : maximum intensity of crystalline portion at ~22° and I am : minimum intensity of amorphous portion at ~18°. \n The absorption bands in the FTIR spectrum related to functional groups in hemicellulose and lignin decreased in the one-step pretreated solid as compared to that of raw YP (Fig. 6 ). The ester linkage C = O between lignin and hemicellulose at 1720 cm −1 and the C-O-C stretch of the acetyl group in hemicellulose at 1245 cm −1 disappeared. The absorption bands at 1300–1600 cm −1 related to lignin also decreased. These decreases indicate that the one-step pretreatment removed xylan and lignin. In addition, several absorption bands associated with cellulose increased in the one-step pretreated solid as compared to that of raw YP. The O-H stretch at 3330 cm −1 and C-H stretch at 2900 cm −1 associated with cellulose were stronger after one-step pretreatment than raw YP. Similarly, the C-O-C glycosidic bond stretching at 1160 cm −1 , C-O-C ring skeletal vibration at 1100 cm −1 and C-O-H stretching of primary and secondary alcohols at 1030 cm −1 were also more intense than in raw YP. These increases are consistent with an increase in the relative amount of glucan. In contrast, after DA pretreatment, only the absorption bands related to hemicellulose decreased, while the bands related to lignin increased. This difference is consistent with selective removal of xylan by the DA pretreatment, leaving a glucan- and lignin-enriched solid. Figure 6 FT-IR spectra of raw yellow poplar, DA-pretreated solid and one-step pretreated solid. After one-step pretreatment, the absorption band related hemicellulose and lignin decreased, and the band associated with cellulose increased. \n The surface morphology of the solid after one-step pretreatment showed an extensively disrupted structure with exposed cellulose fibers (Fig. 7 ). The surface of raw YP appeared compact with rigid and highly ordered fibrils, and some flakes on the surface (Fig. 7a ). The surface of the solid pretreated with DA showed enlarged pores and irregular cracks, but preserved the major features of raw YP. A thin layer covered the surface, likely consisting of redeposited lignin, which can inhibit binding of the cellulase to cellulose 24 . The surface of the one-step pretreated solid showed completely different surface morphology (Fig. 7c ). The structure separated into fibers with the width of typical fragment decreasing from >250 µm in raw YP to ~10 µm. Similar decreases in the width of fibers in sugar cane bagasse occurred upon pretreatment with concentrated acetic acid and hydrogen peroxide 25 . In addition, the pores disappeared and the surface appeared smooth, which is consistent with the removal of xylan and lignin. One-step pretreatment destroyed the structure of YP and exposed the cellulose fibers, thereby increasing accessibility of cellulase to cellulose. Figure 7 SEM images of raw yellow poplar ( a ), DA-pretreated solid ( b ), and one-step pretreated solid ( c ) at magnification 500 × (1), 3,000 × (2), and 10,000 × (3). Scale bars are shown. The raw YP had a rigid and compact surface. DA-pretreated solid showed enlarged pores and surface covered by a thin layer of deposited lignin. One-step pretreated solid showed completely defibrated structure and smooth cellulose fiber."
} | 5,475 |
25641390 | null | s2 | 3,291 | {
"abstract": "Developing renewable energy sources is critical to maintaining the economic growth of the planet while protecting the environment. First generation biofuels focused on food crops like corn and sugarcane for ethanol production, and soybean and palm for biodiesel production. Second generation biofuels based on cellulosic ethanol produced from terrestrial plants, has received extensive funding and recently pilot facilities have been commissioned, but to date output of fuels from these sources has fallen well short of what is needed. Recent research and pilot demonstrations have highlighted the potential of algae as one of the most promising sources of sustainable liquid transportation fuels. Algae have also been established as unique biofactories for industrial, therapeutic, and nutraceutical co-products. Chlamydomonas reinhardtii's long established role in the field of basic research in green algae has paved the way for understanding algal metabolism and developing genetic engineering protocols. These tools are now being utilized in C. reinhardtii and in other algal species for the development of strains to maximize biofuels and bio-products yields from the lab to the field."
} | 297 |
22289118 | null | s2 | 3,292 | {
"abstract": "In bacteria, many small regulatory RNAs (sRNAs) are induced in response to specific environmental signals or stresses and act by base-pairing with mRNA targets to affect protein translation or mRNA stability. In Escherichia coli, the gene for the sRNA IS061/IsrA, here renamed McaS, was predicted to reside in an intergenic region between abgR, encoding a transcription regulator and ydaL, encoding a small MutS-related protein. We show that McaS is a ∼95nt transcript whose expression increases over growth, peaking in early-to-mid stationary phase, or when glucose is limiting. McaS uses three discrete single-stranded regions to regulate mRNA targets involved in various aspects of biofilm formation. McaS represses csgD, the transcription regulator of curli biogenesis and activates flhD, the master transcription regulator of flagella synthesis leading to increased motility, a process not previously reported to be regulated by sRNAs. McaS also regulates pgaA, a porin required for the export of the polysaccharide poly β-1,6-N-acetyl-d-glucosamine. Consequently, high levels of McaS result in increased biofilm formation while a strain lacking mcaS shows reduced biofilm formation. Based on our observations, we propose that, in response to limited nutrient availability, increasing levels of McaS modulate steps in the progression to a sessile lifestyle."
} | 340 |
22355791 | PMC3282947 | pmc | 3,293 | {
"abstract": "Microbes providing public goods are widespread in nature despite running the risk of being exploited by free-riders. However, the precise ecological factors supporting cooperation are still puzzling. Following recent experiments, we consider the role of population growth and the repetitive fragmentation of populations into new colonies mimicking simple microbial life-cycles. Individual-based modeling reveals that demographic fluctuations, which lead to a large variance in the composition of colonies, promote cooperation. Biased by population dynamics these fluctuations result in two qualitatively distinct regimes of robust cooperation under repetitive fragmentation into groups. First, if the level of cooperation exceeds a threshold, cooperators will take over the whole population. Second, cooperators can also emerge from a single mutant leading to a robust coexistence between cooperators and free-riders. We find frequency and size of population bottlenecks, and growth dynamics to be the major ecological factors determining the regimes and thereby the evolutionary pathway towards cooperation.",
"discussion": "Discussion In this article, we have studied the influence of population dynamics and fluctuations on the evolution and maintenance of cooperation. We specifically account for alternating population bottlenecks and phases of microbial growth. Thereby, our model serves as a null-model for cooperation in rearranging populations 25 26 28 29 31 , e.g. during microbial and parasitic life-cycles 24 41 59 60 61 , and bacterial biofilm formation 24 34 35 36 37 . The final outcome of the dynamics depends on the interplay between the time evolution of size and composition of each subpopulation. While a growth advantage of more cooperative groups favors cooperators, it is counteracted by the evolutionary advantage of free-riders within each subpopulation. We have investigated the stochastic population dynamics and the ensuing correlations between these two opposing factors. Depending on whether groups are merged while they are still exponentially growing or already in the stationary phase, two qualitatively different mechanisms are favored, the group-growth and the group-fixation mechanism. Importantly, our analysis identifies demographic noise as one of the main determinants for both mechanisms. First, demographic noise during population bottlenecks creates a broad distribution in the relative abundance of cooperators and free-riders within the set of subpopulations. The growth advantage of more cooperative subpopulations implies an asymmetric amplification of fluctuations and possibly yields to an increase of cooperation in the whole population (group-growth mechanism). Our analysis shows that this can enable a single cooperative mutant to spread in the population which then, mediated by the dynamics, reaches a stationary state with coexisting cooperators and free-riders. Second, if the founder populations contain only very few individuals, demographic fluctuations strongly enhance the fixation probability of each subpopulation which then consists of cooperators or free-riders only. Purely cooperative groups can reach a much higher carrying capacity. However, only if the relative weight of purely cooperative groups is large enough, this effect leads to an increase in the level of cooperation in the whole population (group-fixation mechanism). From our theoretical analysis of the population dynamics we conclude this to be the case only if the initial fraction of cooperators is above some threshold value. As shown by comparison with experiments by Chuang et al. 29 the proposed model is able to describe microbial dynamics quantitatively. Moreover, our model makes predictions how the evolutionary outcome varies depending on population dynamics and bottlenecks, and how the discussed mechanisms can provoke cooperation. These predictions can be tested experimentally by new experiments similar to those of Chuang et al. and others 25 26 28 29 31 : For example, by varying easily accessible parameters like the bottleneck size n 0 or the regrouping time T , the relative influence of both mechanisms can be tuned. Then the resulting level of cooperation and the ensuing bifurcation diagrams can be quantitatively compared with our theoretical predictions. As we assume the worst case scenario for cooperators, e.g randomly formed groups and no additional assortment, our findings are robust: The discussed pathways towards cooperation based on a growth-advantage of more cooperative groups and restructuring are expected to stay effective when accounting also for other biological factors like positive assortment, spatial arrangements of groups, mutation, or migration 1 . Shown by our analysis, a regular life-cycle favors cooperation. Besides better nutrient exploitation, this advantage for cooperation might be one reason for the evolution of more complex, controlled life-cycles including collective motion of microbes, local lysis, and sporulation 24 34 35 36 37 ."
} | 1,253 |
36453153 | PMC10107794 | pmc | 3,294 | {
"abstract": "Abstract Microbial activity is a major contributor to the biogeochemical cycles that make up the life support system of planet Earth. A 613 m deep geomicrobiological perforation and a systematic multi‐analytical characterization revealed an unexpected diversity associated with the rock matrix microbiome that operates in the subsurface of the Iberian Pyrite Belt (IPB). Members of 1 class and 16 genera were deemed the most representative microorganisms of the IPB deep subsurface and selected for a deeper analysis. The use of fluorescence in situ hybridization allowed not only the identification of microorganisms but also the detection of novel activities in the subsurface such as anaerobic ammonium oxidation (ANAMMOX) and anaerobic methane oxidation, the co‐occurrence of microorganisms able to maintain complementary metabolic activities and the existence of biofilms. The use of enrichment cultures sensed the presence of five different complementary metabolic activities along the length of the borehole and isolated 29 bacterial species. Genomic analysis of nine isolates identified the genes involved in the complete operation of the light‐independent coupled C, H, N, S and Fe biogeochemical cycles. This study revealed the importance of nitrate reduction microorganisms in the oxidation of iron in the anoxic conditions existing in the subsurface of the IPB.",
"conclusion": "CONCLUDING REMARKS This work has identified the most represented microorganisms inhabiting the solid rock subsurface of the IPB and, together with the measured metabolic products, suggests that they carry out complete and coupled C, H, N, S and Fe biogeochemical cycles. Our results show that the IPB deep rock subsurface contains sufficient biologically accessible energy sources to support diverse microbial communities that, collectively, may amount to 4 × 10 24 microbial cells, equivalent to 90 Mt of C (Table S10 ). These findings favour the hypothesis of a massive underground bioreactor that contributes to the characteristic extreme conditions detected in the Río Tinto basin, thus opening a path to the identification of analogous biogeochemical cycles likely operating in other continental subsurface formations and, eventually, even in the subsurface of other planets as it is the case of Mars.",
"introduction": "INTRODUCTION Rock continental subsurface geomicrobiology, which seeks to understand how life is sustained in the resource‐poor confines of rock matrices lacking solar radiation inputs, is a new research frontier (Colman et al., 2017 ; Escudero, Oggerin, & Amils, 2018 ; Gold, 1992 ; Magnabosco et al., 2018 ; Pedersen, 1993 ). Subsurface ecosystems are also instructive for astrobiology, as models for both the origin of life in putative early Earth scenarios (Pedersen, 2000 ) and for assessing potential subsurface life in other planetary bodies (Boston et al., 1992 ; Purkamo et al., 2020 ). Although Charles Darwin predicted the existence of subsurface life almost 200 years ago (Darwin, 1839 ), and a few pioneering early 20th century observations suggested the existence of active microorganisms in the subsurface (Bastin et al., 1926 ; Zobell, 1938 ), the first report describing the results of a dedicated continental rock matrix drilling was published relatively recently (Zhang et al., 2005 ). Most studies on continental subsurface microbial diversity are based on the analysis of groundwater samples (Chapelle et al., 2002 ; Momper, Reese, et al., 2017 ; Nuppunen‐Puputti et al., 2022 ; Purkamo et al., 2018 ; Sherwood Lollar et al., 2019 ; Stevens & McKinley, 1995 ; Suzuki et al., 2013 ; Wu et al., 2016 ), which, although providing useful microbiological diversity information, cannot directly relate it to the pertinent geological features of the complex subsurface solid matrix which the microorganisms inhabit. Despite recent progress in the field (Cabugao et al., 2022 ; Dutta et al., 2018 ; Purkamo et al., 2020 ; Soares et al., 2019 ), information concerning the abundance, diversity and ecophysiological integration of extant microbial species, as well as microbiome function, connectivity and sustainability, in continental subsurface rock ecosystems is still scarce. The Iberian Pyrite Belt (IPB) stretching for some 250 km across SW Iberian Peninsula hosts the largest concentration of volcanogenic massive metal sulfide deposits and arguably the largest sulfide anomaly in the Earth's crust (Barriga, 1990 ; Tornos, 2006 ). Its formation through hydrothermalism took place during the Hercynian orogenesis (Barriga, 1990 ; Lescuyer et al., 1998 ). Río Tinto is a 92 km long river with its source in Peña de Hierro, in the core of the IPB, which flows into the Atlantic Ocean at Huelva. The Río Tinto is an unusual extreme environment due to its acidity and high concentration of heavy metals, as well as its high level of microbial diversity (Amaral‐Zettler et al., 2002 ; Amils, 2016 ; Gónzalez‐Toril et al., 2003 ). It has been generally assumed that the extreme conditions found in the Río Tinto basin were the result of 5000 years of mining activity in the area (Alvarez & Nieto, 2015 ; Leblanc et al., 2000 ; van Geen et al., 1997 ). However, recent geophysical, hydrogeological, and other geological data suggest that the IPB subsurface acts as a huge underground reactor, in which sulfidic minerals are the main energy source and the metabolic reaction products drain to the river (Allman et al., 2021 ; Gómez‐Ortiz et al., 2014 ). Here, we report a detailed multidisciplinary analysis of the microbiology and microbially driven geochemical processes operating in the deep subsurface rock matrix of the IPB. The results allowed the identification of the most representative microorganisms, which are able to carry out the light independent, coupled C, H, N, S and Fe biogeochemical cycles. Enrichment cultures have been used to identify the most characteristic metabolic activities operating in the deep subsurface of the IPB. The analysis of the genomes of nine isolates from the enrichment cultures identified the presence of genes involved in the operation of the biogeochemical cycles and highlighted the role of the nitrogen cycle and the nitrate‐reducing microorganisms in the anoxic conditions existing in the subsurface of the IPB.",
"discussion": "DISCUSSION Continental deep subsurface geomicrobiology is essential to our understanding of the importance of Earth's biogeochemical cycles at a local and planetary scale. Recent evaluations estimate that most of the prokaryotic biomass is located in the deep subsurface (Colman et al., 2017 ; Magnabosco et al., 2018 ). Unfortunately, most of the available subsurface continental microbiological information has been obtained from groundwater samples, with their intrinsic limitations (Escudero & Amils, 2022 ; Escudero, Oggerin, & Amils, 2018 ). To generate information on the abundance, diversity, as well as microbiome functions in continental subsurface rock systems, devoted drillings are required to generate core samples with which to perform essential complementary analysis. The few devoted continental drilling operations carried out to date have reported, in general, microbial diversity information from samples obtained at great depth distances and/or using just one methodology, which do not produce sufficient reliable information to describe the operation of the biogeochemical cycles in the deep subsurface (Breuker et al., 2011 ; Cockell et al., 2021 ; Dutta et al., 2018 ; Fry et al., 2009 ; Lehman et al., 2004 ; Liu et al., 2020 ; Momper, Reese, et al., 2017 ; Zhang et al., 2005 ). To overcome these limitations, this work employed 47 core samples, in order to generate an exhaustive complementary and multidisciplinary analysis of the microbiology and microbial‐driven geochemical processes operating in the deep subsurface of the IPB. The Iberian Pyrite Belt Subsurface Life Detection project (IPBSL) was planned to evaluate the existence of an underground reactor as the possible origin of the extreme conditions detected in the Río Tinto basin. A thorough geophysical analysis using resistivity tomography (ERT) and time‐domain electromagnetic sounding (TDEM) allowed the subsurface areas where water and reduced minerals were most likely to intersect to be identified, producing representative information on the mineral substrates and the associated microbial diversity that exists in the deep subsurface of the IPB (Gómez‐Ortiz et al., 2014 ). The selected drilling site, BH10, is located on the north flank of the Río Tinto anticline, in the area known as Peña de Hierro (Iron Mountain) (Figure S1 ). Borehole BH10 was drilled through the upper part of the volcano sedimentary complex of the district, which hosts a large zone of hydrothermal alteration with widespread replacement by quartz, clinochlore, illite, pyrite, sericite and siderite. Among these minerals, most contained Fe, which agrees with the elemental content detected by ICP‐MS along the borehole (Datasets S1 and S2 ). From our previous drilling experience, we had learned that a fast in situ geochemical analysis of the retrieved cores was the best way to select samples for a deeper analysis (Fernández‐Remolar et al., 2008 ; Puente‐Sánchez, Moreno‐Paz, et al., 2014 ). The use of IC on site to analyse the soluble anionic content of core samples overnight allowed samples with an interesting pattern of electron acceptors, content of organic acids and with low levels of Br − (used as a drilling fluid contamination marker) to be selected. From among the different contamination markers tested in previous drilling operations in the IPB (Amils et al., 2008 ; Fernández‐Remolar et al., 2008 ; Puente‐Sánchez, Moreno‐Paz, et al., 2014 ) Br − was selected due its low concentration in the subsurface of the IPB, its efficient detection with IC, economical price and ecological considerations. The presence of organic acids such as acetate, formate, oxalate and propionate identified at different depths is good indicator of the presence of biological activity along the column. Of these, acetate and formate are interesting metabolic products, which can be used as electron donors and a source of carbon for other subsurface microorganisms (Purkamo et al., 2017 ). The detection of sulfate strongly suggests the existence of active bioleaching of metal sulfides along the borehole (Vera et al., 2013 ) and the existence of SRB (Bell et al., 2020 ; Itävaara et al., 2011 ; Momper, Jungbluth, et al., 2017 ; Onstott et al., 2009 ). The presence of nitrate, nitrite and ammonia are good indicators of an operative nitrogen cycle (Lau et al., 2014 ; Rempfert et al., 2017 ). All these data together with the detection of carbohydrates and proteins at different depths were strong signals of the existence of extant or recent microbiological activities in the subsurface of the IPB (Dataset S3 ). To overcome the bias introduced using only one methodology to describe microbial diversity along the borehole and the problems associated with the unavoidable contamination associated with drilling operations (Sheik et al., 2018 ), complementary methodologies based on different principles (immunological, sequencing, cloning, hybridization, enrichment cultures and isolation) were used to identify, at the genus level, the most representative microorganisms along the borehole. Although extracting high‐quality nucleic acids from hard rock cores is always challenging, we were able to recover DNA from 16 core samples from different depths to identify the bacterial diversity along borehole BH10. PCR amplicons from these samples were analysed through hybridization with PAM (Garrido et al., 2008 ), cloning and massive 16S rRNA gene ultra‐deep sequencing by means of two techniques, Illumina MiSeq and Roche 454. Despite the use of several recommended sets of archaeal PCR primers and diverse protocols, we were unable to amplify 16S rDNA sequences for Archaea, although we know that members of this domain are present in the deep subsurface of the IPB because other methodologies, like immunological (LDchip300) and hybridization (FISH and CARD‐FISH), gave positive identification results. It seems that insufficient yield in the preparation of DNA and/or the integrity of 16S rDNA contained in the retrieved samples are the most plausible causes for this unfortunate situation. Of the different methodologies used in this work, FISH and CARD‐FISH stands out because it not only identifies the presence of microorganisms but also quantifies them and detects their close contact with other microorganisms, suggesting the functional operation of complementary metabolic activities. In this work, we have detected the presence of ANAMMOX bacteria, which could be responsible for the oxidation of the NH 4 \n + detected in the column (Kuenen, 2008 ; Strous et al., 2006 ); the co‐occurrence of archaeal ANME‐2 and SRB, which could explain the methanotrophic activities detected along the borehole (Knittel & Boetius, 2009 ); the co‐occurrence of the Fe oxidizer Acidovorax and the Fe reducer Acidiphilium suggesting the operation of an Fe cycle (Kappler et al., 2021 ) and the sulfur oxidizer Sulfobacillus and SRB suggesting the operation of an S cycle (Bell et al., 2020 ) (Figures 1 and 2 ). To the best of our knowledge, this is the first time that anaerobic ammonia oxidation and methanotrophy have been identified using FISH in continental hard rock samples from the deep subsurface. In addition, an important advantage over the rest of the methodologies used is that FISH requires only a very small sample, generating information on the presence of different microorganisms at microscopy size resolution, which is unobtained with the rest of the methodologies employed as they require larger quantities of sample for their analysis In the case of solid rock matrices a fair amount of sample is required to obtain analysable DNA, in our case between 0.5 and 10 g of core samples. Furthermore, FISH is a non‐destructive method that allows the same sample to be re‐hybridize using complementary probes. This facilitates the identification of the diverse microbial components of the sample. Except for FISH, the other methodologies yield interesting diversity results but without information on the interconnection between the identified microorganisms and the mineral features of the complex matrix in which they inhabit. The positive hybridization signals using the FISH protocol strongly suggest the presence of metabolically active microorganisms in the deep subsurface (Figure 1 ), a fundamental question in subsurface geomicrobiology (D'Hondt et al., 2002 ; Escudero, Oggerin, & Amils, 2018 ; Lovley & Chapelle, 1995 ; Morita, 1999 ; Phelps et al., 1994 ). In this work, most of the microbial identification has been done using CARD‐FISH to amplify the hybridization signal and facilitate the distinction between real hybridizations and artefacts, such as unspecific binding of the probe or the dye (Escudero, Vera, et al., 2018 ). In addition, FISH demonstrated the existence of biofilms in the oligotrophic deep subsurface of the IPB (Figure 1 ), contrary to the generally accepted idea that in these conditions microorganisms are unable to use their limited source of energy in the generation of very metabolically expensive structures (Escudero, Vera, et al., 2018 ; Poulsen et al., 1993 ; Sauer, 2003 ; Saville et al., 2011 ). From our data, we strongly support the idea that if needed microorganisms will use their limited resources to make biofilms, to take advantage of their useful properties such as the ability to interconnect metabolically complementary functional microorganisms, protect against desiccation, control metabolic products diffusion, and so on (Coyte et al., 2017 ; Vera et al., 2013 ). As observed at other continental drilling operations in the subsurface of the IPB Bacteria are much more abundant than Archaea (Figure 2 ) (Breuker et al., 2011 ; Dutta et al., 2018 ; Fry et al., 2009 ; Magnabosco et al., 2018 ; Momper, Reese, et al., 2017 ; Suzuki et al., 2013 ; Takai et al., 2001 ; Zhang et al., 2005 ), which seems to be a common property of the continental deep subsurface. We did not observe any depth‐related patterns of distribution of taxonomic/functional groups along the column, at least along the 612 m analysed. Despite the difficulties in assessing cell density within a solid, low‐porosity rock and variable mineralogical content, conservative estimates derived from the analysis of different samples along the borehole yielded values between 10 4 and 10 5 cells/g of rock sample, regardless of depth. This is in the same order of magnitude as that reported for other continental hard rock drilling operations (Breuker et al., 2011 ; Cockell et al., 2012 ; Cockell et al., 2021 ; Dutta et al., 2018 ; Fry et al., 2009 ; Onstott et al., 2003 ). A convenient system to identify putative microbial metabolisms in the deep subsurface is to establish enrichment cultures for suspected activities related with the detected geochemical variables. Obviously, enrichment cultures have the bias that the conditions are optimal for the observation of those activities selected and these can be quite different from those existing in the native subsurface conditions, giving opportunistic microbes the advantage over the rest of the microorganisms. In our case, enrichment cultures were used to test the metabolic activities, which were expected due to the characteristics of the ecosystem, such as iron and sulfide oxidation (Fernández‐Remolar et al., 2008 ). Other activities, for example, methanogenesis and sulfate reduction were selected because they had been detected on previous drilling campaigns in the IPB (Puente‐Sánchez, Moreno‐Paz, et al., 2014 ). And finally, activities related with the detected geochemical compounds along the borehole, like acetogenesis (acetate), methanotrophy (CH 4 ) and nitrate‐reducing activities (NO 3 \n − ) were also selected. Although we could not generate archaeal sequences in this work, the presence of methanogenic archaeal activity was confirmed using complementary methodologies. The presence of occluded CH 4 in different samples and CH 4 produced after core samples activation, together with the presence of H 2 and CO 2 , the substrates for hydrogenotrophic methanogenesis, are strong indicators for the existence of methanogenic activities in the ecosystem. Recently, it has been shown that an important proportion of H 2 and CO 2 detected in the subsurface of the IPB are biologically produced (Mateos et al., 2022 ; Sanz et al., 2021 ). This observation is extremely important in our ecosystem because is generally assumed that most of the detected H 2 in the subsurface is abiotically produced (Pedersen, 1997 ; Stevens & McKinley, 1995 ). The generation of CH 4 was detected, with variable intensities, along the length of the borehole, using hydrogenotrophic, acetoclastic and methylotrophic substrates (Table S7 ). These results agree with the detection of Methanobacterium using the immunological LDChip300 and the positive hybridization signals observed using specific hybridization probes for Methanosarcinales and Methanobacteriales orders (Figures 1F and 2 ). Methanogenesis was one of the first activities detected in the continental deep subsurface and has been reported in most of the drilling operations (Kotelnikova, 2002 ; Pedersen & Albinsson, 1992 ). The presence of CH 4 along the column called for testing for the presence of methanotrophic activities. Methanotrophy was detected at variable intensities in diverse enrichment cultures from core samples at different depths (Table S7 ). As in other anoxic environments, this activity requires the syntrophic cooperation of an archaeal anaerobic methane oxidizer (ANME 2) and a SRB. This co‐occurrence was observed using specific hybridization probes for both types of microorganisms (Figure 1G ). Although ANME archaea (Fry et al., 2009 ) and SRB (Motamedi & Pedersen, 1998 ) have been identified previously in the continental deep subsurface; to the best of our knowledge, this is the first demonstration of this syntrophic activity in the hard rock matrix of a deep subsurface. Knowing that this activity can also be obtained by syntrophic association of ANME 2 archaea with nitrate and iron‐reducing activities, and that both activities occur in the subsurface of the IPB (Table S5 ), it is reasonable to expect anaerobic oxidation of methane through these activities in the subsurface of the IPB (Schnakenberg et al., 2021 ). Five additional activities have been detected using enrichment cultures: acetogenesis, autotrophic denitrification, Fe oxidation, and sulfate and Fe reduction. As shown in Table S5 , these activities were detected in core samples at different depths with variable intensities as expected for an irregular solid matrix. Acetogenic activity, also described previously in the continental deep subsurface (Magnabosco et al., 2016 ; Rempfert et al., 2017 ), could be predicted by the high concentration of acetate detected along the column. Autotrophic denitrification was considered an activity of interest after the detection of nitrate and nitrite by IC and the presence of reduced sulfur compounds generated by the operation of the S cycle (Lau et al., 2016 ). Sulfate‐reducing activity (SRB) was also expected due to the presence of SO 4 \n 2− as a result of the metal sulfides oxidation. Sulfate‐reducing activity is also a classical metabolic activity detected in continental deep subsurface (Motamedi & Pedersen, 1998 ; Onstott et al., 2009 ). In the case of SRB, two electron donors were used, H 2 and a mixture of lactate, methanol and glycerol. The generation of H 2 S from the sulfate‐reducing activity can explain the detection of secondary pyrite and the attack of primary sulfates under reducing conditions (e.g. baryte, BaSO 4 ) through the biological activity along the borehole (Fernández‐Remolar et al., 2008 , 2018 ). The highest activities detected for sulfate reduction, methanotrophy and autotrophic denitrification at 352.7 mbs could be related to the presence at this depth of a fault, which facilitates the water and dissolved substrates movement. Enrichment cultures for anaerobic Fe oxidation and Fe reduction activities were tested with core samples along the column (Table S5 ). In the case of anaerobic Fe oxidation, acetate was used as electron donor and nitrate as electron acceptor, both compounds detected in the IPB subsurface. For Fe reduction, glucose was used as electron donor. Table S5 shows the distribution of both activities along the borehole. The detection of both activities at the same depth in 8 out of the 32 analysed samples, suggest an operative Fe cycle in the subsurface of the IPB, which agrees with the co‐occurrence of Fe oxidizing and reducing microorganisms observed by hybridization (Figures 1 , 2 and S6 ). Sixteen genera belonging to the Pseudomonadota ( Acidiphilium , Acidovorax , Acidithiobacillus , Brevundimonas , Desulfovibrio , Pseudomonas , Rhizobium , Rhodoplanes , Shewanella ), Actinomycetota ( Arthrobacter , Propionibacterium , Tesaracoccus ), Bacillota ( Bacillus , Desulfosporosinus , Sulfobacillus ) and Nitrospirota ( Leptospirillum ) phyla and members of the class Cyanobacteria, were selected as the most representative bacterial genera in the subsurface of the IPB as they were detected by at least two independent methodologies at five depth intervals (Figure 3 ). Pseudomonadota, Actinomycetota and Bacillota have been described as the most common phyla identified in the continental deep‐subsurface (Fry et al., 2009 ; Magnabosco et al., 2016 ; Nuppunen‐Puputti et al., 2022 ; Onstott et al., 2009 ; Wu et al., 2016 ; Zhang et al., 2005 ). Members of the most representative genera were previously identified in different continental deep subsurface drilling operations, Acidiphilium (Cockell et al., 2021 ; Johnson, 2012 ), Acidovorax (Liu et al., 2020 ; Miyoshi et al., 2005 ; Onstott et al., 2003 ; Shimizu et al., 2006 ), Acidithiobacillus (Johnson, 2012 : Lau et al., 2016 ), Brevundimonas (Bell et al., 2020 ; Bose et al., 2020 ; Nuppunen‐Puputti et al., 2022 ; Onstott et al., 2009 ), Desulfovibrio (Bell et al., 2020 ; Motamedi & Pedersen, 1998 ; Shimizu et al., 2006 ), Pseudomonas (Boivin‐Jahns et al., 1996 ; Onstott et al., 2009 ; Shimizu et al., 2006 ; Zhang et al., 2005 ), Rhizobium (Dutta et al., 2018 ; Momper, Reese, et al., 2017 ; Zhang et al., 2005 ), Shewanella (Dutta et al., 2018 ; Fredrickson et al., 1998 ; Onstott et al., 2009 ), Arthrobacter (Lehman et al., 2004 ; Zhang et al., 2005 ), Propionibacterium (Boivin‐Jahns et al., 1996 ), Tessaracoccus (Cockell et al., 2012 ), Bacillus (Cockell et al., 2012 ; Dutta et al., 2018 ; Onstott et al., 2009 ; Zhang et al., 2005 ), Desulfosporosinu s (Onstott et al., 2009 ), Sulfobacillus (Gihring et al., 2006 ), Leptospirillum (Gihring et al., 2006 ; Johnson, 2012 ), and Cyanobacteria (Bose et al., 2020 ; Dutta et al., 2018 ; Gihring et al., 2006 ; Momper, Reese, et al., 2017 ), with the exception of Rhodoplanes for which this is the first report of its identification in the deep subsurface. The presence of genes encoding nitrate ammonification, denitrification, sulfur oxidation and thiosulfate reduction activities in the Rhodoplanes sp. T2.26MG‐98 genome is sufficient to explain its development in the deep subsurface in the absence of light (Mariñán et al., 2019 ). Members of the Cyanobacteria class and the Acidithiobacillus , Acidovorax , Desulfosporosinus , Pseudomonas , Sulfobacillus and Tessaracoccus genera were detected in 13 out of 19 analysed intervals, using at least three independent methodologies. As mentioned, Cyanobacteria had been previously reported in several drilling operations (Bose et al., 2020 ; Dutta et al., 2018 ; Gihring et al., 2006 ; Momper, Reese, et al., 2017 ) and in samples from borehole BH10 (Puente‐Sánchez et al., 2018 ), indicating the existence of non‐photosynthetic alternative metabolisms, such as the use of H 2 , in this important group of microorganisms. Moreover, we have previously isolated and characterized an endogenous IPB subsurface nitrate‐reducing bacterium from the same drilling, Tessaracoccus lapidicaptus (Puente‐Sánchez, Sánchez‐Román, et al., 2014 ). Members of this genus must have an important role in the subsurface of the IPB because they have been detected at different depths using diverse independent methodologies and identified in all sequenced enrichment cultures (Dataset S7 ). Furthermore, Acidovorax , Pseudomonas and Rhizobium correspond to a core terrestrial deep subsurface bacteria of eight genera ( Acidovorax , Diaphorobacter , Defluvimonas , Palnomicrobium , Pseudomonas , Rhizobium , Rhodoferax and Thauera ) selected using the sequence diversity of eight drilling operations from different lithological and geographical locations (Soares et al., 2019 ). In our case, 2 of the selected genera, Acidovorax and Pseudomonas , were detected by 3 independent methods in 13 of the 19 analyzed depth intervals, and Rhizobium was identified by 4 different methodologies in 10 depth intervals of the deep subsurface of the IPB. Rhodoferax has been detected in BH10 borehole at only one depth, 352 mbs, by means of cloning. Twenty‐nine bacteria belonging to the Pseudomonadota ( Brevundimonas , Desulfovibrio , Lelliotia , Pseudomonas [five isolates], Rhizobium [two isolates], Rhodoplanes [three isolates], Shewanella and Xanthobacter ), Actinomycetota ( Aestuarimicrobium , Cellulomonas [two isolates], Microbacterium , Nocardoides , Propionicimonas and Tessaracoccus [four isolates]), Bacillota ( Acetoanaerobium , Bacillus and Paenibacillus ) and Bacteroidota ( Macellibacteroide ) phyla were isolated from the most active hydrogenotrophic methanogenic and autotrophic denitrifying enrichment cultures under strict anaerobic conditions (Table S6 ) (Leandro, 2018 ; Leandro et al., 2018 ). Most of these bacterial genera have been identified previously in the deep subsurface ( Brevundimonas , Onstott et al., 2009 ; Bacillus , Zhang et al., 2005 ; Cellulomonas , Fry et al., 2009 ; Desulfovibrio , Motamedi & Pedersen, 1998 ; Microbacterium , Onstott et al., 2009 , Nocardoides , Purkamo et al., 2020 , Paenibacillus , Purkamo et al., 2020 ; Pseudomonas , Boivin‐Jahns et al., 1996 , Rhizobium , Zhang et al., 2005 ; Shewanella , Onstott et al., 2009 ; and Tessaracoccus , Cockell et al., 2012 ), but for some of them ( Acetoanaerobium , Aestuarimicrobium , Lelliotia , Macellibacteroides and Xanthobacter ), this is the first time that have been identified and isolated from continental hard rock deep subsurface. Currently, they are being characterized genotypically and phenotypically to better understand their role in the continental deep subsurface microbiome. Identifying the most representative microorganisms in the subsurface of the IPB made it possible to evaluate their correlation with the minerals identified in the ecosystem and their metallic content (Figure 4 ). A positive correlation was observed for members of Arthrobacter , Acidovorax , Pseudomonas , Rhodoplanes , and Sulfobacillus genera with Fe and pyrite, in addition, two of them, Acidovorax and Pseudomonas , can oxidize Fe 2+ in anaerobic conditions. Acidiphilium , an iron reducer, and Tessaracoccus , an iron oxidizer, showed a correlation with Cu and clinochlore, a phyllosilicate with Fe; Brevundimonas with Zn and illite, another phyllosilicate with Fe; Shewanella , an Fe reducer, with siderite, a ferrous carbonate; and Bacillus with Mn. Thus, most of the identified representative microorganisms in the deep subsurface of the IPB correlate with primary and secondary Fe minerals and/or elements present in the metallic sulfides existing in the IPB, underlying the intimate relationship between the identified microbial diversity and the Fe mineralogy existing in the IPB. The activation of Fe oxidation in anaerobic conditions after the addition of water to three dry core samples with high pyrite content could be visualized as the formation of Fe 3+ precipitates, which strongly suggest the existence of anaerobic Fe‐oxidizing activities in the subsurface of the IPB (Figure S7 ). A metabolic reaction of importance not only in this ecosystem but also in applied biotechnological processes such as biohydrometallurgy, in which anoxic conditions are generated in the bioleaching heaps because of the exhaustion of O 2 by the aerobic respiring microorganisms, among them the Fe oxidizers (Malki et al., 2006 ). Isolates from four representative genera identified in the BH10 core samples, Acidovorax , Tessaracoccus , Pseudomonas and Shewanella showed efficient oxidation of ferrous iron using nitrate as electron acceptor for anaerobic respiration (Table S9 ). This activity could also be visualized through fluorescence microscopy of native subsurface samples by the co‐occurrence of ferric iron, the oxidation product, and the presence of nitrate‐reducing microorganisms, Acidovorax and Tessaracoccus , clearly identified by CARD‐FISH (Figure S8 ). The genomic analysis of these microorganisms showed the lack of recognizable genes associated with this metabolic activity (Carlson et al., 2013 ; Leandro et al., 2017 ; Martínez et al., 2020 ; Mateos et al., 2022 ; Puente‐Sánchez, Pieper, & Arce‐Rodríguez, 2016 ), so we have to conclude that the observed oxidation of iron, at least for the tested microorganisms, is due to the chemical oxidation of Fe promoted by the high oxidizing capacity of nitrite and nitric oxide generated by the use of nitrate as electron acceptor. These results strongly support the notion that some nitrate reducers can efficiently generate reactive nitrogen species able to oxidize iron under strict anaerobic conditions (Bryce et al., 2018 ; Carlson et al., 2013 ; Straub et al., 2004 ). Remarkably, 82% of the most representative genera identified in this work have been described as putative nitrate reducers. In fact, we have identified the presence of genes coding for nitrate reduction in eight of the nine sequenced genomes isolated from the IPB subsurface. This result, together with the Fe 2+ oxidation capacity shown by some IPB isolates, strongly suggests the importance of this metabolic activity in the IPB subsurface, the origin of the high concentration of secondary Fe minerals and the presence of soluble Fe along the column as the source of the high concentration of iron detected in the Tinto basin (Allman et al., 2021 ; Fernández‐Remolar et al., 2018 ). Recently, the interaction of members of the Acidovorax genus with pyrite in the subsurface of the IPB and the correspondent Raman spectral change of this mineral associated with this interaction has been reported (Escudero et al., 2021 ). In addition, preliminary experiments performed in our laboratory showed that Acidovorax is able to solubilize Fe from pyrite using acetate as a source of energy and nitrate as electron acceptor (Escudero, 2018 ). Further research is needed to clarify the role of nitrate reduction Fe oxidation activities (NRFeOx) in the subsurface of the IPB as well as other environments. Given the impossibility of generating useful metagenomic information from the retrieved DNA samples, and in order to obtain data on the enzymatic activities associated with the different biogeochemical cycles operating in the deep subsurface of the IPB, we have annotated the genome sequences of nine IPB subsurface isolates ( Brevundimonas sp. T2.26MG‐97, Desulfosporosinus meridei DEEP, Psudomonas sp. T2.31D.1, Rhizobium sp. T2.30D‐1.1, Rhizobium sp. T2.26MG‐112.2, Rhodoplanes sp. T2.26MG‐98, Shewanella sp. T2.3D‐1.1, Tessaracoccus sp. T2.5‐30 and Tessaracoccus lepidicaptus IPBSL‐7), and the shotgun metagenomic data for Cyanobacteria, all of them belonging to the most representative genera of this ecosystem. The complete set of genes coding for the enzymatic activities able to functionally maintain the carbon cycle (CO 2 fixation, CO 2 production through respiration and fermentation), the hydrogen cycle (H 2 production and H 2 oxidation), the nitrogen cycle (N 2 fixation, dissimilatory nitrate reduction to ammonia (DNRA), nitrate reduction, denitrification), iron reduction and the sulfur cycle (S oxidation and reduction), have been detected in eight core samples obtained at different depths (Figure 5 and Table S8 ). The proposed roles of the most relevant identified and isolated microbial genera, their genes, and their metabolic products in the maintenance of the basic C, H, N, S and Fe biogeochemical cycles operating in a coupled mode in the deep subsurface of the IPB is shown in Figure 6 . The existence of a significant number of microorganisms identified through independent methodologies at different depths, showing genes in their sequenced genomes involved in the N cycle, underscores the likely importance of this biogeochemical cycle in the subsurface, which had been previously suggested, and is confirmed by these results (Lau et al., 2014 ; Nuppunen‐Puputti et al., 2022 ; Rempfert et al., 2017 ). FIGURE 6 Geomicrobiological model of the C, H, N, S and Fe biogeochemical cycles operating in the deep subsurface of the IPB. Brown: C cycle; Purple: H cycle, Blue: N cycle; Green: S cycle and Red: Fe cycle. Filed arrows indicate biologically mediated reactions, hollow arrows abiotic reactions. In red: isolated genera in which the corresponding gene has been identified in their sequenced genomes; in bold‐black: isolated genera without genomic information; in black: no isolated identified genera. *: genera detected by only one methodology; within black ovals: metabolites identified and quantified in this work. ANAMMOX, anaerobic ammonium oxidation; ANME, anaerobic methane oxidizing archaea; DNRA, dissimilatory nitrate reduction to ammonium; F, fermentation; FeR, iron reduction; HO, hydrogen oxidase; MS, metal sulfides; NR, nitrate reduction; NiR, nitrite reductase; NoR, nitric oxide reductase; R, respiration; SRB, sulfate reducing bacteria; SO, sulfur oxidation; TeR, tetrathionate reductase; ThO, thiosulfate oxidase, ThR, thiosulfate reductase The performance and coupling of some geomicrobiological cycles in the deep subsurface have been suggested by some authors using diffused groundwater samples (Bell et al., 2020 ; Momper, Jungbluth, et al., 2017 ; Nyyssönen et al., 2014 ), but this is the first time that the coupling of five complete basic biogeochemical cycles is shown operating in the presence of diverse hard rock substrates at different depths, underlying the absolute need for complementary metabolisms to maintain the deep subsurface microbiome operative. As mentioned in the Introduction, the astrobiological interest of continental subsurface life is mainly related with the search for life in other planetary bodies. The current concept of habitability, in other words, the presence of conditions that could support life in a given planet resides mainly on the detection of conditions that support the existence of liquid water on its surface (Cockell et al., 2016 ). Obviously, the demonstration of the existence of life in the continental deep subsurface has expanded the possible existence of life and hence the habitability of a planet by an important factor, although at this moment impossible to evaluate. A significant limitation to the estimation of the real habitability of an exoplanet is that, currently, we can only obtain information from its surface and atmosphere, and as a consequence of the distances involved, it is impossible to determine the conditions existing in their subsurface. This problem does not exist in our solar system, where exploration missions could be sent to collect sufficient information on the deep subsurface properties, or even better, to bring samples back to Earth for deeper analysis. An interesting case can be found in Mars. As the consequence of the conditions reported by diverse exploration missions, life in the surface of the planet is unlikely due to the lack of water, intense radiation, extremely oxidizing conditions and low temperature (Margulis et al., 1979 ; Martínez et al., 2017 ; Rafkin et al., 2016 ; Schofield et al., 1997 ). Definitively, the demonstration of Darwin's prediction of life in the deep subsurface has radically changed the situation, and the next Mars missions are considering this possibility, especially after the report of liquid water in the subsurface (Orsei et al., 2018 ). The existence of microbial life sustaining the most important geobiological cycles in the subsurface of one mineralogical and geochemical terrestrial analogue of Mars, the IPB (Fernández‐Remolar et al., 2005 ), allow us to conclude that the possibility of past or even extant life in the subsurface of Mars must be contemplated (Koike et al., 2020 ; Price et al., 2018 , 2022 ; Purkamo et al., 2020 )."
} | 9,836 |
22530002 | PMC3328440 | pmc | 3,296 | {
"abstract": "Background \n Methanocellales contributes significantly to anthropogenic methane emissions that cause global warming, but few pure cultures for Methanocellales are available to permit subsequent laboratory studies (physiology, biochemistry, etc.). Methodology/Principal Findings By combining anaerobic culture and molecular techniques, a novel thermophilic methanogen, strain HZ254 T was isolated from a Chinese rice field soil located in Hangzhou, China. The phylogenetic analyses of both the 16S rRNA gene and mcrA gene (encoding the α subunit of methyl-coenzyme M reductase) confirmed its affiliation with Methanocellales , and Methanocella paludicola SANAE T was the most closely related species. Cells were non-motile rods, albeit with a flagellum, 1.4–2.8 µm long and by 0.2–0.3 µm in width. They grew at 37–60°C (optimally at 55°C) and salinity of 0–5 g NaCl l −1 (optimally at 0–1 g NaCl l −1 ). The pH range for growth was 6.4–7.2 (optimum 6.8). Under the optimum growth condition, the doubling time was 6.5–7.8 h, which is the shortest ever observed in Methanocellales . Strain HZ254 T utilized H 2 /CO 2 but not formate for growth and methane production. The DNA G+C content of this organism was 52.7 mol%. The sequence identities of 16S rRNA gene and mcrA gene between strain HZ254 T and SANAE T were 95.0 and 87.5% respectively, and the genome based Average Nucleotide Identity value between them was 74.8%. These two strains differed in phenotypic features with regard to substrate utilization, possession of a flagellum, doubling time (under optimal conditions), NaCl and temperature ranges. Taking account of the phenotypic and phylogenetic characteristics, we propose strain HZ254 T as a representative of a novel species, Methanocella conradii sp. nov. The type strain is HZ254 T ( = CGMCC 1.5162 T = JCM 17849 T = DSM 24694 T ). Conclusions/Significance Strain HZ254 T could potentially serve as an excellent laboratory model for studying Methanocellales due to its fast growth and consistent cultivability.",
"conclusion": "Taxonomic conclusions The collective traits of strain HZ254 T with regard to its physiology and phylogeny support it as a member of the order Methanocellales . It shares common phenotypic features with the other two strains ( M . arvoryzae MRE50 T and M. paludicola SANAE T ) of Methanocellales , such as the rod-shaped morphology, the growth via hydrogenotrophic methanogenesis and the requirement of acetate as a carbon source. However, they differ in formate utilization, possession of a flagellum, antibiotic susceptibility, temperature range, pH range and salinity range. In addition, the ANI values further distinguish the three strains on the species level, given that they are far below 95 to 96% which is the suggested boundary for species delineation [25] . The comparative characteristics of strain HZ254 T , MRE50 T and SANAE T are listed in Table 1 . Interestingly, strain HZ254 T seems to be closer to MRE50 T than SANAE T in major phenotypic traits including temperature range, possession of a flagellum and salinity range, albeit it more resembles SANAE T in regard of 16S rRNA and mcrA genes and ANI. The 16S rRNA gene sequence divergence of 5% between HZ254 T and SANAE T implies that strain HZ254 T could potentially represent a new genus within Methanocellales , given that it is generally considered that a 5 to 7% divergence of 16S rRNA gene sequence is sufficient to delineate different genera [29] . However, the knowledge regarding the physiology of Methanocellales is still quite limited due to the lack of sufficient isolates. In addition, chemotaxonomy [30] , [31] and genome-based taxonomy [32] , [33] is of importance to further discriminate the taxonomy of the three strains of Methanocellales . Therefore, we decide to propose strain HZ254 T as a novel species of the genus Methanocella , Methanocella conradii sp. nov.",
"introduction": "Introduction The order Methanocellales , previously recognized as uncultured archaeal group Rice Cluster I (RC-I), plays a key role in methane production from rice field soils [1] , [2] , [3] . Members of Methanocellales are widely distributed in various environments [1] , which further strengthens their roles in global carbon cycling, especially in those microaerophilic environments [4] . However, despite the early detection by molecular techniques in the late 1990s [5] , pure cultures of RC-I were not obtained until recently due to their slow growth and fastidious culture conditions [6] , [7] , [8] . The first axenic culture, a mesophilic hydrogenotrophic methanogen Methanocella paludicola strain SANAE T , was isolated under low hydrogen concentrations (<30 Pa) from a Japanese rice field soil [9] , [10] . The second isolate, a thermophilic, hydrogenotrophic methanogen Methanocella arvoryzae strain MRE50 T , was purified recently from an enrichment culture which had been established since 2000 [7] , [11] . Many ecological questions of importance that are difficult to solve by culture-independent methods remain to be answered by pure culture studies of Methanocellales . For example, (1) why are members of Methanocellales more active under low hydrogen partial pressures prevailing in their natural habitats in comparison with other methanogens [1] , [12] ? (2) Why do they become predominant at moderate high temperatures while their natural habitats are often mesophilic [13] , [14] ? (3) How are they able to regulate the expression and translation of their antioxidant machinery thus allowing a presumable adaptation to microaerophilic and even oxic environments [2] , [4] , [15] ? However, despite a successful yet difficult isolation of strain SANAE T and MRE50 T and their ecological significance, to the best of our knowledge, no subsequent cultivation of them has been reported. In fact, many workers that we know including ourselves have failed to cultivate those strains. Therefore, the available Methanocellales strains remain difficult to cultivate, and more isolates particularly fast-growing ones are needed to push the studies of Methanocellales forward. Here we report the isolation, physiology and phylogeny of the fastest-growing strain of the order Methanocellales , and propose a new species, Methanocella conradii sp. nov. Its consistency of cultivability is presented as well.",
"discussion": "Results and Discussion Enrichment and isolation Enrichment of strain HZ254 T was directed by both gas and molecular analyses. Measurement of hydrogen consumption and methane formation and T-RFLP analysis based on 16S rRNA genes were performed frequently to monitor the methanogenic activity and the structure of the archaeal and bacterial communities in the enrichment cultures. Cloning and sequencing of the 16S rRNA genes were also conducted occasionally to determine the identity of the predominant archaeal and bacterial groups. Enrichment cultures with neither RC-I as the predominant archaeal group nor significant methanogenic activity were abandoned. The T-RF patterns for the archaeal community along with the successive transfers of the successful enrichments for strain HZ254 T are shown in Figure 1 . The figure demonstrates that RC-I quickly predominated after just the first transfer from pre-incubated soil slurries, and it exclusively represented the sole archaeal member after at most 13 successive transfers over 338 days, albeit a diverse archaeal community was present during the initial pre-incubation. Therefore, besides the low hydrogen method [9] , our results demonstrate that moderate high temperature remains an effective strategy for enrichment of RC-I methanogens, which is consistent with previous studies that RC-I became predominant upon incubation at 45 to 50°C [13] , [14] . Nevertheless, novel methods are needed to increase the cultivability of RC-I. The combination of the two already effective methods (i.e. by inoculating thermophilic propionate- or acetate-degrading syntrophs into samples incubating at 45 to 55°C with propionate or acetate as substrates) would be an approach worth trying, because it may provide a more selective environment for RC-I. Indeed, in both the Chinese and Italian rice field soils, the predominance of RC-I under syntrophic acetate-degrading conditions was observed at 50°C [27] , [28] . 10.1371/journal.pone.0035279.g001 Figure 1 T-RFLP patterns based on 16S rRNA genes for enrichment cultures of strain HZ254 T along with successive transfers. The analysis was performed using Ar109f/915r primer set and TaqI restriction enzymes [14] . T-RFLP fingerprints were normalized to a total of 100 relative fluorescence units (RFU), and T-RF peaks with RFU less than 1 were discarded. The 254-bp T-RF was affiliated with Methanocellales (RC-I) as determined by cloning and sequencing of 16S rRNA genes, and the T-RF length calculated from the sequence was actually 258-bp (data not shown). All other T-RF peaks could be assigned correspondingly to Methanomicrobiales (Mm), Methanobacteriales (Mb), Methanosarcinaceae (Msr)/Crenarchaeotal group 1.1b (G1.1b), Methanosaetaceae (Msa) and RC-I/ Methanomicrobiales (Mm), according to our previous studies in the same soil [14] , [34] , [35] , [36] , respectively. The pre-incubation samples were sampled after 24 hours of incubation, and all other samples were sampled after that methane production ceased and/or hydrogen could not be detected in the headspace. After the 13 th transfer, the archaeal community was still frequently monitored by T-RFLP analysis along with subsequent transfers, but the 254-bp was always the sole T-RF product. Isolation was carried out after the establishment of a stable enrichment culture with RC-I as the sole archaeal group. Deep agar and roll tubes were prepared in an attempt to isolate RC-I colonies. However, colonies formed under standard conditions belonged to bacteria instead of RC-I as screened by 16S rRNA gene sequencing. Therefore, various efforts were made to grow colonies. Firstly, cofactors (e.g. acetate, yeast extract, soil extract, sludge extract and coenzyme M) were supplemented in the medium both individually and in combination. Secondly, agar concentrations of 1.50%, 1.75% and 2.00% were tried. Lastly, antibiotics were included occasionally to eliminate bacteria. The roll tube medium that worked contained 1.50% agar supplemented with 0.05% yeast extract and tryptone and 1 mM acetate. Under these conditions, blue fluorescent colonies of RC-I appeared in several roll tubes after 5 months of incubation, as determined by 16S rRNA gene sequencing. The colonies were picked with Pasteur pipette and further purified by serial dilution in liquid medium supplemented with 200 mg l −1 kanamycin. The purity of the culture was confirmed by four criteria: (1) the failure to grow in anoxic PYG medium; (2) the failure to detect bacterial 16S rRNA gene using the universal bacterial primer pair 27f ( 5′-AGAGTTTGA TCMTGGCTCAG-3′ ) and 907r ( 5′-CCGTCAATTCMTTTRAGTTT-3′ ); (3) a homogenous cell morphology by phase contrast microscopy; (4) homogenous 16S rRNA gene sequences of 27 clones (pair-wise sequence similarity >99.9%) obtained using the universal archaeal primer pair Arc21f/1492r. All results indicated that the HZ254 T culture was axenic. Morphology Colonies of strain HZ254 T were nearly lens-shaped. Both the cells (not shown) and colonies autofluorescenced when excited at 420 nm under an epifluorescence microscope ( Figure 2b ), which is a characteristic feature of methanogens. Single cells were rod-shaped, 1.4–2.8 µm long and 0.2–0.3 µm wide ( Figure 2a ). No specific intracytoplasmic structures (intracytoplasmic membranes, inclusion bodies, etc) were found in the cells ( Figure 2c ). A flagellum was observed after negative staining of the cells ( Figure 2d ), which was consistent with the presence of a fla gene cluster encoding the flagellum in its genome [23] . Therefore, strain HZ254 T is probably motile. However, motility was not observed under our laboratory conditions. Further analyses would be needed to test its motility under different conditions. 10.1371/journal.pone.0035279.g002 Figure 2 Photomicrographs of strain HZ254 T . ( a ) Phase contrast micrograph; ( b ) fluorescence (left) and bright field (right) micrographs of the lens-shaped colony in the same field of view; transmission electron micrograph of ( c ) a thin section and of ( d ) negatively stained cells with flagellum; Bars, 10 µm ( a ); 0.5 mm ( b ); 500 nm ( c ); 1 µm ( d ). Growth requirements Strain HZ254 T utilized H 2 /CO 2 for growth and methane production but not the following tested substrates: 40 mM formate; 20 mM acetate, propionate, lactate or pyruvate; 10 mM methanol, ethanol, 1-propanol, 2-propanol, 1-butanol, 2-butanol or cyclopentanol; and 10 mM methylamine or trimethylamine. Acetate (1 mM) was required as a carbon source for growth. Yeast extract (0.02%) stimulated growth but was not required. Growth parameters, antibiotic and SDS sensitivity Growth for strain HZ254 T was observed at 37 to 60°C with an optimum at 55°C ( Figure S1a ). The upper limit of methanogenesis observed in rice soil samples so far is below 60°C [13] , thus our results suggest a potentially new upper boundary (60°C) for methane emission from rice field soils. However, further studies using environmental samples are still needed to confirm this new boundary. The pH range for growth was between pH 6.4 and 7.2, with an optimum around pH 6.8 ( Figure S1b ). Although a small amount of methane (partial pressure up to 1 kPa) was produced at pH 7.4 over the initial 5 days of incubation, the amount of methane did not increase during a prolonged incubation up to 50 days. The pH remained nearly constant during incubation for most of the treatments. However, at pH 6.8 and 7.2, a slight increase of 0.4 units was observed at the end of the incubation. The strain grew at NaCl concentrations ranging from 0 to 5 g l −1 , the optimum growth occurred at 0 to 1 g l −1 ( Figure S1c ). Under optimal conditions (pH 6.8, 55°C, without NaCl), the doubling time calculated from the methane production rate was 6.5 to 7.8 hours ( Figure S1d ), which was the shortest so far observed in Methanocellales ( Table 1 ). The maximum specific growth rates calculated from both model fitting and linear regression analyses were consistently around 0.1 h −1 ( Figure S1a and S1d ). Strain HZ254 T could tolerate ampicillin, penicillin-G and kanamycin, but not apramycin, neomycin, rifampicin and chloramphenicol. Cells lysed in 0.5% but not under <0.1% of SDS, and intact cells were hardly seen at 1–2% of SDS when observed by a phase contrast microscope. 10.1371/journal.pone.0035279.t001 Table 1 Comparative characteristics of strain HZ254 T and Methanocella paludicola SANAE T and Methanocella arvoryzae MRE50 T . Characteristics HZ254 MRE50 SANAE Cell morphology rod rod, coccoid rod, coccoid Cell width (µm) 0.2–0.3 0.4–0.7 0.3–0.6 Cell length (µm) 1.4–2.8 1.3–2.8 1.8–2.4 GC content (mol %) 52.7 * \n 54.6 (56.7) 54.9 (56.6) Flagellum + + − Temperature range (optimum) (°C) 37–60 (55) 37–55 (45) 25–40 (35–37) pH range (optimum) 6.4–7.2 (6.8) † \n 6.0–7.8 (7) 6.5–7.8 (7) NaCl range (optimum) (g l −1 ) 0–5 (0–1) 0–20 (0–2) 0–1 (0) Doubling time (h) 6.5–7.8 8.0 100.8 \n ANI values (%) \n Versus HZ254 N.A. 69.6 74.8 Versus MRE50 69.4 N.A. 70.5 Versus SANAE 74.8 70.6 N.A. \n Substrate utilization \n H 2 /CO 2 \n + + + Formate − + + Acetate − − − Methanol or Methylamines − − − Secondary alcohols − − − \n Tolerance for antibiotics \n Rifampicin − + − Data for strain HZ254 T is from this study, and strain SANAE T and MRE50 T were retrieved from Sakai et al. , 2008 and 2010. * The data in parentheses were determined by HPLC, other data were taken from genome information [2] , [23] , [24] . † pH for HZ254 T and other strains were determined at 55°C and 25°C, respectively. Abbreviations, −, negative; +, positive; N.A., not applicable. Consistency of cultivability Because of the probable difficulty in cultivation of available Methanocellales species, special focus was paid to assess the cultivable consistency of strain HZ254 T . An excellent consistency for cultivating strain HZ254 T was judged by three empirical standards: (1) the strain could well survive through successive transfers (seven transfers over more than two years, Table S1 ); (2) the strain was able to recover from rather long time of storage at 4°C (the maximum storage time allowing recovery was 502 days so far, Table S1 ); (3) multiple persons within our laboratory could successfully handle the cultivation of the strain. Therefore, strain HZ254 T could serve an excellent starting material for laboratory studies of Methanocellales . GC%, phylogenetic and ANI analyses The DNA G+C content of strain HZ254 T , as determined by genome sequencing, was 52.7 mol% [23] . Strain HZ254 T is affiliated with the order Methanocellales , as revealed by the phylogenetic analyses based on the 16S rRNA and mcrA genes ( Figure 3 and see Figure S2 and S3 for the detailed alignments). The closest relative of strain HZ254 T was M. paludicola SANAE T , having gene sequence identities of 95.0% for 16S rRNA gene and 87.5% (nucleotide level) or 94.1% (amino acid level) for the mcrA gene. The corresponding sequence identities between strain HZ254 T and M. arvoryzae MRE50 T were 92.4–92.5% and 86.5 or 92.0% respectively, and the slight variation for the former values is due to the presence of two slightly different copies of 16S rRNA genes within the genome of strain MRE50 T . Moreover, the calculated ANI values among the three strains of Methanocella based on their complete genome sequences were between 69.4 to 74.8%. 10.1371/journal.pone.0035279.g003 Figure 3 Phylogeny of strain HZ254 T based on (a) 16S rRNA gene and (b) deduced McrA amino acid sequences. The trees were constructed using neighbor-joining method. The McrA tree is based on 155 deduced amino acid positions and Poisson correction. The sequences of Methanopyrus kandleri AV19 T , (AE009439; 516778–518289) and (U57340) were used as out groups for rooting the 16S rRNA gene and McrA trees, respectively. The accession number of each reference sequence is shown after the strain name. The coordinates of the sequence were indicated in parenthesis, if it was taken from the complete genome sequence. Bootstrap support (>50% indicated only) was obtained from neighbor-joining (first value) and maximum-parsimony (second value) based on 1000 replicates. The bar represents the number of changes per sequence position. Taxonomic conclusions The collective traits of strain HZ254 T with regard to its physiology and phylogeny support it as a member of the order Methanocellales . It shares common phenotypic features with the other two strains ( M . arvoryzae MRE50 T and M. paludicola SANAE T ) of Methanocellales , such as the rod-shaped morphology, the growth via hydrogenotrophic methanogenesis and the requirement of acetate as a carbon source. However, they differ in formate utilization, possession of a flagellum, antibiotic susceptibility, temperature range, pH range and salinity range. In addition, the ANI values further distinguish the three strains on the species level, given that they are far below 95 to 96% which is the suggested boundary for species delineation [25] . The comparative characteristics of strain HZ254 T , MRE50 T and SANAE T are listed in Table 1 . Interestingly, strain HZ254 T seems to be closer to MRE50 T than SANAE T in major phenotypic traits including temperature range, possession of a flagellum and salinity range, albeit it more resembles SANAE T in regard of 16S rRNA and mcrA genes and ANI. The 16S rRNA gene sequence divergence of 5% between HZ254 T and SANAE T implies that strain HZ254 T could potentially represent a new genus within Methanocellales , given that it is generally considered that a 5 to 7% divergence of 16S rRNA gene sequence is sufficient to delineate different genera [29] . However, the knowledge regarding the physiology of Methanocellales is still quite limited due to the lack of sufficient isolates. In addition, chemotaxonomy [30] , [31] and genome-based taxonomy [32] , [33] is of importance to further discriminate the taxonomy of the three strains of Methanocellales . Therefore, we decide to propose strain HZ254 T as a novel species of the genus Methanocella , Methanocella conradii sp. nov. Description of Methanocella conradii sp. nov \n Methanocella conradii ( con.rad'i.i. N.L. gen. masc. n. conradii , named after Ralf Conrad, who has pioneered the studies on RC-I methanogens in environmental samples). Cells are rods and occur singly with a flagellum. Methane is produced exclusively from H 2 /CO 2 . Acetate is required for growth and yeast extract can stimulate growth. Growth occurs at 37–60°C (optimum 55°C), at pH 6.4–7.2 (optimum 6.8) and with less than 5 g l −1 of NaCl (optimum 0–1 g l −1 ). The DNA G+C content is 52.7 mol% determined by genome sequencing. The species was isolated from a rice field soil localized in Hangzhou, China. The type strain is HZ254 T ( = CGMCC 1.5162 T \n = JCM 17849 T = DSM 24694 T )."
} | 5,332 |
26689675 | PMC4683866 | pmc | 3,297 | {
"abstract": "Background Microalgae are a potential source of sustainable commodities of fuels, chemicals and food and feed additives. The current high production costs, as a result of the low areal productivities, limit the application of microalgae in industry. A first step is determining how the different production system designs relate to each other under identical climate conditions. The productivity and photosynthetic efficiency of Nannochloropsis sp. CCAP 211/78 cultivated in four different outdoor continuously operated pilot-scale photobioreactors under the same climatological conditions were compared. The optimal dilution rate was determined for each photobioreactor by operation of the different photobioreactors at different dilution rates. Results In vertical photobioreactors, higher areal productivities and photosynthetic efficiencies, 19–24 g m −2 day −1 and 2.4–4.2 %, respectively, were found in comparison to the horizontal systems; 12–15 g m −2 day −1 and 1.5–1.8 %. The higher ground areal productivity in the vertical systems could be explained by light dilution in combination with a higher light capture. In the raceway pond low productivities were obtained, due to the long optical path in this system. Areal productivities in all systems increased with increasing photon flux densities up to a photon flux density of 30 mol m −2 day −1 . Photosynthetic efficiencies remained constant in all systems with increasing photon flux densities. The highest photosynthetic efficiencies obtained were; 4.2 % for the vertical tubular photobioreactor, 3.8 % for the flat panel reactor, 1.8 % for the horizontal tubular reactor, and 1.5 % for the open raceway pond. Conclusions Vertical photobioreactors resulted in higher areal productivities than horizontal photobioreactors because of the lower incident photon flux densities on the reactor surface. The flat panel photobioreactor resulted, among the vertical photobioreactors studied, in the highest average photosynthetic efficiency, areal and volumetric productivities due to the short optical path. Photobioreactor light interception should be further optimized to maximize ground areal productivity and photosynthetic efficiency.",
"conclusion": "Conclusions The performance of different pilot-scale photobioreactor designs under identical conditions was evaluated. Flat panel photobioreactors resulted in high ground areal productivities (≥24 g m −2 day −1 ) and high ground areal photosynthetic efficiencies (≥2.7 %) over 36 days. Average photosynthetic efficiencies for the other systems were: VT; 2.4 %, HT; 1.5 % and ORP; 1.2 %. Vertical photobioreactors resulted in higher areal productivities than horizontal photobioreactors because of the higher light interception and the resulting lower incident photon flux densities on the reactor surface. Among the vertical photobioreactors studied, the flat panel photobioreactor showed the highest average photosynthetic efficiency, areal and volumetric productivities due to its short optical path. Concluding, photobioreactor light interception should be optimized to maximize ground areal productivity and photosynthetic efficiency. This makes vertical photobioreactors promising for large scale production. However, an economical analysis should be made to assess if the higher photosynthetic efficiency and higher areal productivity compensate for the higher investment costs generally associated with vertical photobioreactors.",
"discussion": "Results and discussion Areal productivity and photosynthetic efficiency of four different outdoor photobioreactors operated at different dilution rates were determined. The effect of the photon flux density on the areal productivity for each dilution rate is evaluated. Furthermore, the effect of photon flux density on photosynthetic efficiency is evaluated for all systems studied. The horizontal tubular photobioreactor, vertical tubular photobioreactor, open raceway pond and flat panel were in operation for 111, 102, 42 and 77 days, respectively. During these periods, all four systems were restarted three times due to different reasons. In the tubular photobioreactors this was due to fouling, in the OPR this was due to contamination and growth limiting temperatures (<20 °C). The flat panel was restarted because of clogging of aeration holes, resulting in suboptimal operation. Effect of photon flux density on productivity In Fig. 1 , areal productivities versus photon flux densities are shown for all cultivation systems operated. For all systems, areal productivities increased with higher photon flux densities, indicating cultures could experience light limitation at low photon flux densities. For HT, VT and ORP areal productivities appear to increase linearly with PFD up to 30 mol m −2 day −1 , this has been reported previously by [ 7 – 10 ]. For the flat panel photobioreactor this trend could not be observed, a possible explanation could come from the limited mixing of the culture over the entire reactor. Maximal areal productivities for all systems were obtained above 30 mol m −2 day −1 . Highest areal productivities were obtained with the flat panel photobioreactor. In the vertical tubular system similar areal productivities as in the flat panel photobioreactor were obtained, followed by the horizontal tubular photobioreactor and the raceway pond. The areal productivities in the ORP were low in comparison to the other systems. The large optical path (0.2 m) and long light dark cycles as a result of poor mixing in this system contribute to lower areal productivity [ 11 – 13 ]. Fig. 1 Influence of daily photon flux density and dilution rate on areal productivity. For the horizontal tubular (HT), open raceway pond (ORP), vertical tubular (VT) and flat panel (FP). The different colors of markers indicate the different dilution daily rates In vertical photobioreactors, microalgal cell dissipate less of the absorbed light energy as a result of lower photon flux densities because of light dilution on the reactor surface in comparison to the horizontal systems. Therefore, higher areal productivities were found in vertical systems. The higher photon flux density on the exposed reactor surface of the horizontally oriented cultivation systems results thus in lower areal productivity and photosynthetic efficiency. The short optical path of the flat panel photobioreactor results in small dark zone in the culture; respiration takes place in a small part of the culture. The long optical path in the open raceway pond results in a large dark zone in the culture. [ 11 – 13 ]. In the dark zone microalgae respire energy that otherwise could be used for growth. The presence of a dark zone in a cultivation system will reduce the net productivity of the culture, as part of the culture in the dark has negative growth. A long optical path results in lower productivities (Fig. 1 ) [ 12 , 14 ]. Higher photon flux densities will penetrate deeper in the culture and will decrease the size of the dark zone present in the culture. Variations in areal productivity were larger for all photon flux densities and dilution rates in the flat panel photobioreactor and the open raceway pond than in the tubular systems. The large variations in the flat panel photobioreactor are a result of the plug flow regime moving the culture through each panel. The culture is not mixed well over all panels, while in the other systems the entire culture volume is mixed resulting in less variation in areal productivity. In the open raceway pond the large variation in areal productivity is the result of low culture temperatures and automated level control. The low culture temperatures resulted in suboptimal conditions during a large part of the day, for many days throughout the experimental period. The automated level control in the open raceway pond resulted in negative areal productivity; for days with heavy rainfall, dilution rates were higher than intended because of the automated level control. The variations in areal productivities within the different photobioreactors are a result of variations in biomass concentrations. The biomass concentrations in the different cultivation systems varied as a result of applied dilution rates and photon flux densities. The highest dilution rates in the flat panel photobioreactor (0.4 day −1 ) and open raceway pond (0.24 day −1 ) were only applied for a short period of time, 6 and 11 days, respectively, as these resulted in a strong decrease in biomass concentration. For each cultivation system the average areal productivity was calculated for each dilution rate. These average values were calculated over the summer period to ensure similar values for photon flux density (Fig. 2 ). Fig. 2 Average areal productivity versus dilution rate for each photobioreactor. Flat panel (FP), vertical tubular (VT), horizontal tubular (HT) and open raceway pond (ORP). Average areal productivity was calculated over a number of days for each dilution rate; FP; 6, 3, 40, 4, VT; 18, 39, and 14, HT; 19, 38, and 11, ORP; 22, 13, and 5 The system with the shortest optical path (0.02 m), the flat panel photobioreactor, resulted in the overall highest average areal productivity. The overall lowest average areal productivity was obtained with the open raceway pond, because of the long optical path (0.2 m). The vertical tubular photobioreactor resulted in higher average areal productivity compared to the horizontal tubular. The vertical tubular photobioreactor has a lower photon flux density on the surface of the reactor that penetrates less far in the culture. The horizontal tubular photobioreactor resulted in a higher biomass concentration, as this system receives higher photon flux density. No significant difference in average areal productivity at different dilution rates was found among all cultivation systems with the exception of the flat panel. Effect of photon flux density on photosynthetic efficiency Photosynthetic efficiency (PE sunlight ) is an important parameter for the evaluation of photobioreactor performance. Photosynthetic efficiency is the efficiency at which solar light energy is captured as stored chemical energy in biomass and it allows the estimation of the productivity for other locations if the photon flux density is known. Photosynthetic efficiency was calculated based on the ground areal productivity and ground areal irradiance. At the same ground areal photon flux density, vertical photobioreactors have lower photon flux densities on the surface of the cultivation system than horizontal systems. Lower photon flux densities result in less energy dissipation by microalgal cells in the form of heat, resulting in a higher photosynthetic efficiency. In Fig. 3 , photosynthetic efficiencies versus photon flux densities are shown for all cultivation systems operated. For all systems, photosynthetic efficiencies varied over the range of photon flux densities. Maximal photosynthetic efficiencies were obtained for the three closed photobioreactors below 20 mol m −2 day −1 . Furthermore, the more stable culture temperatures in the closed photobioreactors could have contributed to the higher photosynthetic efficiencies. Highest photosynthetic efficiencies were obtained with the vertical photobioreactors with intermediate dilution rates; 0.2 day −1 for VT and 0.3 day −1 for FP. Lower photosynthetic efficiencies were obtained with the horizontal tubular photobioreactor and the raceway pond. The photosynthetic efficiency is low in the horizontal tubular compared to the other closed systems. Variations in photosynthetic efficiencies were the result of the variations in areal productivities that were discussed before. Fig. 3 Influence of daily photon flux density on photosynthetic efficiencies on sunlight for the different photobioreactors. For the horizontal tubular photobioreactor (HT), open raceway pond (ORP), vertical tubular photobioreactor (VT) and flat panel photobioreactor (FP). The different colors of the squares indicate different dilution rates applied to each different photobioreactor Evaluation of performance For a comparison of the performance of the cultivation systems among each other and with literature average and maximal values, for areal productivity and photosynthetic efficiency, were calculated over summer (Table 1 ). Volumetric productivities were calculated as these are often reported in literature. Table 1 Overview of average and maximal areal and volumetric productivities and average and maximal photosynthetic efficiencies obtained in summer 2013 (July–August) Photobioreactor ORP HT VT FP Avg Max Avg Max Avg Max Avg Max \n P \n x,ground (g m −2 day −1 ) 9.7 14.0 12.1 15.7 19.4 24.4 20.5 27.5 \n P \n x,vol (g L −1 day −1 ) 0.03 0.08 0.65 0.85 0.57 0.71 0.90 1.20 Dilution rate (day −1 ) 0.14 0.12 0.25 0.34 0.27 0.40 0.27 0.36 Number of days 24 8 36 8 36 8 36 4 Photosynthetic efficiency (% sunlight) 1.1 1.5 1.5 1.8 2.4 4.2 2.7 3.8 Dilution rate (day −1 ) 0.16 0.12 0.25 0.28 0.27 0.24 0.27 0.18 Number of days 24 8 36 6 36 9 36 3 Dilution rates are measured values. Maximal areal and volumetric productivities were obtained in a single week in July with a high average photon flux density; 44 mol m −2 day −1 \n The highest average areal productivity was found in the flat panel photobioreactor, followed by the vertical tubular, the horizontal tubular photobioreactor and open raceway pond. Maximal areal productivities for each photobioreactor were obtained in a single week in July with a high average daily photon flux density of 44 mol m −2 day −1 . The highest average photosynthetic efficiency was found for the flat panel (FP) photobioreactor followed by the vertical tubular (VT) photobioreactor, horizontal tubular (HT) photobioreactor and the open raceway pond (ORP). The highest maximal photosynthetic efficiency was found for the VT; followed by the FP, HT and ORP. In the flat panel photobioreactor the highest areal and volumetric productivities and photosynthetic efficiencies were obtained. The highest volumetric productivity obtained for the FP (1.20 g L −1 day −1 ) is higher than values reported in literature, with the exception of data reported by Zou et al., of 1.7 g L −1 day −1 [ 5 ] (Table 2 ). However, this higher volumetric productivity was obtained in a flat panel photobioreactor with a shorter optical path of 1.3 cm, resulting in a higher light supply per volume of culture [ 5 ]. The photosynthetic efficiency obtained in this study for the flat panel photobioreactor is almost double of the values reported by Camacho-Rodriguez et al. for Nannochloropsis gaditana (1.7–0.3 %) and Rodolfi et al. for Nannochloropsis sp. F&M-M24 (0.96 %) [ 15 , 16 ]. Table 2 Overview of volumetric and areal productivities and photosynthetic efficiencies (PE sunlight ) for different photobioreactors outdoors reported in literature Photobioreactor Optical path (cm) Algal species \n P \n x,vol (g L −1 day −1 ) \n P \n x,ground (g m −2 day −1 ) PE sunlight (%) Author Location Horizontal tubular 4.3 \n Nannochloropsis sp. 0.51–0.76 13–19.5 a \n 2.3–3.5 a \n [ 19 ] Italy Horizontal tubular 9.0 \n Nannochloropsis gaditana \n 0.12–0.20 10.8–18.0 0.7–1.04 a \n [ 15 ] Almeria Spain Horizontal tubular 4.6 \n Nannochloropsis sp. 0.30–0.85 5.8–15.7 1.2–1.8 This study The Netherlands Vertical panel 1.2 \n Nannochloropsis sp. 0.61–1.45 5.8–10.2 2.0–3.5 a \n [ 17 ] Artificial light Vertical tubular 10.4 \n Scenedesmus obliquus \n ? 21.76 2.5 a \n [ 20 ] South Spain Vertical tubular 5 \n Nannochloropsis gaditana \n 0.59 15.4 – [ 18 ] Almeria Spain Vertical tubular 4.6 \n Nannochloropsis sp. 0.31–0.71 10.6–24.4 2.4–4.2 This study The Netherlands Raceway pond 30 \n Scenedesmus obliquus \n 0.03 8.26 0.95 a \n [ 20 ] South Spain Raceway pond 30 \n Muriellopsis sp. 0.04 8–20 0.97–0.69 a \n [ 21 ] South Spain Raceway pond 12 \n Nannochloropsis salina \n 0.2 24.5 – [ 23 ] Israel Raceway pond 11 \n Nannochloropsis gaditana \n 0.09–0.19 22.4 – [ 22 ] Almeria Spain Raceway pond 20 \n Nannochloropsis sp. 0.03–0.08 6.2–14.0 0.5–1.5 This study The Netherlands Flat panel 1.3–17 \n Nannochloropsis sp. 1.7–0.25 11–22 – [ 5 ] Israel Flat panel 10 \n Nannochloropsis sp. 0.27 14.2 – [ 28 ] Israel Flat panel 5 \n Nannochloropsis gaditana \n 0.16–0.36 8–18 1.74–0.31 a \n [ 15 ] Almeria Spain Flat panel 4.5 \n Nannochloropsis sp. 0.36 15.8 0.96 a \n [ 16 ] Italy Flat panel 5 \n Nannochloropsis oculata \n 0.15–0.37 – [ 29 ] Colorado, USA Flat panel 2 \n Nannochloropsis sp. 0.9–1.2 20.5–27.5 2.7–3.8 This study The Netherlands The values for the raceway pond and FP for this study were collected in summer 2013. For both tubular photobioreactors average productivities and photosynthetic efficiencies were used to indicate the range of productivities and photosynthetic efficiencies; average data were obtained over the period from July to December 2013 \n a Calculated based on the illuminated area, not considering the ground area occupied by the photobioreactor In the vertical tubular photobioreactor similar photosynthetic efficiencies (2–3.5 %) were obtained as for a modular flat panel system illuminated with artificial light as reported by Zittelli et al., [ 17 ]. In our study a lower volumetric productivity (0.3–0.7 g L −1 day −1 ) was obtained than values reported by Zittelli et al. [ 17 ] because of a larger optical path; 0.05 vs 0.012 m. The larger optical path could result in the formation of a dark zone in our system; resulting in a lower volumetric productivity. In our study a higher areal productivity (24 g m −2 day −1 ) was obtained than the areal productivity reported by Zittelli et al. (10 g m −2 day −1 ). Higher photon flux density than the photon flux density used by Zittelli et al., was measured outdoors, which contributed to the higher areal productivity obtained in our study. San Pedro et al., reported a maximal areal productivity of 15 g m −2 day −1 or 0.59 g L −1 day −1 for Nannochloropsis gaditana at a dilution rate of 0.3 per day [ 18 ]. These values are in the range of the values obtained in this study. Volumetric productivities (0.3–0.85 g L −1 day −1 ) for the horizontal tubular photobioreactor obtained in this study are similar to the volumetric productivities (0.5–0.7 g L −1 day −1 ) reported by Zittelli et al. [ 19 ]. Lower volumetric productivities (0.12–0.2 g L −1 day −1 ) were reported by Camacho-Rodriguez et al., probably due to the larger tube diameter (9 cm). In our design, distance between tubes equals the diameter of the tube (external diameter 5 cm), this results in a lower culture volume per ground area, resulting in lower areal productivities than values reported by Zittelli et al. [ 19 ]. Camacho-Rodriguez et al. found similar areal productivities (10–18 g m −2 day −1 ) as in this study for Nannochloropsis gaditana cultivated in a horizontal tubular photobioreactor [ 15 ]. Areal productivities obtained for the open raceway pond in this study, 6–14 g m −2 day −1 , were lower than the areal productivities reported by Arbib et al. and Blanco et al. (8–20 g m −2 day −1 ), due to the higher photon flux densities at the locations of the studies of Arbib et al. and Blanco et al. [ 20 , 21 ]. Higher photon flux densities penetrate further and reduce the dark zone in a culture. Furthermore, in the south of Spain higher ambient temperatures are present, avoiding low culture temperatures down to 15 °C at night as experienced in our study. San Pedro et al., found maximal volumetric and areal productivity (0.19 g L −1 day −1 and 22.4 g m −2 day −1 ) for shallow (11 cm deep) raceway ponds [ 22 ]; the lower depth results in a smaller dark zone. In the study of San Pedro, higher productivities were obtained at higher photon flux densities and at temperatures close to optimum for growth [ 22 ]. Boussiba et al. reported higher areal productivity (24.5 g m −2 day −1 ) as well for Nannochloropsis salina cultivated in a shallow pond [ 23 ], this indicates that lower culture depth or more light per culture volume results in higher productivity."
} | 5,018 |
27761134 | PMC5051215 | pmc | 3,298 | {
"abstract": "Sulfate reduction is the predominant anaerobic microbial process of organic matter mineralization in marine sediments, with recent studies revealing that sulfate reduction not only occurs in sulfate-rich sediments, but even extends to deeper, methanogenic sediments at very low background concentrations of sulfate. Using samples retrieved off the Shimokita Peninsula, Japan, during the Integrated Ocean Drilling Program (IODP) Expedition 337, we measured potential sulfate reduction rates by slurry incubations with 35 S-labeled sulfate in deep methanogenic sediments between 1276.75 and 2456.75 meters below the seafloor. Potential sulfate reduction rates were generally extremely low (mostly below 0.1 pmol cm −3 d −1 ) but showed elevated values (up to 1.8 pmol cm −3 d −1 ) in a coal-bearing interval (Unit III). A measured increase in hydrogenase activity in the coal-bearing horizons coincided with this local increase in potential sulfate reduction rates. This paired enzymatic response suggests that hydrogen is a potentially important electron donor for sulfate reduction in the deep coalbed biosphere. By contrast, no stimulation of sulfate reduction rates was observed in treatments where methane was added as an electron donor. In the deep coalbeds, small amounts of sulfate might be provided by a cryptic sulfur cycle. The isotopically very heavy pyrites (δ 34 S = +43‰) found in this horizon is consistent with its formation via microbial sulfate reduction that has been continuously utilizing a small, increasingly 34 S-enriched sulfate reservoir over geologic time scales. Although our results do not represent in-situ activity, and the sulfate reducers might only have persisted in a dormant, spore-like state, our findings show that organisms capable of sulfate reduction have survived in deep methanogenic sediments over more than 20 Ma. This highlights the ability of sulfate-reducers to persist over geological timespans even in sulfate-depleted environments. Our study moreover represents the deepest evidence of a potential for sulfate reduction in marine sediments to date.",
"conclusion": "Conclusion pSRR was detected in the deep sediments at IODP Site C0020 off the Shimokita Peninsula, Japan, down to 2456 m below the ocean floor. The potential rates were extremely low but showed a significant increase in the coal-bearing horizon. Although the measured potential rates do not reflect in-situ activity of sulfate reducers, they show that microorganisms capable of employing sulfate reduction are still present in the deep coal-bearing sediments. This represents the deepest persistence of this type of microorganisms in marine sediments to date. The finding highlights the ability of sulfate reducers to survive over geological timespans even in sulfate-depleted environments, which might support the existence of a “paleome.” After having survived over more than 20 million years after burial, it might well be that sulfate reducers in the coalbeds to date have entered a dormant, spore-like state and were reactivated by the supply of excess sulfate during our incubations. Nevertheless, it is suggested from the strongly δ 34 S-enriched pyrite present in the coals, that they have been active long after burial and it might even be that a small fraction is still active operating at extremely low rates. The organic matter rich habitat provides significant amounts of energetically rich substrates (volatile fatty acids, methane, and hydrogen) and the availability of the electron acceptor sulfate is the obvious limitation for the survival of deeply buried sulfate reducers in the coalbed biosphere. A slow recycling of sulfate by Fe(III) might provide trace amounts of sulfate via re-oxidation and disproportionation and may have prevented a small population from dying out.",
"introduction": "Introduction Sulfate reduction is a globally important microbial process in anoxic marine sediments (Canfield, 1991 ; Jørgensen and Kasten, 2006 ; Bowles et al., 2014 ). It is an important pathway for carbon recycling in the seabed and represents the predominant terminal process of carbon remineralization in sulfur-rich marine shelf sediments (Jørgensen, 1982 ). From the overlaying seawater, sulfate diffuses downwards into the sediments where it can serve as an electron acceptor for microbial sulfate reduction. Diffusion and microbial turnover result in a concentration gradient from ~28 mmol L −1 at the sediment surface down to a few μmol L −1 , which determines the bottom of the sulfate zone (Froelich et al., 1979 ; Berner, 1981 ; Jørgensen and Kasten, 2006 ). The sulfate methane transition zone (SMTZ) marks the end of the sulfate zone and the onset of the methane zone, where methane is diffusing upwards from deeper sediments in which methanogens predominate (Iversen and Jørgensen, 1985 ). At the SMTZ, methane is oxidized by methane-oxidizing sulfate-reducing microorganisms (Barnes and Goldberg, 1976 ; Treude et al., 2005 ; Caldwell et al., 2008 ). In the sulfate reduction zone, sulfate-reducing microorganisms typically outcompete methanogens for shared energy substrates, such as H 2 and acetate, by bringing the concentrations of these compounds to such low levels that methanogenesis is not thermodynamically feasible (Hoehler et al., 1998 , 2001 ). Nonetheless, small populations of methanogens are ubiquitous in sulfate-reducing sediment, and typically consist of methanogens that are capable of metabolizing “non-competitive substrates,” i.e., C 1 compounds, such as methanol, methylamines, and methyl sulfides, which are not utilized by most sulfate reducers (Oremland and Polcin, 1982 ; Orsi et al., 2013 ; Watkins et al., 2014 ). Similarly, in recent studies, sulfate reduction was also detected in methane zones, operating at low background concentrations of sulfate (Leloup et al., 2006 ; Holmkvist et al., 2011 ; Treude et al., 2014 ; Brunner et al., 2016 ; Orsi et al., 2016 ). This shows that although there is a general zonation of predominant microbial processes in the sediment column determined by pore water chemistry and thermodynamics, this zonation is not absolute and exceptions are common. When substrate concentrations and concomitantly the available energy for the microbial activity decrease, microbes slow down their metabolism, and biomass turnover to generation times of several 100 years (Lomstein et al., 2012 ; Hoehler and Jørgensen, 2013 ). However, slow turnover rates and long generation times also reduce the speed of necessary cellular maintenance processes, such as DNA and protein repair (Johnson et al., 2007 ; Morita et al., 2010 ; Lever et al., 2015 ). Increasing burial depth does not only lead to exhaustion of energy-rich substrates but also leads to increasing damage rates as sediment temperature increases (Lever et al., 2015 ). Recently it was discovered that, despite the slow metabolic rates in the deep biosphere, the expression of DNA repair genes increases with sediments depth (Orsi et al., 2013 ), highlighting the increased importance of damage repair for microorganisms in deeply buried sediments. Consequently, there is a balance of available substrates providing the metabolic energy for necessary maintenance of basic cell functions and environmentally induced damage that marks the boundary between life and death. A potential strategy for microbial life to cope with periods of starvation is the formation of endospores (Schrenk et al., 2010 ; Lomstein et al., 2012 ). In this dormant stage of life, the cell has formed a metabolically inactive endospore that will only germinate when conditions become more supportive of growth. However, it is questionable if such a strategy helps to increase survival as damage to the cell will continue to occur and nutrient supply is greatly limited in the deep biosphere. Nevertheless, endospores might persist over long timespans in nutrient limited sedimentary environments. The deeply buried coalbeds off Shimokita explored during the Integrated Ocean Drilling Program (IODP) Expedition 337 represent a very unique environment to investigate the boundaries of microbial life in deep subsurface sediments. Several layers of thermally immature lignites were buried sub-adjacent to marine sediments and contain energy-rich potential substrates that may create oases of life in the deep subseafloor (Fry et al., 2009 ; Glombitza et al., 2009b ). Microbial life discovered in the Shimokita coalbeds consists mainly of persisters of microbes that initially inhabited the ancient forest soil and that have survived more than 20 Ma of burial (Inagaki et al., 2015 ). Cell numbers are extremely low in these deep sediments (1–10 cells cm −3 ) but are elevated up to ~1000 cells cm −3 in the coal bearing horizons. The increased temperature of >45°C most likely causes difficulties for microbial survival as DNA depurination and amino acid racemization reactions increase dramatically at these temperatures (Inagaki et al., 2015 ; Lever et al., 2015 ). The increased abundance of potential substrates in the organic matter-rich lithologies might, however, provide a large energy reservoir to sustain microbial life operating at its limits. Little is known about the variety of in-situ metabolic processes occurring in these sediments. Based on high concentrations of methane with an isotopic signature that indicates a biogenic origin, methanogenesis is an important metabolic process, however, the potentially huge availability and variety of electron donors might also enable other biotic processes. In this study, we investigated sulfate reduction by measurements of potential sulfate reduction rates (pSRR) in the Shimokita coalbeds using the radio-tracer ( 35 SO 4 2 − ) incubation technique (Jørgensen, 1978 ; Røy et al., 2014 ). The aim of this study was to reveal whether sulfate-reducing microorganisms were able to persist in the deeply buried, sulfate-depleted sediments over several millions of years of burial. In this context, we discuss the availability of potential electron donors (volatile fatty acids, methane, hydrogen), as well as the electron acceptor sulfate using the concentrations and isotopic composition of solid phase sulfur fractions, in particular of pyrite, in these deep coal-bearing sediments.",
"discussion": "Discussion Potential sulfate reduction rates in the deep coalbeds The highest rates of sulfate reduction are typically found in near-surface sediments (the upper 10's of centimeters up to a meter sediment depth) and decrease with depth in an exponential manner (Jørgensen, 1977 , 1982 ; Jørgensen and Parkes, 2010 ). This general pattern was also observed in the near-surface sediments at Site C0020 retrieved during the shakedown cruise CK 06-06 (Figure 2A ). The significant increase of pSRR in incubations with amended methane between 4 and 12 mbsf indicates the occurrence of AOM in the SMTZ (Barnes and Goldberg, 1976 ; Iversen and Jørgensen, 1985 ; Caldwell et al., 2008 ). However, the detection of pSRR in the deep samples between 1500 and 2456.75 mbsf was surprising because pore water sulfate was likely depleted already in much shallower and younger sediments similar as observed in the shallow cores retrieved during the CK 06-06 cruise (Tomaru et al., 2009 ). Persisting sulfate reducers in the deep sediments off Shimokita thus would have remained metabolically intact over long periods of starvation at no or only trace amounts of sulfate. However, our finding shows that the deep sediments host microorganisms capable of sulfate reduction even after 20–25 million years of burial. In addition to nutrient availability in the deep sediments (which is discussed further in the following sections) resulting in energetic limits of life in the deep biosphere (Lever et al., 2015 ; Jørgensen and Marshall, 2016 ), the sulfate reducing microorganisms buried in the deep sediments offshore Shimokita have to cope with physiological effects of increasing pressure and temperature. Increasing pressure affects e.g., motility, cell division, DNA replication, transcription, translation, or certain enzymatic reactions (Marietou and Bartlett, 2014 ) and increasing temperature has recently been shown to increase damage of cell walls and DNA by protein racemization and DNA depurination reactions (Lever et al., 2015 ). In a recent study, sulfate reducers isolated from deep and hot (~60°C, 30 MPa) sediments at the Juan de Fuca Ridge showed adaptation to the increased pressure and temperature e.g., by exchanged membrane lipid composition and an increase of their optimum growth temperature (Fichtel et al., 2015 ). The measured potential rates in the deep samples (0.02–1.75 pmol cm −3 d −1 ) were among the lowest sulfate reduction rates measured so far (around 0.1 pmol cm −3 d −1 ; Jørgensen and Marshall ( 2016 ), Parkes et al. ( 1990 ), and references therein). The detectability of such low sulfate reduction rates was a result of our optimized long incubation times and the high initial radioactivity (3.7 MBq) incubated in each sample. The highest potential rate, observed in the Unit III that contained the coal beds was at the level of the lowest rates measured in the deepest samples from the CK06-06 cruise at ~350 mbsf (Figure 2A ). It is important to note that the rates measured in our incubation experiments are not in-situ rates. It has been demonstrated that making sediment slurries affects the measured rates and the results differ from incubations of sub-cores where the original sediment structure remains undisturbed (Jørgensen, 1978 ; Meier et al., 2000 ). An important factor is also that the sediment slurries were amended with 1 mmol L −1 sulfate to maintain a sufficient background concentration of sulfate to avoid immediate turnover of the carrier-free 35 SO 4 2 − tracer, which would result in false positive rates. This background concentration is a significant difference from the natural conditions in the deep sediments at Site C0020, where pore water sulfate is assumed to be depleted. The chosen incubation time (10 days) was rather long and in combination with the elevated sulfate concentration in the slurries, it is likely that sulfate-reducers have been stimulated during incubation. The sulfate-reducers might have been present only as spores in these sediments and the incubation experiment might have triggered germination. It has been shown previously that spores are frequently abundant in marine sediments with numbers equal to those of vegetative cells (Lomstein et al., 2012 ). In fact, spore-like particles were also detected by microscopic observations in the deep sediment samples (Inagaki et al., 2015 ). However, even if the sulfate reducers have only survived in a dormant, spore-like state, our results indicate the capacity for microbial sulfate reduction in the very deep sediments and provide evidence for the deepest occurrence of sulfate reducers in sediments to date. Availability of potential electron donors It is remarkable that the pSRR were elevated in the Unit III where the coal beds are located. It suggests that a larger number of sulfate reducers have survived in that particular, organic matter-rich sediment zone. The most important electron donors for sulfate reduction in anoxic sediments are organic acids such as volatile fatty acids (Sørensen et al., 1981 ; Christensen, 1984 ; Finke et al., 2006 ; Glombitza et al., 2015 ) and amino acids, which have been found to be actively cycled in the subsurface (Lomstein et al., 2012 ), especially by sulfate reducing bacteria (Parkes et al., 1994 ; Orsi et al., 2016 ). Volatile fatty acids are primary products of fermentation. As intermediates in the microbial mineralization of organic carbon in the sediments, their concentrations in the pore water especially in surface-near sulfate reducing sediments are usually relatively low, a result of their fast turnover (Sansone and Martens, 1982 ; Glombitza et al., 2014 , 2015 ). In sediments where the turnover is slow or even prevented, volatile fatty acids can, however, accumulate and are found in higher concentrations (e.g., Martens, 1990 ; Wellsbury et al., 1997 ; Dhillon et al., 2005 ; Heuer et al., 2009 ). Substantial concentrations of volatile fatty acids have been found in water extracts of organic matter-rich sediments, in particular from coals and organic matter rich shales (Bou-Raad et al., 2000 ; Vieth et al., 2008 ; Zhu et al., 2015 ). Coals contain high amounts of macromolecular organic matter (Vandenbroucke and Largeau, 2007 ; Vu et al., 2009 ). Especially in low maturity coals, this macromolecular organic matter contains significant amounts of oxygen bearing functional groups, such as esters (Glombitza et al., 2009a , 2016 ) and ethers (Glombitza et al., 2011 ). In a previous study we showed that lignites can release acetate and formate from the macromolecular organic matter network during ongoing maturation in rates that are sufficient to sustain deep microbial life (Glombitza et al., 2009b ). Such a constant supply of volatile fatty acids may provide electron donors for sulfate reduction in the deeply buried coalbeds. In addition to organic acids, the sediments in Unit III are characterized by high amounts of methane (Inagaki et al., 2015 ). Methane can be oxidized by sulfate reduction in the deep sediments at Site C0020, in a similar fashion as it was observed by increased sulfate reduction rates in the SMTZ at 4–12 mbsf. The observation that no difference between incubations with and without amendment of methane to the headspace was found during incubations of the deep samples suggests that sulfate reduction at depth is not coupled to AOM. However, the coal bearing sediments have excess methane, and combined with the high adsorption affinity of hydrocarbons (including methane gas) in the microporous coal matrix (Clarkson and Bustin, 2000 ; Strapoc et al., 2007 ), splits from these samples might have led to methane-saturated incubation slurries in all incubations containing higher amounts of lignite. In this case, the pSRR from the coal-bearing Unit III might indeed reflect methane-driven sulfate reduction. Another important electron donor utilized in microbial sulfate reduction is hydrogen (Lovley and Goodwin, 1988 ; Lovley and Chapelle, 1995 ; Hoehler et al., 1998 ), which was suggested to be of increased importance in deep sediments (Adhikari et al., 2016 ). Especially in deep methanogenic sediments (Schink, 1997 ) or in sediments lacking sufficient organic matter (Chapelle et al., 2002 ; Nealson et al., 2005 ) microbial processes were found to be dominated by hydrogen utilization. Usually hydrogen concentrations in shallow, relatively active sediments remain low as a result of the fast turnover rates (Hoehler et al., 2001 ). In contrast, at Site C0020 the concentrations of dissolved hydrogen below 1500 mbsf are relatively high with up to 500 μM (Inagaki et al., 2015 ; Figure 4B ), pointing to very slow turnover rates and decoupling of hydrogen producing and consuming processes; the onset of such decoupling starts already in the shallower subsurface (Lin et al., 2012 ). As a result of the high hydrogen concentrations, Gibbs energy yield of hydrogenotrophic methanogenesis at Site C0020 is more negative (i.e., ~−100 kJ mol −1 ) than previously reported for deep sediments, and the combined carbon and hydrogen isotopic compositions of methane support its production by hydrogenotrophic methanogenesis (Inagaki et al., 2015 ). Gibbs energy yield for hydrogenotophic sulfate reduction should be highly negative as well, even at very low sulfate concentrations. However, Gibbs energy yield from sulfate reduction cannot be calculated due to the lack of pore water sulfide and sulfate concentrations. An indication of hydrogen utilization might be found in the hydrogen oxidation rates measured by the tritium assay (Figure 4A ). The measured hydrogen oxidation rates reflect the activity of hydrogenases in the sediment (Adhikari et al., 2016 ). Hydrogenases form a diverse group of enzymes that are employed by microorganisms for both, hydrogen production (e.g., in fermentation) or hydrogen utilization. Thus, the increase in hydrogen oxidation rates observed in the Unit III might partly be the result of increased fermentation but at the same time the rates might indicate increased hydrogen consumption. The increase in hydrogenase enzyme activity in Unit III is not reflected by a significant increase in hydrogen concentrations. This suggests increased turnover of hydrogen in the coal-bearing unit. The fact that this increase was observed in the same depth interval as the increase in pSRR might point to potential hydrogenotrophic sulfate reduction. This is consistent with the observation that sulfate reducers were found to express hydrogenases in deeply buried sediments such as the carbon-monoxide dehydrogenase, as recently reported from the Peru Margin subseafloor (Orsi et al., 2016 ). There are several potential electron donors for sulfate reduction (volatile fatty acids, amino acids methane, and hydrogen) that are presumably or evidently available in high amounts in the deep sediments at Site C0020. They are all released by biotic and abiotic degradation of organic matter and their high abundance relates to the high organic matter concentrations in the coals. Thus, sulfate reduction in the deep coalbed biosphere is obviously not electron donor limited. Availability of the electron acceptor sulfate The availability of the electron acceptor sulfate is most likely the limiting factor for the occurrence of in-situ activity and presence of sulfate reducers at depth in Site C0020. Sulfate concentrations in the pore water obtained from the deeper samples of the CK06-06 cruise were between 0.1 and 0.3 mmol L −1 , or below detection (Tomaru et al., 2009 ). Thus, the deep sediments drilled during IODP Expedition 337 are most likely almost sulfate-free or contain sulfate only in trace amounts. Sulfate concentrations measured in pore water samples from the deep drill cores were used as an indicator for a potential contamination of the pore water sample by seawater-containing drill mud (Inagaki et al., 2013 ). This approach was furthermore justified by the observation that the highest amounts of sulfate in pore water samples were found in samples, in which a contamination assay involving perfluorocarbon tracer indicated contamination (Lever et al., 2006 ; Inagaki et al., 2013 ). Recently, it has been shown that sulfate reducers can persist also in methane bearing sediments below the SMTZ (Leloup et al., 2007 , 2009 ) in sediments where trace amount of sulfate can be generated enabling a reductive sulfur cycling (Brunner et al., 2016 ). It was demonstrated that sulfate reduction occurs at low rates (0.2–1 pmol cm −3 d −1 ) also in the methane zone at constantly low background sulfate concentrations below 0.5 mmol L −1 (Holmkvist et al., 2011 ). It was speculated that the sulfate reduced in this depth was regenerated in a “cryptic sulfur cycle” by which the sulfide produced by microbial sulfate reduction is partly re-oxidized to sulfate in the presence of deeply buried Fe(III). In the sediments at Site C0020, glauconite was identified (Inagaki et al., 2013 )—a Fe(III) source that can further be reduced to the final product pyrite via sulfide oxidation to thiosulfate by Fe(III) and subsequent disproportionation to sulfide and sulfate (e.g., Canfield and Thamdrup, 1994 ). The reduced Fe(II) can then form pyrite in the reaction with sulfide (Berner, 1970 , 1984 ) whereas the sulfate is available for microbial reduction. By this process, part of the sulfate might be recycled and help to drive sulfate reduction in the deep sediments. As recently reported from Peru Margin sediments, the oxidation of sulfide via Fe(III) in the sediments may also be mediated by chemolithoautotrophic sulfur oxidizers (Orsi et al., 2016 ). It is interesting that the AVS fraction (e.g., the iron monosulfides) was at such low concentrations (Figure 3A ), because in sulfide limited and iron rich sediments the metastable monosulfides are usually more abundant (Kasten et al., 1998 ). However, the in-situ sulfate reduction rates in the deep sediments off Shimokita are probably extremely low, considerably lower than the potential rates that we have measured in the slurry incubations. Such low rates might simply not significantly increase the AVS fraction and the slowly forming FeS may transform into pyrite at a similar pace. The major sulfur fraction in the sediments was the CRS fraction comprising mainly the pyrites (Figure 3B ). It is remarkable that CRS concentrations in Unit III seem to be lower than in the overlaying sediments. This can, however, simply be a result of the accumulation of the pyrite in large granules and pyrite veins found in the coalbeds (Figure 5 , and the movie clip showing a CT scan of core 30R-2, https://figshare.com/s/6ac50e6f31d5ce0b45f3 ). The analysis of the CRS fraction in bulk sediment samples might have captured only the low amounts of dispersed pyrite. Figure 5 Colored x-ray computer tomography pictures of a 34 cm long core segment of core 30R-2 showing vertical pyrite veins and pyrite granules . (A) Vertical picture with indications of the positions of horizontal panels (B–E) . (B) Patchy pyrite precipitates, (C) Multiple vertical pyrite veins, (D) Mud-coal interface with small pyrites, (E) multiple pyrite veins in coal cavities. The distribution of sulfur isotopes revealed highly 34 S-enriched sulfur in the CRS fraction (up to +45.6‰). This points to the formation of CRS in deeper sediments (Zaback and Pratt, 1992 ) from the reduction of isotopically enriched sulfate that had already experienced intense sulfate reduction in the sediment horizons overlaying the coal beds. In general, pyrites formed in coals can retain a large variability in δ 34 S ranging from approximately −15 to +27‰ (e.g., Price and Shieh, 1979 ). Smith and Batts ( 1974 ) described the occurrence of isotopically enriched pyrite in coalbed that were overlain by marine sediments and explained this by the reduction of sulfate that has diffused downwards and was already isotopically enriched during microbial reduction in the marine sediments. In sediments from the Black Sea, Jørgensen et al. ( 2004 ) showed that pyrite enriched in 34 S (up to +33‰) can be formed during AOM of residual pore water sulfate with high δ 34 S (+43‰). Additionally, Canfield ( 2001 ) showed that the fractionation between sulfate and sulfide during microbial sulfate reduction diminishes at low sulfate concentrations. In our study, the isotopically heavy pyrite with δ 34 S > +45‰ in the Shimokita coalbeds might be explained by continuous sulfate reduction of an increasingly smaller, increasingly 34 S-enriched sulfate reservoir. Although we cannot determine when exactly the pyrites in the Shimokita coalbed have been formed it is obvious that this has continued over long time scales and consequently also long after burial, as also suggested by the pSRR data. The findings of sulfate reducers with DNA from ancestral cell lines in ~100 Ma old black shales led to the discussion of a “paleome,” a pool of ancient DNA and/or descendants preserved in the sediments by living microorganisms buried millions of years back in time which thus can provide insights into ancient forms of life (Inagaki et al., 2005 ). The finding of cells capable of sulfate reduction more than 20 Ma after burial in the sediments offshore Shimokita highlights the ability of sulfate reducers to persist in sediments over geological timespans even in sulfate-depleted environments. Although our data only capture a few tens of millions of years, this observation might support the “paleome” concept."
} | 6,970 |
26787827 | PMC4725000 | pmc | 3,299 | {
"abstract": "ABSTRACT Oil reservoirs are major sites of methane production and carbon turnover, processes with significant impacts on energy resources and global biogeochemical cycles. We applied a cultivation-independent genomic approach to define microbial community membership and predict roles for specific organisms in biogeochemical transformations in Alaska North Slope oil fields. Produced water samples were collected from six locations between 1,128 m (24 to 27°C) and 2,743 m (80 to 83°C) below the surface. Microbial community complexity decreased with increasing temperature, and the potential to degrade hydrocarbon compounds was most prevalent in the lower-temperature reservoirs. Sulfate availability, rather than sulfate reduction potential, seems to be the limiting factor for sulfide production in some of the reservoirs under investigation. Most microorganisms in the intermediate- and higher-temperature samples were related to previously studied methanogenic and nonmethanogenic archaea and thermophilic bacteria, but one candidate phylum bacterium, a member of the Acetothermia (OP1), was present in Kuparuk sample K3. The greatest numbers of candidate phyla were recovered from the mesothermic reservoir samples SB1 and SB2. We reconstructed a nearly complete genome for an organism from the candidate phylum Parcubacteria (OD1) that was abundant in sample SB1. Consistent with prior findings for members of this lineage, the OD1 genome is small, and metabolic predictions support an obligately anaerobic, fermentation-based lifestyle. At moderate abundance in samples SB1 and SB2 were members of bacteria from other candidate phyla, including Microgenomates (OP11), Atribacteria (OP9), candidate phyla TA06 and WS6, and Marinimicrobia (SAR406). The results presented here elucidate potential roles of organisms in oil reservoir biological processes.",
"introduction": "INTRODUCTION Study of the deep subsurface has been limited by access to samples suitable for microbial characterization. However, the infrastructure and sampling techniques developed for oil and gas exploration and recovery enable investigations of deep subsurface life. Petroleum reservoirs are unusual environments due to their combinations of very high carbon compound concentrations, elevated temperatures in deeper locations, and long history of separation from surface inputs (although this changes as soon as the reservoir is drilled). The metabolic capacities of individual organisms in these environments, their survival strategies, and intracommunity interactions may influence some chemical and physical characteristics of oil reservoirs. The types of organisms and their roles in hydrocarbon transformations likely vary over the range of different environmental conditions that occur in oil fields. For example, certain microorganisms degrade short-chain hydrocarbons ( 1 – 5 ), converting light to heavy crude oil that is harder to recover. Heavy oils yield less gasoline and diesel fuel and have a more negative impact on the environment during refining ( 6 ). Natural gas from petroleum reservoirs primarily consists of methane, with small amounts of alkanes, carbon dioxide, nitrogen, and hydrogen sulfide. When sulfate or other sulfur compounds are present, sulfidogenic bacteria and archaea can produce hydrogen sulfide ( 7 ). Overall, microbial production of H 2 S leads to petroleum reservoir souring and has significant economic impacts, in part related to worker health and pipeline corrosion ( 3 , 4 , 8 , 9 ). From the perspective of oil field management, understanding reservoir microbiology, as well as processes that minimize the activities of H 2 S-producing bacteria and archaea, may have important long-term economic benefits. There have been many studies of microbial consortia in oil field environments ( 10 – 34 ). These have used culture-based ( 16 – 21 ), 16S rRNA gene-based culture-independent ( 10 , 20 , 22 – 33 ), and metagenomic ( 10 , 27 , 30 , 34 ) methods. A prior 16S rRNA gene-based PhyloChip study that examined the Alaska North Slope oil field samples studied here identified organisms that may contribute to methane and hydrogen sulfide production and hydrocarbon degradation ( 32 ). Although a number of organisms from lineages lacking cultivated representatives were identified, the full diversity and functional capacities of these organisms remained uncertain. Prior metagenomic analyses of microbial community composition from other systems involved extraction and sequencing of genomic DNA of coexisting organisms ( 10 , 30 , 34 ). Two of these investigations applied relatively small-scale (<1 Gbp) DNA sequencing to two samples from an oil reservoir on the Norwegian Continental Shelf. The authors identified sulfate-reducing bacteria, methanogenic archaea, and fermentative bacteria and concluded that genetically similar organisms occurred in both samples, although at different abundance levels. An et al. investigated diverse hydrocarbon-containing samples, and obtained 10 small (<1 Gbp, from various locations) and 2 larger (>1 Gbp, from coal beds) metagenomic datasets, including one small-scale library from a cool (30°C) and shallow (850-m) oil reservoir in Alberta, Canada. The authors found a surprisingly high proportion of genes for enzymes involved in aerobic hydrocarbon metabolism in several samples, while there were more genes for anaerobic hydrocarbon metabolism and methanogenesis in the oil reservoir sample ( 34 ). A recent study sequenced fosmid libraries to analyze hydrocarbon degradation pathways in an enrichment culture ( 35 ), and an older study ( 27 ) used both 16S rRNA gene amplicon sequencing and fosmid library sequencing to investigate produced water from a mesothermic petroleum reservoir. In this study, we used genome-resolved metagenomic analyses of gigabase-pair-scale sequence datasets for six samples from two North Slope oil fields in Alaska. Compared to 16S rRNA gene profiling, metagenomic analysis provides information about potential microbial physiology. The method also has significantly higher taxonomic resolution, capturing species- and strain-level variants present in natural communities. Furthermore, the approach can detect organisms whose 16S rRNA gene sequences escape detection due, for example, to primer mismatch ( 36 ). Our objectives were to identify the organisms in each sample, to compare samples across the range of physical and chemical conditions and to predict metabolic roles based on de novo recovery of draft genomes for the more abundant organisms. Included within the analysis were samples from different depths and temperatures, with or without hydrogen sulfide production (souring), that had or had not been impacted by seawater injection. The results clearly differentiated consortia from different sampling sites, revealed potential metabolic processes, and uncovered potential roles for candidate phyla in biogeochemical transformations in petroleum reservoirs.",
"discussion": "RESULTS AND DISCUSSION Temperature is one of the key factors that shape the community. Fifty-seven unique 16S rRNA gene sequences (with a minimum length of 960 bp) were reconstructed using EMIRGE. The results indicate the presence of both bacteria and archaea in samples SB1, SB2, K2, K3, and I2 but only bacteria in I1 ( Fig. 1 and 2). The highest-temperature Ivishak samples (I1 and I2) are each dominated by one organism (>95% relative abundance) ( Fig. 1 ; also, see Fig. S1A and B in the supplementl material), Thermoanaerobacter and Desulfonauticus sp. ( Desulfohalobiaceae ), respectively. The number of nearly full-length sequences recovered by EMIRGE for samples K2 and K3 is low (three to four sequences each). In contrast, many more sequences were recovered from SB1 (28 sequences) and SB2 (18 sequences). FIG 1 Dominant microbial community member groups and their relative abundances based on full-length 16S rRNA gene sequences (>960 bp) reconstructed by using EMIRGE ( 76 ). Currently named bacterial phyla were grouped in Bacteria_other (grey), whereas candidate phyla are shown separately (red). The category “methanogen” (yellow) includes several archaeal sequences affiliated with various methanogens. From all of the assembled datasets, we recovered 30 full-length and 30 partial 16S rRNA gene sequences (>300 bp) from bacteria and archaea, including many from organisms in candidate phyla. The sequences from candidate phyla primarily derived from the Schrader Bluff genomic datasets. Specifically, we recovered sequences from Marinimicrobia (SAR406, class AB16), Parcubacteria (OD1), candidate phylum TA06 ( 37 ), Atribacteria (OP9), candidate phylum WS6, and Microgenomates (OP11). However, one full-length 16S rRNA gene of Acetothermia (OP1) was recovered from K3. The overall community structures, based on the combined EMIRGE and contig 16S rRNA gene analysis ( Fig. 2 ), are in agreement with PhyloChip results reported previously for the same samples ( 32 ). However, the prior study failed to detect archaea in Ivishak samples (I1 and I2) using their standard PCR conditions (primers 4Fa and 1492R, 2 µl template, 30 cycles). Additionally, bacteria in the candidate phyla OP1 (Kuparuk), OP11 (Schrader Bluff), and TA06 (Schrader Bluff) were not reported. There were no sequences classified as OP1 or TA06 in the taxonomy used when probes were designed for the G3 PhyloChip, and there was only one sequence noted as being included in a “former candidate division OP11,” but that operational taxonomic unit (OTU) was not detected in the data set. FIG 2 Phylogenetic tree (constructed using the RAxML method [ 84 ] in the ARB software package [ 85 ]) illustrating microbial communities represented by 16S rRNA genes. The sequences most closely related to those recovered in this study were included from the Silva database ( 86 ). Sequences recovered from Ivishak, Kuparuk, and Schrader Bluff samples were colored in groups of green, red, and purple, respectively (dark green, sample I1; light green, sample I2; dark red, sample K2; light red, sample K3; dark purple, sample SB1; light purple, sample SB2). Closely related reference sequences are in black. The relative abundances of organisms (calculated based on the fraction of reads for any sample that were binned to specific genomes and normalized based on estimated genome size) also agreed with the observation that as temperature increased, the microbial community appeared to be less complex and dominated by a few organisms (see Fig. S1A to F in the supplemental material). Inference of major biogeochemical functions and metabolite roles by recovered genomes. Our analyses focused on 37,933 assembled genome fragments (scaffolds) >2,000 bp in length, a total of 227 Mbp of reconstructed genomic sequences (see Table S2 in the Text S2 file in the supplemental material). We recovered 3 to 50 draft (partial and nearly complete) genomes for bacteria and 0 to 13 draft genomes for archaea per sample (see Table S3 in the Text S2 file in the supplemental material). Subsequent analyses of the potential roles microbial community members played in different geologic formations and souring environments are based on these genomes (although many other scaffolds were assigned to plasmids and phage). Based on homology of conserved proteins, some genomes have very closely related sequences to the genomes in public databases (see Table S4 in the Text S2 file in the supplemental material). (i) Ivishak Formation. Samples I1 and I2 were both from 80 to 83°C Ivishak Formation produced water. I1 was not considered soured, whereas I2 was the most soured (200 mg/liter sulfide) of the samples analyzed in this study (see Table S1 in the Text S2 file in the supplemental material). Consistent with the prediction from the 16S rRNA data (see above), almost 90% of the sequences from Ivishak sample I1 were assigned to two high-quality genomes and one partial genome. This sample was almost entirely dominated by a Thermoanaerobacter organism ( Fig. 1 ; also, see Fig. S1A in the supplemental material). Based on the genome data, we identified the organism as Thermoanaerobacter thermocopriae (see Table S4 in the Text S2 file in the supplemental material). We expected that this highly dominant organism would have metabolic attributes consistent with the geochemistry of this well. The dissimilatory sulfate reduction pathway is absent from the reconstructed genome, consistent with I1 not being soured (see Table S1 in the Text S2 file in the supplemental material). The Ivishak sample I2 also was highly dominated by one organism ( Fig. 1 ; also, see Fig. S1B in the supplemental material), a Desulfonauticus sp. (the 16S rRNA gene is 99% identical to that of Desulfonautics autotrophicus DSM 4206, a thermophilic, sulfate-reducing organism isolated from oil production water [ 38 ]). Additionally, both methanogenic and nonmethanogenic archaea were present. Notably, a partial genome for Archaeoglobus fulgidus (not reported previously [ 32 ] because only bacteria were profiled for Ivishak samples in the previous study) was recovered. The 1,492-bp 16S rRNA gene from this organism is 99.46% identical to that of Archaeoglobus fulgidus . This soured sample has a longer history of seawater injection than I1, and the sulfate availability of I2 produced water was still high (611 mg/liter) (see Table S1 in the Text S2 file in the supplemental material) ( 32 ). There are three major sulfate reducers in this sample ( Desulfonauticus , Thermodesulfobacterium , and Archaeoglobus ), based on key enzymes in the dissimilatory sulfate reduction pathway predicted in the respective genomes ( Fig. 3 ). Considering that Desulfonauticus is 63.2% in relative abundance and the other two genomes combined comprise <5%, we believe that Desulfonauticus is the principal source of H 2 S. Desulfonauticus has been isolated and its sequences recovered from oil fields previously ( 38 , 39 ). It is a thermophilic ( D. autotrophicus has a growth optimum of 58°C), halophilic, and sulfidogenic bacterium ( 38 ) which uses hydrogen and formate as electron donors [supported by the presence of non-F(420)-reducing hydrogenase and formate dehydrogenase in the binned genome (this study)] and a variety of sulfur compounds as electron acceptors ( 38 ). Given the sulfate reduction potential and abundance of sulfate, it makes sense that sample I2 was soured. FIG 3 Key enzymes of the dissimilatory sulfate reduction pathway recovered in draft genomes (from metagenome data) from produced water samples collected from oil reservoirs in the Schrader Bluff Formation (SB1 and SB2), the Kuparuk Formation (K2 and K3), or the Ivishak Formation (I2) of the Alaska North Slope. APS, adenosine-5′-phosphosulfate; dsr, dissimilatory sulfite reductase. The asterisk indicates a genome that is likely for a member of the family Peptococcaceae , based on the marker enzymes (GyrA and ribosomal protein S3 are 71% and 82% identical to those of “ Candidatus Desulforudis audaxviator”). We evaluated genome bins in this sample for genes related to hydrogen cycling. Hydrogenases were found in 10 of 11 genomes recovered from sample I2, though it is generally uncertain whether these are involved in hydrogen production or oxidation. One Thermotoga organism (about 1% in relative abundance) possesses an Fe hydrogenase and therefore is a candidate for hydrogen production in this community. Since the complete hydrocarbon degradation pathway overlaps other carbon catabolism pathways, we defined hydrocarbon degradation capability based on the presence of at least one of the genes in the activation phase or acting on aromatic substrates (enzymes listed in Table S5 in the Text S2 file in the supplemental material). By this criterion, no hydrocarbon degradation pathways were found in any of the genomes in the two Ivishak samples, consistent with oil from this reservoir being a lighter crude than from the shallower reservoirs and therefore indicating little biodegradation in situ . A large inventory of glycosyl hydrolases was found in both I1 ( Thermoanaerobacter ) and I2 (several Thermotoga genomes). Oil reservoirs are not known to contain abundant polysaccharides, but these compounds may have been introduced in the drilling fluids. Cellulose is often used in these fluids to block the fluid leak-off into the rock, and polymers (usually Biozan, containing heteropolysaccharides) are used to increase the viscosity of drilling fluids so that rock cuttings and cellulose can be swept out of the well prior to cementation and oil production. The introduced polysaccharides may have promoted growth of organisms with glycosyl hydrolases (although the wells under study were drilled several years ago). Given that we do not know whether these enzymes are active (since we studied only DNA), it is not certain how much of the drilling influence is still seen today. In the reservoir, these enzymes also could be used for degradation of cell wall materials or may be used to take advantage of dissolved organic matter (DOM), likely brought in by the seawater flooding process. Ocean DOM is known to contain polysaccharides ( 40 , 41 ), such as xylan from marine algae ( 42 ), and sugars, such as galactose and mannose ( 43 ). Harvey reported mono- and polysaccharide concentrations in seawater, including one study reporting 70 to 280 µg/liter monosaccharides and 160 to 225 µg/liter polysaccharides in summer months ( 44 ). Sakugawa and Handa reported mono-, oligo-, and polysaccharide concentrations of 4 to 100 µg/liter in north Pacific Ocean and Bering Sea water ( 45 ). We did not, however, analyze the injection water for sugars in this study. Additionally, genes potentially involved in polysaccharide degradation also exist in ocean microbial population ( 46 ). Various marine bacteria have been shown to have such activities ( 47 – 50 ). (ii) Kuparuk Formation. The Kuparuk samples (K2 and K3) have relatively low diversity, although they are not highly dominated by a single genotype, as were the Ivishak samples. Fourteen and sixteen partial genomes were reconstructed from these samples, respectively (see Fig. S1C and D in the supplemental material). It is interesting that the dominant organism in sample K2 is Archaeoglobus fulgidus , a well-known archaeon that is capable of H 2 S production ( 51 ) and is commonly found in oil reservoirs ( 1 , 22 , 52 , 53 ). Sulfate reduction genes were found in Archaeoglobus fulgidus and Thermodesulfobacterium commune genomes ( Fig. 3 ). Based on the community composition and predicted metabolic potential, we would have expected that the well from which sample K2 was collected would have been soured; however, at 14 mg/liter hydrogen sulfide, this well is not considered soured. The low sulfate concentration (1.4 mg/liter) of the water used to support secondary production (Table 2 in reference 32 ) is expected to limit the possibility of souring. Although sulfide oxidation, if it occurred in the reservoir, could keep sulfide concentrations low, we did not recover any genomes of known sulfide oxidizers, so it is not a plausible explanation, given the data. We evaluated other possible electron donors and acceptors that may be used by Archaeoglobus . Its genome content supported the ability to use fatty acids, amino acids, and other small organic acids ( 51 ). A previous enrichment culture study demonstrated that Archaeoglobus is capable of oxidizing hydrogen ( 54 ), and a recent transcriptomic analysis suggested roles of fatty acid metabolism during growth with H 2 ( 55 ). We speculate that in K2, Archaeoglobus uses organic acids with H 2 as the electron donor, since many of the consortium members have the ability to produce H 2 . Notable in this regard is Thermococcus sibiricus ( 56 ). Additionally, previous studies showed that multiple species of Thermotoga can produce H 2 ( 57 , 58 ), and Fe hydrogenase genes, which are predicted to produce hydrogen in fermentative organisms, were recovered from four Thermotogaceae genomes in sample K2, including from a highly abundant (23%) species. Fe hydrogenase genes also were identified in one Caldanaerobacter genome in this study. While information on genomes alone is insufficient to determine for certain the active hydrogen donor(s), several members of these genera have been shown to produce hydrogen from various fermentable substrates ( 54 , 57 ), though attempting to measure such substrates was beyond the scope of the current work. Sample K3 was collected from a low-sulfate and high-sulfide produced fluid. Due to the management of the well, it is not clear what fraction of the sulfide in the produced fluid, if any, is attributable to biological activity, since there was no increase in sulfide of the produced fluid compared to the miscible injectant. Based on recovered sulfate reduction genes, a potential sulfate reducer was Thermodesulfobacterium commune , and a member of a novel genus within the Clostridiales (likely a member of the family Peptococcaceae ) also may be able to reduce sulfate ( Fig. 3 ). The reconstructed Clostridiales genome lacks a sulfate adenylyltransferase gene, though it is possible that we did not detect this gene because the genome is partial (this genome was estimated at 74.5% completeness based on the inventory of ribosomal proteins recovered). A Thermococcus organism also could contribute to sulfide production in K3 (see the supplemental material). The microbial community in K3 was distinct from that in K2 in another way, in that K2 had only nonmethanogenic archaea, whereas the three archaea in K3 were exclusively methanogens. Conversely, bacteria such as Thermotoga , Thermococcus (a member of the Thermodesulfobacterales ), Caldanaerobacter , Thermodesulfobacterium commune , and Clostridia were present in both K2 and K3. Since the injection water sources for these two wells are very different, these shared bacteria could be indigenous to the Kuparuk Formation. Hydrocarbon degradation genes were rare in Kuparuk samples (only one partial benzoyl coenzyme A [benzoyl-CoA] reductase sequence was present in K3). A. fulgidus has been shown to be capable of long-chain alkane degradation ( 59 ); however, due to very low homology of the proposed activation enzyme to the known alkylsuccinate synthases or benzylsuccinate synthases, detailed investigation of candidate proteins would be required to support their inclusion in hydrocarbon transformation processes. Acetate oxidation has been proposed as an important mechanism in anaerobic hydrocarbon degradation in oil reservoirs ( 2 , 5 ). Piceno et al. suggested that syntrophic acetate-oxidizing and hydrogentrophic methanogenesis processes were prominent in the Kuparuk reservoir ( 32 ). They speculated that acetate from degraded carbon might be oxidized to CO 2 and H 2 , with subsequent utilization of H 2 and CO 2 by hydrogentrophic methanogens, as discussed by Jones et al. ( 2 ). We recovered a genome for Thermoacetogenium phaeum in sample K3, an organism reported previously from the Kuparuk Formation ( 22 , 32 ). This is a thermophilic, syntrophic acetate oxidizer, perhaps associated with hydrogentrophic methanogens ( 60 ). Genes for previously described major enzymes in T. phaeum grown syntrophically on acetate ( 61 ) (CO dehydrogenase, formate dehydrogenase, hydrogenase, and formyl-hydrofolate ligase) were identified in the T. phaeum genome bin. Sample K3 was from an area that at the time of sampling had a higher CO 2 concentration (measured as moles percent in the gas phase in equilibrium with the oil and water at standard temperature and pressure) than other parts in the same formation. The elevated CO 2 concentration was a result of this area having been swept with miscible injectant (containing 25 mol% CO 2 ). The gas phase CO 2 was much higher in K3 (11 to 12.5 mol%, in 2013) than in K2 (~0.5 mol%). This condition may provide an additional opportunity for organisms that are able to fix CO 2 with concomitant acetate production. A nearly complete genome of Acetothermia (OP1) was recovered from sample K3 ( Table 1 ). The 1,534-bp 16S rRNA gene for this organism is 99% identical to a sequence (1,538 bp) recovered from a nonflooded, high-temperature petroleum reservoir ( 25 ), but the previous study authors did not reconstruct a genome. The first genome of this phylum was recovered from a subsurface thermophilic microbial mat community, and it was predicted to have an acetogenic lifestyle based on the Wood-Ljungdahl pathway ( 62 ), which removes hydrogen that accumulates during biodegradation, and assimilates CO 2 to produce acetate ( 63 , 64 ). The 16S rRNA gene and RecA protein sequences of the new OP1 genome recovered from K3 were 86% and 71% identical to that of the prior draft genome, respectively. We evaluated autotrophic CO 2 fixation pathways, i.e., reductive tricarboxylic acid cycle and the Wood-Ljungdahl pathway. The new OP1 genome has genes for 2-oxoglutarate synthase and ATP citrate lyase (alpha subunit) but lacks a fumarate reductase gene. While we found several enzymes in Wood-Ljungdahl pathway, one key component, CO dehydrogenase/acetyl-CoA synthase, was not detected in the current assembly, which still has many gaps. TABLE 1 OP1 ( Acetothermia ) draft genome statistics and major metabolic functional pathway genes recovered in the genome Characteristic Result No. of contigs 22 Total sequence length (bp) 1,816,458 G+C content 64.3% 16S rRNA gene 1,525 bp, 99.6% identical to OP1, class OPB14 Ribosomal proteins 46/55 Single copy genes 48/51 Carbon utilization Glycosyl hydrolases Hydrogenases Membrane bound (MBH 2) Dissimilatory sulfate reduction Not found Sulfur oxidation Not found Nitrate-nitrite reduction Not found OP1 has many glycosyl hydrolase genes. Most of these enzymes (except one endoglucanase) were not found in the previous OP1 genome ( Candidatus “Acetothermum autotrophicum”), suggesting significant differences in metabolic capacity between the two genomes. Since both genomes have gaps, discussion here is limited to the sequences available. OP1 has a group 4 NiFe membrane-bound hydrogenase (MBH). This type of MBH could produce hydrogen using reduced ferrodoxin (Fd) from carbohydrate fermentation or oxidize hydrogen, pumping protons via electron transfer to various quinones and cytochromes. We found no evidence of aerobic metabolism (no cytochrome oxidase), or alternative pathways for energy production. For instance, OP1 lacks genes for dissimilatory sulfate reduction and nitrate or nitrite reduction. This organism also appears to lack flagellum-based motility and has no lipopolysaccharide biosynthetic genes, suggesting that it does not have a Gram-negative cell envelope. (iii) Schrader Bluff Formation The ability to degrade hydrocarbons was more prominent in organisms of the mesothermic Schrader Bluff samples (SB1 and SB2) than in other samples studied here. This is consistent with previous hydrocarbon profiles showing that Schrader Bluff oil was the most degraded of the oils from the Alaska North Slope samples ( 32 ). Hydrocarbon degradation genes were identified in Desulfotomaculum and in another partial genome in Clostridiales (Clostridiales_45_118_partial in Table 2 ). These genomes have the key enzyme required for the first step in anaerobic hydrocarbon degradation (alkylsuccinate synthase [ASS] or benylsuccinate synthase [BSS]) and the requisite activase. Additional genomes contain incomplete BSS subunits or only enzymes involved in downstream steps or steps in degrading aromatic compounds ( Table 2 ). It is not certain whether the partial gene structures are due to the lack of intact operons or the incompleteness of the genomes. TABLE 2 Anaerobic hydrocarbon degradation genes recovered from binned genomes (metagenome analysis) from produced water samples collected from oil reservoirs in the Schrader Bluff Formation (SB1 and SB2) or the Kuparuk Formation (K3) of the Alaska North Slope a Draft genome Sample Anaerobic hydrocarbon degradation gene product(s) Recovered genome size (Mbp) Estimated genome coverage based on rRNA gene retrieval (%) Clostridia_62_21 K3 Benzoyl-CoA reductase 1.3 74.5 Bacterium_34_27_partial SB1 Tungsten-dependent benzoyl-CoA reductase 0.82 5.5 Clostridia_33_59 SB1 Benzylsuccinate synthase (gamma subunit); glycyl- radical enzyme activating protein 0.5 65.5 Clostridia_51_5 SB1 Benzylsuccinate synthase (alpha, gamma subunits); 0.64 18.2 Desulfotomaculum_46_80 d SB1 Alkylsuccinate synthase; benzoyl-CoA reductase; (R)-benzylsuccinyl-CoA dehydrogenase; glycyl-radical enzyme-activating protein 2.25 80.0 Desulfotomaculum_46_296 d \n SB1 Benzylsuccinate synthase (alpha, beta, gamma subunits); glycyl-radical enzyme activating protein; benzoyl-CoA reductase; (R)-benzylsuccinyl- CoA dehydrogenase 2.33 81.8 Firmicute_34_26_partial SB1 Benzylsuccinate synthase (gamma subunit); glycyl- radical enzyme activating protein 1.2 38.2 Firmicute_40_6_partial SB1 Benzylsuccinate synthase (gamma subunit) 1.19 14.5 Mesotoga_prima_46_7 SB1 Benzoyl-CoA reductase 1.71 54.5 OP9_34_73_partial SB1 Benzylsuccinate synthase (gamma subunit); glycyl- radical enzyme activating protein 0.22 47.3 OP9_34_128 SB1 Alkylsuccinate synthase (AssA); glycyl-radical enzyme-activating protein 0.9 76.4 Syntrophobacterales_55_5 _plus b SB1 Benzoyl-CoA reductase; benzoate-CoA ligase 35/55+ Unbinned b SB1 Alkylsuccinate synthase; benzoyl-CoA reductase Chloroflexi_43_5_mix b SB2 4-Hydroxybenzoate-CoA ligase 42/55+ OP9_34_191_partial SB2 Benzylsuccinate synthase (gamma subunit); glycyl- radical enzyme activating protein 0.63 67.3 Clostridiales_45_118_partial d SB2 Benzylsuccinate synthase (alpha, beta, gamma subunits); glycyl-radical enzyme activating protein; benzoyl-CoA reductase; (R)-benzylsuccinyl- CoA dehydrogenase 2.34 10.9 OP9_34_868 SB2 Benzylsuccinate synthase (gamma subunit); glycyl- radical enzyme activating protein 0.2 36.4 OP9-like_34_37 SB2 Benzylsuccinate synthase (alpha, gamma subunits); glycyl-radical enzyme activating protein 0.91 38.2 Syntrophobacterales_51_5_partial SB2 Benzoyl-CoA reductase 1.11 60 Unbinned c SB2 Alkylsuccinate synthase; glycyl-radical enzyme activating protein benzylsuccinate synthase a Genome names have the format taxonomy_percent G+C content_calculated genome coverage. b These bins contains multiple marker genes, indicating 1 to 3 genomes in the same family or genus. c Contig that was not binned to any draft genomes. d Predicted hydrocarbon-degrading bacteria. Schrader Bluff produced water samples were not soured, and sulfate concentrations were below detection levels (see Table S1 in the Text S2 file in the supplemental material). From the metagenomic data reported here, we did not recover a sulfate reduction pathway in any of the Schrader Bluff genome bins. Therefore, neither chemical nor biological factors indicated souring of this reservoir. Compared to published Desulfotomaculum cluster 1 sequences ( 65 ), the Desulfotomaculum 16S rRNA genes from SB1 and SB2 are similar, clustering with Ii (see Fig. S2 in the supplemental material). The current genome-based findings are consistent with the role proposed previously ( 32 ) for the Schrader Bluff Desulfotomaculum organisms, where syntrophic growth rather than sulfate reduction likely explains the prominence of members of this genus in this nonsoured reservoir. We propose that the microbial community has adapted to this low-sulfate environment by relying on fermentation of organic substrates (e.g., propionate, reported in produced water from the Schrader Bluff Formation [SB] [26]). To make this energetically feasible, the hydrogen concentrations must be kept low. The hydrogen- and formate-consuming methanogens in the community likely make a synthophic lifestyle favorable. The presence of many methanogens, including acetoclastic methanogens, is consistent with the detection of biogenic methane based on stable isotope data ( 32 ). In SB1 and SB2, both hydrogentrophic and acetotrophic methanogens are present, but the latter dominate. The same species, Methanosaeta harundinacea ( gyrA genes are 100% identical), is relatively abundant in both SB1 and SB2. Methanosaeta is likely to produce methane from acetate (acetoclastic methanogenesis) using the acetyl-CoA synthetase pathway ( 66 , 67 ). This is consistent with the previous assertion that acetogenic methanogenesis is more prominent in the Schrader Bluff than in the Kuparuk Formation ( 32 ). Several organisms may be syntrophs. We recovered partial Syntrophobacteriales genomes from both SB1 and SB2. Members of this order have been studied for aromatic compound degradation and syntrophic metabolism ( 60 ). The benzoyl-CoA reductase genes associated with this genome support this function. We also recovered some components proposed to be essential for syntrophic metabolism: formate hydrogenlyase and heterodisulfide reductase (HdrA), which is part of the HdrABC electron transfer complex ( 37 ). We infer that Syntrophobacteriales organisms in oil field environments degrade aromatic compounds in syntrophy with hydrogentrophic methanogens (contributing to syntrophic H 2 and formate generation). Additionally, genomes of Proteiniphilum acetatigens were reconstructed from SB1 (and a genome was assigned to Proteiniphilum but not to the species Proteiniphilum acetatigens in SB2). The possible function for this member is utilizing protein substrates from cellular debris and producing acetate and CO 2 ( 68 ). In contrast to the samples from Ivishak and Kuparuk, where bacteria from candidate phyla comprised 0 to 0.4%, bacteria from candidate phyla are well represented in the SB1 and SB2 microbial communities, in terms of both variety and abundance ( Fig. 1 ; also, see Fig. S1E and F in the supplemental material). Candidate phylum OP9 ( Atribacteria [ 69 ]) comprises 30% of the community in SB2 and 12% in SB1. Parcubacteria (OD1) represented 9.5% and 6% of communities in SB1 and SB2, respectively. Bacteria from several other candidate phyla, including TA06, WS6, and Microgenomates (OP11), were also sampled. We reconstructed Marinimicrobia (SAR406) genomes from both Schrader Bluff samples (identified based on full-length 16S rRNA genes). The primary water source for Schrader Bluff wells was a mixture of water from other oil wells in the Kuparuk and Schrader Bluff formations and from other Cretaceous era marine sandstone formations. To our knowledge, the SB1 and SB2 samples are not influenced by modern-day seawater, suggesting that Marinimicrobia genomes are indigenous to the subsurface ecosystem. The reconstructed genomes from candidate phyla (see the supplemental material) indicate that some of them may be involved with carbon and hydrogen cycling. For example, Marinimicrobia may produce hydrogen (Fe hydrogenase present), and both WS6 and OP11 have predicted fermentative lifestyles, based on the lack of electron transfer chain components and incomplete TCA cycles. Some archaeal and bacterial genome bins contained nitrogenase genes. However, methanogenic archaea are predicted to have the largest share of nitrogen fixation genes in organisms present in the SB1 and SB2 communities ( Table 3 ), in terms of both diversity (4 archaea versus 1 bacterium) and relative abundance. This finding is in remarkable contrast to those for other ecosystems, where such genes are typically primarily associated with bacteria ( 70 , 71 ). I2 and K3 samples also contain three organisms with genomes that contain nitrogen fixation genes. All three genomes belong to the order Methanobacteriales . Nitrogen fixation genes were not recovered for any organism in samples I1 and K2. TABLE 3 Nitrogen fixation genes present in draft genomes (from metagenome data) from produced water samples collected from oil reservoirs in the Schrader Bluff formation (SB1 and SB2), the Kuparuk formation (K3), or the Ivishak Formation (I2) of the Alaska North Slope a Genome Sample Nitrogen fixation gene(s) Affiliation Methanosaeta_harundinacea_57_489 SB1 nifH (nitrogenase Fe alpha subunit), nifK (MoFe beta subunit), nifE (nitrogenase MoFe cofactor biosynthesis protein) Methanogenic Archaea Methanocalculus_52_23 SB1 nifH , nifK Methanogenic Archaea Methanoculleus_marisnigri_60_61_partial SB1 nifH , nifK Methanogenic Archaea Desulfotomaculum_46_80 SB1 nifH , nifK , nifE , nifB (nitrogenase cofactor biosynthesis protein) Bacteria Methanobacteriales_53_19_partial SB2 nifH , nifK , Methanogenic Archaea Methanoculleus_60_29 SB2 nifH , nifK , nifE , anfO (nitrogenase iron-iron accessory protein) Methanogenic Archaea Methanosaeta_haundinacea_56_747 SB2 nifH Methanogenic Archaea Clostridia_45_118_partial SB2 nifH , nifK , nifE , nifB Bacteria Methanothermobacter_50_10 I2 nifH , nifK Methanogenic Archaea Methanobacteriaceae_41_258_partial I2 nifH , nifK Methanogenic Archaea Methanobacteria_50_154 K3 nifH , nifK , nifE , glnB (nitrogen metabolism regulatory protein) Methanogenic Archaea a Genome names have the format taxonomy_percent G+C content_calculated genome coverage. Summary. In this study, we analyzed petroleum reservoir produced water samples collected from six production wells, from different depths, temperatures, and H2S concentrations using a genome-resolved metagenomic approach. These samples had previously been investigated using 16S rRNA gene-based PhyloChip analyses. The PhyloChip data for bacteria, the 16S rRNA genes reconstructed in metagenomes ( Fig. 3 ), and genome phylogeny, based on other single copy gene information (Fig. S1A to F), are in overall agreement. However, the genome-resolved approach has higher taxonomic resolution and enables detailed metabolic predictions. Generally, the richness of the microbial communities decreased as temperatures increased, with 44 to 60 recovered genomes from the mesothermic reservoir yet only 3 genomes reconstructed from the highest temperature reservoir. The microbial communities are much more diverse and evenly distributed in the mesothermic reservoir (Fig. S1A to F). Clostridiales are likely the major contributors to hydrocarbon degradation in the low temperature Schrader Bluff oil reservoir. Whether some candidate phyla also played a role in this process is uncertain. We clearly demonstrated the existence of the dissimilatory sulfate reduction pathways, regardless of the souring status of the well. We assembled several nearly complete genomes from candidate phyla bacteria and provided insights into their ecosystem roles. Nitrogen fixation potential is predicted to be largely associated with methanogens. The conclusions from this study provide valuable insights into functional roles individual organisms, including those from candidate phyla, may play in these petroleum reservoirs."
} | 9,750 |
36465542 | PMC9709946 | pmc | 3,300 | {
"abstract": "Artificial molecular machines have found widespread applications\nranging from fundamental studies to biomedicine. More recent advances\nin exploiting unique physical and chemical properties of DNA have\nled to the development of DNA-based artificial molecular machines.\nThe unprecedented programmability of DNA provides a powerful means\nto design complex and sophisticated DNA-based molecular machines that\ncan exert mechanical force or motion to realize complex tasks in a\ncontrollable, modular fashion. This Perspective highlights the potential\nand strategies to construct artificial molecular machines using double-stranded\nDNA, functional nucleic acids, and DNA frameworks, which enable improved\ncontrol over reaction pathways and motion behaviors. We also outline\nthe challenges and opportunities of using DNA-based molecular machines\nfor biophysics, biosensing, and biocomputing.",
"conclusion": "5 Conclusions and Outlook In summary,\na variety of functional DNA molecules and nanostructures\nhave been successfully used to construct complex and sophisticated\nDMMs. 199 − 201 The advancement of DNA nanotechnology promotes\nthe development of DNA walkers, motors, rotors, sensors, and robots.\nMoreover, the development of DMMs aids in the comprehension of physical\ntheories of transport phenomena and aids in the clarification of the\nrelationship between mechanical motions and chemical reactions. We\nhave discussed recent advances in how integrating DMMs into various\ninterfaces can help to empower their functions and applications in\nthis Perspective. For nucleic acid chemistry, an increasing number\nof moieties and functional molecules have been developed, allowing\nfor easy assembly and integration of diverse functions. 77 The versatile intelligent DMMs were developed\nfor a variety of biological applications, including biomolecular rulers,\nbiosynthesis, biocomputing, and biosensing. 202 , 203 One of the most significant challenges for artificial DMMs\nis to\napproach the complexity and intricacy of natural proteins. Since current\nmethods focus on substituting allosteric and mechano-gating coupling\ninto DNA nanostructures, engineering mechanochemical coupling requires\na diverse set of fully predictable monomeric components. 204 The highly precise discrete DNA nanostructures\ncreated by DNA oligomers or DNA origami provide an extremely useful\nmethod for guiding motion propagation. Nanometer-scale precision in\nmolecule arrangement via DNA hybridization, in particular, enables\nthe modification of DMMs with a variety of functions. Meanwhile, the\ninability to program DMM energy landscapes restricts the field of\nintelligent and efficient molecular machines. Later, as mass production\nof DNA and scaled-up DNA self-assembly technologies are developed,\nthe cost and difficulty of building DMMs will decrease, thereby expanding\nthe area of their biologic applications. Thus far, the development\nof integrating DMMs at the interface has paved the way for a sophisticated\napproach to the construction of artificial DMMs with complex structures\nand functions.",
"introduction": "1 Introduction Natural cellular machinery\nis essential for the function and processivity\nof a wide variety of biologic processes, ranging from adenosine triphosphate\n(ATP) synthase at the nanoscale to cell recognition at the microscale. 1 − 7 In general, machinery is composed of a multitude of functional components\nworking in tandem. 8 These primitive biomolecules,\nin particular nucleic acids and proteins, exert mechanical force or\nmotion in response to certain external stimuli (signal input). Inspired\nby these natural biomolecular machines, many researchers have repurposed\nartificial biomolecules to engineer artificial molecular machines\nthat execute a list of functions and accomplish complex tasks in a\ncontrollable, modular manner. 9 − 12 These studies lead to not only advancements in the\ncreation of synthetic cells and lifelike entities but also insights\ninto the structure and functionality of artificial molecular machines\nthat have broad implications for a variety of fields ranging from\nfundamental biology to biomedical applications, including biomedical\nengineering, biosensing, and theragnostics. Since the 1980s,\na variety of chemicals and materials, including\nsmall organic molecules, nanoparticles, proteins, RNA, and DNA, have\nbeen utilized to construct diverse artificial molecular machines. 13 − 16 As an exquisite illustration, Feringa and colleagues created organic\nmolecule-based molecular machinery with a unidirectional rotation\nthat performs complex tasks utilizing chemical fuels, light, or electrochemical\nreact ions, as recognized by the 2016 Nobel Prize in Chemistry. 17 − 20 Alternatively, DNA has also widened our vision and facilitated the\ndevelopment of artificial molecular machines. 21 − 24 In particular, since Seeman’s\npioneering work in the early 1980s, rapidly growing structural DNA\nnanotechnology has opened up new possibilities for the building of\nstatic and dynamic 2D and 3D DNA-based molecular machines (DMMs),\nthat are built from exquisite architectures of DNA sequences and achieve\nmechanical operation by DNA in a dynamic, controllable, modular manner. 25 − 27 Due to the flexible backbone of ssDNA and the rigid framework of\ndouble-helical DNA domains, the local stiffnesses of DNA nanostructures\ncan be programmed and coupled to fit a wide range of structural requirements\nfor each particular molecular machine design. 28 Meanwhile, by exploring DNA’s highly predictable assembly\nqualities and the programmability of its hybridization processes,\nDNA offers a path for programming and controlling complicated motion\nor behavior at the nanoscale. In addition, the diverse kinds of DNA\nsecondary structures found in nature, such as G-quadruplexes and i-motifs,\noffer an exquisite approach to controlling the functionalities and\nbehaviors of DMMs. 29 , 30 Thus, DNA rapidly evolved into\nthis booming field of artificial molecular machine construction, closely\nresembling natural protein motors in terms of nanoscale size. 31 With the development of DNA nanotechnology,\ninitial research focused\non creating and fabricating DMMs. 32 To\ndevelop advanced applications, these DMMs must operate at the interface\nrather than in the liquid. The supporting interface, which is typically\nwhere biological systems or cascade-triggering events are integrated,\nwould enable evaluating its functionality, such as direction control\nand programmability. 33 Specifically, because\nunique DNA can be programmed in a variety of ways, localized motors\non the surface are far more likely to be triggered by adjacent molecules\nor output signals, allowing for better control over reaction pathway\ndirection. Moreover, once they are anchored to solid of soft surfaces,\nanchoring, addressability, and cooperative operation become critical,\nwhich provides a path to system complexity and considerable promise\nfor the realization of functional DMMs. In this Perspective,\nwe focus on recent advances in DMMs. We first\nintroduce the progress of DNA nanotechnology in the construction of\nDMMs and then describe methods for integrating DMMs at the interface\nas well as tactics for regulating motion and behavior. Following that,\nwe provide a detailed review of recent reports on its biological application\nin biological rulers, biologic factories, biocomputing, and biosensing.\nLast, we discussed the future challenges and perspectives of this\nfield."
} | 1,858 |
26300859 | PMC4523816 | pmc | 3,302 | {
"abstract": "Bacteria switch between two distinct life styles – planktonic (free living) and biofilm forming – in keeping with their ever-changing environment. Such switch involves sophisticated signaling and tight regulation, which provides a fascinating portal for studying gene function and orchestrated protein interactions. In this work, we investigated the molecular mechanism underlying biofilm formation in Shewanella oneidensis MR-1, an environmentally important model bacterium renowned for respiratory diversities, and uncovered a gene cluster coding for seven proteins involved in this process. The three key proteins, BpfA, BpfG, and BpfD, were studied in detail for the first time. BpfA directly participates in biofilm formation as extracellular “glue” BpfG is not only indispensable for BpfA export during biofilm forming but also functions to turn BpfA into active form for biofilm dispersing. BpfD regulates biofilm development by interacting with both BpfA and BpfG, likely in response to signal molecule c-di-GMP. In addition, we found that 1:1 stoichiometry between BpfD and BpfG is critical for biofilm formation. Furthermore, we demonstrated that a biofilm over-producing phenotype can be induced by C116S mutation but not loss of BpfG.",
"introduction": "Introduction Biofilm is a type of surface-attached structure composed of microbial cells embedded in their self-produced extracellular polymeric substances (EPS), mainly exopolysaccharides, proteins, and extracellular DNA ( Flemming and Wingender, 2010 ). It has been recognized as the principle life style for microbes in nature ( O’Toole, 2003 ; Hall-Stoodley et al., 2004 ). Although planktonic cells are advantageous to look for favorable niches, biofilm allows cells to remain and thrive in such places. Thus, switching between planktonic and biofilm-forming modes represents a major life style change for microbes, and has been shown to be a tightly regulated process ( O’Toole, 2003 ; Hall-Stoodley et al., 2004 ). Many regulatory cascades controlling transition of microbial life-styles studied to date involve regulatory factors to mediate transcription and translation of proteins for biosynthesis of EPS, including sigma factors, transcriptional factors, several nucleotide messengers, and sRNAs ( Karatan and Watnick, 2009 ; Fazli et al., 2014 ). However, there are exceptions. In Pseudomonas fluorescens Pf0–1, a protein network is reported to regulate biofilm development through sophisticated signaling and protein interactions rather than mediating EPS production ( Newell et al., 2011 ). This system consists of multiple proteins encoded by genes in a lap cluster ( Figure 1A ). Of these Lap proteins, LapA, LapG, and LapD are critical to the process of biofilm formation. LapA, a Bap/RTX hybrid cell surface protein, is exported by a type I secretion system (TISS) encoded by three genes ( tolC – Pfl0135 – hlyD ) immediately downstream of lapA and serves as a cell surface attached adhesin responsible for “gluing” cells together ( El-Kirat-Chatel et al., 2014 ). LapG is a periplasmic proteinase, which cuts LapA off the outer membrane ( Boyd et al., 2014 ). As a result, compared to the wild-type mutants lacking LapG are more robust in forming biofilm and overproduction of LapG promotes biofilm dispersion ( Boyd et al., 2012 ). LapD is a transmembrane protein regulating LapG activity in response to signal molecule c-di-GMP ( Newell et al., 2009 ). The environmental cue for the modification of LapA is conditions unfavorable for biofilm formation, such as low inorganic phosphate concentrations ( Newell et al., 2011 ). FIGURE 1 Identification of a cluster of genes involved in biofilm formation in Shewanella oneidensis MR-1. (A) Arrangement of genes in the lapA operon of Pseudomonas fluorescens Pf0–1 and their homologous in MR-1. The type I secretion system (TISS) is formed by ORF tolC–Pfl0135–hlyD in Pf0–1 and aggA–C ( SO4318–SO4320 ) in MR-1. The ORFs SO4321 , SO4322 ( bpfG ), and SO4323 ( bpfD ) encode an OmpA-like protein, a TISS associated periplasmic transglutaminase-like cysteine proteinase and a bifunctional diguanylate cyclase/phosphodiesterase protein, respectively. Pfl0132 codes for a protein with no impact on biofilm formation. (B) Relative biofilm biomass of mutants lacking genes indicated. Biofilm formation was determined using the standard plate assay, and normalized to the value of MR-1 (wild-type) to yield the relative biofilm for comparison across different experiments. Error bar represents SE of three experiments. Shewanella oneidensis MR-1 is a Gram-negative facultative anaerobe, the best studied representative of the genus Shewanella ( Venkateswaran et al., 1999 ). Following its isolation ( Myers and Nealson, 1988 ), the bacterium was soon found to be able to use a wide range of solid electron acceptors (EA), a subset of which include minerals containing heavy metal ions such as Fe(III), Cr(VI), and U(VI), to name a few ( Fredrickson et al., 2008 ). The feature renders MR-1 an appealing agent for bioremediation, developing microbial fuel cells (MFC) and synthesizing metal nanomaterials ( Logan and Regan, 2006 ; Marshall et al., 2006 ; Pirbadian et al., 2014 ). Previous studies of biofilm formation in MR-1 have identified BpfA (Bpf stands for B iofilm p romoting f actor) and AggA as essential proteins for the process ( De Windt et al., 2006 ; Liang et al., 2010 , 2012 ; Theunissen et al., 2010 ). Sequence comparison reveals that BpfA and AggA are analogous to P. fluorescens LapA and TolC, respectively ( Boyd et al., 2014 ). Like LapA and TolC of P. fluorescens , BpfA and AggA are encoded by two genes next to each other, albeit oppositely oriented ( Figure 1A ). Additionally, AggA is the outer-membrane component of the accompanying TISS system (AggA–AggB–AggC), resembling TolC–Pfl0135–HlyD ( Theunissen et al., 2009 , 2010 ). Despite these similarities, the BpfA-mediated biofilm formation carries novel features as the low inorganic phosphate concentrations could not differentiate the bpfA mutant from the wild-type. Therefore, this work aims to further explore the BpfA-mediated biofilm formation in MR-1. Here, we first identified BpfA, BpfG, and BpfD to be the important players in biofilm development, through bioinformatic, mutational, and molecular analyses. Further investigation uncovered interactions between these proteins and their effects on biofilm formation and dispersion. Although these three proteins constitute a protein network vaguely resembling the one in P. fluorescens , mechanisms underlying roles played by each component differed significantly.",
"discussion": "Discussion Regulation of biofilm formation in microorganisms is a topic of both scientific and practical value. From the standpoint of basic scientific research, microbes have to stay tuned with the external environment to seize the cue(s) calling for the life-style switch from free-living to biofilm and make it through. Although how microorganisms make such decision remains largely unknown, it clearly involves orchestrated processes, including modulation of gene expression and interactions between proteins, as well as proteins and small molecules such as c-di-GMP ( Karatan and Watnick, 2009 ). From a practical view point, biofilm has been associated with various problems in human daily life, especially in the food, environment, and biomedical fields ( Leaper et al., 2010 ; Simões et al., 2010 ), better understanding of biofilm and its formation would help us tackle them. Thanks to extensive studies on various microbes that have accumulated enormous amount of information, we now have gained considerable understanding of the numerous cellular networks that regulate biofilm formation. However, most of them concern regulation of EPS biosynthesis and other mechanisms are much less understood. In this work, we investigated roles of a protein cascade in biofilm formation in MR-1. We discovered that BpfA–BpfG–BpfD forms an interactive system that governs biofilm formation. Central to this system is BpfA, which is a very large protein although substantially smaller than P. fluorescens LapA. Because of a large number of repeats, the bpfA gene in the released genome sequence is ∼2.6 kb shorter. Each repeat, as illustrated in lapA , is about 300 bp for 100 amino acid residues ( Boyd et al., 2014 ). Also because of these repeats, we failed to clone the full-length bpfA for complementation and other analyses, a situation encountered by O’Toole and Kolter (1998) team on lapA (personal communications). To date, many such proteins have been identified and exclusively function as surface-associated adhesions ( Boyd et al., 2014 ). Although this three-membered system partially resembles LapA–LapG–LapD of P. fluorescens ( Newell et al., 2011 ), there are significant differences in certain key features. In the best studied LapA–LapG–LapD system, the transmembrane receptor LapD is activated by high cytoplasmic concentrations of c-di-GMP, which in turn recruits the periplasmic protease LapG, preventing it from cleaving LapA, thereby promoting cell adhesion and subsequent biofilm formation ( Newell et al., 2009 , 2011 ; Boyd et al., 2012 , 2014 ; Chatterjee et al., 2014 ). Our proposed model is as shown in Figure 6 : BpfA, exported by the TISS channel formed by AggABC and anchored in the outer membrane, serves as a surface attached adhesin mediating cell–cell or cell–matrix adhesion. Our data suggest that intracellular BpfA molecules are probably held by BpfD before exportation, and free BpfA may not be exported efficiently. On the contrary, bindings of c-di-GMP and of BpfG to the respective cytosolic and the periplasmic domains of BpfD results in rapid BpfA exportation and biofilm formation. This explains the biphasic impact of BpfD on biofilm formation: enrichment of BpfA in the membrane fraction from cells overproducing BpfD and requirement of c-di-GMP and BpfG for biofilm formation. The balancing point is achieved when the stoichiometry between BpfG and BpfD is maintained at 1:1. BpfG may be released from BpfD upon c-di-GMP hydrolyzation or some other cues, which can move to BpfA for cleavage such that BpfA can be released from the outer membrane. When over-produced, BpfG overwhelms the BpfD control, leading to cleavage of BpfA and defect in biofilm formation. The role of the OmpA-like protein coded by SO4321 in the process is not known. But given its location and predicted functions, the protein probably participates in translocation of BpfD and BpfG, as AggABC TISS transports protein from the cytosol to the extracellular space directly. Efforts to test this notion are under way. FIGURE 6 Proposed model for regulatory biofilm formation mechanism in S. oneidensis MR-1 . In planktonic cells, BpfA is captured by BpfD to prevent biofilm formation. In biofilm forming stage, c-di-GMP and BpfG bind to BpfD, resulting in BpfA release and export by TISS system (not shown in figure). SO4321 facilitates BpfA localization on the outer membrane, and biofilm forms. c-di-GMP hydrolyzation and disassociation from BpfD leads to BpfG release and possibly activation of its proteinases activity, BpfA is subsequently digested and biofilm disperses. Asterisks in the figure indicate places of pure logical speculation at this point, and invites further investigation. Given the phylogenic closeness of Shewanella and Pseudomonas ( Wu et al., 2008 ), it is not surprising that the “glue” function of BpfA, proteinase function of BpfG, and transmembrane regulator role of BpfD are shared between our model and the LapA–LapG–LapD network in P. fluorescens . However, the involvement of SO4321 in biofilm formation, the essentiality of BpfG in BpfA export, and the critical 1:1 ratio of BpfG and BpfD are all data-supported novel aspects of the MR-1 Bpf system. In addition, the lack of impact of medium phosphate level on biofilm formation suggests that the upstream regulation is also distinct in Shewanella . It would be interesting to track down how BpfG and BpfD take on their new roles, as well as how the overarching regulatory scheme diverges in these closely related bacteria."
} | 3,053 |
25658824 | PMC4319750 | pmc | 3,303 | {
"abstract": "Invasive species can alter the succession of ecological communities because they are often adapted to the disturbed conditions that initiate succession. The extent to which this occurs may depend on how widely they are distributed across environmental gradients and how long they persist over the course of succession. We focus on plant communities of the USA Pacific Northwest coastal dunes, where disturbance is characterized by changes in sediment supply, and the plant community is dominated by two introduced grasses – the long-established Ammophila arenaria and the currently invading A. breviligulata . Previous studies showed that A. breviligulata has replaced A. arenaria and reduced community diversity. We hypothesize that this is largely due to A. breviligulata occupying a wider distribution across spatial environmental gradients and persisting in later-successional habitat than A. arenaria . We used multi-decadal chronosequences and a resurvey study spanning 2 decades to characterize distributions of both species across space and time, and investigated how these distributions were associated with changes in the plant community. The invading A. breviligulata persisted longer and occupied a wider spatial distribution across the dune, and this corresponded with a reduction in plant species richness and native cover. Furthermore, backdunes previously dominated by A. arenaria switched to being dominated by A. breviligulata , forest, or developed land over a 23-yr period. Ammophila breviligulata likely invades by displacing A. arenaria , and reduces plant diversity by maintaining its dominance into later successional backdunes. Our results suggest distinct roles in succession, with A. arenaria playing a more classically facilitative role and A. breviligulata a more inhibitory role. Differential abilities of closely-related invasive species to persist through time and occupy heterogeneous environments allows for distinct impacts on communities during succession.",
"introduction": "Introduction Ecologists have sought to understand the processes and mechanisms of succession for well over a century (e.g. [ 1 – 6 ]) with a focus on the way in which individual species can shape community composition through time. Early-colonizing species can have disproportionate influence on subsequent community succession due to founder effects (e.g. [ 7 ]), their ability to capitalize on available resources [ 8 ], or their positive responses to disturbance [ 9 ]. Invasive plant species in particular are often uniquely positioned to influence succession because many are well-adapted to the disturbed conditions which initiate succession [ 10 – 13 ]. In some cases, their high abundance or life-history strategies can also make them ecosystem engineers, capable of transforming habitats and having long lasting effects after they are gone [ 14 ], especially if they are capable of changing the disturbance regime themselves [ 10 , 13 ]. The extent to which early-colonizing invasive species alter succession may depend on how long they can persist in the community. Early-colonizing species tend to capitalize on low competition and high light availability during primary succession, and modify their environment to facilitate later-colonizing species before extirpation [ 3 , 4 , 8 ]. Species that are able to persist longer may inhibit establishment of later species [ 4 ]. For instance, invasive species could alter the dispersal processes of resident species [ 15 ] or directly compete with them for resources (e.g., [ 8 ]). Alternatively, invasive species may give way to later successional species or persist in the community but cease to limit establishment of colonizing species (see facilitation and tolerance models in [ 4 , 16 ]). Different invasive species that play inhibitory or facilitative roles will have distinct effects on the ecological succession of the community. Invasive species could persist longer in communities if they are able to tolerate a wide range of environmental conditions experienced during succession (e.g. [ 17 , 18 ]). Species with broader environmental tolerances likely have wider distributions across spatial and successional gradients [ 19 – 22 ]. Wider environmental distributions could lead to greater impacts on resident species because the invasive species is able to invade more environments and persist within them for longer periods (e.g. [ 23 ]). To better understand how invasive species influence resident communities during succession, we compared the distributions of two congeneric, invasive grasses across space and time in coastal dunes along the USA Pacific Northwest Coast. Coastal foredunes in this region, defined as linear ridges parallel and adjacent to the shoreline [ 24 ], contain rapidly advancing shorelines in many locations creating replicated chronosequences of herbaceous plant communities of up to 75 years ( Fig. 1A ). Furthermore, shoreline change rates vary widely across the region, making it is possible to separate the temporal effects of dune age from the purely spatial gradient created by proximity to the beach. Foredunes are invaded by two early-colonizing, introduced species of Ammophila beach grass—the longer established A . arenaria which is rapidly disappearing from northern foredunes, and the currently invading A . breviligulata which has potentially displaced it [ 25 , 26 ]. Pairs of invasive, congeneric species such as these can provide insights into the mechanisms and long-term consequences of invasion because they allow for comparisons between species occupying similar but not identical distributions (e.g., [ 26 , 27 ]. Whereas both grasses are important foredune stabilizers that can occur in nearly monodominant stands, A . breviligulata dunes are associated with lower plant diversity compared to A . arenaria dunes [ 26 ] and create foredunes of lower height [ 28 ], increasing the risk of coastal flooding [ 29 ]. Using chronosequence data we document shifts in dominance from A . arenaria to A . breviligulata as well as their associated herbaceous communities through successional time. Ammophila breviligulata may outcompete A . arenaria on foredunes [ 30 ], but it is not yet clear whether the former invades by preemptively colonizing new foredunes created by sand deposition or whether it can displace established A . arenaria in foredunes and historical dunes further inland ( Fig. 1B-D ). Understanding the distributions of the two species may provide insight into how A . breviligulata invades. Here we investigated the distributions of two high impact invasive species over two decades to ask the following questions: First, we asked how distributions of these two invaders differed across space and time. We hypothesized that the more recent invader A . breviligulata occupied a wider spatial distribution across the dune and persists in later-successional habitats, which allowed it to replace A . arenaria on foredunes [ 26 ]. Second, we asked how these distributional changes corresponded to impacts on resident communities. We hypothesized that the more broadly distributed species would also be associated with lower total species richness and native species abundance across space and through time. To test these hypotheses, we first used a chronosequence study to determine the distribution of both Ammophila species along successional and spatial environmental gradients. We then asked whether the Ammophila species differed in their associations with native plant cover, total species richness, and soil properties along spatial and successional environmental gradients. Additionally, we resampled transects after 21 years to determine whether A . breviligulata invasion had led to a predictably wider spatial distribution in Ammophila across dune cross-sections and whether A . breviligulata had displaced A . arenaria in backdunes. 10.1371/journal.pone.0117283.g001 Fig 1 Foredune cross-section schematics. (A) Foredunes contain both spatial and temporal gradients along their cross-sections. Foredune consists of toe, crest, and heel moving from left to right. For the spatial dune gradient, quadrats were assigned values between-1 and 1 for their placement along the dune cross-section. Chronosequence age increased from the dune toe to heel (see main text for details). Shoreline and backdune are shown for orientation. (B) Historical dune consisting of only Ammophila arenaria (gray). (C) Invasion of historical dune by A . breviligulata (black) through preemptive colonization of a new dune. Ammophila arenaria retains its original population, and a backdune invasion boundary delineates the two species’ distributions along the dune. (D) Invasion of historical dune by A . breviligulata through displacement of A . arenaria . Note that there is no longer a backdune invasion boundary because the A . arenaria has been locally extirpated.",
"discussion": "Discussion The extent to which invasive species persist through time and tolerate varying spatial environments may determine their impact on succession. We have shown that while closely related invasive species overlap in space and time, their resulting distributions are associated with differential native plant cover and richness. Specifically, we found that the newer invader, A . breviligulata persisted at higher abundance in the backdunes and at later chronosequence ages than the established invader, A . arenaria . These findings show that A . breviligulata occupies a wider distribution than A . arenaria , and has the potential to have broader impacts on plant species richness, native cover, and soil nutrients through time and space. Furthermore, over the past two decades A . breviligulata invasion into foredunes previously dominated by A . arenaria has led to a predictable increase in Ammophila cover in the backdune, though richness did not significantly differ along dune cross-sections in sites of different invasion history. Finally, we observed that A . breviligulata dominates in backdune areas where a boundary between the two species once existed, suggesting that Ammophila breviligulata has displaced A . arenaria and has the potential to limit native cover and richness beyond the foredune. Our results provide evidence that two closely related invasive species occupy similar yet distinct distributions, with implications for their roles in succession. A . breviligulata may play a more inhibitory role in foredune succession than A . arenaria , and the former’s invasion may ultimately slow herbaceous successional processes. Invasive species that are widespread and can tolerate a range of conditions may have the greatest impact on succession. They may inhibit colonizing species for long periods of time [ 4 ], and thus slow the recovery of plant communities after disturbances [ 41 ]. They may also remove spatial refugia for resident species, potentially causing reductions in population growth rates [ 42 , 43 ]. Several mechanisms could explain why A . breviligulata has a wider distribution and potentially larger impacts on species richness than A . arenaria . Ammophila breviligulata may be a superior competitor for resources [ 30 ], or could also be a faster colonizer and preemptively colonize new habitat. Species-specific differences in morphology and sand capture ability may favor A . breviligulata in the dune heels and backdunes and allow it to displace A . arenaria [ 26 , 30 ]. Ammophila arenaria , which tends to grow vertically in response to sand deposition, depends much more on sand burial to achieve high growth than does A . breviligulata [ 28 ]. Therefore, A . breviligulata could have an advantage in backdunes with low sand burial. Finally, A . breviligulata could have more favorable interactions with symbiotic organisms such as arbuscular mycorrhizae [ 44 ] or fungal endophytes [ 45 ] found in dune systems or experience a greater benefit from natural enemy release from pathogens such as nematodes [ 46 , 47 ], particularly if these organisms vary in their host specificity or distribution along dunes. \n Ammophila breviligulata ’s strong impact on native cover and richness could be attributed to feedbacks between vegetation and biophysical processes that alter the physical features of a landscape through time [ 28 , 48 ]. Both Ammophila species build dunes by capturing sand and changing the topography of their habitat [ 28 ], therefore the two species may uniquely alter dune morphologies and the resulting local dune conditions. Spatial gradients may impose an environmental filter that influences where certain species are able to colonize during succession [ 49 , 50 ]. This potentially creates distinct local environmental conditions between dunes dominated by the two Ammophila species in terms of soil properties ( S6 Appendix ), as well as alter salt spray and wind exposure [ 31 ]. Interestingly, soil in dune heels dominated by A . breviligulata was more characteristic of late dune succession (e.g., higher C and N) than A . arenaria soils [ 11 , 51 ] despite having lower native cover. It is possible that plant-soil feedbacks differ between the Ammophila species, leading to higher nutrient content in A . breviligulata soils. Additionally, higher nutrient content simply could have a minimal effect on plant communities given that nutrient levels were generally low, and could suggest that traits such as response to disturbance are more important than competition for resources such as nitrogen (e.g. [ 52 ]). Positive responses to disturbed environments (e.g. higher wind, sand burial [ 53 ]) could be a mechanism by which the two species of Ammophila reduce establishment of colonizing species. For instance A . arenaria may rely on rapid sand burial to displace colonizing native species the foredune toe and crest (e.g. [ 54 ]), but low sand supply in dune heels would lessen its ability to do so. The horizontal growth pattern of A . breviligulata [ 26 , 28 ] could also contribute to lower richness in dune toes by allowing A . breviligulata to rapidly create new dunes devoid of species that have yet to colonize. Furthermore, A . breviligulata may not necessarily differ from A . arenaria in its direct interactions with the herbaceous plant community, but rather its wider distribution may augment its ecological effects. For instance, both Ammophila species may inhibit the establishment of colonizing species by leaving fewer unconsumed resources [ 8 , 55 ], and high Ammophila cover and tiller densities [ 26 , 28 ] may also reduce light availability for colonizing species. In our study, we found that the two Ammophila species were associated with similar native cover and richness in younger dunes, and only found differences in older dunes where A . arenaria cover was reduced. Ammophila species’ interactions with herbaceous plant communities could be likely mediated via differences in biophysical dune feedbacks [ 28 , 30 ], and the Ammophila species’ respective abilities to persist in older, landward parts of the dune. Following the distributions of invasive species over space and time may provide insights into the classical successional roles they play ( sensu [ 4 ]). Specifically, our results suggest that the invasion of the more widely-distributed A . breviligulata has shifted the role of Ammophila on foredunes from that of facilitator to inhibitor. Ammophila arenaria may play a facilitative role as an early colonizer that gives way to later colonizing species through time ( sensu [ 4 ]). In addition to occupying a narrower distribution, A . arenaria was excluded from herbaceous backdune communities, likely due to displacement from A . breviligulata on the shoreside and forest encroachment on the landward side. In contrast, A . breviligulata may play a more inhibitory role ( sensu [ 4 ]), maintaining dominance over longer periods of successional time and reducing native cover and richness. The shift from a more facilitative to inhibitory role of the dominant species has important consequences for how subsequent species establish, interact, and ultimately form communities. Invasive species, particularly those present at the initiation of succession, that are able to persist longer and tolerate more spatially-heterogeneous environments may have the greatest impact on the succession of resident communities. We have shown that two seemingly similar invasive species can differ in these regards and play distinct roles in succession."
} | 4,161 |
34690962 | PMC8529109 | pmc | 3,305 | {
"abstract": "Anthropogenic disturbances and global climate change are causing large-scale biodiversity loss and threatening ecosystem functions. However, due to the lack of knowledge on microbial species loss, our understanding on how functional profiles of soil microbes respond to diversity decline is still limited. Here, we evaluated the biotic homogenization of global soil metagenomic data to examine whether microbial functional structure is resilient to significant diversity reduction. Our results showed that although biodiversity loss caused a decrease in taxonomic species by 72%, the changes in the relative abundance of diverse functional categories were limited. The stability of functional structures associated with microbial species richness decline in terrestrial systems suggests a decoupling of taxonomy and function. The changes in functional profile with biodiversity loss were function-specific, with broad-scale metabolism functions decreasing and typical nutrient-cycling functions increasing. Our results imply high levels of microbial physiological versatility in the face of significant biodiversity decline, which, however, does not necessarily mean that a loss in total functional abundance, such as microbial activity, can be overlooked in the background of unprecedented species extinction.",
"conclusion": "Conclusion For the first time, we present a comparison of five levels of soil microbial diversities of taxonomy and function responding to biodiversity loss based on global soil metagenomes across diverse biomes. We reveal that the relative abundance of microbial function can remain stable despite that taxonomic species decrease dramatically, leading to biotic homogenization but functional stability. Thus, biodiversity loss continuously shrinks the size and complexity of taxonomic interaction networks but did not affect the overall interaction patterns in functions. Sequential species loss also caused the dominant functions to change from broad-scale metabolism to typical nutrient-cycling. This study has potentially far-reaching implications for biodiversity conservation in species-rich terrestrial ecosystems that have high levels of microbial physiological versatility in the face of realistic species loss scenario.",
"introduction": "Introduction Species loss caused by human activities exceeds natural background levels by several orders of magnitude ( Pimm et al., 1995 ; Purvis et al., 2000 ). It is therefore essential to understand the consequences of biodiversity decline in ecosystem processes and functioning ( Purvis and Hector, 2000 ; Dıaz et al., 2003 ). As a result of global biodiversity loss, heterogeneous species are replaced by homogenous thrivers ( McKinney and Lockwood, 1999 ), leading to biotic homogenization at global scales ( Olden et al., 2004 ). Most studies simulating species loss use the random and trait-independent extinction models ( Naeem et al., 1994 ; Tilman et al., 1996 , 1997a , 1997b ; Van Der Heijden et al., 1998 ; Hector et al., 1999 ; Kennedy et al., 2002 ) and assume that species can go extinct in any order. However, biodiversity decline is generally nonrandom ( Purvis et al., 2000 ; Solan et al., 2004 ), because the few “winners” that replace many “losers” are not randomly distributed in taxonomy or ecological groups ( McKinney and Lockwood, 1999 ; Olden et al., 2004 ). Thus, studies that adopted a directed species loss model, such as experiments that nonrandomly remove species or functional types from established communities ( Dıaz et al., 2003 ; Chen et al., 2020 ), are more powerful for discerning how extinction realistically affect ecosystem functioning. Despite being the major regulator for global biogeochemical cycles, the contribution of microbial diversity to ecosystem functions has been obscured until the last decade ( Philippot et al., 2013 ; Wagg et al., 2014 ; Bastida et al., 2016 ; Delgado-Baquerizo et al., 2016b ). Understanding the relationship between microbial composition and function at a global scale is essential for predicting changes in ecosystem function under various environmental disturbances ( Torsvik and Ovreas, 2002 ; Wellington et al., 2003 ; McGill et al., 2006 ). Although microbial communities are highly heterogeneous, their overall functions have been found to be similar ( Louca et al., 2016 ), possibly attributable to the functional redundancy of soil microbes ( Rosenfeld, 2002 ; Allison and Martiny, 2008 ). The extent of decoupling between taxonomy and function may also differ between “general” ecosystem processes carried out by a wide range of microbes, such as substrate decomposition ( Yin et al., 2000 ; Rousk et al., 2009 ; Banerjee et al., 2016 ), and “special” functions specialized by particular microorganisms ( Schimel and Körner, 1995 ; Balser et al., 2002 ), such as methane production. Yet, most microbial species loss studies used a random extinction model to create a gradient of microbial diversity achieved by serial dilutions ( Peter et al., 2011 ; Philippot et al., 2013 ; Delgado-Baquerizo et al., 2016a ). Hence, our knowledge on how soil biodiversity loss and simplification of soil community composition influence microbial functional profiles across the globe is still limited. With the advances in molecular biological technologies, metagenomics have been increasingly used as a promising tool ( Tringe et al., 2005 ) for studying the relationship between functional and taxonomic diversities ( Fierer et al., 2012a , b , 2013 ; Pan et al., 2014 ; Leff et al., 2015 ; Souza et al., 2015 ). Using metagenomics, the abundance of each gene can be assigned to a particular process, and numerous ecosystem functions can be examined simultaneously in one soil sample ( Allison and Martiny, 2008 ). The assessment of multiple functions at the same time acknowledge the importance of multifunctionality ( Hector and Bagchi, 2007 ) and can avoid overestimating functional redundancy ( Gamfeldt et al., 2008 ). To date, open-source web servers are publicly available for metagenomic analyses of taxonomic and functional diversities at global scales ( Nelson et al., 2016 ; Ramírez-Flandes et al., 2019 ), which enable in silico evaluation of changes in functional profiles responding to microbial species loss. Thus, a synthetic metagenome-enabled estimate of microbial community and function resulting from biotic homogenization is urgently needed. Here, we constructed five pairs of taxonomic and functional datasets to evaluate five levels of sequential species loss based on 933 soil metagenomes publicly available from 56 MG-RAST studies published in 56 peer-reviewed papers ( Figures 1 , 2A and Supplementary Table 1 ). On the basis of this global metagenomic study, we tested our hypotheses that: (1) compared to dramatic taxonomic variation, microbial functional structures are resilient to biodiversity loss, and (2) microbial homogenization caused differential responses in functional profiles between “general” and “special” processes. FIGURE 1 Global distribution of soil metagenomes. Locations of 933 soil metagenomes from 56 publications used in this study. Legends show seven groups of publication periods. Sample sizes of each group are given in parentheses. FIGURE 2 Significant species loss. (A) Names of remaining phyla following sequential species loss. (B) The species (S) and individuals (N) of taxonomic compositions at the genus levels and functional categories at the function levels affected by sequential species loss.",
"discussion": "Discussion Forecasting the changes in microbial functional in case of realistic extinction scenarios in terrestrial ecosystems is important for biodiversity conservation and management when confronting global environmental perturbations ( Peter et al., 2011 ; Philippot et al., 2013 ; Delgado-Baquerizo et al., 2016a ). Most insights into the evaluation of ecosystem functioning in response to biodiversity decline are based on animal and plant communities ( Chen et al., 2020 ), but microbial communities differ fundamentally from macroorganisms due to their high diversity and physiological versatility ( Peter et al., 2011 ). In this study, we clearly showed that a relatively stable functional profile calculated by relative abundance could be maintained in face of dramatic species decline in microbial communities ( Figure 4B ), as microbial communities have high taxonomic variability but stable functional structure ( Louca et al., 2016 ). It implies a high extent of functional redundancy in the soil microbial community across the globe. It should be noted that while removing phyla may result in a loss of genera, it does not necessarily lead to the loss of function unless the function concerned happens to be restricted to the removed phyla. Therefore, the functions tested in our study were based on the relative abundance of more than twelve thousands of specific genes, which provided the details of functional composition with resolution finer to function levels. Considering the functions that happen to be restricted to a specific phylum, we can identify the relationship of the loss of certain phyla and specific functions. Yet, the degree of functional redundancy in soil microbes really depends on the levels of manipulated variation in community diversity or the strength of disturbances. Using a dilution-to-extinction approach, some studies have shown that the loss in microbial diversity significantly affects functioning, such as microbial respiration, carbon decomposition, and nitrogen cycling ( Peter et al., 2011 ; Philippot et al., 2013 ; Delgado-Baquerizo et al., 2016a ). In our simulation, only 53 and 54% of the total number of individuals in taxonomy and function were removed from the datasets, respectively ( Figure 2 ), which were much less than the dilution-to-extinction approach that induced reductions by orders of magnitudes. However, all these studies of microbial species loss simulation focused on random extinction scenarios, as it is experimentally impossible to directly remove certain microbial groups sequentially. In reality, extinction risk is typically high for rare species with small populations ( Solan et al., 2004 ), because they are more vulnerable to environmental perturbations. If the extinction direction is random, we could simply attribute the stable functional structures to proportionally declined functional abundances. However, we used a biodiversity loss approach that reflects a more realistic scenario by removing less-common species first, so that highly abundant bacterial phyla, such as Proteobacteria and Actinobacteria, remained till the end to represent the “winning” survivors. Nevertheless, we found a nearly constant functional structure in the simplified communities compared to diverse ones with Archaea, Bacteria, and Eukaryota. It should be noted that in this study, the order of taxon removal was based on the relative abundance at the phylum level. Thus, future studies could examine the effect of ranking the abundance at the genus level or even applying random species loss as comparison for similar analyses. Interestingly, species loss did not reduce microbial taxonomic species and individuals in the same magnitude. For example, the first step of reduction to eight dominant bacterial phyla reduced nearly half of the taxonomic species but only caused a reduction of taxonomic individuals by 9%, suggesting that the removed 77 microbial phyla, including Archaea, Bacteria, and Eukaryota, included more diverse species but less relative abundance compared to the rest of the phylum-removing steps. On the contrary, sequential reduction of phylum numbers caused a linear reduction of both functional species and individuals, suggesting that although sequential species loss may cause an unequal decline of taxonomic species, the functional abundance was more proportionately reduced by each step of phylum number reduction. However, a steady functional response to species loss was calculated by relative abundance, so a significant reduction of total functional abundances, such as microbial activity, can cause serious damage to ecosystems if functional richness is lost together with microbial species. In addition, the functions measured in the previous studies were limited to simple broad-scale functions, which cannot provide a broad and detailed picture of multiple functions performed by different microbes, particularly when high microbial diversity in terrestrial ecosystems was considered. By comparing metagenomes of microbial communities, tens of thousands of functions can be evaluated at the same time, enabling deep assessment of higher level of functional diversity in our simulation. More importantly, the single or limited microbiomes tested in previous studies are too restricted to elucidate the relationship between taxonomic and functional diversities in a global perspective. Our results were simulated based on worldwide soil metagenomic datasets, covering various biomes, and hence can represent the diverse traits of soil microorganisms and strongly support that potential functional profile can be prospectively decoupled from taxonomic composition under certain circumstances, as has been suggested in a previous study ( Louca et al., 2018 ). It is often assumed that genome streamlining ( Morris et al., 2012 ) and horizontal gene transfer ( David and Alm, 2011 ), common in prokaryotic populations, have contributed to the functional similarity among distinct taxa. Some studies have observed a linear relationship between functional and taxonomic diversities, suggesting a somewhat dependency of microbial functional profiles on taxonomic compositions ( Fierer et al., 2012b , 2013 ; Leff et al., 2015 ). Our study differs from these experiments in that the RefSeq database was used for taxonomic assignment, whose diversity was greater than traditional ribosomal RNA databases commonly applied in previous research. Thus, we found that the taxonomic dissimilarity, pseudo- F value, was one order of magnitude larger than the function, leading to a decoupling of function from taxonomy in terrestrial microbial community as functional diversity remains relatively more stable. It is often assumed that microbial diversity reduction in natural soils would affect specialized microbial functions, such as nutrient-cycling processes, more significantly than broad-scale metabolic functions ( Yin et al., 2000 ; Rousk et al., 2009 ; Banerjee et al., 2016 ). We did not evidence that microbial functions of relatively lower abundances responded more sensitively to species loss, as the statistical significance ( F value) of ANOVA was not dependent on the relative abundance of each function ( Figure 5 ). Interestingly, we observed an opposite response that the broad-scale metabolisms conducted by a wide range of soil microbes decreased with community simplification, while typical nutrient-cycling functions relatively increased thereafter. These trends were mainly due to the order by which microbial community were reduced, as the remaining “winners,” Proteobacteria and Actinobacteria, are often considered the major regulators of terrestrial nutrient cycles ( Dai et al., 2018 , 2020 ). For example, certain sulfate- and iron-reducing bacteria, Desulfovibrio and Desulfobulbus , are Deltaproteobacteria ( Muyzer and Stams, 2008 ), and some bacteria conducting N cycling, such as ammonia oxidizers ( Stephen et al., 1996 ) and rhizobia for N fixation ( Moulin et al., 2001 ), mainly belong to Alphaproteobacteria or Betaproteobacteria. Due to the limitation of the functional datasets that are primarily based on metabolic reconstructions of bacterial genomes ( Glass et al., 2010 ), we may underestimate the contribution of those microbes other than the major remaining bacterial phyla to soil nutrient cycling, since archaea and fungi are discovered to play an important role in driving terrestrial biogeochemical cycles ( Offre et al., 2013 ), especially carbon and nitrogen functions ( Read and Perez-Moreno, 2003 ; Veresoglou et al., 2012 ), such as methane production ( Evans et al., 2019 ), and ammonia oxidation ( Stahl and De La Torre, 2012 ). When examining the functional profile of each functional category at level 1, which was detailed to specific function levels, we found that the variation of the beta-diversity of functions responding to species loss positively correlated with their relative abundance, suggesting that the simulated reduction of microbial species potentially affects the composition of the high-abundance functional categories more significantly than those of lower abundance. Therefore, microbial homogenization caused different function-specific effects on the beta-diversity of functional profiles between higher- and lower-abundance functions. However, these differences may be merely because functions with higher abundance contained more categories of specific genes, which had higher relative abundance than those of less abundant functions. Thus, the variation may be more significant for the functional composition of more abundant functions based on the calculation of the relative abundance of each gene at function levels. When we calculated the relative abundance of each functional category at level 1, the statistical significance was independent on their relative abundance. Thus, it is unlikely to draw a direct conclusion that less abundant functions react to simulated species loss less significantly than more abundant functions. Future studies evaluating the functional changes caused by species loss should emphasize on finer levels of functional resolution to avoid missing the variation of functional profiles occurring at finer levels. Due to the relatively stable functional structure, the interaction patterns of functional species were also similar across diversity decline levels without any notable loss of certain functional categories ( Figure 6 ). Simulated species loss caused a significant decline in the numbers of total nodes and negative links, suggesting that when community simplification makes the remaining microbes more uniform and similar to each other, the microbial interactions become mostly cooperative ( Faust and Raes, 2012 ). Thus, soil microbes under community simplification tended to respond to the environment in a similar fashion, while distinct microorganisms before community simplification competitively interact with each other, reflecting regulatory or suppression relationships ( Ma et al., 2018 ). However, the removal of certain phyla may reduce the numbers of species and individuals but did not affect the functional beta-diversity based on the relative abundance, and thus did not affect the overall interaction patterns in functions. The negative links also remained stable across different levels of species loss, showing that species loss did not make functional networks more facilitative or inhibitive. These findings support potentially decoupling responses of co-occurring patterns in taxonomy and function under simulated species loss. Future research, using a series of diversity reductions, to evaluate specific functions should also focus on the co-occurring patterns of multiple functions, which may help better elucidate the influence of species diversity on ecosystem functioning."
} | 4,836 |
36975332 | PMC10046621 | pmc | 3,308 | {
"abstract": "Biomimetic nanotechnology pertains to the fundamental elements of living systems and the translation of their properties into human applications. The underlying functionalities of biological materials, structures and processes are primarily rooted in the nanoscale domain, serving as a source of inspiration for materials science, medicine, physics, sensor technologies, smart materials science and other interdisciplinary fields. The Biomimetics Special Issues Biomimetic Nanotechnology Vols. 1–3 feature a collection of research and review articles contributed by experts in the field, delving into significant realms of biomimetic nanotechnology. This publication, Vol. 3, comprises four research articles and one review article, which offer valuable insights and inspiration for innovative approaches inspired by Nature’s living systems. The spectrum of the articles is wide and deep and ranges from genetics, traditional medicine, origami, fungi and quartz to green synthesis of nanoparticles."
} | 249 |
38647965 | PMC10992200 | pmc | 3,309 | {
"abstract": "In the context of the rapid development of low-carbon economy, there has been increasing interest in utilizing naturally abundant and cost-effective one-carbon (C1) substrates for sustainable production of chemicals and fuels. Moorella thermoacetica , a model acetogenic bacterium, has attracted significant attention due to its ability to utilize carbon dioxide (CO 2 ) and carbon monoxide (CO) via the Wood–Ljungdahl (WL) pathway, thereby showing great potential for the utilization of C1 gases. However, natural strains of M. thermoacetica are not yet fully suitable for industrial applications due to their limitations in carbon assimilation and conversion efficiency as well as limited product range. Over the past decade, progresses have been made in the development of genetic tools for M. thermoacetica , accelerating the understanding and modification of this acetogen. Here, we summarize the physiological and metabolic characteristics of M. thermoacetica and review the recent advances in engineering this bacterium. Finally, we propose the future directions for exploring the real potential of M. thermoacetica in industrial applications.",
"conclusion": "Conclusions and future prospects Microbial fixation and conversion of C1 gases are poised to play an important role in green biomanufacturing. As a representative autotrophic acetogen, M. thermoacetica has shown immense potential for industrial production of commodity chemicals using CO 2 /CO. However, due to the poor understanding an d insufficient genetic tools, the progresses in improving its metabolic capabilities have been limited to date. It is imperative to establish more efficient genetic tools for M. thermoacetica , particularly CRISPR-Cas-based genome editing and the derivative high-throughput screening technologies, such as pooled CRISPRi screening (Wang et al. 2018 ). This will help to accelerate our understanding of M. thermoacetica and strain modification for desired phenotypic traits. From the perspective of industrial applications, construction of artificial cell factories of M. thermoacetica for direct conversion of C1 gases into value-added products is the preferred route. Simultaneously, other approaches are also worth considering. For example, given the superior ability of M. thermoacetica in acetate synthesis, an attractive route is functional cooperation of the acetate production of M. thermoacetica grown on C1 gases and the acetate conversion mediated by other microorganisms, such as E. coli or yeasts. Such an integrated process will bypass the obstacles in genetic modification of M. thermoacetica , thereby enabling efficient synthesis of various value-added chemicals from C1 gases.",
"introduction": "Introduction C1 gases such as CO 2 and CO are abundant and cost-effective carbon resources that can be derived from various sources, including industrial off-gases (e.g., steel manufacture, and oil refining and coal chemical industries) or through gasification of forestry and agricultural wastes (De Tissera et al. 2019 ). In addition, CO 2 is a major greenhouse gas that contributes to global warming (Balcombe et al. 2018 ). Consequently, the capture and utilization of these C1 gases have attracted great attention due to the need to reduce greenhouse gas emission and achieve sustainable production of chemicals and fuels with minimal and even negative carbon footprint. In comparison with chemical catalysis, microbial conversion has specific advantages in the utilization of C1 gases, particularly in the synthesis of medium and long-carbon chain products (Bae et al. 2022 ; Liu et al. 2020a ). For example, acetogenic bacteria have ability to capture C1 gases and convert them into multiple products using different energy forms (Liao et al. 2016 ). Furthermore, several acetogenic bacteria can use both C1 gases (CO and CO 2 ) and liquid C1 sources, such as formate, showcasing a wide substrate range (Jia et al. 2021 ; Neuendorf et al. 2021 ). Moorella thermoacetica, initially known as Clostridium thermoaceticum due to its morphological and physiological similarities to Clostridium species (Fontaine et al. 1942 ), is one of the earliest isolated acetogens (Drake et al. 2008 ). However, in the late 1990s, it was officially renamed M. thermoacetica during the reclassification of the genus Clostridium (Collins et al. 1994 ). Over time, a series of M. thermoacetica strains have been identified (Table 1 ), in which some have received extensive concern (Redl et al. 2020 ; Sakai et al. 2005 ; Wang and Wang 1984 ). As a thermophilic bacterium, M. thermoacetica normally grows within 45‒65 °C, with an optimum temperature of 55–60 °C. The thermophilic characteristic of M. thermoacetica reduces the risk of bacterial contamination during its fermentation (Kato et al. 2021 ). Despite showcasing the potential in the utilization of C1 gases, natural M. thermoacetica strains still have large promotion space in carbon conversion efficiency and product yield. Consequently, much effort has been taken in the design and construction of artificial M. thermoacetica strains with the advent of suitable genetic tools for this bacterium in the past decade. Table 1 Physiology and traits of major M. thermoacetica strains Organisms Genome Size (Mbp) Carbon sources Optimal temperature (℃) Products a References HUC22-1 ‒ H 2 /CO 2 , fructose 55 840 mM acetate, 15.4 mM ethanol (Sakai et al. 2005 , 2004 ) ATCC 31490 Contig (2.61680) H 2 /CO 2 , fructose, glucose 60 48.3 mM (Redl et al. 2020 ; Schwartz Robert and Keller Jr Frederick 1980 ) ATCC 33924 Contig (2.91484) Xylose, CO, CO 2 55 222 mM acetate (Redl et al. 2020 ; Savage et al. 1987 ) ATCC 39073 Complete (2.62878) Xylose, fructose, glucose, H 2 /CO 2 , CO, pyruvate, formate, vanillate 55 933 mM acetate, 10 mM acetone (Fröstl et al. 1996 ; Kato et al. 2021 ; Poehlein et al. 2015 ; Redl et al. 2020 ; Rosenbaum et al. 2021 ; Schaible 1997 ; Wang & Wang 1984 ) ATCC 39073-HH Complete (2.64566) Sucrose, xylose, fructose, glucose, H 2 /CO 2 , methanol, pyruvate 55 − (Redl et al. 2020 ) ATCC 39289 − Xylose, glucose, pyruvate, formate 55 750 mM acetate (Keller Jr Frederick et al. 1983 ; Reed William 1984 ) ATCC 49707 Contig (2.61685) Glucose, fructose, xylose, H 2 /CO 2 55 401.7 mM acetate (Andreesen et al. 1973 ; Brumm Phillip and Datta 1985 ; Redl et al. 2020 ; Schaible 1997 ) DSM 103132 Complete (2.97608) Sucrose, arabinose, formate, fructose, glucose, H 2 /CO 2 , methanol, pyruvate, 60 − (Redl et al. 2020 ) DSM 103284 Complete (2.56038) Xylose, fructose, glucose, H 2 /CO 2 , methanol, pyruvate, rhamnose, xylose 60 − (Redl et al. 2020 ) DSM 11768 Contig (2.85144) Fructose 60 − (Redl et al. 2020 ) DSM 12797 Contig (2.74601) H 2 /CO 2 , CO/CO 2 , lactate, formate, cellobiose, fructose, glucose 60 18.4 mM acetate, 13.7 mM succinate, 1.8 mM lactate, 8.6 mM ethanol, 2.4 mM formate (Gößner et al. 1999 ; Redl et al. 2020 ) DSM 12993 Contig (2.64895) Fructose 60 − (Redl et al. 2020 ) DSM 2955 Complete (2.62335) Xylose, fructose, glucose, H 2 /CO 2 , methanol, pyruvate, CO 60 − (Bengelsdorf et al. 2015 ; Redl et al. 2020 ) Y72 Scaffold (2.60381) Xylose 60 − (Tsukahara et al. 2014 ) − no available data a The highest product levels reported for corresponding strains In this review, we summarize the current knowledge regarding the physiological and metabolic characteristics of M. thermoacetica . We also discuss the recent progresses in metabolic design, engineering, and fermentation optimization of this acetogen. While genetic tools are currently available for M. thermoacetica , we propose the direction of further optimizing the toolbox for efficient strain modification and improvement. Furthermore, we highlight the future challenges that need to be addressed to fully explore the real potential of M. thermoacetica in C1 gas utilization."
} | 1,978 |
37197028 | PMC10173371 | pmc | 3,310 | {
"abstract": "Microbial communities play a crucial role in ecosystem function through metabolic interactions. Genome-scale modeling is a promising method to understand these interactions. Flux balance analysis (FBA) is most often used to predict the flux through all reactions in a genome-scale model. However, the fluxes predicted by FBA depend on a user-defined cellular objective. Flux sampling is an alternative to FBA, as it provides the range of fluxes possible within a microbial community. Furthermore, flux sampling may capture additional heterogeneity across cells, especially when cells exhibit sub-maximal growth rates. In this study, we simulate the metabolism of microbial communities and compare the metabolic characteristics found with FBA and flux sampling. We find significant differences in the predicted metabolism with sampling, including increased cooperative interactions and pathway-specific changes in predicted flux. Our results suggest the importance of sampling-based and objective function-independent approaches to evaluate metabolic interactions and emphasize their utility in quantitatively studying interactions between cells and organisms.",
"conclusion": "6. Conclusion In this work, we evaluate the effect of flux sampling on three standard approaches for modeling the interactions between microbes at the genome-scale. The method clearly distinguishes between optimization-based and sampling-based characterizations of the metabolic interactions within a community. We demonstrate the utility of flux sampling in quantitatively studying metabolic interactions in microbial communities.",
"introduction": "2. Introduction Microbes are essential components of all living ecosystems, and the metabolic interactions between them are a significant factor in the functioning of these ecosystems. Microbe-microbe metabolic interactions affect nutrient cycling, energy production, and the maintenance of microbial diversity 1 – 3 . Though our understanding of those microbial communities is aided by metagenomics and in vitro analyses, there is a significant gap in mechanistic understanding of the makeup and interactions between members of microbial consortia 4 , 5 . Genome-scale modeling has emerged as a promising method by which we can probe an organism’s metabolic states, behaviors, and capabilities, alone or as a community 6 – 12 . Genome-scale metabolic modeling is a mathematical approach that uses the known biochemical reactions of a species to reconstruct a genome-scale metabolic network. Genome-scale models (GEMs) provide a holistic view of an organism’s metabolism, allowing for mathematical analyses that simulate metabolic fluxes and thus provide insight into metabolic pathways and physiological processes. The genome-scale model consists primarily of a stoichiometric matrix, characterizing the interconversion of metabolites by the set of metabolic reactions, linked with a set of Boolean expressions describing the gene-protein-reaction relationships 40 . Flux balance analysis is a constraint-based approach for analyzing that metabolic network to predict metabolic fluxes through the GEM. Much work has recently been applied to understand the metabolic interactions of a microbial community in various contexts, including the human gut microbiota and in environmental bioremediation 14 – 19 . Given the ubiquity of microbial activity, there is substantial value in using metabolic modeling to understand these communities’ emergent behaviors and abilities. Most metabolic modeling of microbial interactions is performed in one of three ways ( Figure 1 ): (1) compartmentalization , wherein two metabolic models are merged into a single stoichiometric matrix with a shared compartment representing the extracellular space, (2) lumped model (also called “enzyme soup”) approach, where all metabolites and reactions are pooled into a single model in proportion to the community makeup, and (3) costless secretion , where models are separately simulated while dynamically and iteratively updating the simulated environment by adjusting the models’ exchange reactions and available nutrients based on metabolites that can be secreted without decreasing growth (costless metabolites) 19 – 26 . Each of these approaches has shown promise, and selection of which approach to use heavily depends on available data and models and the intended goal of the analysis. As currently implemented, each method uses flux balance analysis (FBA), a linear programming technique that predicts the flow of material through the metabolic network 27 – 29 . FBA depends on the maximization of an objective function, and maximizing biomass production is most commonly used. Optimizing for biomass assumes species are entirely oriented towards maximal growth, thus ignoring the multiplicity of achievable sub-optimal phenotypes 30 . When simulating the metabolism of a community, this assumption can disregard the variety of metabolic interactions that the microbes may carry out. Furthermore, the selection and definition of the best objective function substantially affect model predictive power and generated results 31 – 34 . As an alternative to FBA, flux sampling has recently been used to predict flux distributions in a variety of cases and may provide a more holistic and accurate description of the cell’s flux distribution 35 – 39 . This is done by randomly generating many flux values for each reaction in a genome-scale metabolic model, while respecting its defined constraints, such as mass or energy balance and thermodynamic restrictions. Flux sampling employs Markov chain Monte Carlo methods to estimate cellular flux and generate many feasible metabolic flux distributions. Flux sampling estimates the most probable network flux values, enabling statistical comparisons of the flux distributions. Notably, the approach does not require a selected cellular objective, thus reducing user-introduced bias on model predictions and exploring the entire constrained solution space. The approach therefore enables studies of phenotypic heterogeneity, as a single constrained model can generate a range of flux predictions. However, flux sampling has not been widely employed in analyses of microbial communities. Furthermore, comparisons between FBA-based and sampling-based analyses of communities are currently lacking. In this work, we apply flux sampling to existing analyses of microbial metabolic interactions, showing the range of potential consortia-wide flux distributions achievable with genome-scale modeling. We find significant differences in model predictions between FBA and flux sampling, with substantial heterogeneity across sampled simulations. We see emergent patterns at sub-maximal growth rates, such as increased cooperation between microbes in anoxic conditions compared to oxygen-rich environments. In total, we systematically evaluate the effect of flux sampling, and emphasize the utility of objective function-agnostic approaches to evaluate metabolic interactions.",
"discussion": "5. Discussion Phenotypic heterogeneity, even in the monoculture of a genotypically uniform population, is known to have a substantial effect on observed community outcomes. However, the effects of this heterogeneity have yet to be fully studied, despite the rapid and substantial increases in modeling efforts at the genome-scale. In addition, microbes have been shown to exhibit sub-maximal growth, which needs to be sufficiently addressed with GEMs. While phenotypic heterogeneity and sub-maximal growth dynamics have been studied in individual GEMs of microbial activity , these two phenomena have not been analyzed for models of microbial interactions 30 , 52 – 58 . In this work, we demonstrate how pairing disparate existing approaches of flux sampling and modeling of communities pushes the field of metabolic modeling forward. We systematically evaluate the predictive effects of replacing FBA and its central assumption of maximal growth with flux sampling approaches. In particular, we assess the effect of exploring the entire flux solution space with three distinct approaches of microbial community modeling: the compartmentalized approach, the lumped model or “enzyme soup” approach, and the costless secretion approach. With each approach, we replicate the major conclusions achieved with optimization of biomass using FBA For example, we predict higher frequency of cooperation under anaerobic conditions. Furthermore, applying flux sampling expands our understanding of the systems-level heterogeneity that gives rise to observed community activity. For the compartmentalized approach, we show increased tendency toward stable consortia and provide an ability to identify distinct growth rate-dependent interaction regimes. For the lumped modeling approach, we predict large differences in the predicted flux for certain pathways and reactions than others, and in the turnover of specific metabolites. With the costless secretion approach, we predict a substantially wider range of metabolites secreted, enabling growth on substrates that had not been predicted when optimizing biomass using FBA. As previously found, most observable metabolic heterogeneity across a population has two primary sources: variation in network structure and variation in network usage (divergence in form and functional utilization) 59 . Ensemble modeling of GEMs has been shown to lead to increased accuracy and is of particular focus to the field with the emergence of novel tools; however, an equivalent effort has not been put towards understanding heterogeneous states achieved with a consistent network, despite the existence of flux sampling of GEMs as a tool for the past 20 years 60 , 61 . To our knowledge, one paper has used sampling to study cell-cell metabolic interactions 62 . Other researchers have identified this gap, and future work can more earnestly utilize and leverage the technique 63 . We recognize some limitations of our work. A particular area for improvement of genome-scale modeling is the difficulty in assigning constraints for the reaction fluxes. Without appropriate bounds on metabolic reaction rates, flux sampling may explore biologically unreasonable metabolic states. The emergence of novel experimental tools is particularly promising to address this limitation. For example, -omics technologies enable in vitro and in vivo measurements of growth rates, metabolite secretion, and impact of enzymatic knockouts. Such data can be used to provide biologically reasonable constraints on reaction fluxes. In addition, we used thresholding to keep the analyses computationally feasible. However, this potentially limits our results. Improvements in computational ability, from advances in computing speed and algorithm development, will enable us to investigate the full range of biological outcomes possible with flux sampling without imposing artificial thresholds. Finally, we evaluated microbial fitness and interspecies relationships based on growth rate using flux sampling, eliminating the necessity of maximizing biomass. Future work can explore alternative metrics to assess cellular behavior. This is especially important because genome-scale modeling is increasingly used for eukaryotic (principally human) cells, where growth rate as a proxy for cell health is less supported 64 – 69 . For example, rather than focusing on growth, we could instead study flux through a specific reaction or pathway known to mediate the behavior of a particular cell type."
} | 2,870 |
40069904 | PMC11899425 | pmc | 3,311 | {
"abstract": "Background In plants, root exudates selectively influence the growth of bacteria that colonize the rhizosphere. Bacterial communities associated with root systems are involved in macro and micronutrients cycling and organic matter transformation. In particular, iron is an essential micronutrient required for the proper functioning of iron-containing enzymes in processes such as photosynthesis, respiration, biomolecule synthesis, redox homeostasis, and cell growth in plants. However, the impact of changes of iron availability on the structure and set of ecological interactions taking place in the rhizosphere remains poorly understood. In this study, field experiments were conducted to compare the effects of iron supplementation (0.1 and 0.5 mM of FeSO 4 ) on the assembly of the bacterial community of rhizosphere soil and bulk soil in a perennial grass present in the Andes steppe of Atacama Desert. Results The results indicated that the difference in beta diversity between bulk soil and rhizosphere soil detected before supplementation did not persist after iron supplementation, in addition, co-occurrence networks showed a significant reduction in negative interactions among soil bacteria, mainly in rare taxa (< 0.1% relative abundance). Conclusions These observations suggest that iron availability contributes to the differentiation between bulk soil and rhizosphere bacterial communities, a process that is linked to significant changes in the relative abundance of more abundant species (> 0.1% relative abundance) and with a decrease in the negative interactions in both compartments after metal exposure. The differential effect of iron on the competition/cooperation ratio between bulk soils and the rhizosphere microbiome supports the hypothesis that the host limits the degree of cooperation that can be achieved by the bacterial community associated with an organ dedicated to nutrient absorption. Supplementary Information The online version contains supplementary material available at 10.1186/s40793-024-00661-7.",
"conclusion": "Conclusions Our study indicates that iron supplementation led to a significant reduction in the beta diversity difference between rhizosphere soil and bulk soil, suggesting that iron has a role in the differentiation between these two compartments. Additionally, the co-occurrence networks revealed a notable decrease in negative interactions among soil bacteria, particularly among rare taxa. These findings suggest that changes of iron availability play an important role in shaping the bacterial community dynamics, enhancing cooperation while reducing competition. Although, the distinct effect of iron supplementation in competition/cooperation ratio between the rhizosphere and bulk soil supports the notion that the host plant modulates the degree of cooperation that can be reached by a bacterial community associated with a host.",
"discussion": "Discussion Iron supplementation influences beta-diversity of soil bacterial communities Understanding how soil bacterial communities respond to environmental changes, such as nutrient availability, is crucial to address global challenges like desertification and climate change [ 69 ]. Soil microorganisms in the Andes of Atacama Desert cope with a general nutrient limitation, including a low availability of soluble iron [ 48 , 70 ], a metal that has a predominant role in microorganism communities [ 71 ]. In this work, compared to reference values [ 48 ], the soluble iron content in the BS and RS compartments was below the lower limit detected in agronomic soils. After iron supplementation, the soluble content of the metal increased, reaching a value that exceeded 1.4 to 1,9 times the minimal agricultural reference value for this nutrient. Moreover, after iron supplementation, the iron content in the root tissue of P. frigida increased four to five times, suggesting that P. frigida root system was able to absorb the supplemented iron and that the plant was far from its maximum iron storage capacity. Thus, it seems reasonable to assume that changes in the structure and interaction pattern of the bacterial community were associated with an increase in iron availability due to iron supplementation in the soil. Surprisingly, beta-diversity analysis revealed that before supplementation, the BS and RS bacterial communities of P. frigida showed marked dissimilarity and after supplementation, this dissimilarity no longer persisted. Interestingly, an increase in beta diversity or community dispersion has been observed across different environments and stressor types [ 72 ]. In this scenario, the observed changes in beta diversity could be interpreted according to the Anna Karenina principle [ 73 ], i.e. “stressed microbiota vary more than those unstressed” [ 74 ]. In this line of reasoning, Rocca et al. [ 72 ] suggests that stress increases beta diversity (dissimilarity) among microbial communities, and when stress decreases, the differences in beta diversity caused by the stressor also decreases, making the communities more similar to each other. Thus, our results indicate that iron availability can be a crucial factor driving microbiome structure and assembly in both the BS and the RS. Although plant species tend to assemble relatively distinct rhizobacterial communities [ 74 ] by stimulating or repressing bacterial growth [ 12 – 14 ] or by altering the soil microhabitat [ 15 – 17 ], Our results suggest that the increase in iron content produced by supplementation modified the availability of iron in BS and RS, shaping the assembly of microbiomes in both compartments. On the other hand, it is known that the nutrient status of the plant has a profound effect on the exudation pattern of the roots [ 38 , 75 ], therefore it the increment of iron in roots of P. frigida may have triggered a response in the plant, affecting the plant–microbe interactions at the rhizosphere level. In fact, the rhizosphere of P. frigida exhibits a variety of compounds such as organic acids, sugars, as well as, primary and secondary metabolites [ 18 ] that might have a substantial influence on the composition and structure of the rhizosphere microbiome [ 19 , 41 ]. In this context, the synthesis of plant-derived coumarin in response to changes in iron availability has been shown to modulate the composition of rhizosphere [ 38 , 43 , 76 ] due to coumarin antimicrobial activity [ 43 ]. Interestingly, among the wide range of metabolites that P. frigida exudes, the presence of coumarins was detected [ 18 ]. Thus, we speculate that synthesis and secretion of coumarin (without iron supplementation), may be part of the mechanism that sustains the dissimilarity between BS and RS of P. frigida , a mechanism that could be altered after iron supplementation. However, further studies are required to evaluate when coumarin synthesis and secretion decreases in response to an increase in iron availability. In terms of how the change in beta diversity metrics was produced, our data indicate that the percentage of ASVs with significant differences in abundance between BS and RS decreased from 81 to 43% after iron supplementation, including known plant growth-promoting bacteria [ 48 ]. At the family level, 23 families representing the 17% of relative abundance in RS, exhibited significant differences in their relative abundance only before iron supplementation. This result supports the notion that the recruitment strategy of plants can be modulated by the nutrient availability, as has been proposed by Trivedi et al. [ 77 ] for plants under iron or phosphorus stress conditions. Moreover, iron availability can modify the ecological interactions among members of the bacterial community. For example, it has been suggested that the low availability of iron in soil and the high iron demand of plants and microorganisms could induce a considerable level of competition for iron in the rhizosphere [ 78 , 79 ]. Iron modifies the positive/negative interactions in soil bacterial communities Since that the ratio of positive/negative interactions strongly impacts the structure of the bacterial communities [ 20 , 80 ], we assessed whether iron supplementation modulates the ratio of positive/negative interactions in the BS and RS bacterial communities. Our results showed that most of the negative interactions were inter-modules while positive interactions were intra-modules and that according to our hypothesis, negative interactions decreased among members of bacterial communities both in the BS and RS compartments after iron supplementation, mainly among rare taxa. The decrease in negative interactions in response to iron was also observed in the subnetworks of candidate driver taxa. Interestingly, two of the three driver taxa that change their abundance from rare to abundant after iron supplementation belong to the genera Blastococcus (Actinobacteria) and Haliangium (Proteobacteria), which are more abundant in the bulk soil than the rhizosphere [ 80 ] suggesting that these bacteria respond to change of iron availability increasing their abundance and modifying the interaction pattern of bacterial community. The third driver taxa belong to Sphingomonadaceae family (Proteobacteria), which has been has been observed to enhance plant growth [ 81 ], suggesting that these bacteria could connect the function of PGP with the assembly of bacterial community. As observed within the microbiomes of diverse plant hosts [ 82 , 83 ], the rhizosphere of P. frigida showed a large proportion of low abundance species (relative abundance less than 0.1% or 0.01%) defined as “rare biosphere” [ 28 , 84 ], which may be the result of competition induced by nutrient-poor conditions [ 83 ]. It is therefore reasonable to assume that an increase in iron concentration will reduce the competition for this micronutrient, especially in rare taxa. This idea is supported by a study comparing bacterial communities in nutrient-rich coastal sediment and nutrient-scarce pelagic zones of the ocean [ 24 ], and demonstrates that the abundance profiles of bacterial species (rare versus abundant) were influenced by nutrient availability. Furthermore, a continental-scale study in the eastern China [ 85 ] showed that the factors that most affected co-occurrence relationships between taxa were organic matter and iron content, further supporting the importance of these factors on soil bacterial interactions. On the other hand, co-occurrence networks showed that there was a 3-fold increase in the ratio of positive/negative interactions within bulk soil bacterial community, while in the P. frigida rhizosphere the increase was 1.5-fold. Since cooperative interactions in bacterial communities promote overall metabolic efficiency [ 86 ], an increase in positive interactions may be beneficial to the community. However, an increase in cooperativity can result in a decrease in bacterial community stability, as it may lead to metabolic dependencies among bacteria [ 20 ]. Considering that bacterial communities not only evolve, but also co-evolve with their host [ 86 ], it is of vital importance for the host, as well as for any taxa being part of their associated microbiome, that the community equilibrium remains stable. Following this line of reasoning, our results provide empirical evidence in support to the model of Coyte et al. [ 20 ], which proposes that the host can impose a limitation to increase cooperativity (in our case caused by iron availability) within the community. In a more practical context, this study contributes to understanding the effects of nutrient supplementation strategies on microbial interactions and their impact on plant health, a knowledge that will help to develop nutritional interventions in arid regions. Study limitations and perspectives Although valuable insights were gained in this study by applying an experimental strategy to test ecological theories in a natural environment, some limitations need to be considered. First, the length of the experimental intervention, the use of a single iron pulse, and the short interval between its application and sampling may not have been enough to capture the full extent of microbial community responses to iron supplementation over time. For example, it has been proposed that the Anna Karenina principle may be a transient state in nature that may precede the resilience of the animal/plant holobiont [ 74 ]. Alternatively, the loss of dissimilarity in microbiome composition between bulk and rhizosphere soils could be a consequence of the selection pressure exerted by the iron supplementation on the microbiome and/or plant, overcoming or masking the differentiating effect exerted by the plant exudates. When the effect of iron supplementation dissipates, we can expect that differences in beta diversity between BS and RS will be restored. Second, it is important to be cautious when interpreting interactions between taxa predicted by co-occurrence network analysis, as they are often interpreted as direct biotic interactions (true ecological relationships such as competition or cross-feeding). However, they may reflect changes in indirect interactions among species that correlate as a consequence of responding in the same way to iron supplementation."
} | 3,324 |
33273477 | PMC7712892 | pmc | 3,312 | {
"abstract": "As a new-era of energy harvesting technology, the enhancement of triboelectric charge density of triboelectric nanogenerator (TENG) is always crucial for its large-scale application on Internet of Things (IoTs) and artificial intelligence (AI). Here, a microstructure-designed direct-current TENG (MDC-TENG) with rationally patterned electrode structure is presented to enhance its effective surface charge density by increasing the efficiency of contact electrification. Thus, the MDC-TENG achieves a record high charge density of ~5.4 mC m −2 , which is over 2-fold the state-of-art of AC-TENGs and over 10-fold compared to previous DC-TENGs. The MDC-TENG realizes both the miniaturized device and high output performance. Meanwhile, its effective charge density can be further improved as the device size increases. Our work not only provides a miniaturization strategy of TENG for the application in IoTs and AI as energy supply or self-powered sensor, but also presents a paradigm shift for large-scale energy harvesting by TENGs.",
"introduction": "Introduction As a common phenomenon, the contact electrification (CE) has been known for a long time 1 . Based on the fundamental physical mechanism of CE, the triboelectric nanogenerator (TENG) was first invented by Wang and colleagues 2 , which provides a strategy for converting randomly distributed and irregular mechanical energy into electric energy 3 – 5 . Various TENGs have been intensively conducted in two categories: (i) coupling CE with electrostatic induction, the TENG gives an alternating current (AC-TENG) 6 – 8 ; (ii) coupling CE with electrostatic breakdown, the TENG generates a direct current (DC-TENG) 9 , 10 . These different types of TENGs provide effective techniques for harvesting distributed mechanical energy, wave energy, and biomechanical energy, and show a great potential in application of Internet of Things, implantable medical devices, and artificial intelligence as micro/nano energy or self-powered sensors 11 – 16 . As an energy harvester, how to improve the output performance of TENG, which is determined by its surface charge density quadratically 17 , is a crucial problem for its commercial applications. The limitation factors of effective surface charge density of AC-TENG ( σ AC-TENG ), which can be effectively converted into electric power to drive an external load, can be described as 18 : 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}$$\\sigma _{{\\mathrm{AC}} - {\\mathrm{TENG}}} = {\\mathrm{min}}\\left( {\\sigma _{{\\mathrm{triboelectrification}}},\\sigma _{{\\mathrm{r}},{\\mathrm{air}}\\,{\\mathrm{breakdown}}},\\sigma _{{\\mathrm{dielectric}}\\,{\\mathrm{breakdown}}}} \\right)$$\\end{document} σ AC − TENG = min σ triboelectrification , σ r , air breakdown , σ dielectric breakdown where σ triboelectrification is the triboelectrification charge density, σ r, air breakdown is the remaining surface charge density after the air breakdown between two friction surfaces, and σ dielectric breakdown is the maximum charge density that the dielectric can store. The charge density of TENGs can be increased with the enhancement of σ triboelectrification by materials optimization and structure design 19 – 21 . However, with rising charge density on dielectric surface, the air breakdown will occur between two friction surfaces and part of charges will be released, resulting in the limitation of σ r, air breakdown . High-vacuum environment can avoid the air breakdown and thus significantly improve the charge density of TENG up to ~1 mC m −2 18 . Ultrathin friction dielectric film is another strategy to elevate the threshold of σ r, air breakdown 22 . Furthermore, taking advantage of external circuit optimization to break through the limitation of σ triboelectrification , e.g., the charge pumping 23 , 24 and charge excitation 25 , 26 , the charge density reaches to a milestone of 2.38 mC m −2 26 . However, the effective surface charge density of TENG is still limited by the dielectric breakdown of friction dielectric layer ( σ dielectric breakdown ). As a new type of TENG, the DC-TENG can directly power electronic devices without the auxiliary rectifier circuits and energy storage units 9 . The working mechanism of DC-TENG is based on the triboelectrification effect and the electrostatic breakdown between the friction surface and the charge-collecting electrode (CCE; detailed in Supplementary Note 1 ), which is free from the limitation of σ dielectric breakdown . Therefore, the limitation of its effective surface charge density ( σ DC-TENG ) can be described as: 2 \\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}$$\\sigma _{{\\mathrm{DC}} - {\\mathrm{TENG}}} = {\\mathrm{min}}\\left( {\\sigma _{{\\mathrm{triboelectrification}}},\\sigma _{{\\mathrm{c}},\\,{\\mathrm{electrostatic}}\\,{\\mathrm{breakdown}}}} \\right)$$\\end{document} σ DC − TENG = min σ triboelectrification , σ c , electrostatic breakdown where σ c, electrostatic breakdown is the collected charges from electrostatic breakdown (generally air breakdown), which can be improved by the enhanced thermionic emission of electrons or the avalanche breakdown effect 27 . However, the reported maximum value is only 0.64 mC m −2 due to the limitation of σ triboelectrification 27 , which is lack of the accumulation process of triboelectric charges compared with AC-TENG. Here we provided a strategy to significantly enhance the charge density of DC-TENG by microstructural design with rationally patterned electrode structure, whose limitation factor can be described as follows: 3 \\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}$$\\sigma _{{\\mathrm{DC}} - {\\mathrm{TENG}}} = {{k}} \\times {\\mathrm{min}}\\left( {\\sigma _{{\\mathrm{triboelectrification}}},\\sigma _{{\\mathrm{c}},\\,{\\mathrm{electrostatic}}\\,{\\mathrm{breakdown}}}} \\right)$$\\end{document} σ DC − TENG = k × min σ triboelectrification , σ c , electrostatic breakdown where the k is a factor related to the electrode structure. The microstructure-designed DC-TENG (MDC-TENG) realizes the miniaturized sliding block structure and high-output performance at the same time. By tailoring the electrode structure (where k = 50), the effective surface charge density of MDC-TENG with the size of 1 cm × 5 cm can be improved to 5.4 mC m −2 , which is more than two times of existing record for various type of TENGs. Of particular significance is that the charge density of the MDC-TENG can be further improved with a larger size and a higher k -value. Except for the high-output performance, its output current is closely related with the motion vector parameters, such as velocity, acceleration, and distance. These excellent performances represent potential applications of the MDC-TENG in mechanical energy harvesting and motion vector sensing. Especially, its advantages of miniaturization and simple external circuit resulted from DC output provide a solution strategy for TENGs to be applied in small electronic device systems or micro-electro-mechanical system (MEMS) as an energy supply resource or self-powered sensor. Moreover, the significantly enhanced charge density for the large-sized TENG also shows huge potential for the large-scale energy-harvesting application.",
"discussion": "Discussion In summary, contributed by the microstructural design, we provide an MDC-TENG device with rationally patterned electrode structure, whose triboelectrification charges on the friction charged dielectric surface can be released by electrostatic breakdown and collected by CCEs repeatedly. The effective surface charge density of MDC-TENG (with the size of 1 cm × 5 cm) increases with the electrode structure factor ( k ), reaching 5.4 mC m −2 with k = 50, which is a milestone of TENGs. More interestingly, the MDC-TENG realizes the miniaturized device structure with high output, and the output characteristic shows good relationship with motion vector parameters (velocity, acceleration, and distance). This provides a huge potential applications in miniaturized electronic device systems as energy supply resource or in MEMS as sensor unit. On the other hand, the charge density can be further improved not only by the finer optimization of device structure and preparation technology via micro/nano processing technology to improve k -value furthermore in the future, but also by the enlargement of the DC-TENG size. The latter optimization method can overcome the charge density and current density attenuation of AC-TENG with the device size increasing, which provides a paradigm shift of the large-scale energy-harvesting system for TENGs."
} | 2,303 |
39496625 | PMC11535214 | pmc | 3,313 | {
"abstract": "Microbes perform critical functions in corals, yet most knowledge is derived from the photic zone. Here, we discover two mollicutes that dominate the microbiome of the deep-sea octocoral, Callogorgia delta , and likely reside in the mesoglea. These symbionts are abundant across the host’s range, absent in the water, and appear to be rare in sediments. Unlike other mollicutes, they lack all known fermentative capabilities, including glycolysis, and can only generate energy from arginine provided by the coral host. Their genomes feature several mechanisms to interact with foreign DNA, including extensive CRISPR arrays and restriction-modification systems, which may indicate their role in symbiosis. We propose the novel family Oceanoplasmataceae which includes these symbionts and others associated with five marine invertebrate phyla. Its exceptionally broad host range suggests that the diversity of this enigmatic family remains largely undiscovered. Oceanoplasmataceae genomes are the most highly reduced among mollicutes, providing new insight into their reductive evolution and the roles of coral symbionts.",
"introduction": "Introduction Corals are foundation species that support diverse animal communities from shallow waters to the deep sea. Corals also associate with a diversity of microbes 1 , including the well-studied algal symbionts of the family Symbiodiniaceae and other microbial taxa that perform a variety of roles, from providing nitrogen through fixation 2 to causing disease 3 . Most of these microbes were identified in scleractinian corals from the photic zone 1 , while studies investigating the roles of microbes in octocorals 4 and deep-sea corals are rarer because of the limitations that great depths impose on sampling and experimentation. Such work requires the use of remotely operated vehicles or submersibles launched from ships. Still, studies have demonstrated that octocorals and deep-sea corals host some of the same associates as shallow-water scleractinians, such as corallicolid apicomplexans 5 – 8 and Endozoicomonas 9 – 12 . However, one study comparing deep-sea coral microbiomes to those in shallow-water corals found differences in metabolic activities, including increased anaerobic ammonia oxidation and increased chitin degradation 13 . In addition, deep-sea octocorals also host associates that are rare or absent in shallow-water and/or scleractinian corals. These associates include bacteria from the SUP05 cluster, whose role is linked to cold seeps in the deep sea 14 , and members of the class Mollicutes. Members of the class Mollicutes associate with many coral species and a wide diversity of plant, fungal, and animal hosts, including humans 15 , 16 . Several members are well-studied parasites 17 , while the impact of others on their hosts is unclear such as the ubiquitous intracellular symbionts of arbuscular mycorrhizal fungi 18 – 20 . Yet others are mutualists, such as Spiroplasma spp., that infect insects and confer protection against nematodes, parasitoid wasps, and fungi through the production of unique toxins 21 . Reflecting their lifestyles as symbionts, their evolutionary history is dominated by genome reduction, with some species considered to have the most reduced genomes capable of supporting cellular life 22 , 23 . Recently, novel and divergent mollicutes were discovered in diverse marine invertebrates, including a deposit-feeding holothurian from a deep-sea trench 24 ; pelagic, photosynthetic jellyfish 25 , 26 ; wood-boring, deep-sea chitons 27 ; ascidians from a coastal lagoon 28 , and crown-of-thorns sea stars from the Great Barrier Reef 29 . However, the impacts these symbionts have on their hosts remain unclear. Among coral species, mollicutes are most commonly found in octocorals 30 – 39 , but have also been reported in black corals 40 and stony corals 41 , 42 . These corals occupy a wide breadth of habitats from shallow-water reefs 36 , 39 , 43 , through the mesophotic zone 40 and the deep sea 31 , 32 , 41 to abyssal depths 44 . In these coral species, Mycoplasma spp. are the dominant microbes, comprising more than 50% of their associated microbial communities 32 , 39 , 43 . Interestingly, the relative abundances of Mycoplasma vary substantially across the ranges of individual coral species 38 , 43 . Thus, this association may be influenced by environmental conditions or otherwise shaped by geography, such as through limited dispersal. In addition, Mycoplasma spp. exhibit varying degrees of host specificity 33 , 38 , 39 . Co-occurring coral species host different Mycoplasma variants 33 suggesting that they may have adapted to their coral hosts and closely interact with them as symbionts. Despite these insights, the interactions between mollicutes and their host corals remain unknown. Here, we discover two novel bacteria of the class Mollicutes, which are abundant in the deep-sea octocoral Callogorgia delta. C. delta is common along the continental slope in the Gulf of Mexico between 400 and 900 m depth, where it is often the dominant habitat-forming coral species 45 , 46 . Like many deep-sea coral species, C. delta colonies create habitats for numerous animal species, including Asteroschema ophiuroids and the chain catshark, Scyliorhinus retifer , which lay their eggs directly on C. delta colonies 47 . To characterize the association between Callogorgia delta and these newly discovered mollicutes, we screen colonies from six sites in the Gulf of Mexico across 3 years of sampling (Fig. 1a ) using 16S metabarcoding to determine the prevalence of these novel mollicutes and quantify their relative abundances. We also screen the closely related species Callogorgia americana to assess the phylogenetic breadth of the association. C. americana , is another dominant habitat-forming species in the northern Gulf of Mexico and provides a good comparison species. C. americana occurs at shallower depths (300–400 m) while C. delta is often found near hydrocarbon seeps 46 . Further, we assess the specificity of the association to corals by screening sediment and water in addition to Callogorgia . We assemble the genomes of these novel mollicutes to describe their metabolic capabilities, determine their phylogenetic positions, and compare them to other mollicutes. To complement metabolic inferences, we sequence metatranscriptomes and so identify active genes and those with the highest transcription levels. Finally, we locate these mollicutes within coral tissue using catalyzed reporter deposition fluorescence in situ hybridization (CARD-FISH) microscopy and transmission electron microscopy. Fig. 1 Sampling locations and prevalence of novel mollicutes in Callogorgia delta and C. americana. a Map of locations where Callogorgia delta (black circles) and C. americana (gray diamonds) were sampled. Lines represent 500 m isobaths. The depth range of samples collected from each site is denoted below the site name followed by the number of colonies, sediment samples, niskin water samples (~2.5 L), then McLane pump water samples (~400 L) in parentheses. If no water or sediment samples were collected, only the number of colonies is shown. If no McLane pump water samples were taken, only the number of niskin water samples are shown. Map made using QGIS. Basemap attributions [World Light Gray Base]: ESRI, DeLorme, HERE, MapmyIndia. Bathymetric contours obtained from the Bureau of Ocean Energy Management. b Image of Callogorgia delta . c The relative abundances of novel mollicute ASVs. Each column represents the microbial composition based on 16S rRNA amplicon libraries obtained from a single colony. Colonies are organized by species, site, and sampling year. C. delta sites are ordered left to right by increasing depth. C. americana samples were extracted with a DNeasy allprep kit and C. delta samples from 2015 were preserved in ethanol. All other samples shown were frozen and extracted with DNeasy powersoil kits. For colonies with multiple replicates, the first replicate using frozen tissue is shown, and others are excluded.",
"discussion": "Discussion Novel mollicutes in Callogorgia delta are symbionts The data presented here suggests that Ca. Oceanoplasma callogorgiae and Ca. Thalassoplasma callogorgiae are symbionts of Callogorgia delta sensu Goff 65 . First, they were detected in C. delta colonies from all sites and sampling years. Further, their genomes were very reduced and demonstrated a reliance on compounds that are likely obtained from C. delta . Finally, Ca. Oceanoplasma callogorgiae likely resides within the coral. Abundant bacteria with mollicute-like morphology were observed in the mesoglea of C. delta and Ca. O. callogorgiae was the most abundant bacterium by far in both the amplicon dataset and the metagenomes. Additional evidence to confirm the presence of Ca. O. callogorgiae and Ca. T. callogorgiae in the coral mesoglea could come from applying species-specific FISH probes. Detection in sediment samples and transmission The two novel mollicute species may associate specifically with corals in the genus Callogorgia since both were absent in the surrounding water and appear to be rare in sediment, as indicated by their low relative abundance. However, it is possible that Oceanoplasmataceae have a relatively high absolute abundance in the sediment but only comprise a low relative abundance because the total abundance of the entire microbial community may be high. Another possibility is that DNA from Callogorgia and its symbionts can be found in the sediment as environmental DNA originating from sources such as the fecal matter of grazers. Interestingly, eDNA from fish species is orders of magnitude more abundant in the sediment compared to the surrounding water and degrades slower 66 , 67 . Alternatively, their detection in sediment libraries may be due to low levels of contamination from Callogorgia samples such as through tag jumping or lane jumping. Up to five Molli-1 sequences were detected in three out of four sequencing blanks whereas it averaged 19 reads in sediment samples and over 7000 in Callogorgia libraries. See Supplementary Information for further details. Further experimental work is needed to confirm the prevalence of Oceanoplasmataceae in the sediment. It is not clear how these symbionts are transmitted between coral colonies. Their streamlined genomes suggest they do not have a free-living stage. Therefore, it is possible that they are transmitted vertically through coral larvae. In addition, grazing fauna such as snails may serve as vectors transmitting symbionts between coral colonies. In shallow-water corals, corallivores including grazing gastropods are associated with the spread of bacterial and fungal pathogens 68 . Further, other mollicutes infect sessile hosts and are transmitted by mobile vectors, such as phytoplasmas, that infect plants and are spread by insects 69 . Metabolic processes and other fundamental activities of the symbionts Both Ca. Oceanoplasma callogorgiae and Ca. Thalassoplasma callogorgiae lacked genes encoding complete fermentative pathways and depended on arginine to generate ATP. They likely receive this arginine from their coral hosts as well as essential compounds such as amino acids, riboflavin, and biotin. Conversely, they export ornithine and possibly short peptides to their coral host. Ca. Oceanoplasma callogorgiae possessed extensive mechanisms to defend against viruses or other forms of foreign DNA. Its genome contained an extensive CRISPR array and some of the most abundant transcripts in both of our libraries were restriction-modification systems and endonucleases. Further, it shared additional genomic features with Ca. Thalassoplasma callogorgiae including comEC to import foreign DNA and enrichment of thymidine kinase genes that may salvage thymidine from DNA degradation. The presence of these antiviral characteristics in such highly reduced bacterial genomes suggests that they play a central role in the lifestyles of these bacteria. Other, not yet well-understood processes likely underly the basic functioning of these novel mollicutes since some of the most highly transcribed genes in this study had unknown functions. This includes U1, which is likely membrane-bound and potentially degrades cyclic di-GMP. Cyclic di-GMP is a second messenger involved in morphogenesis, motility, and virulence 70 . U1 may respond to external or host-derived stimuli as part of signaling pathways that could be linked to host innate immunity and symbiont recognition. However, the metabolic insights gleaned from the most abundant transcripts in this study are limited by a low sample size ( n = 2) which precludes standard statistical analyses and may not be reflective of general expression levels across populations. While Callogorgia delta is found near cold seeps, neither Ca. Oceanoplasma callogorgiae nor Ca. Thalassoplasma callogorgia appear to have an association with seeps. Their genomes did not possess any genes or pathways that could utilize compounds from seeps for energy or nutrition, such as reduced sulfur species or hydrocarbons including light alkanes. Further, both mollicutes were also detected in C. americana , which is not found near cold seeps. Residence in the mesoglea Ca. O. callogorgiae likely resides in the mesoglea of C. delta . The mesoglea of cnidarians is composed of a largely acellular, mucoid matrix of collagen containing some cells such as amoebocytes 71 . The mesoglea provides rigidity upon which the muscles of the polyp can act but also facilitates the transport of nutrients 72 , 73 . Some compounds diffuse through the mesoglea, like glucose and fatty acids 72 , 73 , while amoebocytes can shuttle compounds such as amino acids 72 . Ca. O. callogorgiae probably acquires compounds including arginine, other amino acids, and the precursors of coenzymes such as riboflavin from the mesoglea because it lacks the genes necessary to synthesize them. The mesoglea in cnidarians is also a site of immune defense 74 – 76 . Bacteria that reside in the mesoglea must evade the coral’s immune defenses, such as phagocytic amoebocytes 74 . A few bacteria have been localized within the mesoglea of cnidarians, including Pseudomonas and spirochetes in Hydra spp. 77 , 78 and pathogenic cyanobacteria in the coral Orbicella annularis suffering from black band disease 79 . In contrast, the only mollicute previously localized in any coral was Mycoplasma corallicola , which was found on the surface of the tentacle ectoderm of Lophelia pertusa 41 . Unlike M. corallicola, Ca. O. callogorgiae likely resides within its host coral and therefore must somehow evade phagocytic amoebocytes in the mesoglea and potentially other immune defenses. Consequences for the coral host It is still unclear if Ca. Oceanoplasma callogorgiae incurs a cost or provides any benefit to its coral host. These novel mollicutes may simply be commensals or parasites with a minimal impact on their host corals since they did not display any obvious pathology and nearly every colony appears to be infected. Conversely, the metabolism of arginine may provide the coral with an alternative pathway to process nitrogenous waste or could function to recycle nitrogen which would be useful for deep-sea corals because many rely on a nitrogen-poor diet of marine snow 80 . It is also possible that some of the unannotated genes are peptides that confer protection from pathogens or parasites like those that Spiroplasma spp. produce in insects 21 . Others have suggested that the symbionts of hadal sea cucumbers, identified herein as belonging to Oceanoplasmataceae, may provide protection to their hosts from animal viruses using their CRISPR-Cas and restriction-modification systems 24 . It is unclear if this is a possibility for Ca. O. callogorgiae since it likely resides in the mesoglea where direct exposure to viruses may be low. Virus-like particles have been observed in the mesoglea of a shallow-water, stony coral 81 , however they were rare and far less abundant than those found in the epidermis and gastrodermis. Exposure to viruses in the mesoglea may increase when predators graze on corals or when branches break. Indeed, gastropods have been observed grazing on Callogorgia delta colonies and they suffer higher rates of branch loss compared to other deep-sea corals in the genus Paramuricea which do not host Oceanoplasmataceae 82 . Further, upon injury, phagocytic amoebocytes migrate from the mesoglea to the wound where they provide defense against invading pathogens 83 . If Ca. O. callogorgiae has a role in immune defense, it may also reside in the mesoglea and migrate when tissue is wounded. The novel family Oceanoplasmataceae We propose the family Oceanoplasmataceae, which includes Ca. Oceanoplasma callogorgiae , Ca. Thalassoplasma callogorgiae , and other associates of marine invertebrates. This is supported by the fact that it forms a highly divergent and well-supported monophyletic clade, it is ecologically distinct from other Mollicutes since all members associate with marine invertebrates, and it shares specific genomic features such as lacking the genes involved in glycolysis while retaining genes encoding ribose-phosphate pyrophosphokinase, glyceraldehyde-3-phosphate dehydrogenase, and ATP synthase. The hosts of Oceanoplasmataceae are phylogenetically diverse comprising five animal phyla, exhibit diverse lifestyles from being photosynthetic to wood-borers, and originate from a wide range of habitats from the epipelagic zone to hadal trenches 24 – 28 . In addition to this, the large phylogenetic distances between members of the Oceanoplasmataceae suggests that a substantial amount of diversity remains undiscovered. Interestingly, Ca. Moeniiplasma spp. appear to be the closest relatives of Oceanoplasmataceae. They clustered together in the phylogenetic analyses and shared some genomic similarities, such as a lack of glycolysis. Compared to other mollicutes, Oceanoplasmataceae exhibit extensive viral defense systems. All were enriched in thymidine kinase genes and the two genomes with unfragmented CRISPR arrays had more spacers than other Mollicutes. Only the associate of a hadal snailfish, Mycoplasma liparidae , had more spacers 53 . This may reflect a general evolutionary trend among animal-microbial symbioses in marine environments where exposure to viruses is high. Similarly, the symbionts of marine sponges are enriched in CRISPR-Cas systems compared to surrounding seawater 84 , 85 . Oceanoplasmataceae possess the most reduced genomes among all mollicutes. They possess the smallest genomes, which contain the fewest protein-encoding genes and lack any complete fermentative pathway. Extensive genome reduction dominates the evolutionary history of Mollicutes. Mollicute genomes are used to identify the minimum set of genes essential for cellular life 23 and are utilized as precursors in efforts to design minimal genomes 86 , 87 . These synthetic genomes retain glycolysis. However, the lack of glycolysis in Oceanoplasmataceae and Moeniiplasma spp. suggests that these synthetic genomes could be reduced further. Our comparative genomics analysis also revealed that Moeniiplasma spp. lack ATP synthase, suggesting alternative gene sets may permit further reduction. Strangely, no mollicutes except Acholeplasma laidlawii are known to use cyclic di-GMP and all mollicutes instead use cyclic di-AMP 88 . The presence of an EAL domain in gene U1 of Ca. O. callogorgiae implies that the use of cyclic di-GMP was not lost in all other mollicutes or was regained through horizontal gene transfer in some lineages. Here we describe two novel members of the Mollicutes that associate with the deep-sea coral, Callogorgia delta , and propose the names Ca. Oceanoplasma callogorgiae and Ca. Thalassoplasma callogorgiae . We characterize their association with C. delta , generate genomic resources, and produce phylogenetic and metabolic inferences advancing our understanding of coral-associated mollicutes and symbiosis in the deep sea. Further, we propose a new family, Oceanoplasmataceae, which has not yet been recognized and whose diversity remains largely uncharacterized. We show that its genome reduction exceeds what was known among Mollicutes, informing their evolutionary history, the consequences of symbiosis, and the concept of minimal bacteria."
} | 5,136 |
23526120 | null | s2 | 3,314 | {
"abstract": "In Nature, directional surfaces on insect cuticle, animal fur, bird feathers, and plant leaves are comprised of dual micro-nanoscale features that tune roughness and surface energy. This feature article summarizes experimental and theoretical approaches for the design, synthesis and characterization of new bioinspired surfaces demonstrating unidirectional surface properties. The experimental approaches focus on bottom-up and top-down synthesis methods of unidirectional micro- and nanoscale films to explore and characterize their anomalous features. The theoretical component of the review focuses on computational tools to predict the physicochemical properties of unidirectional surfaces."
} | 173 |
36160923 | PMC9487992 | pmc | 3,315 | {
"abstract": "Methane emissions and plastic pollution are critical global challenges. The biological conversion of methane to poly-β-hydroxybutyrate (PHB) not only mitigates methane emissions but also provides biodegradable polymer substitutes for petroleum-based materials used in plastics production. This work provides an early overview of the methane-based PHB advances and discusses challenges and related strategies. Recent advances of PHB, including PHB biosynthetic pathways, methanotrophs, bioreactors, and the performances of PHB materials are introduced. Major challenges of methane-based PHB production are discussed in detail; these include low efficiency of methanotrophs, low gas-liquid mass transfer efficiency, and poor material properties. To overcome these limitations, various approaches are also explored, such as feast-famine regimes, engineered microorganisms, gas-permeable membrane bioreactors, two-phase partitioning bioreactors, poly-β-hydroxybutyrate- co -hydroxyvalerate synthesis, and molecular weight manipulation.",
"conclusion": "6 Conclusions Methane-based PHB production has an excellent potential to benefit the environment as a substitute for petroleum-based materials and to reduce GHG emissions. This review provided an analysis of PHB biosynthetic pathways and identified the challenges and opportunities associated with methanotrophic PHB production. Obtaining high-efficiency methanotrophs through a feast-famine strategy and microorganism engineering, coupled with gas-permeable membrane bioreactors and two-phase partitioning bioreactors could help enhance gas-liquid transfer efficiency. Further, manipulating the molecular weight of PHB and generating PHBV are necessary to achieve high-quality products. Further investigations of methane-based PHB would help support the complex needs of the bioplastics market.",
"introduction": "1 Introduction Plastics have become indispensable in our daily lives and are widely used in packing materials, household appliances, transportation equipment, and electronic devices [ 1 ]. The estimated annual plastics production is 311 million tons [ 2 ], and is predicted to surpass 500 million metric tons by 2050 [ 3 ]. Plastics are non-degradable, which is the primary disadvantage [ 4 ] and has led to the accumulation of plastics in many environments [ 5 ]. Further, only a small portion of plastics can be effectively recycled. The cumulative quantity of plastic waste entering the oceans has been estimated at up to 12.7 million metric tons and is predicted to increase by an order of magnitude by 2025 in the absence of waste-management infrastructure enhancements [ 6 ]. More importantly, microplastics transfer pollutants via food chains [ 7 ] and have negative effects on human health due to their small size and wide distribution in water bodies [ 7 , 8 ]. Moreover, conventional plastics generate two greenhouse gases (GHGs), methane and ethylene, when exposed to ambient solar radiation [ 9 ]. Methane is the second-most prevalent GHG after carbon dioxide (CO 2 ), contributing 18% of the total atmospheric radiation forcing [ 10 ]. The global warming potential of methane has increased from 25 to 34 times that of CO 2 over the past 100 years [ 11 ], indicating that methane emissions have a significant environmental impact [ 12 ]. More than 63% of global methane emissions are anthropogenic [ 13 ] and are generated from fossil fuels, anaerobic wastewater treatment, landfilling, coal mining, and natural gas refineries [ 14 ]. Moreover, methane accounts for 90% of natural gas, worldwide demand for which is estimated to increase by 44.0% by 2040 [ 15 , 16 ]. Polyhydroxyalkanoates (PHAs) are a kind of polyester produced by microorganisms [ 17 ] with potential applications as a substitute material for conventional plastics [ 18 ]. Methanotrophs could accumulate PHB when their nutrient supply is imbalanced [ 19 ], and the theoretical yield of PHB synthesis is 67% [ 20 ]. Recently, based on its properties of biodegradability and biocompatibility [ 21 , 22 ], demand for PHB products has expanded from its initial applications in packaging materials [ 22 , 23 ] to industrial and agricultural applications [ 24 ] and to the biomedical and pharmaceutical sectors [ 5 , 25 ]. Employing PHB into commodities does not require new technological investments, as existing equipment originally developed for processing polyethylene and polypropylene can be used [ 26 ]. However, the high production costs of PHB, which are 3–4 times higher than those of conventional plastics and similar biopolymer plastics, limits its commercial utilization [ [27] , [28] , [29] ]. A major proportion of the total costs of PHB (30–40%) is attributed to feedstock [ 27 , 30 ], such as palm oil, glucose, sucrose, and corn starch [ 19 , 31 , 32 ]. The utilization of methane could reduce production costs by at least 30–35% and make the PHB production process more economically and environmentally friendly [ 33 , 34 ]. A study of the economic feasibility of methane-based PHB production showed that the biosynthesis cost was $8.5/kg PHB when produced at a relatively small scale (500 tons/a) [ 34 ]. If the scale of production would be expanded to 100,000 tons/a, costs would be reduced to $4.1–$6.8/kg PHB [ 33 ]. Methane emissions from landfills and anaerobic digesters could be used to synthesize PHB, which could theoretically replace 20–30% of the total annual plastics market [ 35 , 36 ]. Therefore, the introduction of methane-based PHB not only opens up a new path for PHB production, but also mitigates the issues related to non-degradable plastics and GHG emissions. As methane-based PHB has economic and environmental advantages over petroleum-based plastics, this review explores PHB biosynthetic pathways, methanotrophs, bioreactors, and material performance of PHB with an emphasis on overcoming the challenges such as low efficiency of methanotrophs, low gas-liquid mass transfer efficiency, and poor material properties and strategies to overcome them. Further, development opportunities, including feast-famine regimes, engineered microorganisms, gas-permeable membrane bioreactors, two-phase partitioning bioreactors, poly-β-hydroxybutyrate- co -hydroxyvalerate, and high molecular weight of PHB are outlooked."
} | 1,562 |
33072283 | PMC7548198 | pmc | 3,316 | {
"abstract": "Abstract Although soil microbial communities are central in ecosystem functioning, we know little of their characterization for those associated with grazing‐tolerant host plant species in grassland ecosystems in response to grazing. In this study, we used a high‐throughput sequencing approach to characterize soil microbes from the rhizosphere and bulk soil of grazing‐tolerant grass species, Stipa breviflora , in the Inner Mongolian desert steppe. We found that response mechanisms of soil bacteria distinct from fungal communities, and variance also occur between the rhizosphere and bulk soil communities under long‐term grazing. Soil fungal communities and the co‐occurrence networks in S. breviflora rhizosphere were more sensitive to long‐term grazing than bacteria. We reveal that rhizosphere effects and soil water content were the main drivers of the changes in fungal communities and their co‐occurrence networks. Moreover, the dominant bacterial phyla Bacteroidetes and Proteobacteria and fungal phyla Ascomycota and Glomeromycota might participate in regulating processes of S. breviflora's response to grazing. Overall, these findings give new snapshots of mechanisms of how grazing affects soil microbial communities, in an attempt to contribute to a clearer understanding of grazing‐tolerant mechanism of S. breviflora .",
"conclusion": "5 CONCLUSIONS The bacterial and fungal communities have different response characteristics to long‐term grazing, with fungal community was more sensitive to grazing than the bacterial community. Long‐term grazing greatly affected rhizosphere microbial communities, but did not influence them in the bulk soil. More importantly, the dominant bacterial taxa such as Adhaeribacter , Alcaligenaceae, Blastocatella , Chitinophagaceae, Desulfurellaceae, Haliangium , Hymenobacter , and Sphingomonadaceae and fungal taxa Alternaria , Aureobasidium , Glomeraceae, Mortierellaceae, and Pyronemataceae shed new light on the involvement of soil microbes in grazing. Further studies of the regulatory mechanisms of these taxa are essential to better understand the grazing‐tolerant characteristics of S. breviflora and enrich theoretical knowledge of plant–soil–microbe interactions under grazing conditions.",
"introduction": "1 INTRODUCTION The soil microbial community plays an important role in grassland ecosystem dynamics and has a crucial influence upon plant ecophysiological traits (Andres et al., 2017 ; Ford, Rousk, Garbutt, Jones, & Jones, 2013 ). A major challenge in applied ecology is to understand response mechanisms of those complex microbial communities to grazing, especially for those associated with grass species tolerant of grazing. Many studies have demonstrated that herbivores largely determine aboveground biomass, and also directly and indirectly affect the belowground soil microbial community through their impact on plants and soil properties (Dawson, Grayston, & Paterson, 2000 ; Yang et al., 2013 ). In this interaction, a common response of grazed grass plants to browsing is the stimulation of microbial processes and nitrogen availability within their rhizospheres, and the reallocation of belowground resources to aboveground structures (Bardgett, Wardle, & Yeates, 1998 ; Paterson, 2003 ). In response to defoliation, soil microbes either positively or negatively affect their host plant growth through nutrient transformation, phytohormone synthesis, and pathogen inhibition (Wardle, Bardgett, Klironomos, Setälä, & Van der Putten, 2004 ). Recently, an increasing number of researches have focused on the role of top‐down effects and bottom‐up feedback (Chen et al., 2018 ; Eldridge & Delgado‐Baquerizo, 2018 ). However, these researches have been mostly limited to single properties of soil microbial composition and their function (Andres et al., 2017 ; Ford et al., 2013 ), rather than explicitly considering the characteristics associated with a grazing‐tolerant grass species under extreme grazing stress. In natural habitats, soil microbial community coexists in complex arrays and has a highly structured complex network (Faust & Raes, 2012 ). It has been shown that the response characteristics of soil microbial communities can be influenced by certain numerical properties of interaction networks under the environmental change (De Vries & Wallenstein, 2017 ). The recent emergence of microbial network analysis has revealed an array of astonishing potential interactions and strong linkages between taxa within soil microbial communities and uncovered ubiquitous characteristics of microbes in soils (Shi et al., 2016 ; Zhou et al., 2010 ; Zhou, Deng, Luo, He, & Yang, 2011 ). Such studies can provide insights into community composition and interactions among soil microbes at the community level that could not be obtained by traditional analytical approaches under grazing stress conditions (Zhang, Liu, Song, Wang, & Guo, 2018 ). Accordingly, the better understanding of the interaction networks of soil microbial communities, as well as the interdependent relationships among taxa under long‐term grazing, is critical for better understanding the grazing tolerance mechanisms of different host plants and for implementing restoration management and sustainable development programs in degraded grassland ecosystems (Newman, 2006 ; Shi et al., 2016 ). \n Stipa breviflora is a palatable, grazing‐tolerant, and drought‐resistant grass species, which grows rapidly during springtime in desert steppe communities and is widely distributed in the western Inner Mongolia (Ren et al., 2017 ). Since this plant species plays a central role in soil and water conservation and desertification control (Zhang, Niu, Wu, Buyantuyev, & Dong, 2012 ), it has attracted attention for its potential use in the restoration of degraded grasslands. While vegetation and soil responses to grazing have been elucidated (Lu, Zhou, Wang, & Song, 2016 ), there is limited empirical description of the soil microbial community structure and composition hosted by S. breviflora (Gao, Han, & Zhang, 2017 ). Crucially, the potential interactions of soil microbial community members and mechanisms of S. breviflora grazing tolerance remain unclear. In this study, we characterized soil microbes from the rhizosphere and bulk soil of a grazing‐tolerant grass species, S. breviflora . We aimed to address the following questions: (a) Are the soil microbes in the rhizosphere and bulk soil of S. breviflora different in response to long‐term grazing? and (b) How do different soil microbial taxa of grazing‐tolerant grass species, S. breviflora , interact with each other in response to long‐term grazing?",
"discussion": "4 DISCUSSION 4.1 Shifts of soil microbial community composition This study focused on the identification of characterization of soil microbes associated with a grazing‐tolerant grass species, S . breviflora . We found that long‐term grazing greatly affected rhizosphere microbial community composition, but did not influence them in the bulk soil, indicating that the influence of grazing was more evident in structuring the microbial communities present in rhizosphere than bulk soils (Hamilton & Frank, 2001 ). These results are consistent with previous findings that grazing has a significant impact on the rhizosphere bacterial community structure, but has no effect on bulk soil bacterial community structure in S . breviflora desert steppe (Zhang et al., 2019 ). Evidence suggests that effects of grazing on soil microbes have been attributed to increased release of root exudates that are rapidly used by rhizosphere microbes and increase available N in plant shoots; this process may result in a positive feedback to the plant of improved nutrient recycling and uptake (Bardgett et al., 1998 ). It has also been shown that grazing‐tolerant grass species responded to defoliation by increasing the allocation of resources to aboveground tissue and reduction in root biomass (Guitian & Bardgett, 2000 ). These findings indicated that reduction in root C allocation leads to lower amount of resources to belowground, which ultimately affected the soil microbial community (Bardgett et al., 1998 ). Consequently, we proposed that shift of microbial community composition was presumably related to the exudative response of S. breviflora to defoliation (Paterson, 2003 ). In addition, soil properties have been considered as the crucial drivers of the changes in the composition of soil microbial communities (Calleja‐Cervantes et al., 2015 ). We found that grazing increased TN and TP and decreased soil water content, TOC, and pH. This finding was in general agreement with previous studies that were conducted in different grassland types (Andres et al., 2017 ; Yang et al., 2013 ). Previous studies showed that grazing could increase N inputs into the microbial community and ultimately increases the soil microbial activity (Guitian & Bardgett, 2000 ; Yang et al., 2013 ). This increase in soil microbial activity could feedback to the plants by increasing soil nutrient availability, which supports more greater shoot nutrient to rapid regrowth of aboveground tissue following defoliation (Cantarel et al., 2017 ). However, numerous studies have concluded that long‐term grazing will decrease soil water content and TOC through soil trampling and the removal of vegetation, which would also negatively affect soil microbial communities (Eldridge & Delgado‐Baquerizo, 2018 ; Zhang, Liu, et al., 2018 ). Our findings supported these observations. Therefore, we believe that soil properties also play an important role in shaping microbial communities, ultimately driving changes in plant community composition. 4.2 Characterization of soil microbial interactions Our results showed that grazing affected the co‐occurrence networks of overall fungal networks more than those of bacterial networks. Fungal networks in grazed grassland soils had stronger interaction, higher average degree, shorter path distance, lower modularity, and more negative correlations than ungrazed grassland soils, suggesting the more sensitive and quick response to environmental changes under long‐term grazing (De Vries et al., 2018 ). On the contrary, bacterial networks in grazed grassland soils had more cooperative relationships within bacterial members, indicating higher stability and more tolerance for stress imposed by grazing disturbance (Zhang, Zhang, Liu, Shi, & Wei, 2018 ). This may be due to a direct effect of grazing by reducing the soil carbon substrates available for colonization. Fungi are more dependent than bacteria on soil carbon substrates (Deng et al., 2012 ), which result in a higher level of competition for a reduced supply of nutrients from plants and soil in the grazing grassland (Chen et al., 2018 ). Studies have found that heavy grazing decreased organic carbon stock in soil through decreasing productivity of plant biomass, roots, and litter in S. breviflora desert steppe (Wang et al., 2017 ). Therefore, the reduction of TOC increased the competition for soil carbon substrate within fungal community, which possibly weakened the microbial associations and consequently could decrease the system stability to resist to adverse environmental conditions (Newman, 2006 ). Interestingly, we found that more rhizosphere communities were regarded as connectors and module hubs in bacterial co‐occurrence network under grazing treatment, while more bulk soil communities dominated in fungal co‐occurrence network under grazing treatment. This may be due to the fact that bacterial community develop faster than fungal communities and can use root exudates more quickly (Paterson, 2003 ), while fungi may not have many available niches in the rhizosphere (Shi et al., 2016 ). These findings are consistent with the result that bacteria are the most abundant microbes in the rhizosphere due to their excellent substrate utilization capacities (Dawson et al., 2000 ). A recent research showed that grazing increased the dominant role of S. breviflora in the plant communities, which would have occupied more niche space in the community that thereby reduced the number of coexisting species possible (Lv et al., 2020 ). This increase in dominant role also indicated that S. breviflora exert selective forces to influence microbial community in rhizosphere, thereby resulting in strong interspecific competition within microbial communities (Godoy, Bartomeus, Rohr, & Saavedra, 2018 ). Therefore, we proposed that the rhizosphere effects of S. breviflora presumably modified the soil microbial interactions following herbivory (De Vries & Wallenstein, 2017 ). 4.3 Keystone taxa response to grazing The links between plant species and soil microbes are long established (Cantarel et al., 2017 ), but understanding the relationship between grazing‐tolerant plant species and soil microbes was previously unclear. An additional goal of this study was to determine soil bacterial and fungal keystone taxa, which would be beneficial for host plant adaptation to grazing. We identified several system‐specific taxa in the S . breviflora rhizosphere in grazed grassland soils. For example, the phyla Bacteroidetes and Proteobacteria, as the most dominant bacteria, were the strongest responders to grazing and drive the bacterial network structure, indicated that S . breviflora established root‐inhabiting microbial communities by selecting a limited number of phyla (Dawson et al., 2000 ). Hymenobacter , the most dominant bacterial genus in the rhizosphere, has been reported as a plant growth‐promoting bacteria, could increase the antioxidative properties and content of fatty acids and phenolic compounds in plants (Dimitrijevic et al., 2018 ). Adhaeribacter has the same lineage as Hymenobacter , which could indicate a genus that specializes in the degradation of complex products derived from different composts (Calleja‐Cervantes et al., 2015 ). Blastocatella has been reported elsewhere to be associated with phosphorus‐accumulating herb, played key roles in mobilizing soil mineral‐P (Ye et al., 2020 ). In particular, co‐occurrence network analyses identified several genera (e.g., Cnuella , Flavisolibacter , and Segetibacter ) of the family Chitinophagaceae, which was a type of ammonia‐oxidizing bacteria (AOB). These specific taxa identified above could play important roles in nitrogen transformation (Wu et al., 2019 ). Other keystone taxa including family Sphingomonadaceae (oligotrophic character), family Alcaligenaceae (related to phenolic compounds), family Desulfurellaceae (sulfate‐reducing bacteria), and genus Haliangium (halophilic myxobacteria) are related to the transformations of complex product (Calleja‐Cervantes et al., 2015 ; Dimitrijevic et al., 2018 ). These observed taxa might play important roles in maintaining cooperative associations within bacterial community to survive under grazing stress (Zhang, Zhang, et al., 2018 ). Although little is known about their grazing tolerance mechanisms, however, their ability to maintain network stability might suggest that these taxa adapted to the long‐term grazing and might play an important role in the S . breviflora rhizosphere. In addition, Aureobasidium and Alternaria were the most dominant fungal genera in the S . breviflora rhizosphere, which belong to phylum Ascomycota, indicating that Ascomycota dominated the composition of root‐associated fungi, which is in line with the results of previous studies (Chen et al., 2018 ; Yin, Nan, Li, & Hou, 2008 ). Aureobasidium is an endophytic or epiphytic fungus that is beneficial to its host plant and helps the plant endure heavy metal ions, osmotic pressure, and extreme environmental conditions (Chi et al., 2009 ). When a greater abundance of this genus occurs in the S . breviflora rhizosphere, it would positively feedback into host plant, so as to response to grazing stress (Bardgett et al., 1998 ; Wardle et al., 2004 ). Previous study has reported that fungal drought‐tolerant taxa mainly belong to phyla Ascomycota and Glomeromycota, whereas drought‐sensitive taxa mainly belong to phylum zygomycota (family Mortierellaceae) (De Vries et al., 2018 ). In the present study, we identified several drought‐tolerant taxa Pyronemataceae (phylum Ascomycota) and Glomeraceae (phylum Glomeromycota), and drought‐sensitive taxa Mortierellaceae (phylum zygomycota), indicating that SWC also drive the fungal interactions. Grazing decreased the total aboveground biomass, resulting in decreased SWC, which indirectly affected the soil fungal network, in this case, triggering strong interspecific competition, potentially weakening network stability. This assumption would explain why fungal networks show more sensitive to grazing than bacterial networks in the S. breviflora desert steppe. In contrast, Alternaria is a common saprophyte, majority of species are animal and plant pathogens, and often occurring in plant leaf spot and tissue decay (Liu, Li, Hu, Wang, & Gao, 2018 ). Recent study has shown that the accumulation of root pathogens can produce negative feedback to plant growth through directly reducing root uptake capacity (De Vries & Wallenstein, 2017 ). However, other studies have shown that the root pathogens do not cause the same level of negative feedback to all plant species in the community, and thus, their existence can lead to the qualitative difference in plant community composition (Wardle et al., 2004 ). Therefore, we cannot definitively conclude whether these taxa are beneficial for S. breviflora adaptation to grazing, but the presence of these keystone taxa might participate in regulating processes of S. breviflora's response to grazing stress."
} | 4,452 |
37213224 | PMC10197150 | pmc | 3,317 | {
"abstract": "Summary Owing to superior softness, wetness, responsiveness, and biocompatibility, bulk hydrogels are being intensively investigated for versatile functions in devices and machines including sensors, actuators, optics, and coatings. The one-dimensional (1D) hydrogel fibers possess the metrics from both the hydrogel materials and structural topology, endowing them with extraordinary mechanical, sensing, breathable and weavable properties. As no comprehensive review has been reported for this nascent field, this article aims to provide an overview of hydrogel fibers for soft electronics and actuators. We first introduce the basic properties and measurement methods of hydrogel fibers, including mechanical, electrical, adhesive, and biocompatible properties. Then, typical manufacturing methods for 1D hydrogel fibers and fibrous films are discussed. Next, the recent progress of wearable sensors (e.g., strain, temperature, pH, and humidity) and actuators made from hydrogel fibers is discussed. We conclude with future perspectives on next-generation hydrogel fibers and the remaining challenges. The development of hydrogel fibers will not only provide an unparalleled one-dimensional characteristic, but also translate fundamental understanding of hydrogels into new application boundaries.",
"conclusion": "Conclusion and outlook Hydrogel fibers show many unique properties because of their high specific surface area, high water content, mechanical durability and other structural advantages, which not only improve the material properties but also expand the application range. In this review, we summarize the recent advances in hydrogel fibers. The newly emerging requirement, characterization and fabrication of hydrogel fibers are comprehensively illustrated. In addition, device performance and applications of these hydrogel fibers based wearable sensors in human motion detection/monitoring and soft actuators are highlighted. Successful outcomes from these efforts shine a bright light on the potential applications of the hydrogel-based sensors in next-generation wearable electronic devices. However, a higher electrical conductivity, sensitivity and biocompatibility were not enough to implement these high-performance hydrogel-fiber-based soft electronics for practical applications, several imminent challenges need to be further investigated. As the main component of hydrogel fibers is water, flexible electronic devices based on hydrogel fibers face a series of problems caused by dehydration. Compared to bulk hydrogels, hydrogel fibers have inferior water retention ability and loss ionic conductivity within several minutes without proper encapsulation, hindering their long-term applications. On the other hand, the hydrogel fibers will freeze and become brittle under sub-zero conditions, limiting their use in harsh environment. 119 Thus, effective strategies to improve the water retention and anti-freeze ability of hydrogel fibers are highly demanded. Second, the mechanical properties of the hydrogel fiber and the devices based on these materials are important for wearable and actuator applications. Hydrogels are typically soft and fragile materials, and one-dimensional hydrogel fibers are more delicate than bulk hydrogels, which may make them susceptible to damage or deformation during use. This may affect the performance and reliability of electronic devices. Researchers need to further explore ways to improve the mechanical durability of hydrogel fibers. 120 The long-term stability and robustness of the devices at the real working conditions, where human sweating, body friction and environment temperature variation coexist, is largely unexplored. For wearable electronics that need to adhere to human tissue surfaces, common problems include slow adhesion formation, weak bonding, and low biocompatibility. 121 Most hydrogels work well under dry conditions only, and their wet adhesion capability needs further validation. 122 In addition to the pursuit of strong adhesion, the development of reversible adhesion is essential because of the urgent requirement for benign separation of electronic devices from adherent tissues. Reversible adhesion is crucial for repositioning misplaced bioadhesives and retrieval devices. Work in these areas would be important steps in moving flexible electronics based on hydrogel fiber materials toward future practical applications. Third, hydrogel fibers show diverse applications in strain, temperature, pH and humidity sensing. But the development of soft electronics requires integration, efficiency and multidimensionality, unitary sensing ability is insufficient to meet future development. At present, most CHF-based sensors only show a single function, thus, how to improve the multifunctionalities of CHF-based sensors is a priority. 123 , 124 New approaches need to be explored to improve the sensing capabilities of hydrogel fibers, such as by incorporating new materials, developing novel preparation methods or more sophisticated signal processing techniques that allow it to detect a wider range of parameters or provide more accurate and precise measurements. On the other hand, the integration of electronic units with different functions (including luminescence, energy harvesting devices, energy storage devices, smart sensors, data acquisition units and feedback systems) in one platform can effectively promote the development of flexible, wearable and portable electronic products. 125 The variation of luminescence intensity of luminescent hydrogel fibers in response to external stimuli makes them promising for bioelectronics. 126 , 127 For example, luminescent hydrogels allow continuous glucose monitoring because of the linear relationship between optical power and glucose concentration. 128 Energy harvesting equipment can convert mechanical energy or heat energy around the human body into electricity, and integrate energy storage devices to build a self-powered system. 129 Wearable items sewn with energy-harvesting hydrogel fibers, such as wristbands or sportswear, not only have self-lighting capabilities, but can also extract energy from human movement as an active sensor to detect human movement or temperature, and have applications in fields such as artificial intelligence and biomedicine. 130 Moreover, the design concept of energy storage devices based on hydrogel fibers, such as supercapacitors, provides new power for the next generation of wearable and portable electronics. 131 , 132 Fourth, hydrogel fibers are developing toward flexibility, but the response time of devices needs to be reduced significantly. Currently, the response time of CHF-based sensors to external stimuli ranges from tens of seconds to minutes, which is highly correlated with materials and device designs, where there is still much room left. Fifth, hydrogel fiber actuators face similar problems as sensors. 133 The common issues are slow response rate and low mechanical strength, which have been considered as the main obstacles hindering their further development. 134 For instance, mammalian skeletal muscles have actuation power densities in excess of 10 4 W m −3 , a power density level that is ideal for artificial muscles used in medical devices and bionic robots. However, the power densities of existing hydrogel actuators are only in the range of 0.1 to 10 3 W m −3 , which is much lower than that of skeletal muscle. 135 In addition, most applications of hydrogel fiber actuators are still in the conceptual stage, and long-term durablity must be resolved in practical applications. 136 Therefore, the invention of new responsive hydrogels with fast response rate, high actuation power density and excellent mechanical properties represents a future direction of the field. 137 Sixth, mass production in industry is still challenging because of the complex fabrication process, bare long-term stability and unitary sensing ability, leading to the application scenario of hydrogel fibers is still limited to laboratory conditions. 138 Nowadays, optimization, structural design and multifunctional assembly rely on the interdisciplinary (e.g., textile, biological, mechanical and electronic) turns to promote hydrogel fibers into practicalization and industrialization. Moreover, although research on hydrogel fibers has developed rapidly in the past decade, for the materials/devices, device standardization, modeling, and simulation are required to understand the relationship between the performance of the pressure sensor and the structures (e.g., pore size/size distribution, dimensions, etc.) of the hydrogel fibers. This understanding may help develop materials with excellent sensing ability and multifunctionality. Though with these challenges, there are several promising directions for future development of hydrogel fibers, such as wearable healthcare, biomedical, electronic skin, soft robotics, human-machine interactions and smart textiles. Hydrogel-based electrodes have been widely used for monitoring vital signs, the fiber topology extends their applications to smart drug delivery, wearable or implantable medical devices and soft robotics by combining drug-loaded microspheres, conductive materials and magnetic particles for controlled drug release, biosensing, and minimally invasive surgery. 139 In addition, stretchable conductive hydrogel fibers are essential for the development of smart e-textiles. Incorporating hydrogel fibers can be incorporated into clothing or other textiles, giving the textiles a variety of functions that go far beyond traditional warmth/fashion functions, such as detection of environmental or body changes, energy generation and storage. 140 , 141 This may lead to the development of clothing that can regulate temperature, monitor hydration levels, or provide feedback about posture and movement.",
"introduction": "Introduction Hydrogels are viscoelastic materials consisting of a three-dimensional network of chemically or physically cross-linked hydrophilic polymers that have the ability to absorb and retain large amounts of water. 1 , 2 , 3 , 4 Hydrogels have the advantages of excellent stretchability, flexibility, self-healing and biocompatibility, and by introducing electrical conductors (e.g., graphene, carbon nanotubes) and ions (e.g., NaCl, KCl), they are endowed with certain electrical/ion conduction properties, making them ideal materials for flexible sensors. 5 , 6 , 7 , 8 , 9 , 10 The sensing function is achieved by measuring the changes in electrical signals such as current, voltage, resistance, and capacitance of conductive hydrogels subjected to external stimuli (e.g., pressure, temperature, humidity, and pH). 11 , 12 , 13 , 14 Compared with sensors based on other materials (e.g., silicon, metals, carbon materials, metal oxides, and conducting polymers), conductive hydrogels have obvious advantages in terms of stretchability, flexibility, adhesion, ease of preparation, and biocompatibility, which have been widely reported for the applications in the fields of wearable electronics, bioelectronics, and soft robotics. 15 , 16 , 17 , 18 Bulk hydrogels have been extensively studied because of their simplicity of preparation; however, these conductive hydrogels are large and have an isotropic homogeneous structure, so the response rate and sensitivity are limited. In recent years, a wide variety of hydrogel forms (e.g., columns, spheres, films, fibers, and granules) have been developed. 19 , 20 , 21 , 22 , 23 These hydrogel forms are available in sizes ranging from nanometers to millimeters to meet different application scenarios. Among them, hydrogel fibers have been reported for bio-scaffolds, wound dressings and surgical suture owing to its quasi-one-dimensional structure, good breathability and weaveability. 24 , 25 , 26 , 27 , 28 , 29 , 30 Likewise, conductive hydrogel fibers (CHFs), when used as sensors, exhibit anisotropic responsiveness, enhanced specific surface area and better air permeability compared to bulk hydrogels. Also, CHFs can be woven and non-woven into hydrogel textile with 3D structures, which exhibit good conformability. Furthermore, CHF-based devices can act as soft actuators that respond well to external stimuli. 31 Despite the great promise and recent advances in hydrogel fibers, to the best of our knowledge, there is no systematic discussion on hydrogel fibers for wearable sensors and actuators. The literature on bulk hydrogels for tissue engineering, drug delivery, soft machines, and human-machine interfaces has been extensively reviewed, but existing reviews usually do not account for unique 1D hydrogel fibers nor do they provide the fabrication and applications of hydrogel fibers. 32 , 33 , 34 , 35 Such a systematic discussion is central for the future development of this nascent yet impactful field. In this Review, we first summarize the basic properties of hydrogel fibers that are closely related to flexible electronics. Then we summarize the methodologies for fabricating hydrogel fibers with diameter varying from nanometers to millimeters. In the following part, which constitutes the largest section, recent studies on hydrogel fibers for flexible electronics are summarized, with emphasis on applications for strain, temperature, PH and humidity sensors and actuators. Figure 1 provides applications of hydrogel fibers in the field of sensors and soft actuators and Table 1 summarizes the materials, design strategies, and performance of the sensors and actuators relevant to this paper. We conclude with future perspectives on next-generation hydrogel fibers and the remaining challenges and opportunities. Figure 1 Schematic diagram of the application of hydrogel fibers in the field of sensors and soft actuators Reproduced with permission. 124 Copyright 2020, American Chemical Society. Reproduced with permission. 103 Copyright 2020, WILEY-VCH. Table 1 Summary of materials, design strategies and performance of the electronic devices relevant to this article Application Material Method Diameter (μm) Mechanical properties (strength/elongation) Conductivity (S m −1 ) Working range a Year Ref Strain sensor Alginate and PAAm Template 420 80 kPa/730% N/A 0-120% 2016 91 Sodium polyacrylate and SWCNT Wet spinning 900 1.2 MPa/2630% 88.7 0-1000% 2022 22 PAAm Template 1200 2000% 0.16 N/A 2019 92 Alginate and PEGDA Wet spinning 450 400% 0.765 50-300% 2020 93 PEDOT:PSS and PVA Template 1000 13 MPa/519% 0.163 0.01–130% 2022 73 SA/PANI/rGO Wet spinning 180 10.36 MPa/154% 0.5 10-50% 2022 94 KGM/KC/PANI Electrospinning 0.25 239.26 kPa/340.69% 0.7261 N/A 2022 95 Temperature sensor PVA and HEC Template 800 2.86 MPa/400% 5.77 28-45°C 2022 98 Chitosan and polypyrrole Wet spinning 244 872 MPa/2% 310 10-40°C 2011 99 pH-sensitive sensor H-PAN and SP Wet spinning 90 N/A N/A 3–10.5 2008 100 Alginate and glycerol Microfluidic spinning 200–1000 N/A N/A 5.2–9 2016 101 NIPAm and SA Template 220 N/A N/A 3–11 2018 102 Humidity sensor P(AAm-co-AA)/Fe(III) Draw-spinning 85 N/A 0.0042 10-90 RH% 2020 103 Agarose/SMF/PCF Template 153 N/A N/A 10-90 RH% 2014 104 Actuator TPU/P(NIPAM-ABP) Electrospinning 501 N/A N/A N/A 2015 114 GO and alginate Wet spinning 500 N/A N/A N/A 2020 115 PAA and PCL Electrospinning 1.28 N/A N/A N/A 2022 118 a The unit of working range for strain sensor is strain. The unit of working range for temperature sensor is °C. The unit of working range for humidity sensor is RH%."
} | 3,868 |
26052941 | PMC4460010 | pmc | 3,318 | {
"abstract": "Ferroproteins arose early in Earth’s history, prior to the emergence of oxygenic photosynthesis and the subsequent reduction of bioavailable iron. Today, iron availability limits primary productivity in about 30% of the world’s oceans. Diatoms, responsible for nearly half of oceanic primary production, have evolved molecular strategies for coping with variable iron concentrations. Our understanding of the evolutionary breadth of these strategies has been restricted by the limited number of species for which molecular sequence data is available. To uncover the diversity of strategies marine diatoms employ to meet cellular iron demands, we analyzed 367 newly released marine microbial eukaryotic transcriptomes, which include 47 diatom species. We focused on genes encoding proteins previously identified as having a role in iron management: iron uptake (high-affinity ferric reductase, multi-copper oxidase, and Fe(III) permease); iron storage (ferritin); iron-induced protein substitutions (flavodoxin/ferredoxin, and plastocyanin/cytochrome c6) and defense against reactive oxygen species (superoxide dismutases). Homologs encoding the high-affinity iron uptake system components were detected across the four diatom Classes suggesting an ancient origin for this pathway. Ferritin transcripts were also detected in all Classes, revealing a more widespread utilization of ferritin throughout diatoms than previously recognized. Flavodoxin and plastocyanin transcripts indicate possible alternative redox metal strategies. Predicted localization signals for ferredoxin identify multiple examples of gene transfer from the plastid to the nuclear genome. Transcripts encoding four superoxide dismutase metalloforms were detected, including a putative nickel-coordinating isozyme. Taken together, our results suggest that the majority of iron metabolism genes in diatoms appear to be vertically inherited with functional diversity achieved via possible neofunctionalization of paralogs. This refined view of iron use strategies in diatoms elucidates the history of these adaptations, and provides potential molecular markers for determining the iron nutritional status of different diatom species in environmental samples.",
"conclusion": "Conclusions The data presented in this study provides a revised perspective on the distribution and prevalence of key genes involved in iron metabolism in marine diatoms. The presence of transcripts encoding the three elements of the reductive uptake system ( FRE , MCO , FTR ) throughout the diatom lineage is evidence that this system has been evolutionarily conserved. We report that ferritin ( FTN ) coding genes are present in ancient diatoms, comprising a lineage distinct from canonical eukaryotic FTN . Additionally, two FTN paralogs are present in many diatoms, with one divergent clade displaying distinct differences on in silico translated C-terminal residues. The distribution of transcripts encoding the non-ferrous electron carriers plastocyanin ( PCYN ) and flavodoxin ( FLDA ) suggests the potential use of alternative redox metal strategies in a greater range of species than previously observed. Homologs of all four superoxide dismutase (SOD) metalloforms were found, illustrating the potential for adaptive use of different isozymes to ensure protection against oxidative damage in the face of metal scarcity. Based on our analyses, much of the physiological diversity found in diatoms appears to come from gene duplications and subsequent divergence. In the majority of cases, we found species harbor multiple paralogs suggestive of functional diversification and lending insight into the adaptable nature of diatoms that may have contributed to their expansion into so many habitats.",
"introduction": "Introduction Earth’s early oceans were rich in dissolved ferrous iron, which fostered the evolution of catalytic proteins that relied upon the redox potential of iron [ 1 ]. The onset of the Great Oxygenation Event approximately 2.3 Gya [ 2 ] caused iron(III) to precipitate out of seawater, transforming iron from a readily-available nutrient to a scarce commodity. Yet the legacy of ferroproteins persists with iron remaining an obligate cofactor of many essential metalloproteins. Photosynthetic organisms have particularly high iron requirements, with about half their total intracellular iron contained within photosynthetic proteins [ 3 – 5 ]. Approximately 20% of global photosynthesis is carried out by marine diatoms [ 6 ]. As members of the stramenopiles, diatoms appeared in the fossil record about 190 million years ago [ 7 ] and subsequently diverged into four Classes–the more ancient Coscinodiscophyceae and Mediophyceae diatoms (commonly referred to as centric diatoms), and the more recently diverged Fragilariophyceae and Bacillariophyceae diatoms (commonly known as pennate diatoms). Today, diatoms are one of the more species-rich groups of eukaryotic micro-organisms, able to bloom in both iron-rich coastal and iron-poor open ocean environments [ 8 ]. Diatoms rely on a diversity of strategies to meet cellular iron demands, including a high-affinity iron uptake system; iron storage capacity; substitutions of iron-requiring proteins with non-ferrous functional equivalents; and mechanisms to mitigate the risk of damage from reactive oxygen species produced in the presence of this redox-active metal [ 9 – 11 ]. The high-affinity reductive uptake system for iron was initially described in yeast [ 12 – 14 ] and consists of a high-affinity ferric reductase (FRE) that dissociates iron(III) from organic ligands; a multi-copper oxidase (MCO) that oxidizes the released iron(II) to iron(III); and an iron permease (FTR) that receives iron(III) from MCO for translocation across the cell membrane. Genes encoding putative ferric reductases [ 15 ], the putative multi-copper oxidase [ 16 ] and an iron(III) permease [ 17 ] have been detected in a limited number of examined diatoms. Once inside the cell, intracellular concentrations of iron must be tightly regulated to avoid oxidative damage. The best understood system for storing iron is ferritin (FTN), which self-assembles into a multimeric nanocage that sequesters iron(III) within its spherical structure [ 18 ]. Initially, genes encoding ferritin were conspicuously absent from the stramenopiles with publicly available whole genome sequences. The discovery in 2009 of FTN in a subset of diatoms led to the hypothesis that acquisition of this gene may have facilitated expansion of diatoms into the low-iron environment of the open ocean [ 19 ]. Low iron availability in today’s oceans appears to have driven the evolution of proteins that are functionally equivalent to ferroproteins but do not use iron as a cofactor. Common examples are found in the photosynthetic electron transfer chain. The iron-requiring ferrodoxin (encoded by petF ) can be replaced by flavodoxin (encoded by FLDA ), which uses flavin, rather than iron, as the redox cofactor [ 10 , 20 – 22 ]. Two isoforms encoded by a clade I and a clade II FLDA differ in their response to iron availability, with the clade II FLDA transcript abundance apparently regulated by iron levels [ 21 ]. The gene encoding ferredoxin appears plastid-encoded in most diatoms [ 23 , 24 ], although an evolutionarily recent transfer of the gene to the nucleus was reported for Thalassiosira oceanica [ 25 ]. A second substitution example is replacement of the iron-requiring cytochrome c \n 6 (CYTC6) with the copper-coordinating plastocyanin (PCYN). Thus far, this replacement has only been observed in T . oceanica [ 26 ], though detection of plastocyanin transcripts have been reported for Pseudo-nitzschia granii and Fragilariopsis cylindrus [ 9 ]. Superoxide dismutases (SODs) combat the formation of reactive oxygen species in the presence of redox-active metals like iron, catalyzing the transformation of O 2 \n - into molecular oxygen and hydrogen peroxide [ 27 ]. Four types of SODs are defined by the use of different metal cofactors: Fe, Mn, Cu-Zn, or Ni. The Fe- and Mn-binding SODs are structurally similar and likely diverged following an ancient gene duplication [ 27 , 28 ]. Cu-Zn- and Ni-utilizing SODs are evolutionarily distinct from each other and from the Fe/MnSODs and may represent convergent evolution of similar function [ 29 ]. NiSODs were recently recognized in eukaryotes, having now been identified in the diatom Phaeodactylum tricornutum as well as the prasinophytes Ostreococcus and Micromonas [ 30 – 32 ]. Limited availability of genetic data from diatoms has hindered a better understanding of the influence of various iron utilization strategies on the distribution and ecological success of diatom species. The Marine Microbial Eukaryote Transcriptome Sequencing Project [ 33 ] has greatly expanded our knowledge of the breadth and depth of functional genetic diversity of marine microeukaryotes. At the time of this study, the MMETSP consisted of 367 transcriptomes derived from 151 genera and included 77 diatom transcriptomes from 47 species and 31 genera. With this data, in conjunction with existing whole genomes from other microeukaryotes, we examined the diversity and evolutionary history of genes required for different iron metabolic strategies in diatoms.",
"discussion": "Discussion We used the sequence data generated for the Marine Microbial Eukaryote Transcriptome Sequencing Project (MMETSP) [ 33 ] to investigate the prevalence of select iron metabolism genes across diatoms. Previous research on the metabolic capabilities of these organisms had necessarily been limited by sequence data derived from a relatively low number of samples. Here, we re-evaluate previous hypotheses in light of the expanded resolution and breadth of organismal diversity enabled by the MMETSP. Of the 77 examined diatom transcriptomes, nine were derived from four diatom species grown under potentially iron-limiting conditions (media with less than 60 nmol Fe L -1 ): Thalassiosira weissflogii (MMETSP0878-0881), Chaetoceros sp. (MMETSP0200), Fragilariopsis kerguelensis (MMETSP0735, 0736), and Skeletonema marinoi (MMETSP0319, 0320). A publicly available transcriptome of Pseudo-nitzschia granii grown under iron-limiting conditions was also included. Despite the majority of cultures having been grown in iron-replete conditions, we detected transcripts for genes more commonly associated with iron limitation. Given this bias in growth conditions, it is important to note that the absence of detected transcripts in any given sample may mean that the culture conditions tested did not result in significant transcription of a gene. Due to differences in culturing conditions inherent to a distributed collaborative effort, we cannot confidently compare quantitative read counts of genes between samples. Therefore, these data provide information about the presence, but not absence or differential transcription, of particular sequences. Taken together, the data reveal a more complete picture of the distribution of iron metabolism genes across taxa, challenging assumptions and providing insight into gene origins, copy number, and divergent functions and affinities. Revisiting hypotheses of lateral gene transfer Lateral gene transfer (LGT) in eukaryotes is a recognized mechanism for the gain of new biochemical functions, increasing the potential for expansion into new ecological niches. Accurate detection of LGT, however, requires significant representation of sequences across a comprehensive taxonomic range [ 43 ]. The MMETSP data reveal one case that supports, with modifications, a hypothesis of LGT origin ( FTN ), a second case that expands upon a hypothesis of endosymbiotic gene transfer ( petF ), and two cases where previously hypothesized LGT instead likely reflects vertical inheritance within diatoms ( NiSOD and PCYN ). Prior to the MMETSP, the handful of available ferritin sequences from diatoms came from pennate lineages. FTN sequences from pennate diatoms were separated from the other eukaryotes by long branches on a phylogenetic tree. The dissimilarity of the pennate diatom FTN from other eukaryotes, together with its apparent absence from other stramenopiles supported the original hypothesis of LGT acquisition of FTN in pennates [ 19 ]. The MMETSP data serve to extend and modify the story by showing FTN transcription in all four extant diatom Classes ( Fig 1 ), while remaining largely absent from other stramenopiles. The additional diatom sequences identified here confirm that diatom ferritin does not branch with other eukaryotic ferritins and instead branches with cyanobacterial true ferritin, which is believed to also possess iron storage functionality, suggesting an ancient acquisition of FTN from this group ( Fig 3 ). Two putative diatom FTN sequences appear more closely related to those from heterotrophic bacteria rather than photosynthetic cyanobacteria. One of the “bacteria-like” sequences is found in the Phaeodactylum tricornutum whole genome sequence [ 44 ] and groups closely with a sequence from a different diatom species, Nanofrustulum sp ., suggesting that these sequences may have been acquired as separate LGT events from closely related heterotrophic bacteria ( Fig 3 ). Embedded within the clade of diatom ferritins are sequences derived from two dinoflagellates and one silicoflagellate ( Fig 4 ). The two dinoflagellates ( G . foliaceum and K . foliaceum ) are closely related ‘dinotoms’ whose plastids are derived from a diatom endosymbiont [ 45 ], likely a member of the Bacillariophyceae [ 46 ]. The close affiliation of the dinotom FTN sequences with Nitzschia , Cylindrotheca and Nanofrustulum suggest that they are derived from their diatom endosymbiont rather than the dinoflagellate host. In contrast, the unrelated silicoflagellate may have acquired ferritin through the phagotrophy of a diatom, specifically a member of the Mediophyceae. The absence of FTN in some diatoms, such as certain members of Thalassiosira , may be tolerated due to the presence of an alternative, non-ferritin based iron storage system. Such a system has been proposed for both the brown alga Ectocarpus siliculosis [ 47 ] and the Thalassiosiroid diatoms [ 48 ], both of which lack a known genomic copy of FTN and appear to store iron in mineralized clusters. Similar to LGT, endosymbiotic gene transfer (EGT) is the acquisition of genetic material from outside the host genome, in this case from an endosymbiont or endosymbiotically-derived organelle. We identified evidence for transfer of petF , which encodes ferredoxin, from the plastid to the nuclear genome. petF transcripts from multiple species across classes were detected despite the use of mRNA isolation protocols that bias against plastid encoded transcripts. A majority of these transcripts appear to encode a plastid-targeting peptide ( Fig 5 ) similar to that detected for the T . oceanica variant [ 25 ], including conserved motifs recognized for plastid localization [ 36 ]. Transfer of petF from the plastid to the nucleus may have occurred several times, or alternately, this transfer may have occurred once in an ancestral diatom with subsequent loss in some descendant lineages ( S8 Fig ). Nuclear regulatory control of PETF has been suggested to provide a more nuanced response to iron availability in T . oceanica [ 25 ], and this may reflect a more ancestral method of acclimation to trace metal availability in diatoms. In contrast to the incorporation of FTN and petF into the diatom nuclear genome by LGT and EGT, respectively, two genes with hypothesized recent LGT origins appear to instead have roots deeper in the chromalveolate lineage. NiSOD and PCYN homologs are broadly distributed throughout diatoms, but unlike FTN they follow organismal phylogeny, clustering with other chromalveolates ( S13 Fig , Fig 6 ). The gene encoding nickel superoxide dismutase ( NiSOD ) was originally hypothesized to have arisen relatively recently in eukaryotes via a lateral gene transfer from bacteria to prasinophytes ( Ostreococcus ) based on available molecular data at the time [ 31 , 32 ]. More recently, a NiSOD homolog was found in the diatom Phaeodactylum tricornutum [ 30 ]. Similarly, the apparent scarcity of PCYN , only previously identified in T . oceanica [ 26 ] and Fragilariopsis cylindrus [ 49 ] was hypothesized to reflect LGT events in select diatom species [ 50 ]. Our analyses demonstrate that homologs of both genes are present in every class of diatoms and many of the major branches of the chromalveolates, which supports vertical, rather than lateral, inheritance of these genes. The multi-copy nature of iron genes contributes to interspecies variability Iron metabolism proteins in diatoms appear to be encoded primarily by multi-gene families, presumably resulting in proteins with divergent functions. For example, in many diatom species, multi-copy gene families were detected for two of the iron uptake system proteins–multicopper oxidase and ferric reductase. Multi-copper oxidases include members with ferroxidase and cuprous oxidase activity, and share sequence similarities with laccases [ 14 ]. The residues implicated in ferroxidase activity in yeast [ 14 ] are not maintained in diatoms, although ferroxidase activity has been demonstrated in vivo with T . oceanica [ 16 ]. Similarly, the vast majority of diatoms harbor multiple copies of putative diatom ferric reductase genes ( FRE ). This variability in copy number could allow for neofunctionalization of paralogs, perhaps resulting in separate metabolic functions. An ancient duplication event appears to have led to at least two distinct paralogs of diatom ferritin, with a well-supported subset, FTN-II , showing distinct divergence of residues on the C-terminus of the predicted translation ( Fig 4 , S7 Fig ). Mammals possess a light chain and heavy chain of ferritin: the heavy chain oxidizes iron(II), while the light chain fosters ferrihydrite nucleation, having lost the capacity to oxidize iron [ 51 ]. Whether or not the two paralogs of diatom ferritin form a complex or demonstrate functional differences is unknown, as only one paralog from P . multiseries (PID 237986) from FTN-I has been characterized [ 19 , 52 ]. Three putative plastocyanin paralogs were detected in Fragilariopsis kerguelensis and Pseudo-nitzschia heimii , both of which are found in low-iron open ocean regions. These alternate paralogs possess the canonical Cu-coordinating residues for Populus nigra plastocyanin [ 38 ], with one notable exception in P . heimii ( PCYN1 ), which has His37Gln and Cys84Ser substitutions at the Cu-coordinating site relative to P . nigra PCYN, conceivably leading to altered binding capacity or neofunctionalization ( S10 Fig ). Characterization studies would be useful to determine the role of these additional copies of PCYN in P . heimii and F . kerguelensis , and to assess whether they confer an advantage in low-iron regimes. Multiple superoxide dismutase metalloforms illustrate adaptive preferences for different transition metals Diversification of function through gene duplications is exemplified with the SODs. The biochemical importance of SOD is underscored by the presence of multiple isozymes. At least two different metalloforms of SODs were detected in every species of diatom ( Fig 1 ). The gene encoding manganese superoxide dismutase ( MnSOD ), a metalloform that has been suggested to substitute for FeSODs under iron-limiting conditions [ 26 ], appears to have duplicated early in eukaryotic history, with most diatoms transcribing two or more paralogs ( Fig 1 , Fig 8 ). The common detection of NiSOD transcripts implies an important, constitutive role for the NiSOD as well. Most NiSOD transcripts identified here are fused to an ubiquitin-coding sequence ( S13 Fig ). In yeast, post-translational cleavage of ubiquitin-fusion proteins is performed by at least four ubiquitin-specific proteases [ 53 ]. Similar cleavage by ubiquitin-specific proteases of the NiSOD fusion protein would provide a mechanism for the immediate activation of the Ni-hook motif and suggest the possibility that UBQ regulatory pathways may control activated NiSOD protein abundance. Unlike NiSOD from bacteria, the complete putative NiSOD homolog from these eukaryotes has yet to be fully functionally characterized, although SOD functionality has been demonstrated in oligopeptide maquettes [ 31 , 54 ]. In contrast to the near ubiquity of Mn and NiSOD transcripts, Fe and Cu-Zn SODs displayed distinctive patterns. FeSOD was not detected in any members of the Bacillariophyceae, the most derived class of diatoms. Instead, FeSOD transcripts were more commonly detected as two distinct copies in members of the most ancient class of diatoms, the Coscinodiscophyceae ( Fig 1 ). The Cu-ZnSOD s displayed an opposite trend to the FeSOD s, with transcripts more frequently detected in the more derived diatoms ( Fig 1 ). The apparent preference of pennate diatoms for Cu-ZnSOD in Fe-replete media, and their parallel lack of FeSOD transcripts, suggests a permanent shift in metal-use priorities for this group of diatoms. While previous studies have emphasized the role of Fe and Cu-Zn SODs in diatoms, our analyses suggest that they may play an accessory role to the dominant Mn and Ni metalloforms."
} | 5,370 |
28379466 | PMC5860119 | pmc | 3,320 | {
"abstract": "Abstract Summary Reconstructing and analyzing a large number of genome-scale metabolic models is a fundamental part of the integrated study of microbial communities; however, two of the most widely used frameworks for building and analyzing models use different metabolic network representations. Here we describe Mackinac, a Python package that combines ModelSEED’s ability to automatically reconstruct metabolic models with COBRApy’s advanced analysis capabilities to bridge the differences between the two frameworks and facilitate the study of the metabolic potential of microorganisms. Availability and Implementation This package works with Python 2.7, 3.4, and 3.5 on MacOS, Linux and Windows. The source code is available from https://github.com/mmundy42/mackinac .",
"conclusion": "3 Conclusion The rapid reconstruction of GEMs using ModelSEED and the powerful analysis features in COBRApy enable the comprehensive study and exploration of the metabolic function of organisms. Now, Mackinac makes it easy to use the ModelSEED web service to create GEMs that can be seamlessly analyzed with COBRApy. This significantly streamlines the workflow required to explore the large number of species that make up microbial communities.",
"introduction": "1 Introduction Reconstructing genome-scale metabolic models (GEMs) is a complex process that involves integrating multiple data sources. A GEM for a particular organism can be reconstructed manually using a standard protocol and current knowledge from literature ( Thiele and Palsson, 2010 ). Alternatively, a GEM can be reconstructed automatically, which enables the creation of models for the large number of organisms that typically make up microbial communities. Automated reconstruction uses the annotated genome of the organism to predict reactions to include in the draft GEM and specialized methods to gap fill missing reactions in the metabolic network ( Benedict, 2014 ; Henry, 2010 ; Kumar and Maranas, 2009 ; Reed, 2006 ; Thiele, 2014 ). ModelSEED is the most widely used of the existing frameworks for automated GEM reconstruction. Using the ModelSEED web service, a researcher can reconstruct and gap fills GEMs from a large database of reactions and functional roles. The GEMs can then be used to analyze the growth characteristics of the organisms and to evaluate the effects of reaction or gene knockouts using constraint-based analysis methods ( Henry, 2010 ). COBRApy ( Ebrahim, 2013 ) is a Python package that uses constraint-based analysis to study the metabolism of both single organisms and microbial communities. This popular package is under continuous development, and new functionalities for model analysis and exploration are frequently added. While the ModelSEED web service and COBRApy are widely used in the field of microbial metabolism, they are independent frameworks. The integration of their capabilities to study organisms can only be done manually, which is a very laborious and time-consuming process if a large number of species is to be studied. We developed Mackinac, a Python package that creates a COBRA model object directly from a ModelSEED model object, seamlessly providing a bridge between the two frameworks. The reconstruction of the ModelSEED model object is accomplished within the ModelSEED framework ( Henry, 2010 ). The COBRA model then created contains all of the information from the ModelSEED model, including features that are commonly lost when the models are exported to the SBML format ( Chaouiya, 2013 ) on the ModelSEED web service. Among these are the chemical equations of metabolites, and the names of the genes in the gene-protein-reaction evidence for a particular reaction. By allowing the reconstruction of models using the ModelSEED framework, Mackinac allows the comprehensive storage of all the information associated with the models in the COBRA model object, and provides direct access to many of the functions available from this web service, such as functions to reconstruct, gap fill and optimize GEMs. It also provides functions to manage and work with models stored in the user’s ModelSEED workspace. Thus, Mackinac combines ModelSEED’s ability to rapidly reconstruct GEMs with COBRApy’s ability to analyze, inspect, explore and draw conclusions from the models, all in one integrated framework."
} | 1,074 |
33629071 | PMC7881767 | pmc | 3,322 | {
"abstract": "As a promising renewable energy source, it is a challenging task to obtain blue energy, which is irregular and has an ultralow frequency, due to the limitation of technology. Herein, a nonresonant hybridized electromagnetic-triboelectric nanogenerator was presented to efficiently obtain the ultralow frequency energy. The instrument adopted the flexible pendulum structure with a precise design and combined the working principle of electromagnetism and triboelectricity to realize the all-directional vibration energy acquisition successfully. The results confirmed that the triboelectric nanogenerator (TENG) had the potential to deliver the maximum power point of about 470 μ W while the electromagnetic nanogenerator (EMG) can provide 523 mW at most. The conversion efficiency of energy of the system reached 48.48%, which exhibited a remarkable improvement by about 2.96 times, due to the elastic buffering effect of the TENG with the double helix structure. Furthermore, its ability to collect low frequency wave energy was successfully proven by a buoy in Jialing River. This woke provides an effective candidate to harvest irregular and ultralow frequency blue energy on a large scale.",
"conclusion": "3. Conclusions Overall, a nonresonant hybridized electromagnetic-triboelectric nanogenerator was presented to efficiently harvest the ultralow frequency blue energy. Through the circumferential swing structure design, the low frequency, random, and irregular vibration energy harvesting was achieved successfully. On the basis of a linear motor platform and wave pump, this paper systematically studied the influence of oscillation frequency and wavelength. The results confirmed that the triboelectric nanogenerator (TENG) had the potential to deliver the maximum power point of about 470 μ W while the electromagnetic nanogenerator (EMG) can provide 523 mW at most. The energy conversion efficiency of the system was successfully improved to 48.48% due to the elastic buffering effect of the TENG with the double helix structure. Furthermore, its effectiveness for wave energy harvesting was verified on a simple float in the Jialing River. Finally, the device was proven to successfully create a self-powered wireless temperature sensing system, demonstrating its extensive applications toward blue energy.",
"introduction": "1. Introduction With the depletion of petroleum energy and a series of environmental problems, searching for new sources of energy is extremely urgent in nowadays in society [ 1 – 4 ]. It is generally acknowledged that blue energy is able to meet the need. If used widely in commercial applications, it will bring great changes to the global energy structure, economy, and social development [ 5 , 6 ]. Although the potential for ocean energy harvesting is enormous, most of the technologies for capturing this energy are still in the testing stage. In addition, most of the devices are expensive, inefficient, and so on. Therefore, new blue energy harvesting methods should become an urgent research topic [ 7 – 12 ]. Traditional blue energy generators are mainly based on EMGs, which require additional complex mechanical and hydraulic structures to convert wave motion into linear reciprocating or rotational motion to drive the generator to generate electricity [ 10 , 13 , 14 ]. This kind of devices generally has good output performance only at high frequency and in a regular environment. TENGs have many advantages, including low cost, simple structure, light weight, high power density, and random acquisition of low frequency vibration energy. [ 15 – 20 ]. However, most TENGs are only capable of effectively obtaining them from only one direction or within a relatively very narrow bandwidth [ 21 – 26 ]. For the purpose of improving the efficiency of blue energy collection, a variety of strategies is supposed to be combined to achieve the goal of working in a highly cooperative manner. A hybridized electromagnetic-triboelectric mechanism has been proven to be a convincing method to obtain blue energy [ 27 – 30 ]. Herein, a nonresonant hybridized electromagnetic-triboelectric nanogenerator is presented to efficiently obtain the ultralow frequency blue energy. The oscillating component of the device was supported on a fixed surface by a spring, and it can swing around this support position as a sphere, thus successfully achieving all-dimensional vibration energy obtainment. What is more, integrating the TENG with the double helix structure into the system can not only harvest energy but also effectively reduce the energy loss caused by the collision between the magnet and the outer wall, due to its elasticity as a buffer. The influences of vibration frequency on the output characteristics of the device were systematically studied based on a linear motor, and its ability to collect low frequency wave energy was proven. At the same time, the outputs under different wave heights were characterized with the action of random and irregular water waves, which proved the device's ability to collect wave energy. The results confirmed that the TENG had the potential to deliver the maximum power point at about 470 μ W under the loading resistance of 0.5 M Ω at a driving frequency of 2.2 Hz. And the electromagnetic nanogenerator (EMG) can provide 523 mW at most when the load resistance was 280 Ω . The energy conversion efficiency of the system reached up to 48.48%. Furthermore, we demonstrated its success on a buoy in Jialing River. Finally, the device was properly applied to powering a wireless temperature sensor, demonstrating its extensive applications toward the blue energy.",
"discussion": "2. Results and Discussion 2.1. Model of the Hybridized Nanogenerator A nonresonant hybridized electromagnetic-triboelectric nanogenerator is proposed in this work, as illustrated in Figure 1(a) , which includes eight main parts: a magnet support, a cylindrical NdFeB magnet, a coil, a spring, four TENGs, a hollow cylindrical shell, an end cover, an adjusting stud, and a locking screw. The NdFeB magnet and the magnet support constituted the swing assembly, while the spring, adjusting stud, and locking screw constituted the support assembly which was installed in the inner part of the circular shell by a threaded connection. The NdFeB magnet was fixed inside the magnet support with strong glue, and the magnet support was placed on the adjusting stud after being covered on the spring, in which the adjusting stud played the role of supporting the swinging assembly and the spring was used to constrain the radial movement of the supporting position. The swing component could swing around the pivot position of the adjusting stud with a swing trajectory of a sphere, as shown in Figure 1(b) . The four TENGs were uniformly spaced and pasted on the inside of the hollow cylindrical shell, and the coil was fixed on the top cover of the hollow cylindrical shell. Under the action of external excitation, with the oscillation of the oscillating component, magnetoelectric energy would be generated through the relative change of position between the magnet and coil, while triboelectric energy would be generated through the collisions between the magnet and TENGs. In order to understand the pendulum swing more intuitively, the position of the fulcrum was equivalent to the ball hinge. Movie S1 and Movie S2 are the kinematic simulation of the pendulum swing, which indicate that the swing trajectory of the pendulum is a sphere. Taking the swing of the device to one side as an example to illustrate, the simplified model is shown in Figure 1(c) . θ is the instantaneous angle of the oscillating component, and ma represents the resultant of the inertial force of the oscillating component and the reaction force after crashing with the shell. N is the supporting force, mg is the gravity force, T is the elastic force, and O is the fulcrum. Through force analysis of the swinging component, its radial force ( F r ) and tangential force ( F t ) can be given as follows:\n (1) F r = N + ma sin θ − mg cos θ , (2) F t = ma cos θ + mg sin θ − T . When there is an external disturbance, such that F r = 0 and F t ≠ 0, the oscillating component will oscillate. For the purpose of improving the output capability of the triboelectric unit, a double helix structure triboelectric nanogenerator was employed, which we have reported in our previous study. It can not only harvest energy but also effectively reduce the energy loss caused by the collision between the magnet and the outer wall, due to its elasticity as a buffer in the system. It is constructed by two parts (part I and part II) through a novel and simple paper-folding process, as shown in Figure 1(d) . Part I consisted of two pairs of copper foil (top electrode) taped together, and part II consisted of two pieces of FEP films which were attached on a copper foil (bottom electrode). In a natural state, the surfaces of part I and part II were separated because of the excellent elastic property of the double helix structure. When an external force was applied, the FEP films of part II would be in contact with the copper foil (top electrode) of part I, thus triboelectrification would be generated. The double helix structure triboelectric nanogenerator consists of five layers with the dimensions of 30 m × 30 m × 27 mm, as displayed in Figure S1 . 2.2. Working Principles The example of left and right swaying was taken to demonstrate the complete operating principle of the hybridized nanogenerator, as depicted in Figure 2 . Initially, the swinging part swung to the left under the action of external force and contacted with TENG 1 , assuming that no current was generated in the coil at this time ( Figure 2 , I). The FEP layer and the top electrode produced physical contact due to the compression of TENG 1 , so positive charges would transfer from the Fluorinated Ethylene Propylene (FEP) film to the copper film, giving rise to a mass of charges with opposite sign on each surface ( Figure 2 , I). When the swinging part started to swing from left to right ( Figure 2 , II), the top electrode was separated from the FEP film due to the elastic property of TENG 1 , resulting in a current signal from the top copper film to the bottom copper film. Meanwhile, as the magnet swung closer to the coil with the swing, the lines of magnetic induction through the coil would increase, and a clockwise current would come into being in the coil to obstruct this change. When the magnet was placed in the middle position, the top electrode was completely separated from the FEP film, and no current was generated in TENG 1 , while the magnetic flux in the coil reached its maximum value, and no induced current was generated too ( Figure 2 , III). When the magnet continued to swing to the right under external excitation and exerted pressure on TENG 2 , there was going to be a current signal from the bottom copper film to the top copper film in TENG 2 . Besides, a counterclockwise current was generated in the coil due to a decrease in the lines of magnetic induction through the coil ( Figure 2 , IV). If the magnet swung to the far right, no current was generated in TENG 2 and the coil ( Figure 2 , V). When the magnet started to swing from right to left, the top electrode was separated from the FEP film under the elastic force of TENG 2 , and a current from top to bottom would be generated in TENG 2 . At the same time, the lines of magnetic induction through the coil increased, producing a clockwise induced current ( Figure 2 , VI). When magnet was placed in the middle position, in the same state as Figure 2 , III, no current was generated in the TENG and EMG ( Figure 2 , VII). As the magnet continued to swing to the left and began to exert pressure on TENG 1 , there would be a same current and the counterclockwise current ( Figure 2 , VII). When the magnet continued to swing to the left and returned to its initial position, an energy collection cycle was completed. 2.3. The Output Capability of the Hybridized Nanogenerator The output characteristics were evaluated on a linear motor platform (model: DGL200-AUM4); also, oscillation frequency's influence on the output of the hybridized nanogenerator was systematically studied. Firstly, the electrometer (model: Keithley 6514) was selected to demonstrate the output capability of the TENG, as shown in Figures 3(a) and 3(b) . With the frequency increasing from 0.8 Hz to 2.3 Hz, the current curves and voltage curves of the TENG show the same trend of first increasing and then stabilizing. They reached their maximum values at 2.2 Hz, 12.4 μ A, and 190 V. This is because vibration acceleration increases with the frequency, which will lead to the increasing of the pressure on the TENG, resulting in more triboelectric charges being on the surface. The transferred charges in one period can be obtained by integrating one period of current. Figure 3 (c) shows the current integral for TENG in one cycle at the frequency of about 2.3 Hz, and it can be seen that the transferred charges in one period are about 143.04 nC. The same method was used to calculate the transferred charges at other vibration frequencies, as shown in Figure 3(d) . It indicates that the amount of transferred charge increased with the increase of the vibration frequency. In order to further verify the ability to capture the energy of the TENG, the output voltages were measured when the external load was from 1 M Ω to 1000 M Ω , and the instantaneous powers were calculated by Ohm's law. The results confirmed that the TENG has the potential to deliver a peak output power of 470 μ W, when the loading resistance was 0.5 M Ω , as presented in Figure 3(e) . The charging capacity of the TENG to different capacitors was also studied, and the result shows that the voltage of an electrolytic capacitor of 10 μ F can be increased to 3 V within 100 seconds. According to Faraday's law, the induced voltage in the coil is expressed as the following formula [ 31 ]:\n (3) V = − N d ϕ d t = − N S d B x d t = − N S d B x d x d x d t = − N S d B x d x v , where N is the number of windings of the coil, S is the area of the coil, B ( x ) is the magnetic field strength, and v is the moving speed of the magnet. When the internal resistance is R coil , the induced current in the coil is listed as\n (4) I = V R coil = − N S R coil d B x d x ν . Therefore, the output voltages and currents induced in the coil are positively correlated with the moving speed of the magnet. The magnitude and direction of the swing velocity v of the magnet are periodic, so is the current I induced in the coil. Assuming that the maximum swing angle of the magnet is θ , the swing angle of the magnet moving from one side to the other is 2 θ , and the time taken is half a period, we can then calculate according to the average angular velocity of the magnet:\n (5) ω ¯ = 4 θ T . \n T is the period of the oscillation. Let us say the length of the pendulum is l , then the average velocity of the oscillation is\n (6) v ¯ = ω ¯ l = 4 θ l T = 4 θ l f , where f is the frequency of oscillation. Simultaneous Formulas ( 3 ), ( 4 ), and ( 6 ) can be obtained as follows:\n (7) V ¯ = − N S d B x d x 4 θ l f , (8) I ¯ = − N S R coil d B x d x 4 θ l f . Therefore, the average voltage and average current induced in the coil are positively correlated with the oscillation frequency of the magnet. The output characteristics of the EMG were evaluated on a linear motor platform, and the results are demonstrated in Figure 4 . As the motion frequency of the linear motor increased from 0.8 Hz to 2.1 Hz, the maximum induced current in the coil increased from 14.50 mA to 22.45 mA, and the maximum induced voltage increased from 10.63 V to 37.42 V. The EMG represented high efficiency in the ultralow frequency range of 0.8 Hz-2.1 Hz, and the output characteristic increased with the increase of the frequency, which was consistent with the previous theoretical analysis. When the frequency was greater than 2.1 Hz, the induced current and induced voltage in the coil tend to be stable and no longer increased with the increase of the frequency. This is because the vibration frequency of the device did not rise with the increase of the external frequency due to the limitation of the structure of the device. The relationship between the induced voltage and the impedance is shown in Figure 4(c) . The relationship between peak power and impedance is obtained by calculation. It indicates that the instantaneous peak power reached its maximum of 523 mW, when the matching resistance was 280 Ω . 220, 330, 470, and 1000 μ F capacitors charged by the TEMG are shown in Figure 4(d) . The voltage of an electrolytic capacitor of 1000 μ F can be increased to 3 V in 10 s, while the voltage of a electrolytic capacitor of 220 μ F can be increased to 3 V in only about 3.8 s. 2.4. The Wave Energy Harvesting Tests Under the action of irregular and complex water waves produced by a wave pump, the outputs of a hybridized electromagnetic-triboelectric nanogenerator in different wave heights were characterized, as shown in Figure 5 . Figures 5(a) and 5(b) show the output currents and output voltages of TENG at a frequency of 1.0 Hz, with wave heights ranging from 4 mm to 9 mm. The output currents of TENG improved from 0.59 μ A to 2.12 μ A and the output voltage from 36.52 V to 53.89 V with the wave height raised up from 4 cm to 9 cm, so both the output currents and output voltages of TENG showed a trend of increasing with the wave height. Similar trends were observed in the induced currents and induced voltages in the coil of the EMG, and when the wave height increased from 4 mm to 9 mm, the short-circuit current increased from 5.26 mA to 11.57 mA and the induced voltage in the coil from 1.05 V to 3.16 V, as displayed in Figures 5(c) and 5(d) . In addition, a simple buoy was built to characterize the output of the hybridized electromagnetic-triboelectric nanogenerator in the Jialing River, as shown in Figure 5(e) . Movie S3 explains the test of EMG in the Jialing River, and Movie S4 proves the output of TENG in the Jialing River. As shown in Figure S2 , under the action of irregular and complex water waves, the peak voltages of EMG and TENG reached 93.15 mV and 60 mV, respectively. 2.5. The Energy Harvesting Efficiency of the Hybridized Nanogenerator Furthermore, the captive energy efficiency of the hybridized nanogenerator was evaluated. Firstly, the energy of a single external excitation was estimated. Under the limitation of device size, the maximum swing angle of the magnet is about 30°. As can be seen from Figure 2 , within the interval between two zero-current states in the coil, the device just swung 30°. Under a single excitation, the induced voltage in the coil of the EMG is shown in Figure 5(f) , so the time difference between the first zero point and the second zero point can be calculated as about 0.05 seconds. Therefore, the initial angular velocity of the magnet is approximately\n (9) ω = θ t 2 − t 1 = π / 6 0.05 = 10 π 3 . The pendulum length of the device ( l ) is about 0.052 m, so the initial velocity of the magnet can be obtained through the following equation:\n (10) v = ω l . The initial velocity of the magnet can be calculated to be about 0.54 m/s. Therefore, the initial energy obtained by the magnet can be obtained by the following formula:\n (11) E i = 1 2 m ν 2 . The mass of the magnet ( m ) is about 0.043 kg, so the initial energy obtained by the magnet was about 6.3 × 10 −3 J. The electrical energy captured by the hybridized nanogenerator can be obtained through the following equation:\n (12) E o = ∫ t 1 t 2 U TENG 1 2 R TENG 1 d t + ∫ t 1 t 2 U TENG 2 2 R TENG 2 d t + ∫ t 1 t 2 U EMG 2 R EMG d t . Under a single excitation, the output voltages of two TENGs under an 0.5 M Ω load after the integral is shown in Figure S3(a-b) , and the energy they captured was 1.19 × 10 −5 J and 1.17 × 10 −5 J, respectively. Using the same method, under a single excitation, the output voltage of the EMG under a 280 Ω load after the integral is shown in Figure S3(c) , and the energy it captured was 3.03 × 10 −3 J. Therefore, the electromechanical conversion efficiency of the hybridized nanogenerator is\n (13) η = E o E i × 100 % = 3.054 × 1 0 − 3 6.3 × 1 0 − 3 × 100 % ≈ 48.48 % . From the previous analysis, it can be seen that except for harvesting energy, the TENG also acts as a buffer layer to reduce the energy loss caused by the collision between the magnet and the outer wall. To verify this effect, the TENG was removed and the energy harvesting capability of the EMG under a single excitation was tested, as shown in Figure S3(d) . In this state, the energy captured by the EMG was 1.036 × 10 −3 J, and its electromechanical conversion efficiency was only 16.4%. It can be seen that the TENG greatly improved the energy conversion efficiency of the system. The following is an explanation for this phenomenon based on collision theory. The power efficiency of a conventional electromagnetic generator is generally very high; however, in the system described in this paper, a lot of energy will be lost in the violent collision between the magnet and the outer wall in the narrow space during the swing process, which lowers down the most on the energy conversion efficiency of the electromagnetic generator. To settle this problem, we designed a double helix triboelectric nanogenerator of excellent resilience to save the energy loss, which also serves as another energy harvester. This sophisticated designed mechanism improved the energy conversion efficiency of the whole system. The specific collision process is shown as follows. In this paper, the collision model of the system without the TENG can be described as Figure S4(a) , in the case of ignoring the power generated by the EMG and the TENG. Because the double helix triboelectric nanogenerator can be represented by a spring model due to its excellent elastic properties, the collision model of the system with the TENG can be described as in Figure S4(b) . Collisions include elastic collisions, inelastic collisions, and completely inelastic collisions. The types of collisions can be represented by the recovery coefficient e :\n (14) e = v 2 − v 1 v 10 − v 20 , where v 10 is the speed of the magnet before collision, v 1 is the speed of the magnet after the collision, v 20 is the speed of the outer shell before collision, and v 2 is the speed of the outer shell after the collision. When e = 1, it corresponds to the elastic collision, that is, after the collision, the deformation can recover; there is no heat, no sound, and no kinetic energy loss. When e = 0, it corresponds to a completely inelastic collision, that is, after the collision, the objects are combined together, or the velocities are equal, and the kinetic energy loss is the greatest. When 0 < e < 1, it corresponds to inelastic collision, that is, the object cannot completely recover to its initial state after collision. In this paper, for the models in Figure S4(a) and Figure S4(b) , the velocities of the outer shell were zero before and after the collision:\n (15) v 2 = v 20 = 0 . Therefore, Formula ( 15 ) can be simplified as\n (16) e = − v 1 v 10 . The kinetic energy of the magnet before collision was\n (17) E 1 = 1 2 m v 10 2 . The kinetic energy of the magnet after collision was\n (18) E 2 = 1 2 m v 1 2 . Therefore, the energy loss after the collision was\n (19) Δ E = 1 2 m v 10 2 − 1 2 m v 1 2 = 1 2 m v 10 2 1 − e 2 . In the model which is shown in Figure S4(a) , the magnet would make a huge noise during the direct collision with the outer shell (white resin). At the same time, the elastic property of the white resin was poor. After deformation, it was not easy to recover, so it was an inelastic collision. Namely, 0 < e < 1 and the energy loss after collision was\n (20) Δ E = 1 2 m v 10 2 1 − e 2 ⋯ 0 < e < 1 . As for the model shown in Figure S4(b) , because the spring had excellent recovery performance, it can be approximately equivalent to the elastic collision, which was e = 1, and the collision energy loss was zero. Therefore, the energy loss in the collision process can be effectively reduced, and the energy conversion efficiency of the system can be increased after integrating the double helix structure triboelectric nanogenerator on the inner wall of the system. 2.6. The Application of the Hybridized Nanogenerator On the linear motor, lighting LED experiments had been accomplished. In Figure S5(a-b) and Movie S5-6 , 100 LEDs in parallel were lighted up simultaneously by the EMG; besides, 50 LEDs in series were lighted up by the TENG. Finally, a self-powered wireless temperature sensing system was successfully integrated with a simple power management module, and the system block diagram is shown in Figure 6(a) . Figure 6(b) displays the voltage of an electrolytic capacitor of 2000 μ F which could be raised up to 4 V in about 10 seconds by the hybridized nanogenerator. The core management component of the power management module was the LTC3106 made by the ADI company for energy acquisition and power management. The temperature sensor is a K-type thermocouple, whose measurement range is 0-200°C. The main control chip of the wireless transmission module is CC2530F256, and its longest distance of transmission is 600 m. The electronic photos of the power management are depicted in Figure 6(c) . During the testing phase, we added a switching element at the front end of the wireless temperature sensor. Firstly, turning off the switch, the hybridized nanogenerator charged a rechargeable battery of 1 mAh through the input capacitor, and the charging protection voltage was 3 V. After charging for a period of time, the switch was turned off, and the energy of the hybridized nanogenerator was transferred from the input capacitor to the wireless temperature sensing module through the DC/DC module, where the excess energy was stored in the rechargeable battery. Wireless temperature data can be displayed in the serial port program via the USB to serial port. The system photo is shown in Figure 6(d) . Experiments show that the hybridized nanogenerator can successfully support the wireless temperature sensing to complete data transmission with an interval of 10 seconds, as shown in Move S7 ."
} | 6,620 |
25852671 | PMC4365725 | pmc | 3,324 | {
"abstract": "Microbial communities play important roles in health, industrial applications and earth's ecosystems. With current molecular techniques we can characterize these systems in unprecedented detail. However, such methods provide little mechanistic insight into how the genetic properties and the dynamic couplings between individual microorganisms give rise to their dynamic activities. Neither do they give insight into what we call “the community state”, that is the fluxes and concentrations of nutrients within the community. This knowledge is a prerequisite for rational control and intervention in microbial communities. Therefore, the inference of the community structure from experimental data is a major current challenge. We will argue that this inference problem requires mathematical models that can integrate heterogeneous experimental data with existing knowledge. We propose that two types of models are needed. Firstly, mathematical models that integrate existing genomic, physiological, and physicochemical information with metagenomics data so as to maximize information content and predictive power. This can be achieved with the use of constraint-based genome-scale stoichiometric modeling of community metabolism which is ideally suited for this purpose. Next, we propose a simpler coarse-grained model, which is tailored to solve the inference problem from the experimental data. This model unambiguously relate to the more detailed genome-scale stoichiometric models which act as heterogeneous data integrators. The simpler inference models are, in our opinion, key to understanding microbial ecosystems, yet until now, have received remarkably little attention. This has led to the situation where the modeling of microbial communities, using only genome-scale models is currently more a computational, theoretical exercise than a method useful to the experimentalist.",
"conclusion": "Concluding remarks In this paper, we described current methods to model the metabolism of single species and how we think such system approaches could be used at the microbial community level. These methods go from genomic information to understanding and directing microbial community metabolism. We argued that metagenomics data are great, but they need to be augmented with flux measurements and model-based inference methods to identify the community structure and state. We arrive at a proposed approach where models are combined with quantitative data. Such models can vary in their level of coarse-graining depending on the research questions, data and experimental options at hand. Genome-scale stoichiometric models will be the knowledge base with which to integrate genomic, physiological and physicochemical data, and can be developed parallel to coarse-grained models to understand the community structure, state and function. We feel that what is missing -but is within reach- is a description of the functioning of a microbial community in terms of the fluxes through its members. We therefore advocate that flux analysis specialists from the fields of biotechnology, microbial physiology, and systems biology team up with microbial ecologists, as they increasingly do. Conflict of interest statement The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.",
"introduction": "Introduction Microbial communities are ubiquitous in nature and play key roles in the ecosystems of our planet. Humans depend on their activities as they play essential roles in element cycling and agriculture, e.g., through interactions between plants on the one hand and mycorrhiza and nitrogen fixing bacteria on the other hand (Fellbaum et al., 2012 ). Microbial communities are also exploited in food fermentations, e.g., in the production of cheese, yogurt, soy sauce, sauerkraut, and vinegar. Despite this major impact on human society, we still have little understanding of the design principles that determine microbial ecosystem functioning, robustness, evolution, and control. This means that the opportunities to rationally optimize the performance of such communities are currently very limited. In view of the complexity of the systems we are dealing with, it should be clear that experimental data alone will not provide the desired understanding -regardless of how impressive current experimental techniques may be. For example, think about high-throughput DNA-, RNA and protein-sequencing that gives high resolution information on the identities of the occurring species, their (expressed) metabolic potentials and their (relative) abundances. Yet, the information gained from such meta-omics studies (we consider 16S rRNA gene sequencing to fall under meta-omics) is still relatively limited, as they only provide an indirect view into the metabolic activities of such microorganisms and virtually none about their relationship with the environment and each other. These properties must, in turn, be inferred from the data (see Figure 1 , in which an ecosystem with various interactions between species is depicted). Typically, such data, at best, include metagenomics at different time points, revealing the differences in relative species abundances in the ecosystem. Methods such as stable isotope probing (SIP) (Dumont and Murrell, 2005 ), MAR-FISH (Lee et al., 1999 ) or nano-SIMS (Li et al., 2008 ) can provide additional and independent information on metabolites that are consumed by the various organisms in an ecosystem (He et al., 2012 ). Figure 1 Illustration of the diversity of a microbial ecosystem with various interactions. (A) Is a schematic representation of an ecosystem with interactions among community members and the environment. The small particles are the metabolites, the big particles the community members, the boxes show the different interactions between community members. (B) Shows an example time series data set of the relative biomass abundances in this ecosystem. (C) Shows the real dynamics of the various species of the ecosystem in time. The mechanisms behind the dynamics cannot be captured by metagenomics time series data alone. Inferring the metabolic activities of the species in a microbial community from the molecular data is largely an open problem in the field (Myrold et al., 2014 ). The huge challenge that microbial ecologists currently face is therefore how to infer the community state, i.e., the values of all the metabolite concentrations, species abundances and microbial activities (see also Glossary and below) from experimental data. A key question is therefore to determine what can and cannot be inferred from only metagenomic data and knowing this, what additional experimental measurements and computational methods are required to get a more complete understanding of a microbial ecosystem. This challenge is to a large extent solved for single species where systems biology has delivered many methods for inference, data integration, and predictive modeling. These methods have become useful tools in more applied fields such as synthetic biology and metabolic engineering. Similarly, experimental methods such as MFA (see Glossary) (Toya and Shimizu, 2013 ) [e.g., isotopomer based (see Glossary) (Nöh et al., 2006 )] and metabolomics (Wisselink et al., 2010 ) can be used to identify active metabolism of single species. Genome-based and genome-scale metabolic reconstructions can be used to integrate such data and help to understand and predict phenotypes of a microbial species (Bordbar et al., 2014 ; Long and Antoniewicz, 2014 ). The question is to what extent these existing quantitative and computational approaches can be applied to microbial communities; several reviews and perspectives (Röling et al., 2010 ; Zengler and Palsson, 2012 ; Röling and Van Bodegom, 2014 ) pointed out the need for a more quantitative and systems based approach that can be used to understand microbial communities. In this contribution we will focus on the subsequent step: how to deal with quantitative data on ecosystem level? Our approach will be to investigate whether methods developed for monocultures, such as inference and quantitative modeling, are at all applicable for use in microbial ecosystems. The single species methods we will describe have all been developed for the analysis of, and are therefore focused on, metabolism. One must therefore ask whether the microbial community state is dominantly shaped by metabolism-driven factors or whether it is also significantly dependent on factors unrelated to metabolism? One could distinguish two major classes of interactions between community members and the environment: those dictated by social traits and those driven by metabolism. We postulate that in many relevant cases, the metabolic component of the community is dominant. For instance, in glucose-fed biogas reactors the dominant species are all involved in the process of the metabolic conversion of glucose to methane (Fernandez et al., 2000 ). Many species-species interactions are metabolically driven, such as cross-feeding, nutrient competition, and predator-prey relations. All such metabolic processes account for mass flow through the ecosystem and the concomitant growth and turnover of microorganisms and metabolite levels. However, communities are not solely structured by metabolic interactions. The non-metabolic interactions we exclude are social traits such as chemical warfare, bacteriocin production, quorum sensing, and other cell-to-cell interactions (either direct attachment, or other signaling mechanisms). We cannot exclude that social traits may play an important role in specific cases. Phages, for instance, can shape and alter whole ecosystems (Fuhrman, 1999 ), yet this important type of interaction cannot be covered by metabolism-based models. On the other hand, interactions such as quorum sensing also play a role in mono-cultures of Escherichia coli and Pseudomonas aeruginosa , however, model simulations suggests that quorum sensing has a minor effect on the phenotype of those single species (Oberhardt et al., 2008 ; Orth et al., 2011 ). We will argue that limited quantitative experimental data, when combined with coarse-grained metabolic models, will be able to help researchers infer the community structure, i.e., the topology of species interactions (see Glossary for our definition of these often loosely defined terms). What do we mean by coarse-grained models? Basically, reduced complexity of the model. There are several ways to coarse-grain models, but in general it involves either ignoring parts of the system that are deemed less relevant, or lumping of many details of a subsystem into a higher-order description of that subsystem. A whole metabolic pathway can be lumped into one enzymatic reaction; the growth of a cell can be described by one Monod-type equation; a group of organisms can be summarized as one ecotype with an archetypical metabolic profile (“acetate consumer”). Such coarse-grained models can be gradually increased in detail over time. Parallel to these coarse-grained models, genome-scale metabolic models can be used as data repositories where new data and constraints are imposed on the models. These two approaches should in the end converge into the same description of the community. We will provide an example to illustrate how the combination of these approaches could aid in improving mechanistic understanding of microbial communities."
} | 2,880 |
31658297 | PMC6816544 | pmc | 3,325 | {
"abstract": "Plant-pollinator networks have been repeatedly reported as cumulative ones that are described with >1 years observations. However, such cumulative networks are composed of pairwise interactions recorded at different periods, and thus may not be able to reflect the reality of species interactions in nature (e.g., early-flowering plants typically do not compete for shared pollinators with late-flowering plants, but they are assumed to do so in accumulated networks). Here, we examine the monthly sampling structure of an alpine plant-pollinator bipartite network over a two-year period to determine whether relative species abundance and species traits better explain the network structure of monthly networks than yearly ones. Although community composition and species abundance varied from one month to another, the monthly networks (as well as the yearly networks described with annual pooled data) had a highly nested structure, in which specialists directly interact with generalist partners. Moreover, relative species abundance predicted the nestedness in both the monthly and yearly networks and accounted for a statistically significant percentage of the variation (i.e., 20%-44%) in the pairwise interactions of monthly networks, but not yearly networks. The combination of relative species abundance and species traits (but not species traits only) showed a similar prediction power in terms of both network nestedness and pairwise interaction frequencies. Considering the previously recognized structural pattern and associated mechanisms of plant-pollinator networks, we propose that relative species abundance may be an important factor influencing both nestedness and interaction frequency of pollination networks.",
"introduction": "Introduction In theory, every species within a biological community can directly or indirectly interact with every other species to form a complex ecological network. Studies have shown that ecological networks are often endowed with distinct and repeated patterns [ 1 , 2 ] that are functionally significant. For example, the structure of mutualistic networks has been demonstrated to be associated with long-term species coexistence, community diversity and stability [ 3 , 4 ]. Thus, accurately identifying network pattern and exploring the mechanisms by which it forms are essential to understanding the ecological dynamics of communities [ 5 , 6 ]. Plant-pollinator networks generally have a nested architecture, wherein specialist pollinators interact directly with generalist plants and vice versa [ 1 ]. Nested pollination networks are mostly explained by species traits (a niche process) and relative abundance (a neutral process), as noted in a number of studies [ 7 – 9 ]. Species trait- matches or mismatches have been hypothesized and demonstrated to be the mechanism by which pairwise interactions can or cannot arise [ 9 , 10 ]. Because variation in species composition is not necessarily consistent between plants and pollinators (e.g., plant species composition may remain similar while pollinator species composition may change dramatically between or among successive years [ 11 – 13 ]), relative species abundance has been also frequently suggested to be responsible for the nested structure of a network [ 11 , 13 ] and even responsible for the species-pairwise relationships of pollination networks [ 8 , 14 ]. Nevertheless, despite the success of predicting the nested architecture of pollination networks [ 13 , 15 – 17 ], relative species abundance explains very little of the frequency of species pairwise interactions in pollination networks [ 18 – 21 ]. Even in the models incorporating phenology and species traits, it cannot successfully predict the interaction frequencies of pollination networks [ 8 , 9 , 19 ]. One of the potential causes responsible for the unsuccessful prediction of interaction frequencies is that pollination networks are often described with data accumulated over several consecutive years (because flowering plants and pollinators are highly dynamic with large temporal variation in species composition and abundance). For example, Price et al. (2005) surveyed flower visitors over seven summers in a montane habitat [ 18 ]; Fang and Huang (2012) examined pollination networks over four consecutive years in an alpine meadow [ 21 ]; Chacoff et al. (2018) investigated plant-pollinator networks over six consecutive years in a Monte Desert ecoregion [ 14 ]. Unfortunately, using pooled data may not be able to reflect the reality of species interactions [ 22 ]. For example, early-flowering plants do not necessarily compete for shared pollinator species with late-flowering plant species if their flowering phenologies do not overlap [ 23 ]. Such a plant-plant competition (for shared pollinators) within cumulative pollination networks does not exist in biological reality, and instead they may positively interact, e.g., an early flowering species can provide resources for multivoltine pollinators that pollinate late-flowering species. Importantly, such an error may raise problems in models incorporating phenology as long as accumulative networks are used. For example, if early-season plant species are much more abundant than the late-season ones, models would predict an extremely low frequency for the interaction between the late-season species and their shared pollinators. This prediction could be wrong if the shared pollinators are more abundant in late seasons and hence the late-season plant species could be more frequently pollinated. Thus, networks described with short term data should be examined to determine whether relative species abundance may account for nestedness and pairwise interactions in pollination networks [ 24 ]. Here, we investigated the plant and pollinator assemblages and their pairwise monthly interactions during two growing seasons in a Tibetan alpine meadow. The primary objective of this study is to determine whether relative species abundance together with species traits can better predict the structure of monthly pollination networks than yearly ones. Specifically, we determined whether these networks were consistently nested for both monthly and yearly networks and tested whether relative species abundance and species traits could predict the nestedness and pairwise interactions of pollination networks. We also calculated the frequency of pairwise interactions for both monthly and yearly networks and asked whether relative species abundance and species traits significantly accounted for the variation in the interaction frequency. As noted, we hypothesized that relative species abundance and species traits would be better predictors for the interaction frequency of monthly networks than yearly ones.",
"discussion": "Discussion Our data show that community species composition consistently changes during the growing season, indicating that pairwise interactions and associated pollination networks varied among months and between years. However, the pollination network manifested a nested structure in each month and each year. Moreover, consistent with our hypothesis, relative species abundance (RSA), as well as the combination of RSA and species traits, was a good predictor of network nestedness. In addition, RSA partly but significantly explained the interaction frequency of monthly networks (albeit not for the whole growing season), with a higher explanation efficiency than the combination of RSA and species traits. The constant nestedness of monthly and yearly (accumulative) pollination networks is consistent with a number of previous studies addressing mutualistic networks [ 1 , 14 , 21 , 39 ] showing that nestedness is a structural property regardless of species composition and the configuration of pairwise interactions. It is possible that many configurations of pairwise interactions may give the same value of ‘nestedness’ and ‘weighted NODF’ in the network metrics. Some studies have successfully predicted nestedness but not pairwise interactions [ 8 – 9 , 40 ]. The success of RSA predicting nestedness may be attributable to the fact that the effect of RSA overrides that of species composition. We have observed that plant species differ significantly from month to month, whereas pollinator species are similar between months, particularly in July and August. Consistently, the monthly difference is greater in plant traits than pollinator traits. Yet, networks manifest highly nested structures in all months. The mechanism underlying the effect of RSA on nestedness could be simply because of the right-skewed frequency distribution of relative species abundance of both plants and pollinators ( S1 Table ), which should lead to nested networks according to the neutral process hypothesis [ 12 , 13 , 15 , 23 , 24 ]. Nevertheless, the RSA alone overpredicted nestedness for all the monthly and yearly networks, as indicated by Canard et al. (2014) who showed that RSA overestimated nestedness and failed to predict the natural variation of nestedness values [ 15 ]. Indeed, the combination of RSA and species traits also predicted the network ‘nestedness’ and ‘weighted NODF’ than species traits. Moreover, species traits alone significantly explained the qualitative network ‘nestedness’, further indicating the contribution of species traits to network structural properties. RSA significantly explained part of the variation in the interaction frequency of monthly networks, but not the yearly (accumulative) networks. This is presumably because the monthly networks reflected the biological reality more than the yearly ones. Monthly networks describe short-period interactions, within which plants and pollinators are active at the same time and hence likely to create strong pairwise interactions, reflecting biological reality in nature. In contrast, yearly networks are described using accumulated data including the plants and pollinators that might not be active at the same time and thus often fail to correctly predict the frequency of pair-wise interactions (see Introduction ). Incorrect estimates can be large because some pollinators (e.g., bumblebees, Apis mellifera , and Peleteria iterans ) are often active and can pollinate plants in different months. The problem can negatively affect the relationship between plants and pollinators in the yearly networks. As a test, we calculated the RSA of the pollinators based on the sum of observations and determined the predictive power of RSA regarding interaction frequency. We found that this RSA could not significantly predict the frequency of pairwise interactions for the yearly networks ( Fig 3 ). Indeed, modelling has demonstrated that RSA is a poor indicator for the interaction frequency of cumulative pollination networks, although it can predict network nestedness [ 9 , 38 , 41 , 42 ]. It is worth noting that RSA explained only a small part of variation in the interaction frequency of the monthly networks. This is probably because including RSA only (while neglecting niche process) overpredicts the opportunity of forming a pairwise interaction [ 43 ]. It is worthwhile to note that species traits showed little power to predict the pairwise interaction frequencies. This is perhaps because biological constraints (species trait mismatch) are not crucial to the formation of most pairwise interactions (except for few; e.g. Bombus friseanus primarily visiting Pedicularis spp.). For example, most of the plant species belonging to Compositae and Ranunculaceae are not highly specialized to particular pollinator species but are able to be visited by many different pollinator species with varying leg lengths. To this end, the species trait effect could be overridden by the RSA effect on pairwise interaction frequencies, as indicated by the fact that the RSA effect alone was comparable with the combination of RSA and species traits and much greater than the species trait effect that proved non-significant. Nevertheless, species traits could be more powerful for the prediction of the network structure, if important traits like pollen presentation pattern, flower dimensionality, accessibility of nectar, and flower orientation [ 16 ] had been included in this study. In summary, we have demonstrated that both monthly and yearly networks have nested structures. Incorporating this finding in those of numerous previous network studies indicates that nestedness is widespread in pollination networks. Moreover, our data clearly show that RSA but not species traits can significantly account for the variation in the interaction frequency of monthly networks and is more accurate in predicting interaction frequency in comparison to yearly networks. Thus, describing and evaluating short-term networks may be preferable in further network analyses. Additionally, the importance of RSA to network structure as revealed in this study motivates us to speculate that RSA may not simply affect the frequency by which specific plant-insect interact, but also possibly serves as a selective force for both plants and pollinators to form pairwise interactions if their abundance is evolutionarily stable."
} | 3,295 |
29553156 | null | s2 | 3,327 | {
"abstract": "Here we demonstrate a 3D-printable microvalve that is transparent, built with a biocompatible resin, and has a simple architecture that can be easily scaled up into large arrays. The open-at-rest valve design is derived from Quake's PDMS valve design. We used a stereolithographic (SL) 3D printer to print a thin (25 or 10 μm-thick) membrane (1200 or 500 μm-diam.) that is pneumatically pressed (∼3-6 psi) over a bowl-shaped seat to close the valve. We used poly(ethylene diacrylate) (MW = 258) (PEG-DA-258) as the resin because it yields transparent cytocompatible prints. Although the flexibility of PEG-DA-258 is inferior to that of other microvalve fabrication materials such as PDMS, the valve benefits from the bowl design and the membrane's high restoring force since it does not need a negative pressure to re-open. We also 3D-printed a micropump by combining three Quake-style valves in series. The micropump only requires positive pressure for its operation and profits from the fast return to the valves' open states. Moreover, we printed a 64-valve array constructed with 500 μm-diam. valves to demonstrate the reliability and scalability of the valves. Overall, we demonstrate the 3D-printing of compact microvalves and micropumps using a process that precludes the need for specialized, time-consuming labor."
} | 330 |
28758093 | null | s2 | 3,328 | {
"abstract": "Harvester ant colonies adjust their foraging activity to day-to-day changes in food availability and hour-to-hour changes in environmental conditions. This collective behavior is regulated through interactions, in the form of brief antennal contacts, between outgoing foragers and returning foragers with food. Here we consider how an ant, waiting in the entrance chamber just inside the nest entrance, uses its accumulated experience of interactions to decide whether to leave the nest to forage. Using videos of field observations, we tracked the interactions and foraging decisions of ants in the entrance chamber. Outgoing foragers tended to interact with returning foragers at higher rates than ants that returned to the deeper nest and did not forage. To provide a mechanistic framework for interpreting these results, we develop a decision model in which ants make decisions based upon a noisy accumulation of individual contacts with returning foragers. The model can reproduce core trends and realistic distributions for individual ant interaction statistics, and suggests possible mechanisms by which foraging activity may be regulated at an individual ant level."
} | 293 |
39506750 | PMC11542441 | pmc | 3,330 | {
"abstract": "NorR, as a single-target regulator, has been demonstrated to be involved in NO detoxification in bacteria under anaerobic conditions. Here, the norR gene was identified and deleted in the genome of Vibrio alginolyticus . The results showed that deletion of norR in Vibrio alginolyticus led to lower swarming motility and more biofilm formation on aerobic condition. Moreover, we proved that NorR from E. coli had a similar function in controlling motility. NorR overexpression led to increased resistance to oxidative stress and tetracycline. We also observed a reduced ability of the NorR-overexpressing strain to adapt to iron limitation condition. Transcriptome analysis showed that the genes responsible for bacterial motility and biofilm formation were affected by NorR. The expressions of several sigma factors (RpoS, RpoN, and RpoH) and response regulators (LuxR and MarR) were also controlled by NorR. Furthermore, Chip-qPCR showed that there is a direct binding between NorR and the promoter of rpoS . Based on these results, NorR appears to be a central regulator involved in biofilm formation and swarming motility in Vibrio alginolyticus . Supplementary Information The online version contains supplementary material available at 10.1186/s12915-024-02057-y.",
"conclusion": "Conclusions In Vibrio alginolyticus , NorR, as a central regulator, can regulate various sigma factors, transcriptional regulators, and functional genes to affect related phenotypes, including biofilm formation, swarming motility, and oxidative stress defense. The results indicate that the single-target regulator may have more functions in bacteria than previously thought and further study is needed to reveal the details about its regulatory mechanism.",
"discussion": "Results and discussion A NorR regulator identified in the genome of Vibrio alginolyticus In both the environment and during host infection, Vibrio alginolyticus can encounter various stresses. In our previous study, it was found that a norR gene (AT730_RS23565) was upregulated in Vibrio alginolyticus under oxidative stress [ 24 ], which attracted our attention, since most of the studies on NorR have focused on its regulatory function in NO detoxification. Here, bioinformatics analysis was performed, and it was shown that the NorR protein from Vibrio alginolyticus shared 59% similarity with that from E. coli . It also has the GAF, AAA, and HTH domains (Fig. 1 A), and these all contain four conserved binding sites related to ATP hydrolysis and synthesis (ATP binding, Walker A motif containing conserved sequences GxxxxGK [ST], Walker B motif and arginine finger). Moreover, the norVW gene, which is regulated by NorR, is also located next to the norR gene in the genome (Fig. 1 B). Fig. 1 Comparison of NorR between Vibrio alginolyticus and Escherichia coli . A Alignment of protein sequence of NorR. The conserved amino acids were shown in red color. The domain is positioned at the appropriate position. B The location of NorR gene NorR is involved in oxidative stress defense, TC resistance, and growth under iron limitation condition To demonstrate the function of NorR in Vibrio alginolyticus , the norR gene was deleted in the genome, and also norR was overexpressed by plasmid in the cell as mentioned above. The strains were confirmed by PCR and qRT–PCR (Additional file 1. Fig. S1). The results showed that the expression of norVW was significantly downregulated in the NorR deletion strain (Fig. 2 A), and the expression levels of norR and norVW were increased significantly in Vibrio alginolyticus upon exposure to NO stress (Fig. 2 B), which indicates that NorR in Vibrio alginolyticus also has the function to regulate norVW . Afterwards, phenotype analyses were performed and showed that overexpressing NorR in Vibrio alginolyticus had no effect on its growth but resulted in more resistance to oxidative stress and TC (tetracycline) (Fig. 3 A, C, D). We also observed a reduced ability of the NorR-overexpressing strain to adapt to iron limitation conditions (Fig. 3 B). Moreover, a significant decrease in its ability of ECPase (extracellular proteases) was observed by overexpressing NorR (Fig. 3 E). These results suggest that NorR may have more regulatory functions in bacteria than previously thought. Fig. 2 qRT-PCR analysis of transcriptional levels of genes from cells under NO stress conditions. The error bars indicate the standard deviation from the mean of biological triplicates with 2 technical replicates. A The relative mRNA levels of NO stress-related genes were detected in ΔnorR compared with that in wild type under NO stress. B The relative mRNA levels of NO stress-related genes were detected in wild type under NO stress compared with that without stress. The results are normalized to the control gene 16S rDNA using the 2 −ΔΔCt method. ** indicates a highly significant change ( P ≤ 0.01) according to Students t -test, * indicates a significant change ( P ≤ 0.05) according to Students t -test. ns P > 0.05, t -test Fig. 3 Phenotype analysis. The growth of different strains under normal condition ( A ) and iron deficiency stress condition ( B ) 10 μmol of sodium nitroprusside dihydrate was used to make NO stress condition. The oxidative stress resistance ( C ), tetracycline resistance ( D ), and ECPase production ( E ) of wild type, ΔnorR, C-ΔnorR, and Val/pMMB207-norRVal strains. 1 μmol of 30% H 2 O 2 generate oxidative stress and 5 mg/mL tetracycline was spotted onto the plate. ** indicates a highly significant change ( P ≤ 0.01) according to Students t -test, * P ≤ 0.05, ns P > 0.05 Deletion of NorR results in higher swarming motility and less biofilm formation Interestingly, our study showed that deletion of NorR leaded to higher swarming motility under aerobic condition, which was confirmed by the NorR-overexpressing strain resulting in lower swarming motility (Fig. 4 A). This result raises the question of whether NorR in E. coli has the same function. To answer this question, NorR from Vibrio alginolyticus was overexpressed in E. coli , and NorR from E. coli was overexpressed in both E. coli cells and Vibrio alginolyticus cells. NorR from E. coli was able to regulate swarming motility of E. coli and Vibrio alginolyticus (Fig. 4 B), which indicates that NorR can regulate motility in various bacteria. Furthermore, we found that less biofilm formation was observed in the NorR deletion strain, as shown in Fig. 5 A. By using SEM, the bacterial morphology was examined, as depicted in Fig. 5 B-a, d. It was observed that the WT bacteria exhibited a short rod-shaped form with extracellular products adhering to the surface. In contrast, the ΔnorR bacteria displayed a short rod-shaped form but with a relatively smooth surface and no attached extracellular products. Further, upon local examination of the biofilm (Fig. 5 B-b, e), the WT on the biofilm surface exhibited close bonding, with extracellular products forming connections between bacterial cells. On the other hand, the ΔnorR formed a loosely adhered bacterial layer on the biofilm surface, which appeared smooth and lacked extracellular products. Finally, in the overall view of the biofilm (Fig. 5 B-c, f), the biofilm formed by the WT showcased a compact structure with a substantial presence of extracellular products on the surface. In contrast, the biofilm formed by the ΔnorR appeared relatively loose, with a notable gap between bacteria. Exopolysaccharide as a main product in biofilm. Here, it was found the amount of exopolysaccharide was slightly less produced by NorR deletion strain by using Congo red agar plate [ 25 ] (Additional file 1. Fig. S2). The biofilms were also observed by fluorescent microscopy by using the Live/Dead BacLight Viability kit (Molecular Probes) according to the protocol provided [ 26 ]. The result confirmed that deletion of NorR resulted in less biofilm formation (Additional file 1. Fig. S3). It has been reported that NO is able to increase the bacteria motility and decrease the biofilm formation by affecting the content of cyclic di-GMP [ 27 , 28 ]. In this study, the NO level in the cell was undetected during biofilm formation, may due to the bacteria was cultured on aerobic condition. Moreover, the content of cyclic di-GMP with no change was observed in NorR deletion strain, which indicates the less amount of biofilm of NorR deletion strain was not caused by NO. Fig. 4 NorR negatively regulated swarming motility of Vibrio alginolyticus and Escherichia coli . A Analysis of swarming motility of Vibrio alginolyticus . B Assays of swarming motility of NorR overexpression in Vibrio alginolyticus and Escherichia coli . *** indicates a highly significant change ( P ≤ 0.001) according to Students t -test. ** P ≤ 0.01 * P ≤ 0.05, ns P > 0.05 Fig. 5 NorR positively regulates biofilm formation. A Assays of biofilm formation of wild type, ΔnorR, C-ΔnorR, and Val/pMMB207-norR Val strains. Biofilm formation in petri dish contain LB medium after 48 h of culturing was assayed. *** indicates a highly significant change ( P ≤ 0.01) according to Students t -test. * P ≤ 0.05, ns P > 0.05. B Scanning electron micrographs. Wild type and ΔnorR (× 50,000, × 8000, × 2000 magnification) NorR, as a transcriptional regulator, has been reported to activate NO detoxification in various bacteria, including those of the Vibrio genus. However, its other regulatory functions have not been thoroughly investigated. Here, NorR was found to have various functions in Vibrio alginolyticus , including those related to bacterial swarming motility, biofilm formation, oxidative stress defense, and TC resistance, which led us to suspect that the single-target regulator may have more functions than previously thought. Overall, this is the first study to show that NorR has a regulatory function in swarming motility and biofilm formation in addition to NO detoxification in bacteria. Transcriptome analysis showed that genes involved in bacterial motility and biofilm formation were affected by NorR To reveal the effect of NorR on gene expression in Vibrio alginolyticus , transcriptome analysis was performed by using the NorR overexpression strain and wild type as control. The results showed that the expression of 1285 genes were affected (569 genes with high expression levels, log2-fold change ≥ 0.5 and 716 genes with low expression levels, log2-fold change ≤ − 0.5) by overexpressing NorR in Vibrio alginolyticus (Fig. 6 A, B). Several genes were selected, and qRT-PCR was performed to confirm the reliable of transcriptome data (Additional file 1. Fig. S4). The transcriptome data showed that the genes involved in bacterial motility, including flhB , fliQ , fliP , fliS , motB , pomA , fliR flgN , and lafA , were downregulated (Fig. 6 B). The flagellum consists of the hook, matrix, and filament. Its motor requires MotB and PomA, which are involved in providing proton channels and ion channels [ 29 ]. FliP, FliR, FliQ, and FlhB are mainly involved in matrix-related protein synthesis [ 30 ]. FliP and FliR are able to protect hook-associated proteins from degradation [ 31 ]. FlgN is considered a secretion chaperone for hook-associated proteins [ 32 ]. The lower expression of these genes may have resulted in less flagellar formation, and thus, bacterial swarming motility was decreased. Fig. 6 The regulon of NorR assessed using RNA-seq. A A volcano plot was generated to visualize the differentially expressed genes in Val/pMMB207-norR Val . The x -axis represents the log2 of the fold change plotted against the − log10 of the adjusted false discovery rate. Red and green points indicate the up- and downregulated genes, respectively. B Map of gene expression difference. Orange and blue circle indicate the up- and downregulated genes, respectively Moreover, the genes responsible for biofilm formation were also affected by NorR, including the genes encoding outer membrane beta-barrel protein (AT730_RS20360 and AT730_RS23660), polysaccharide biosynthesis tyrosine autokinase (AT730_RS23650 and AT730_RS22660), polysaccharide export protein (AT730_RS23655), glgA , and the T6SS genes ( tssH , tssE , tssF , tssG , tssK , tssJ , tssM , vgrG , hcp , etc.), which were upregulated by NorR overexpression (Fig. 6 B). In gram-negative bacteria, outer membrane beta-barrel protein is synthesized in the cytoplasm and transported to the outer membrane [ 33 ], which is the outlet for secreted glycans and thus controls biofilm formation [ 34 ]. Glycogen/starch/alpha-glucan phosphorylase and glycogen synthase GlgA are capable of synthesizing glycogen, which is important for biofilm formation [ 35 ]. The synthesis of exopolysaccharide (ESP) requires polysaccharide biosynthesis by tyrosine autokinase [ 36 ], and polysaccharide export proteins play a role in the export of polysaccharides via the outer membrane in gram-negative bacteria [ 37 ], which can improve the formation of biofilms. The T6SS provides a competitive edge in biofilm formation, enabling strains with more effectively establish and sustain their presence within the biofilm by exporting eDNA [ 38 ]. NorR served as a potential central regulator involved in biofilm formation and motility in Vibrio alginolyticus Interestingly, the expressions of several sigma factors (RpoS, RpoN, RpoH) and transcription regulators (MarR and LuxR) were affected by NorR overexpression (Fig. 6 B). The rpoS , rpoN , and luxR mRNA levels were increased by overexpressing NorR, indicating NorR can positively regulate their expressions in Vibrio alginolyticus and rpoH and marR expressions were down regulated by NorR. According to previous results, NorR from E. coli and Vibrio alginolyticus had similar regulatory functions on NO detoxification and bacterial swarming motility, suggesting that the DNA-binding site may be conserved of NorR between E. coli and Vibrio alginolyticus ; therefore, the conserved DNA-binding motif “GT-(N7)-AC” was used to search the promoter regions of genes positively affected by NorR in Vibrio alginolyticus [ 39 ]. The conserved binding motif was identified in the promoter of norVW , and there was also a binding site located in the promoter region of rpoS (− 28 to − 18 and − 150 to − 140), which indicates that NorR could positively regulate RpoS expression by directly binding. The conserved binding motif was also identified in the promoter of rpoN (− 13 to − 3 and − 187 to − 177) and luxR (Additional file 1. Fig. S5). This suggest that NorR has the potential of binding to the promoters of several sigma factors. ChIP-qPCR experiments with a flag-tagged NorR, which was overexpressed in the norR deletion strain were performed (Additional file 1. Fig. S6). The results revealed a 5.5- and 4.88-fold enrichment of NorR binding at the promoters of rpoS and norVW , respectively, but not at rpoN , luxR , and also rpoH , proving that NorR can directly bind to the promoter of rpoS to positively regulate its expression in Vibrio alginolyticus (Fig. 7 ). Fig. 7 CHIP experiments were followed qPCR to determine the relative enrichment of promoters bound to NorR. The results were calculated by ΔΔC T method. * P ≤ 0.05, *** P ≤ 0.001, ns P > 0.05, t -test As shown above, NorR is mainly involved in biofilm formation and swarming motility by regulating the expression of various functional genes and the sigma factors RpoS and RpoH as well as RpoN and the response regulators LuxR and MarR, indicating NorR seems to be a central regulator in Vibrio alginolyticus . It has been shown that RpoS which was directly controlled by NorR could reduce the motility of Vibrio anguillis by an unknown mechanism [ 40 ]. Moreover, RpoS can activate tssB expression to improve biofilm formation [ 41 ]. Peroxidase KatG, whose expression is controlled by RpoS in Vibrio parahaemolyticus , was upregulated in the NorR-overexpressing strain, results in improving its ability to resist oxidative stress [ 42 , 43 ]. RpoN is required for the synthesis of flagella and is widely distributed in Vibrio parahaemolyticus , Vibrio alginolyticus , and Pseudomonas aeruginosa [ 44 , 45 ]. RpoN is able to upregulate the expression of T6SS genes ( vgrG , hcp ) and is presumed to mediate biofilm formation [ 46 , 47 ]. It has been shown that RpoN deletion can lead to increased RpoS expression in E. coli [ 48 ]. RpoH is a significant heat shock response regulator controlled by NorR, which can also negatively affect the expression of related motility genes [ 49 ] (Fig. 8 ). Fig. 8 The regulatory network of NorR in Vibrio alginolyticus . NorR affects the expression of sigma factors and transcriptional regulators to control the swarming motility and biofilm formation of Vibrio alginolyticus In E. coli , overexpressing OmpA leads more biofilm formation [ 50 ], which is regulated by NorR via an unknown mechanism. LuxR as a master regulator can positively regulate biofilm formation in Vibrio [ 46 , 51 ]. The MarR family regulator is able to repress the expression of related RTX adhesion results in less biofilm formation [ 52 , 53 ], and its expression was also affected by NorR in an unknown way (Fig. 8 ). Additionally, flagellum-related genes such as flhB , fliQ , fliP , fliS , motB , pomA , fliR flgN , and lafA were significantly downregulated by NorR via an unknown mechanism."
} | 4,378 |
36079948 | PMC9457562 | pmc | 3,332 | {
"abstract": "Piezoelectric energy harvesters are appealing for the improvement of wearable electronics, owing to their excellent mechanical and electrical properties. Herein, screen-printed piezoelectric nanogenerators (PENGs) are developed from triethoxy(octyl)silane-coated barium titanate/polyvinylidene fluoride (TOS-BTO/PVDF) nanocomposites with excellent performance based on the important link between material, structure, and performance. In order to minimize the effect of nanofiller agglomeration, TOS-coated BTO nanoparticles are anchored onto PVDF. Thus, composites with well-distributed TOS-BTO nanoparticles exhibit fewer defects, resulting in reduced charge annihilation during charge transfer from inorganic nanoparticles to the polymer. Consequently, the screen-printed TOS-BTO/PVDF PENG exhibits a significantly enhanced output voltage of 20 V, even after 7500 cycles, and a higher power density of 15.6 μW cm −2 , which is 200 and 150% higher than those of pristine BTO/PVDF PENGs, respectively. The increased performance of TOS-BTO/PVDF PENGs is due to the enhanced compatibility between nanofillers and polymers and the resulting improvement in dielectric response. Furthermore, as-printed devices could actively adapt to human movements and displayed excellent detection capability. The screen-printed process offers excellent potential for developing flexible and high-performance piezoelectric devices in a cost-effective and sustainable way.",
"conclusion": "4. Conclusions A flexible and high-performance nanocomposite PENG based on a TOS-BTO/PVDF composite film was fabricated via screen printing. An organic TOS functional group in the polymer matrix assists in the uniform dispersion of nanoinorganic fillers. The degree of charge annihilation that occurs during the charge transfer from inorganic particles to the polymer matrix is reduced in the composites. As a result, the TOS-modified BTO/PVDF pressure sensor exhibited a noticeable increase in the output voltage (20 V) and output power density (15.6 μW cm −2 ), which were considerably higher than those of the pristine BTO/PVDF counterpart. These findings demonstrate the importance of the surface modification of inorganic nanofillers implanted in PENGs. These gadgets may also be used to actively detect human movements because of their high flexibility and sensitivity when manufactured on demand. These screen-printed PENGs demonstrate potential as future touch sensors manufactured using additive manufacturing processes in printed electronics applications.",
"introduction": "1. Introduction Printing technology has rapidly advanced owing to the increasing demand for printed electronics, which use analog or digital printing technologies to print electrical circuits or devices [ 1 , 2 , 3 , 4 ]. The development of printed electronics on flexible substrates has the potential to fundamentally change the way of manufacturing electrical devices. Emerging electronic technologies involving new material synthesis, unique device concepts, new functionality, and new manufacturing processes have revolutionized the microelectronics sector, which traditionally focused on silicon and microfabrication techniques [ 5 , 6 , 7 , 8 , 9 ]. Owing to the increase in the number of printing-based electronic devices, several semiconductors, and conductive and dielectric materials have been produced as inks for various printing processes [ 10 , 11 , 12 ]. Electroactive polymers are among the most promising materials for flexible electronics, and piezoelectric materials are among those that can be printed with promising outcomes [ 13 , 14 ]. Electrical signals generated by piezoelectric materials in response to mechanical stress, vibration, or deformation are receiving increasing research interest [ 15 , 16 ]. This lays the groundwork for its use in wearable electronics, such as sensors, actuators, and energy harvesters [ 17 , 18 , 19 ]. Polyvinylidene fluoride (PVDF) and its copolymers are the most suitable piezoelectric materials for printed sensors and actuators because of their biocompatibility, toughness, lightness, and mechanical adaptability [ 20 , 21 , 22 ]. The viscosity and density of PVDF inks can be tailored to match the printing equipment by solubilizing them in acetone or N , N -dimethylformamide (DMF). Furthermore, PVDF can be printed on a variety of soft substrates, including polyethylene terephthalate (PET) or paper, which are most commonly utilized in sensors [ 23 , 24 ]. In particular, PVDF has five crystal forms: α-, β-, γ-, δ-, and ε-phases [ 25 , 26 , 27 ]. The α-phase is nonpolar, whereas the γ- and δ-phases are weakly polar. Owing to its high polarity, the β-phase exhibits optimal piezoelectric and ferroelectric properties. The β-phase can be obtained via applying a high pressure/electric field [ 28 , 29 ], mechanical stretching [ 30 ], electrospinning [ 31 ], or adding nucleating fillers [ 32 , 33 ]. However, despite the high β-phase concentrations of PVDF and its copolymers, their low piezoelectric coefficients (d 33 values) prevent their application in piezoelectric sensors for wearable electronics. Therefore, inorganic materials, such as lead zirconium titanate (PZT) and barium titanate (BTO), have been employed to fabricate high-performance piezoelectric composites [ 34 , 35 , 36 , 37 ]. However, inorganic nanoparticles are unsuitable for fabricating flexible and high-performance piezoelectric nanogenerators (PENGs) because of their easy agglomeration due to their large surface area and high surface activity [ 38 , 39 ]. In ceramic powders, triethoxy(octyl)silane (TOS) has been extensively utilized as a dispersant for nanoparticle suspensions to increase dispersion. Furthermore, TOS is a low-cost, non-toxic silane with concentrated reactive groups and strong chelating activity [ 40 , 41 ]. Therefore, the TOS modification of BTO nanoparticles may be a promising strategy to improve the piezoelectric performance of ceramic–polymer nanocomposites, facilitate uniform nanoparticle dispersion in the polymer matrix and enhance interfacial compatibility. However, to the best of our knowledge, TOS-modified BTO has not been used to alter the nanoparticle interface or enhance the output performance of PENGs. In this paper, we present a novel screen-printing method for fabricating flexible piezoelectric sensors and energy harvesters using a high-performance TOS-BTO/PVDF composite and silver ink. As all of the inks are non-toxic and use environmentally friendly solvents, the technique promotes long-term large-area sensor technology. To print the ceramic–polymer nanocomposite using a screen printer, we synthesized TOS-modified BTO nanoparticles and distributed them into the PVDF polymer matrix to form a nanocomposite with an appropriate viscosity coefficient. The TOS surface modification agent-induced strong hydrogen bonds with PVDF to form a high β-phase content, thereby resulting in a pronounced performance of the nanocomposites. Therefore, the TOS-BTO/PVDF PENG exhibited a noticeable increase in voltage (20 V) and power density (15.6 μW cm −2 ), which were 200 and 150% higher than those of pristine BTO/PVDF PENGs, respectively. Furthermore, wearable electronics, small-sized energy harvesters, and soft robotics may benefit from the wide variety of functionalities and excellent electromechanical coupling properties of TOS-BTO/PVDF PENGs.",
"discussion": "3. Results and Discussion In order to verify the existence of functional groups in their surface structures, the FTIR spectra of the TOS-BTO nanoparticles were obtained using an FTIR spectrometer with a measurement range of 4000–500 cm −1 . FTIR spectra of the pristine BTO nanoparticles were also obtained using the same procedure for comparison. The FTIR spectra of BTO and TOS-BTO nanoparticles are shown in Figure 2 a. For the pristine BTO nanoparticles, a distinctive Ti–O vibration peak was located at 529 cm −1 . In addition, the FTIR spectra did not reveal any further absorption peaks. However, the characteristic peak of the TOS group on the BTO nanoparticles was observed in the FTIR spectra. The absorption peaks that emerged at 2941 and 2840 cm −1 were attributed to the stretching vibration of C–H bonds in the form of -CH 2 - and -CH 3 groups of the TOS-BTO nanoparticles, respectively. Therefore, the presence of these two peaks indicates that nanoparticle surfaces have been grafted with the TOS long carbon chain [ 40 ]. Compared to pristine BTO nanoparticles, particle sedimentation was not observed in the polymer matrix solution containing TOS-BTO particles, even after 10 d, as shown in Figure 2 b. Therefore, the interaction between the long carbon chain of TOS in the polymer matrix and BTO nanoparticles presumably increases the nanoparticle dispersion and stability in the polymer solution. This is one of the most significant challenges faced by traditional compositing techniques, and it is crucial to ensure the possibility of industrial use with long-term storage. The good printing properties of composite inks with acceptable rheological characteristics may result in thinner lines with smoother edges and be useful in eliminating flaws and bubbles in the printed patterns. A plate–plate rheometer was used to explore the effects of BTO nanoparticle concentration and surface modification characteristics on the rheological behavior of PVDF-based composite inks. Viscosity was determined at various shear rates throughout the steady-state flow step test, as illustrated in Figure 3 a. The viscosity of the ink decreased as the shear rate increased, which is characteristic of pseudoplastic fluids. Furthermore, PVDF-based composite inks with higher BTO nanoparticle contents exhibited higher viscosities at the same shear rate owing to the increased degree of aggregation against the dispersion of BTO nanoparticles. In addition, PVDF-based composite inks with surface-modified TOS-BTO nanoparticles displayed lower viscosities at the same shear rate compared to their counterparts with unmodified BTO nanoparticles, owing to the reduced degree of aggregation. The thixotropic properties of the PVDF-based composite inks were examined by retaining the ink at varying shear rates in the three phases, as illustrated in Figure 3 b. Viscosity recovery after the initial squeeze stroke was investigated using three separate stages of shear. The first, second, and final stages had shear rates of 0.5, 5, and 0.5 s −1 , respectively, for 30 s. Viscosity recovery to the first stage, which describes ink elasticity, may impact ink leveling and line creation. A strong hysteresis impact on the viscosity of PVDF-based composite inks was detected when the shear rate increased and decreased, implying that once the shear forces were eliminated, the ink was appropriately leveled in a short time (a few seconds). As a result, the rheological properties of the ink combinations provide effective ink filling and leveling in the empty regions during printing. We then determined that the BTO nanoparticles were distributed in the printed composite films using FESEM. Figure 4 a,b show the surface morphology of the nanocomposites with various quantities of TOS-BTO or BTO nanoparticles in the PVDF polymer matrix. The nanoparticles are uniformly and homogeneously distributed in the polymer matrix when 10% BTO and TOS-BTO nanoparticles are employed, as shown in Figure 4 a,b. However, when 20 wt% nanoparticles were used, there were considerably more differences in the surface morphology between the BTO/PVDF and TOS-BTO/PVDF composite films. Figure 4 d shows that the nanoparticles were uniformly distributed in the PVDF matrix, with no apparent interface hole defects or fractured sections of the material, whereas Figure 4 c shows the pristine BTO/PVDF counterpart with many holes and aggregated clusters. The hydrogen bonding of the –CF in the PVDF polymer matrix and the characteristics of –CH on the TOS-BTO nanoparticles may explain these phenomena, which improve the phase compatibility of the nanocomposites during mixing and reduce the contact interface hole defects in ceramic–polymer nanocomposites. The β-phase content determines the piezoelectricity of PVDF. The crystalline phase composition of the as-prepared samples was investigated using XRD to validate the changes in the phase composition of PVDF. Figure 5 a shows the XRD patterns of the as-printed nanocomposites with different BTO nanoparticle weight fractions. The typical characteristic peaks of pure PVDF are at 2θ = 18.3° and 26.5°, which are related to the α-phase of PVDF. The (020) and (021) reflections of PVDF were attributed to these two peaks. In addition, seven distinct diffraction peaks were clearly observed in the XRD pattern, which corresponds to the reflections of the (200), (100), (110), (111), (200), (210), and (211) crystal planes. The appearance of these peaks in the nanocomposite XRD patterns shows that the crystalline characteristics of the TOS-BTO nanoparticles correspond to a ferroelectric tetragonal phase, and the crystal phase of TOS-BTO nanoparticles was not changed by the TOS surface modification. After blending the TOS-BTO nanoparticles with the PVDF polymer, the intensity of the α-phase peak decreased significantly. Accordingly, the diffraction peaks at 20.5°, corresponding to the reflection of the sum of the (110) and (200) crystal planes, confirm the emergence of the crystal β-phase in the TOS-BTO/PVDF nanocomposite, whereas the related peaks of BTO/PVDF are not visible. The findings reveal that the TOS-BTO nanoparticles may operate as nucleation agents in the nanocomposite film, promoting better dipole alignment and the formation of higher β-phase content in the PVDF. Furthermore, by calculating the ratio of the intensities (I 20.3 and I 18.3 ), the β-phase and α-phase contents can be qualitatively estimated, as shown in Figure 5 b. The surface-modified BTO nanoparticles significantly influenced the β-phase content. Compared to the pristine BTO/PVDF composite film, which exhibits I 20.3 /I 18.3 ratios of 3.4 and 4.5 corresponding to 10% and 20% BTO nanoparticles, respectively, the TOS-BTO/PVDF composite displays I 20.3 /I 18.3 ratios of 4 and 5.3 corresponding to 10% and 20% TOS-BTO nanoparticles, respectively. These results confirm that the surface modification process can lead to a significant proportion of the β-phase content. The crystalline phase composition of the as-printed PVDF-based composites doped with various BTO and TOS-BTO nanoparticle weight fractions was further studied using FTIR spectroscopy, as shown in Figure 5 c. The distinctive peaks at 614, 764, 855, and 976 cm –1 represent the α-phase, whereas the vibrational peak at 840 cm –1 represents the β-phase. The typical absorption strength of the α-phase in the printed PVDF-based composite was lower than that of pristine PVDF. Meanwhile, the absorption intensity of the β-phase is more apparent, demonstrating that the inclusion of BTO nanoparticles increased the crystal phase composition. Significantly, the TOS-BTO/PVDF nanocomposites exhibited lower β-phase peak intensities than the pristine BTO/PVDF nanocomposites. These results indicate that the incorporation of TOS-BTO nanoparticles into the PVDF polymer matrix may promote the formation of β-phase crystalline structures. In addition, the Beer–Lambert law was used to calculate the fraction of the electrically active β-phase (F(β)) in the as-printed nanocomposites: (1) F β = A β K β K α A α + A β \nwhere A α and A β are the absorbance peaks at 762 and 840 cm −1 , respectively, and K α and K β are 7.7 and 6.1 × 10 4 cm 2 mol −1 , respectively. Figure 5 d shows the F(β) values of the pristine PVDF and composite films with various BTO and TOS-BTO nanoparticle weight fractions. The F(β) value increased as the BTO content increased. The nanofillers in PVDF can aid the crystallization of the PVDF matrix by providing suitable nuclei in the polymeric chains. Nanocomposites with 20% TOS-BTO nanoparticles showed a considerable improvement in the F(β) value of 86.38%. Furthermore, the TOS-BTO/PVDF composite film displayed considerably higher F(β) values than its pristine BTO/PVDF counterpart, indicating that surface modification promoted β-phase crystalline formation in the PVDF matrix. Figure 5 e shows the phase transformation of the PVDF film with the addition of TOS-BTO nanoparticles. As illustrated schematically in Figure 5 e, TOS was used to create an interfacial layer between the BTO nanoparticles and the PVDF polymer matrix. The hydroxyl groups in dopamine interacted with the BTO nanoparticles by creating covalent bonds, which produced an encapsulating layer surrounding the BTO surface by cross-linking, resulting in the low surface activity of the nanoparticles. During the mixing process, the positively charged methylene groups in the TOS molecules interacted with the negatively charged difluoromethylene groups in the PVDF chain to generate stable hydrogen bonds and form the electroactive β-phase, promoting compatibility and stability between the BTO nanoparticles and PVDF matrix and maintaining the alignment of the stabilized PVDF chains. A quasistatic d 33 meter was used to record the d 33 of the screen-printed nanocomposites and investigate their piezoelectric capabilities, as shown in Figure 6 a. The d 33 value of the as-printed composites was significantly affected by the BTO nanoparticle concentration. In particular, the d 33 value of the as-printed film increased from 16.7 pC/N for pure PVDF to 33.5 pC/N for the 20% TOS-BTO/PVDF as the TOS-BTO nanoparticle concentration increased. Additionally, compared to pristine BTO/PVDF, the d 33 of the 20% TOS-BTO/PVDF-TrFE was 150% higher, demonstrating that adding TOS-BTO nanoparticles is another technique to enhance piezoelectric performance. The surface modification of nanoparticles significantly increases the piezoelectric properties of nanocomposites. The following are some of the factors that contributed to this improvement: BTO nanoparticles exhibit a higher d 33 than PVDF. By combining the two materials, the piezoelectric capabilities of both phases are superior to that of pure PVDF. The high dielectric constant of the BTO nanoparticles, as ceramic particles, might focus the electric field onto the surrounding PVDF with a low dielectric constant. The stress concentration is another explanation for the increase in piezoelectricity. The addition of BTO nanoparticles increased the stiffness of the nanocomposites while decreasing the fracture strain, demonstrating the capacity of the nanocomposites to withstand high local stress. Furthermore, as shown in Figure 6 c, numerous holes were caused by the loose contact between organic PVDF matrix and inorganic BTO nanoparticles, while there were many defects caused by the agglomerated BTO nanoparticles in the pristine BTO/PVDF nanocomposite. When the force was applied to the nanocomposite, the force-generated charges were accumulated and trapped in the holes and defects, resulting in the undesired piezoelectric properties. In contrast, as shown in Figure 6 d, the TOS-BTO/PVDF nanocomposite achieved a homogenous dispersion of TOS-BTO by improving the compatibility between the nanofillers and polymer matrix following TOS coating on the BTO nanoparticle surface. Additionally, the TOS layer on the BTO surface created a stronger contact between the polymer matrix and nanofillers, resulting in fewer holes and defects in nanocomposites. Therefore, the decrease in the number of holes in the nanocomposites contributed to improved piezoelectricity by suppressing undesired cumulative trap charges. However, the d 33 value reduced to 30.4 pC/N when the TOS-BTO nanoparticle concentration increased to 30 wt%. The explanation for the decline in d 33 is that the nanoparticle aggregation has a negative electromechanical coupling impact. Furthermore, when a vertical pressing and releasing force of 50 N was applied at a frequency of 3 Hz, the open-circuit voltage (V OC ) was measured, as shown in Figure 6 b. As the number of TOS-BTO nanoparticles increased, the V OC and d 33 values also increased, indicating that the piezoelectric contribution to the electrical output was directly related to the d 33 value. In particular, when the TOS-BTO nanoparticle concentration reached 20%, the highest peak-to-peak voltage of 20 V was achieved, which is almost two times higher than that of the pristine BTO/PVDF counterpart. Therefore, we selected the 20% TOS-BTO/PVDF PENG for subsequent experiments and compared it to the 20% BTO/PVDF PENG. In order to study the device performance of the PVDF-based pressure sensors, the output piezoelectric signals were carefully measured under various stress conditions, as shown in Figure 7 . Figure 7 a depicts the voltage responses of the as-printed PENGs plotted as a function of the dynamic pressure ranging from 10 to 500 kPa at a frequency of 3 Hz. Clearly, the voltage output increases approximately linearly with the applied pressure across the entire range of measurements. In general, the piezoelectric potential and output voltage increase when the external impact force increases because of the larger deformation. The peak-to-peak voltages of the TOS-BTO/PVDF PENGs and pristine BTO/PVDF PENGs under dynamic compression stress of 500 kPa at 3 Hz were 20 and 9 V, respectively. The ultralarge linear response area of the as-printed sensor may offer a robust testing procedure and avoid complicated calibration methods. Furthermore, the slope of the linear graph may be used to calculate the voltage sensitivity of printed piezoelectric sensors: S = V/P, where V and P are the corresponding variances in the output voltage signal and applied pressure. According to the linear fitting result, the screen-printed TOS-BTO/PVDF PENGs exhibited better sensitivity (45.4 mV kPa −1 ) and voltage linearity (0.99805) than the pristine BTO/PVDF counterpart, demonstrating improved sensing capability compared to previously reported piezoelectric pressure sensors ( Table 1 ). These results imply that the TOS surface-modification method may significantly increase the sensitivity of the printed device. In addition, as shown in Figure 7 b, the output signals of the screen-printed PENGs were recorded with external load resistances ranging from 10 to 100 M under a 50 N load of 3 Hz to adequately analyze the power density of the screen-printed PENGs as an energy provider. The power density of the screen-printed PENGs can be calculated using the formula P = U 2 /(Rt), where P is the power density; U is the output voltage; R is the load resistance, and t is the effective area of the piezoelectric layer. There was an initial increase in power density, which subsequently decreased as the load resistance increased. At 5 M resistance, the highest power density of TOS-BTO/PVDF PENGs was 15.6 W/cm −2 , which is ~150% higher than that of the pristine BTO/PVDF PENGs, confirming that the TOS surface-modification method can significantly enhance the energy harvesting capability. Furthermore, Figure 7 c shows that as the impact frequency increased, the output voltages of the screen-printed TOS-BTO/PVDF PENGs increased. This phenomenon might have presumably been caused by the increasing frequency-induced strain rate of the nanocomposites. Moreover, to evaluate the durability of the screen-printed TOS-BTO/PVDF PENGs, the cycle test is carried out, and the result is shown in Figure 7 d. After 7500 cycles of operation at a vertical pressing and releasing the pressure of 50 N at 3 Hz, the electric outputs exhibited no fluctuation or attenuation, demonstrating that the screen-printed TOS-BTO/PVDF PENGs display good mechanical robustness and endurance. The wearability and sensitivity of the screen-printed TOS-BTO/PVDF PENGs for active physiological monitoring were systematically investigated by measuring the electrical outputs under different human motions. The screen-printed TOS-BTO/PVDF PENGs created a piezoelectric output voltage under tapping and hand compression conditions, as shown in Figure 8 a,b, respectively. Under the finger tapping and hand compression conditions, the screen-printed TOS-BTO/PVDF PENGs achieved output voltages of 2.6 and 4.5 V, respectively. As a result, the flexible printed sensor device described herein can gather biomechanical energy or detect human movement. The output voltages of the TOS-BTO/PVDF PENGs installed on a human arm are shown in Figure 8 c,d under various arm bending conditions. Under small bending positions (bending angle of 30°), the printed TOS-BTO/PVDF PENGs generated output voltages of 1.5 V, while the printed device generated output voltage of 2.6 V under large bending position (bending angle of 90°), respectively. During massive bending, the TOS-BTO nanoparticles and PVDF polymer were subjected to much more strain, resulting in a larger electrical output. Therefore, this flexible screen-printed TOS-BTO/PVDF PENG is a viable option for real-time/practical applications, such as harvesting biomechanical energy or detecting human body movements."
} | 6,282 |
36033895 | PMC9403865 | pmc | 3,336 | {
"abstract": "The ability of bacteria to resist heat shock allows them to adapt to different environments. In addition, heat shock resistance is known for their virulence. Our previous study showed that the AI-2/luxS quorum sensing system affects the growth characteristics, biofilm formation, and virulence of Glaesserella parasuis . The resistance of quorum sensing system deficient G. parasuis to heat shock was obviously weaker than that of wild type strain. However, the regulatory mechanism of this phenotype remains unclear. To illustrate the regulatory mechanism by which the quorum sensing system provides resistance to heat shock, the transcriptomes of wild type (GPS2), ΔluxS, and luxS complemented (C-luxS) strains were analyzed. Four hundred forty-four differentially expressed genes were identified in quorum sensing system deficient G. parasuis , which participated in multiple regulatory pathways. Furthermore, we found that G. parasuis regulates the expression of rseA , rpoE , rseB , degS , clpP , and htrA genes to resist heat shock via the quorum sensing system. We further confirmed that rseA and rpoE genes exerted an opposite regulatory effect on heat shock resistance. In conclusion, the findings of this study provide a novel insight into how the quorum sensing system affects the transcriptome of G. parasuis and regulates its heat shock resistance property.",
"conclusion": "Conclusion In summary, RNA-seq was conducted to compare the differences in transcriptome and illustrate the regulatory effect of the quorum sensing system in GPS2, ΔluxS, and C-luxS strains. Four hundred forty-four differentially expressed genes were identified in the ΔluxS mutant strain, compared with GPS2. Several of these genes were involved in the molecular signaling pathway interactions with the quorum sensing system. In addition, we demonstrated that G. parasuis could utilize the quorum sensing system to regulate its heat shock resistance. We further confirmed that rseA and rpoE genes exerted an opposite regulating effect in heat shock resistance. In conclusion, we believe that this study provides first-hand information regarding the molecular mechanism by which the quorum sensing system regulates the heat shock resistance of G. parasuis .",
"introduction": "Introduction Glaesserella parasuis ( G. parasuis ) causes serious Glässer’s disease, which is characterized by severe infection of the upper respiratory tract, polyserositis, meningitis, and arthritis in pigs. It can lead to huge economic losses to the global pig industry ( Liu et al., 2016 ). The quorum sensing system is a type of population density-dependent cell–cell signaling in bacteria that was first discovered and described in two luminous marine bacterial species, namely, Vibrio fischeri and Vibrio harveyi ( Nealson and Hastings, 1979 ). Based on the differences in autoinducers, the quorum sensing system is classified into four types. The first type is luxR-I quorum sensing system, in which LuxI is responsible for the production of the N-acyl-homoserine-lactone (AHL) autoinducer; LuxR is activated by this autoinducer to increase the transcription of the luciferase operon. The second type is the autoinducer peptide (AIP, a kind of short peptide signaling) quorum sensing system that exists in gram-positive bacteria. The third type is the luxS/AI-2 quorum sensing system that is present in approximately half of all the sequenced bacterial genomes including gram-negative and gram-positive bacteria ( Waters and Bassler, 2005 ). The fourth type is the AI-3/epinephrine/norepinephrine quorum sensing system ( Kendall and Sperandio, 2007 ). The quorum sensing system has been implicated in the regulation of several physiological activities and abilities in bacteria such as virulence, antibiotic production, symbiosis, motility, and biofilm formation ( Miller and Bassler, 2001 ). We have previously reported that the virulence and abilities of autoagglutination, adherence to PK-15 cells, and hemagglutination were significantly decreased in the luxS mutant strain of GPS2. Furthermore, the tolerance to heat shock stress was reduced in the luxS mutant strain. However, the ability of the luxS mutant strain to form biofilm was significantly increased ( Zhang et al., 2019 ). While the regulatory mechanism of quorum sensing system in G. parasuis remains unclear. RNA-seq has emerged as a very important tool that is commonly used to study pathogen-host interactions, antibiotic resistance, and quorum sensing system ( Wen et al., 2011 ; Liu et al., 2012 ; Fu et al., 2018 ). Therefore, RNA-seq was used to identify the potential regulatory mechanism of quorum sensing system in G. parasuis . Several studies have reported the significance of the luxS/AI-2 quorum sensing system in antibiotic production, biofilm formation, virulence, and carbohydrate metabolism ( Xue et al., 2013 ; Ma et al., 2017 ; Abisado et al., 2018 ). However, the regulation of heat shock resistance by the luxS/AI-2 quorum sensing system is rarely reported. The ability of pathogenic microorganisms to heat shock resistance is crucial for adapting to different environments. In addition, it affects the virulence of pathogenic microorganisms. The LuxS gene decreases the resistance of Porphyromonas gingivalis to heat stress ( Yuan et al., 2005 ). Although we have previously reported that the luxS gene could significantly increase the tolerance of heat shock stress in G. parasuis ( Zhang et al., 2019 ). While the regulatory mechanism of heat shock resistance is still unclear in G. parasuis . HtrA is a heat shock-induced serine protease with homologs present in a wide range of bacteria and eukaryotes ( Pallen and Wren, 1997 ). The HtrA gene is known to affect the bacterium’s ability to withstand heat and other stress and virulence in Bacillus anthracis and Salmonella typhimurium ( Pallen and Wren, 1997 ; Mutunga et al., 2004 ; Chitlaru et al., 2011 ). In G. parasuis , the htrA gene has been reported to increase the ability to heat shock resistance ( Zhang et al., 2016 ). In Escherichia coli , RseB is a periplasmic protein that negatively regulates σ E (RpoE) activity and specifically interacts with RseA, an inner membrane protein. In contrast, RseC is an inner membrane protein that positively modulates the activity of σ E , which is a heat shock transcription factor ( Missiakas et al., 1997 ). DegS is a periplasmic protease anchored to the inner-membrane, whereas ClpP is a cytoplasmic protease; both work together to cleave RseA and release σ E from the RseA-σ E compound to the cytoplasm, thus initiating the transcription of heat shock stress-related genes to resist heat shock stress ( Kim, 2015 ). Therefore, we wanted to study whether this regulatory mechanism of heat shock resistance also exists in G. parasuis . To the best of our knowledge, no study has been conducted to study the regulatory mechanism of heat shock resistance by the quorum sensing system in G. parasuis . Therefore, this study aims to illustrate the regulatory network of the quorum sensing system in G. parasuis and identify the potential mechanism of heat resistance in G. parasuis by RNA-seq and analyze the differentially expressed genes in the transcriptome.",
"discussion": "Discussion The quorum sensing system is associated with a diverse array of physiological activities and abilities, such as symbiosis, virulence, conjugation, antibiotic production, motility, sporulation, and biofilm formation in G. parasuis , Actinobacillus pleuropneumoniae , Glaesserella influenza , and Streptococcus mutans ( Miller and Bassler, 2001 ; Merritt et al., 2003 ; Daines et al., 2005 ; Li et al., 2008 ; Zhang et al., 2019 ). However, the mechanism by which quorum sensing system regulates the resistance to heat shock remains unclear. Therefore, we analyzed the regulatory networks associated with the LuxS quorum sensing system of G. parasuis to reveal the potential regulatory mechanisms. To our knowledge, this is the first study analyzing the function of quorum sensing system in Glaesserella parasuis using RNA-seq. Although we have previously shown that the resistance of quorum sensing system deficient G. parasuis to heat shock is weaker than that of wild type strain ( Zhang et al., 2019 ), the underlying regulatory mechanism is still unclear. The transcriptome results showed that the rseA gene was up-regulated, whereas rseB , degS , clpP , rpoE , and htrA genes were down-regulated in ΔluxS, compared with the wild type strain. All these genes have been reported to be involved in the regulation of resistance to heat shock in E. coli ( Kim, 2015 ). Therefore, based on our transcriptome results, we hypothesized that quorum sensing system regulates the resistance of G. parasuis to heat as follows: under normal conditions, DegS protease is activated by the binding of the outer membrane protein (OMP) C-terminus, and RseB protein is relieved from RseA by the accumulation of lipopolysaccharide (LPS) in the periplasm ( Mecsas et al., 1993 ; Sohn et al., 2007 ). Next, RseA is sequentially digested by DegS and ClpP, thereby releasing σ E to the cytoplasm, which is produced by RpoE ( Missiakas et al., 1997 ; Chaba et al., 2011 ; Lima et al., 2013 ). The released σ E in combination with HtrA increases the ability of G. parasuis to heat shock ( Zhang et al., 2016 ). Finally, the compound can play a positive regulatory effect in the heat shock resistance mechanism ( Figure 6 ). However, when the luxS gene was deleted, the expression of heat shock-related genes is altered, thus suppressing the release of σ E and expression of the htrA gene, and finally reducing the ability of G. parasuis to resist heat shock. And the regulatory network of quorum sensing system to heat shock resistance in G. parasuis requires to in-depth study. Figure 6 Schematic drawing of the σ E signaling pathway. As stress sensor proteins, DegS protease is activated by the binding of the OMP C-terminus, and RseB is relieved from RseA by the accumulation of LPS in the periplasm. RseA is sequentially digested by DegS and ClpP, thereby releasing σ E in the cytoplasm. Finally, σ E along with RNA polymerase can induce the transcription of the htrA gene and other heat shock-relate genes. GO categories results showed that amino acid metabolic process and catalytic activity were down-regulated in the ΔluxS strain, which is consistent with the finding of a previous report that implicated quorum sensing in controlling the amino acid metabolism ( Withers et al., 2001 ). The LuxS protease plays an important role in the activated methyl cycle (AMC) which is a pivotal metabolic pathway that recycles homocysteine from S-adenosyl methionine (SAM) to maintain the de novo methionine biosynthesis ( Hardie and Heurlier, 2008 ). Therefore, the change in the activated methyl cycle could contribute to the downregulation of the amino acid metabolic process and catalytic activity. KEGG pathway analyzing results showed ABC transporters as one of the most abundant pathways of up-regulated genes in ΔluxS strain. ABC transporters are involved in the secretion of antibiotics through the cell membrane and also contribute to acquired antibiotic resistance ( Mendez and Salas, 2001 ), which explains the finding that the quorum sensing system is associated with antibiotic production ( Miller and Bassler, 2001 )."
} | 2,857 |
27547328 | PMC4979722 | pmc | 3,338 | {
"abstract": "Abstract Biological invasion remains a major threat to biodiversity in general and a disruptor to mutualistic interactions in particular. While a number of empirical studies have directly explored the role of invasion in mutualistic pollination networks, a clear picture is yet to emerge and a theoretical model for comprehension still lacking. Here, using an eco‐evolutionary model of bipartite mutualistic networks with trait‐mediated interactions, we explore invader trait, propagule pressure, and network features of recipient community that contribute importantly to the success and impact of an invasion. High level of invasiveness is observed when invader trait differs from those of the community average, and level of interaction generalization equals to that of the community average. Moreover, multiple introductions of invaders with declining propagules enhance invasiveness. Surprisingly, the most successful invader is not always the one having the biggest impact on the recipient community. The network structure of recipient community, such as nestedness and modularity, is not a primary indicator of its invasibility; rather, the invasibility is best correlated with measurements of network stability such as robustness, resilience, and disruptiveness (a measure of evolutionary instability). Our model encompasses more general scenarios than previously studied in predicting invasion success and impact in mutualistic networks, and our results highlight the need for coupling eco‐evolutionary processes to resolve the invasion dilemma.",
"introduction": "Introduction Rapid global changes induced by anthropogenic disturbance constitute a major threat to networks of ecological interactions (Tylianakis et al. 2008 ; Burkle and Alarcón 2011 ), of which biological invasion represents one important component (Morales and Traveset 2009 ; McGeoch et al. 2010 ). Mutualistic networks of pollination and seed dispersal are key service providers in ecosystems (Bronstein 2001 ); understanding how their structures and stabilities respond to biological invasions is paramount to safeguarding ecosystem function and service in a changing world (Traveset and Richardson 2006 ; Lurgi et al. 2014 ; Campbell et al. 2015 ). For efficient prevention and control, the challenge is to foresee the invasiveness and impact of potential invaders in given ecosystems. This is a challenge of complexity as no universal rules, except for the amount of propagules introduced (known as the propagule pressure; Williamson, 1999 ; Jeschke and Strayer 2006 ; Simberloff 2009 ), govern the process and success of invasion which are nearly exclusively contingent on the taxa and context (Williamson and Fitter 1996 ). When introduced into a new environment, an alien species needs to compete for space and resources with native resident species, simply by possessing certain phenotypic and behavioral traits (Romanuk et al. 2009 ). The strength of ecological interactions is often mediated by matching between functional traits of interacting species (Jousselin et al. 2003 ; Santamaría and Rodríguez‐Gironés 2007 ; Stang et al. 2009 ). A certain degree of similarity between the trait of invasive and resident species often indicates a strong mutualistic interaction (Gibson et al. 2012 ). Nevertheless, species with high invasiveness and impact in pollination networks acquire traits atypical of native (Aizen et al. 2008 ; Campbell et al. 2015 ; but see Morales and Traveset 2009 ). As such, features of both invaders and recipient communities play critical roles in predicting the success and impact, two interdependent elements, of an invasion (Shea and Chesson 2002 ; Gurevitch et al. 2011 ). Such interdependence of invasiveness and impact could be further amplified in an ecological network because of cascading interactions (Bascompte and Stouffer 2009 ; Dunne and Williams 2009 ; Traveset and Richardson 2014 ). Species with a high level of interaction generalization, that is, high‐degree nodes in a network, has been shown to determine the invasion success in both food webs (Romanuk et al. 2009 ; Lurgi et al. 2014 ) and mutualistic networks (Traveset and Richardson 2014 ). Functional traits, such as body size and diet breadth that are indicative to species' trophic position in a food web and thus its level of interaction generalization, are good predictors of invasion success. For instance, consumer species with a wide diet breadth or a large body size experience more invasion success in a food web (Lurgi et al. 2014 ). Invasive plants in pollination networks often have higher levels of interaction generalization than natives (Albrecht et al. 2014 ). The overall interactions in a pollination network can even be monopolized by super‐generalist invaders (Aizen et al. 2008 ; Bartomeus et al. 2008 ; Vilà et al. 2009 ). Characteristics of a recipient ecosystem responsible for its susceptibility to the establishment and spread of invasive species defines its invasibility (Lonsdale 1999 ; Alpert et al. 2000 ). Besides physical factors such as habitat suitability and heterogeneity, other major characteristics considered in literature include the network architecture of biotic interactions. For example, a high level of network connectance – the proportion of realized interactions among possible ones – has been predicted to enhance the resistance of food webs to invasion (Romanuk et al. 2009 ), although contested by others (Baiser et al. 2010 ; Lurgi et al. 2014 ). Modularity – the extent to which a network is organized into groups of species interacting more strongly with species from the same group rather than from other groups – is observed to be lower in invaded pollination networks and food webs than in uninvaded ones (Albrecht et al. 2014 ; Lurgi et al. 2014 ). Empirical studies have also revealed that invaded pollination networks are more nested – where specialists interact only with a subset of species with which generalists interact – and normally contain a higher number of species than uninvaded networks (Padrón et al. 2009 ; Stouffer et al. 2014 ). Mutualistic interactions normally have a facilitative effect on the establishment of alien species (Traveset and Richardson 2014 ). Successful invaders in mutualistic networks have been shown to interact with either the most specialist natives (Stouffer et al. 2014 ) or the most generalist ones (Padrón et al. 2009 ). However, empirical observations do not allow for discerning whether some network features could have triggered the invasion or are indeed resulting from the invasion. By comparing the pre‐ and postinvasion architectures of simulated pollination networks, Campbell et al. ( 2015 ) managed to fill the gap in literature and found that, while network connectance decreased, nestedness increased from invasions. The role of particular network architectures in stabilizing networks has been hotly debated, especially regarding mutualistic networks. On one hand, patterns of connectance and nestedness observed in mutualistic networks can facilitate the coexistence of species and thus contribute positively to network stability (Bastolla et al. 2009 ; Thébault and Fontaine 2010 ; Rohr et al. 2014 ). Network complexity, measured as network size and connectivity (number of interactions), can enhance network resilience (Okuyama and Holland 2008 ). On the other hand, some theoretical studies have shown that these typical features specific to mutualistic networks can also be detrimental to network stability. For instance, the stability of a mutualistic network declines with extreme levels of nestedness (Campbell et al. 2012 ) or modularity (Thébault and Fontaine 2010 ). The stability of a mutualistic network was also found to be negatively correlated with connectance especially when interaction strength is taken into account (Allesina and Tang 2012 ; Vieira and Almeida‐Neto 2015 ). Inconsistency of the correlation between network structure and network stability is somewhat caused by the confusion in choosing appropriate measures of network stability. Each metric of network stability only measures one specific facet of stability and thus often leads to contradictions when interpreted as the general stability for comparison (Vallina and Quéré 2011 ). Among these metrics of network stability/instability, network invasibility is a recent emergent concept particularly relevant to invasion biology; it is defined as the amount of opportunity niches in the trait space that allow for positive per‐capita population growth of rare aliens (Hui et al. 2016 ). It is therefore necessary to explore how the concept of invasibility relates to these other measures of network stability/instability, as well as how these stability measures (including invasibility) are correlated with network architectures and the invasiveness of aliens. Although the literature in invasion ecology is dominated by empirical and experimental studies, theoretical works are needed to explore general rules for predicting invasiveness and impacts of alien species. Models with trait‐mediated biotic interactions represent an ideal theoretical framework for exploring issues of biological invasion. For example, Campbell et al. ( 2015 ) formulated the interaction strength between newly introduced species and resident species by the similarity between their phenotypic traits such as between corolla depth of plants and proboscis length of pollinators. In these studies, traits of resident species are static and either randomly assigned (Romanuk et al. 2009 ; Lurgi et al. 2014 ) or empirically inferred (Campbell et al. 2015 ). However, resident traits are often adaptive and results from long‐term ecological and evolutionary processes. The role of such adaptive nature of resident traits in invaded networks needs to be assessed. Here, we deploy a theoretical approach to explore the process of biological invasion in mutualistic networks. Mutualistic networks are described using an eco‐evolutionary model depicting simultaneously ecological dynamics of population densities happening at a faster timescale and evolutionary dynamics of functional traits happening at a slower timescale, using the framework of adaptive dynamics (Metz et al. 1992 ; Dieckmann and Law 1996 ). In these networks, each species is identified by its trait (i.e., as morphospecies) which determines the intensity of both intraspecific competition and mutualistic interaction. Our previous work using a similar model has shown that properties of emerged mutualistic networks are comparable to features of empirical networks (Minoarivelo and Hui 2016 ). However, we did not explore how an introduced species performs and how emerged mutualistic networks, in terms of their architectures and stability, respond to the incursions of these introduced species. Here, we first use the model to generate mutualistic networks as recipient communities, into which we then introduce an alien species. By examining a wide range of possibilities for both invaders and recipient communities, we investigate how they respond to each other. In particular, we study (1) how the invasiveness and the impact of an introduced species depend on whether or not its trait and its level of interaction generalization are relatively similar to the average of the recipient community; (2) how the success of an invasion depends on the way the invasive species is introduced, that is, propagule pressure; and (3) how the invasibility and other metrics of network stability depend on the structure of recipient communities.\n\nRole of introduction mode Invasion success also depends on the way these alien individuals are introduced (e.g., once‐off or multiple introductions), that is, the introduction mode. However, the dependence of invasiveness on introduction mode is sensitive to the level of generalization of the invader. First, when an invader has the same level of generalization as the native species, its invasiveness becomes the highest for the mode of three introductions with decreasing propagule sizes and becomes the lowest for the mode of three introductions with increasing propagule sizes (Fig. 3 A and B). Second, when the invader is either more specialist or more generalist than the native species, the invasiveness of the alien becomes highly dependent on the number of introduction events, with higher numbers of introductions leading to high invasiveness (Figs. 3 C and D, S3). Figure 3 Average (over 100 medium‐size networks) of the invasiveness when the alien has the following: (A) typical trait and similar level of generalization to the native species, (B) average trait and similar level of generalization to native species, (C) typical trait and is more specialist than native species, (D) typical trait and is more generalist than native. Error bars represent tenth of the standard deviation. rtv stands for relative trait value and glr for generalization level ratio. Bars with different characters are significantly different from each other. The dependence of the invasion impact on the mode of introduction is uniform regardless of the invader trait value and its generalization level. The impact of the invasion on the population of the native community is highest when the invader is introduced three times with decreasing propagule sizes (Fig. 4 ). However, when the invader species is highly specialist or highly generalist, the impact of multiple introductions is not significantly different from the impacts caused by a once‐off introduction (Fig. 4 C and D). Regardless of the introduction mode (Figs. S3, S4) and the initial propagule size (Fig. S5), these patterns demonstrated in the previous section regarding the dependence of invasiveness and impact on the invader trait and its level of generalization remained. Figure 4 Average (over 100 medium‐size networks) of the impact when the alien has the following: (A) typical trait and similar level of generalization to the native species, (B) average trait and similar level of generalization to native species, (C) typical trait and is more specialist than native species, (D) typical trait and is more generalist than native. Error bars represent tenth of the standard deviation. rtv stands for relative trait value and glr stands for generalization level ratio. Bars with different characters are significantly different from each other.\n\nPropagule pressure and introduction mode Both the number of introductions and the propagule size at each introduction matter to invasion success. Even if the dependence of invasion success on the number of introductions showed contingent patterns on the level of invader generalization, a general pattern still acknowledges the importance of multiple introductions, especially with decreasing propagule size, consistent with previous studies (Jeschke and Strayer 2006 ; Simberloff 2009 ). Indeed, a high number of introductions could help in lessening environmental stochasticity (Simberloff 2009 ) or rescuing the establishment of each introduction as in the phenomenon of invasion meltdown (Traveset and Richardson 2014 ). In our case, this is probably caused by the indirect positive effect of mutualism: once some individuals of the invader establish in the system, they proliferate the population densities of their mutualistic partners and subsequently facilitate the establishment of new arrivals from future introductions, potentially forming a positive feedback between aliens and natives in mutualistic networks (Memmott and Waser 2002 ; Bartomeus et al. 2008 ; Traveset and Richardson 2014 ). Moreover, the additional effect of decreasing propagule size in multiple introductions suggests that such proliferation from earlier introductions is diminishing or saturating with the number of established individuals.",
"discussion": "Discussion Trait‐mediated invasiveness and impact Ecological network approach in which interactions are mediated by traits constitutes an interesting framework to predict the success or the failure of an invasion. It allowed us to test the invasion success for different combinations of invader characteristics (trait and level of generalization) and the characteristics of the recipient community. In contrast to previous studies (Aizen et al. 2008 ; Albrecht et al. 2014 ; Campbell et al. 2015 ), we found that the effect of invader characteristics on its invasion success is not unidirectional but intertwined. However, our finding that alien species with traits dissimilar to those of the natives are the most invasive ones is consistent with previous studies (Aizen et al. 2008 ; Campbell et al. 2015 ). The importance of high interaction generalization to invasiveness as observed by others (Aizen et al. 2008 ; Bartomeus et al. 2008 ; Vilà et al. 2009 ; Albrecht et al. 2014 ) was only observed in our results when the traits of the invader are dissimilar to the average resident traits. Our results, thus, encompass broader scenarios than those previously studied on mutualistic networks. The most invasive species is not always the one that has the biggest impact, highlighting the need to differentiate highly invasive species from those with big impact in management prioritization. Invasive species should only be targeted by management if their negative impacts outweigh their positive effects. Besides trait distinctiveness, a high level of interaction generalization is also a strong predictor for big impacts (Aizen et al. 2008 ; Albrecht et al. 2014 ), often through the cascading effect of interactions that are strongly associated with generalists. Different from Campbell et al. ( 2015 ) but consistent with Morales and Traveset ( 2009 ), we found that invaders with traits atypical of the native community have the least impact to native population sizes. As the overall impact observed in our model is detrimental rather than proliferating (Fig. S2), the impact probably could have resulted from intraspecific competition in mutualistic networks, suggesting that the detrimental effect from competing with invaders has overridden the proliferation from mutualistic interactions. The impact of biological invasions on native population densities is small in mutualistic networks and thus a negligible effect on network architecture (Fig. S8). Such small impact has been previously documented (Padrón et al. 2009 ; Vilà et al. 2009 ) and can be caused by the peripheral role of the invader in the network. In particular, Albrecht et al. ( 2014 ) found that the overall number of modules in an empirical pollination network was not altered by invasion, but only that modules were more connected from the super‐generalist invaders. The trait value and node degree (level of interaction generalization) of an invader decide its invasiveness and impact in the recipient network. Our results can be explained by the balance between two forces: the detrimental effect of competition and the beneficial effect from mutualism. While a high level of interaction generalization often means large benefits from mutualism, a trait atypical of resident species means the escape from competition. Consequently, a generalist invader also possessing traits atypical of resident species is the most invasive. By contrast, to have the highest impact on the recipient network, the invader's trait should be similar to those of an average resident species so that competition can be intensified. The invader with big impact should either be an extreme generalist so that mutualistic benefits from most resident species can be monopolized, or be an extreme specialist so that benefits from targeted mutualistic partners can be deprived. Propagule pressure and introduction mode Both the number of introductions and the propagule size at each introduction matter to invasion success. Even if the dependence of invasion success on the number of introductions showed contingent patterns on the level of invader generalization, a general pattern still acknowledges the importance of multiple introductions, especially with decreasing propagule size, consistent with previous studies (Jeschke and Strayer 2006 ; Simberloff 2009 ). Indeed, a high number of introductions could help in lessening environmental stochasticity (Simberloff 2009 ) or rescuing the establishment of each introduction as in the phenomenon of invasion meltdown (Traveset and Richardson 2014 ). In our case, this is probably caused by the indirect positive effect of mutualism: once some individuals of the invader establish in the system, they proliferate the population densities of their mutualistic partners and subsequently facilitate the establishment of new arrivals from future introductions, potentially forming a positive feedback between aliens and natives in mutualistic networks (Memmott and Waser 2002 ; Bartomeus et al. 2008 ; Traveset and Richardson 2014 ). Moreover, the additional effect of decreasing propagule size in multiple introductions suggests that such proliferation from earlier introductions is diminishing or saturating with the number of established individuals. Network architecture and invasibility Network structures, such as connectance, level of specialization, nestedness, and modularity, were shown to be not of primary correlates of network stability. Consequently, network architectures alone cannot capture the overall functioning of ecological networks. More importantly, one measure of network stability would suffice for predicting how a community responds to the perturbation of biological invasions. We are certainly not discarding the role of network architectures in stabilizing or destabilizing mutualistic networks (Bastolla et al. 2009 ; Thébault and Fontaine 2010 ; Allesina and Tang 2012 ; Rohr et al. 2014 ; Vieira and Almeida‐Neto 2015 ), but simply state that inferring network function from structure could have been overemphasized. In particular, nestedness was negatively correlated with resilience and robustness, consistent with previous studies (Allesina and Tang 2012 ; Campbell et al. 2012 ), even though it has been observed as one of the most prominent characteristics of mutualistic networks. This counter‐intuitive observation is reconciled by our results that highly nested networks have a low invasibility, thus less likely to be invaded. The more robust and resilient a network is, the more susceptible it is to invasion. Mutualistic networks which are well posed (high robustness) can return quickly to a steady state after perturbations (high resilience); such network features also make it susceptible to invasion (high invasibility; i.e., a high chance of invasion success). Intuitively, this is because the features of a network being well posed also allow it to easily absorb newly introduced species. That is, networks that are insensitive to perturbations, especially to species removal (i.e., being robust) will have a high chance to be invaded. The positive relationships between network stability metrics (resilience and robustness) and network instability metrics (invasibility, invasiveness, disruptiveness, and impact) heighten the necessity to use appropriate measures in network studies. Stability metrics should therefore not be interpreted outside the context defining environmental drivers of change (Ives and Carpenter 2007 ). Moreover, network resilience and disruptiveness are strongly related to each other (Fig. 6 ). As the former is widely used as a proxy of ecological stability and the latter evolutionary instability, resilient networks are disruptive. Ecological stability and evolutionary stability could be two complementary states for systems to handle perturbations. Future works can expand the scope of our model in two aspects. First, although we were able to vary the interaction generalization level of the invader, the levels of interaction generalization of all native species were assumed to be the same (i.e., the tolerance to trait difference σ \n m ). This assumption could have oversimplified the reality that species in real networks often have different diet breadths. Second, we assumed a symmetric model regarding the animal–plant interaction. Empirical studies have often unveiled imbalanced roles of animal pollinators and flowering plants in mutualistic networks, resulting in asymmetric interaction with plants strongly dependent on the pollinators (Bascompte et al. 2006 ; Aizen et al. 2008 ). Extension of our trait‐based model to encompass interaction asymmetry would certainly be worth of further investigation."
} | 6,148 |
33184366 | PMC7661510 | pmc | 3,339 | {
"abstract": "As anomalous heat waves are causing the widespread decline of coral reefs worldwide, there is an urgent need to identify coral populations tolerant to thermal stress. Heat stress adaptive potential is the degree of tolerance expected from evolutionary processes and, for a given reef, depends on the arrival of propagules from reefs exposed to recurrent thermal stress. For this reason, assessing spatial patterns of thermal adaptation and reef connectivity is of paramount importance to inform conservation strategies. In this work, we applied a seascape genomics framework to characterize the spatial patterns of thermal adaptation and connectivity for coral reefs of New Caledonia (Southern Pacific). In this approach, remote sensing of seascape conditions was combined with genomic data from three coral species. For every reef of the region, we computed a probability of heat stress adaptation, and two indices forecasting inbound and outbound connectivity. We then compared our indicators to field survey data, and observed that decrease of coral cover after heat stress was lower at reefs predicted with high probability of adaptation and inbound connectivity. Last, we discussed how these indicators can be used to inform local conservation strategies and preserve the adaptive potential of New Caledonian reefs.",
"conclusion": "Conclusions In this study, we combined remote sensing of environmental conditions with genomic data to predict spatial patterns of heat stress adaptation and connectivity for the coral reefs of New Caledonia. We then retrieved field survey data and showed that recent heat stress was associated with a decrease in living coral cover, but also that such association appeared to be mitigated at reefs predicted with (1) high probability of heat stress adaptation and (2) high levels of incoming dispersal. The metrics computed in this work resumes the adaptive potential of corals against heat stress, and therefore represents valuable indices to support spatial planning of reef conservation.",
"introduction": "Introduction Coral bleaching is one of the main causes of severe declines of coral reefs around the world 1 – 3 . This phenomenon is mainly caused by anomalous heat waves leading to the death of hard-skeleton corals, which are the cornerstone of reefs 2 . Over the last 30 years mass coral bleaching events repeatedly struck worldwide, causing losses of local coral cover up to 50% 1 , 3 . In the coming years, bleaching conditions are expected to occur more frequently and to become persistent by 2050 4 . As up to one third of marine wildlife depends on coral reefs for survival and at least 500 million people livelihoods worldwide 5 , there is an urgent need to define new strategies to improve the preservation of these ecosystems 6 . Recent research reported reefs that rebounded from repeated heat stress and showed an increased thermal resistance 7 – 11 . Adaptation of corals against heat stress might explain such observations 12 , 13 . Under this view, identifying adapted coral populations is of paramount importance, as conservation strategies might be established to protect reefs hosting these corals from local stressors (e.g. via marine protected areas, MPAs) 14 . Furthermore, adapted corals could be of use in reef restoration plans and repopulate damaged reefs 15 . The adaptive potential of corals at a given reef depends on the arrival of propagules from reefs exposed to recurrent thermal stress 16 , 17 . This is why characterizing spatial patterns of thermal adaptation and reef connectivity is crucial to empower the conservation of the adaptive potential of corals 16 , 17 . Seascape genomics is a powerful method to evaluate spatial patterns of environmental variation and connectivity 17 , 18 . This method relies on a thorough analysis of environmental conditions around reefs using satellite data. Daily records of surface temperature are remotely sensed using satellites, and processed to compute indicators of thermal patterns associated with bleaching events 17 , 19 , 20 . Corals exposed to different thermal patterns are then sampled and genotyped to identify genetic variants correlated with these indicators 17 , 18 . The association between genetic variants and a given indicator defines a model of adaptation that can be used to predict the probability of adaptation, based on the value of the indicator itself 17 , 21 . In addition, by remote sensing sea current movements, it is possible to draw a connectivity map between every reef within an area of interest. This can be done using spatial graphs that resume multi-generational dispersal matching spatial patterns of genetic diversity in a given species 22 . This approach results in indices of connectivity defining, for a reef of interest, the predisposition in sending (outbound connectivity) and receiving (inbound connectivity) propagules to/from neighboring reefs 17 . In this study, we predicted spatial patterns of heat stress adaptation and connectivity for over 1000 km of coral reefs of New Caledonia, in the Southern Pacific (Fig. 1 ). The study area encompassed the barrier reef surrounding Grande Terre, the main islands of the Archipelago, as well as the intermediary and fringing enclosed in the lagoon. We also considered reefs surrounding the Loyalty Islands (Ouvéa, Lifou and Maré) and the Astrolabe (east of Grande Terre) and those in the Entrecasteaux and Petri atolls (north of Grande Terre). We first used remote sensing data to (1) evaluate the thermal variability of the study area and (2) estimate patterns of sea current connectivity between reefs. Next, we employed genomic data from a seascape genomics study on three coral species of the region 23 in order to (1) compute the probability of adaptation to heat stress across the whole region, and (2) verify whether predicted sea current connectivity between reefs matched the genetic structure of coral populations. Last, we compared our predictions with field surveys of living coral cover recorded by the New Caledonian observational network of coral reef (RORC 24 ). Our results suggest that negative effects of recent heat stress on coral cover are mitigated at reefs predicted with high probability of heat stress adaptation and inbound connectivity. We then discuss the conservation status of reefs around New Caledonia, and assess how conservation indices of probability of adaptation and connectivity can be used to protect the adaptive potential of corals of the region. Figure 1 Reef system of New Caledonia. Coral reefs are highlighted in green. The blue dots correspond to sites of coral cover survey of the New Caledonian observational network of coral reef 24 . The red dots correspond to the sampling locations of coral specimen (permits No 609011-/2018/DEPART/JJC and No 783-2018/ARR/DENV) for the seascape genomics study that provide genetic data in the present study 23 . Sea regions highlighted in purple correspond to the marine reserves and protected areas as catalogued by the French agency for MPAs ( https://www.aires-marines.fr/ ). Map prepared using R (v. 3.5 53 ).",
"discussion": "Discussion Local divergences in conservation indices The metrics computed in this study stressed the strong asymmetry, in terms of both probability of heat stress adaptation (PA HEAT ) and connectivity (inbound connectivity index, ICI; outbound connectivity index; OCI), between reefs on the two coasts of Grande Terre (Figs. 2 a, 4 ). The climatic differences between the two coasts are modulated by the mountain range covering Grande Terre, and water conditions inside the lagoon reflect the combination of these differences coupled with oceanic influences 25 . For example, the southern part of the west coast of Grande Terre is subjected to coastal upwelling, a seasonal phenomenon bringing cold water to the surface 26 . While logic would suggest that cold water alleviates heat stress, research on the Great Barrier Reef in Australia showed that intense upwelling is followed by severe heat stress, and consequent coral bleaching 27 . While it is unknown whether this same effect occurs on the south-western coast of Grande Terre, this region does enclose the reefs that are predicted to experience the highest frequency of bleaching conditions across New Caledonia, and consequently to host corals with the highest PA HEAT (Fig. 2 ). Asymmetrical spatial patterns between the coasts of Grande Terre were also predicted for connectivity (Fig. 4 ), and this matched the genetic population structure of corals of the region (Fig. 3 ). In this work, we estimated connectivity using a straightforward approach, conceived to be reproduceable on any reef system around the world but that might lead to local inaccuracies 17 . However, our predictions were generally consistent with previous work that characterized the regional water circulation around New Caledonia using more sophisticated methods (i.e. combining oceanographic models, in situ measurements and shipboard detectors of sea currents) 28 . For instance, we observed a higher inbound connectivity index (ICI) on the west coast of Grande Terre (Fig. 4 b), and a higher outbound connectivity index (OCI) on the east coast (Fig. 4 a). This west-oriented connectivity was expected because of the South Equatorial Current crossing the archipelago in this direction 28 . This current bifurcates at the encounter of the New Caledonian shelf into (1) a weak and transient south-east oriented current between the Loyalty Islands and Grande Terre, and (2) a strong north-west oriented current flowing north of the Loyalty Islands 26 , 28 , 29 . This bifurcation explains the lower OCI observed in Lifou and Maré, compared with Ouvéa and the Astrolabe atolls. Last, the water circulation inside the lagoon follows the north-west orientation of trade winds 26 , resulting in higher OCI in the south and higher ICI in the north. Predictions of reef connectivity and PA HEAT varied considerably across the different regions of the study area (Figs. 2 , 4 ), and conservation planning should account for these regional peculiarities 14 , 30 . In Table 1 , we interpret the local divergences in values of PA HEAT , ICI and OCI under a conservation perspective. Table 1 Implications for reef conservation in New Caledonia. The table describes the implications for reef conservation of the probability of heat stress adaptation (PA HEAT ), the outbound and inbound connectivity indices (OCI, ICI) predicted for different regions of the New Caledonia reef system. Information on the existing marine protected areas were retrieved from the French agency for MPAs ( https://www.aires-marines.fr/ ). Maps prepared using R (v. 3.5 53 ). \n The east coast of Grande Terre hosts reefs predicted with low ICI and PA HEAT . In contrast, OCI was generally higher than in the rest of the Archipelago. Reefs of strategic importance might be those located in the southern part as they had the highest OCI of the Archipelago, and also moderate levels of PA HEAT . To date, only 4 km 2 of reefs in this area are protected. In addition, the establishment of nurseries with heat stress adapted corals might increase the adaptive potential of these reefs \n Reefs on the west coast of Grande Terre generally displayed higher levels of ICI and PA HEAT , compared with the rest of the Archipelago. Under an adaptive potential perspective, reefs in the northern part are of paramount importance as they receive the propagules from all the south-western reefs that experienced frequent heat stress. No MPA is established in this area. Another strategic region are the reefs in front of Noumea, in the southern part of the west coast, since they were predicted with high PA HEAT and OCI. Here, more than 200 km 2 of protected areas are already established \n The South Lagoon displayed heterogenous patterns of PA HEAT and connectivity. The highest PA HEAT were observed in the south-western extremity, which in turn was a region predicted with low OCI. The eastern part might be more interesting under a conservation perspective, as it was predicted with moderate PA HEAT and high OCI. These reefs are located upstream of the trade winds, and can simultaneously send propagules to both coasts of Grande Terre. A large marine reserve (180 km 2 ) is already established to protect these reefs. As for the southern part of the east coast, coral nurseries of heat stress adapted colonies might increase the adaptive potential of this region \n Northern reefs and Entrecasteaux reefs were predicted with moderate to high levels of PA HEAT , and low values of OCI and ICI, compared with the reefs around Grande Terre. The critical region under an adaptive potential perspective might be the eastern part of Northern reefs. This is because these reefs depend on the incoming propagules from the east coast of Grande Terre, which are predicted with low PA HEAT \n The main conservation issue for all the reefs in this region is the low ICI. It is likely that arrival of propagules substantially depends on the reefs from Vanuatu (Fig. 1 ), located ~ 200 km upstream on the South Equatorial Current. Reefs in Ouvéa and Astrolabe atolls (already protected) might be of strategic importance, as they were predicted with moderate to high values of PA HEAT and OCI. Since reefs in Maré and Lifou showed low PA HEAT , establishment of nurseries with heat stress adapted coral might be useful under an adaptive potential perspective Predictions on adaptive potential match coral cover Heat exposure is considered to be one of the main drivers of coral mortality worldwide 11 , 31 , 32 . Our results were consistent with this view, as we found a significant negative association of coral cover with BAF previous year (Fig. 5 a). Adaptation might contribute to increase thermal tolerance in corals, but its potential depends on two elements: the existence of adapted corals and the presence of reef connectivity patterns facilitating their dispersal. In this study, we found both of these elements (PA HEAT and ICI) as associated with reduced loss of coral cover after thermal stress. Previous studies have reported reefs that display increased thermal tolerance after recurrent exposure to heat stress 7 – 11 , and recent research suggested that the thermal contrasts of New Caledonia might have driven adaptive processes in corals of the region 23 . Our results supported this view: while recent thermal stress (BAF previous year ) was associated with a reduction in coral cover, this reduction was mitigated at reefs that have experienced past thermal stress and were therefore predicted with high PA HEAT (Fig. 5 e). In addition, PA HEAT alone did not result in a significant association with coral cover rates (Fig. 5 b), and this might be due to the fact that thermal adaptation is advantageous only in response to heat stress. Indeed, previous research reported trade-offs in traits involved in local adaptation and acclimatization to heat stress in corals 33 . These trade-offs might explain why the highest rates of coral cover (> 0.4) in absence of heat stress (BAF previous year = 0) were mainly observed at reefs with low PA HEAT (Fig. 5 e). Outbound connectivity was not found to be associated with changes in coral cover (Fig. 5 c,f). This is not surprising, because beneficial effects of dispersal are expected at reefs receiving incoming propagules, rather than the opposite 16 , 34 . Indeed, inbound connectivity was found to mitigate the negative association between BAF previous year and coral cover (Fig. 5 g). Two non-mutually exclusive reasons might explain this observation. First, high levels of incoming propagules might facilitate the turnover of dead colonies caused by heat stress 35 , although it has to be noted that this kind of recovery usually requires several years 36 . Second, incoming dispersal facilitates the arrival of adapted propagules, and therefore promotes an adaptive response even at reefs that did not experience thermal stress before 37 . Indeed, we observed that the frequency of adaptive genotypes in A. millepora and P. acuta was generally higher at reefs predicted with low PA HEAT and high ICI, than in those predicted with both low PA HEAT and low ICI (Fig. S2). This view on genetic rescue via incoming migration is supported by the fact that every reef depends, to some extent, on its neighbors for larval recruitment 38 . Limitations and future directions The associations found between changes in coral cover and the descriptors of thermal stress, probability of heat stress adaptation and connectivity do not necessarily imply causative relationships. Despite evidence of effects of thermal patterns on coral cover reported by previous studies, there might be other environmental constraints that are asymmetrical between the two coasts of Grande Terre and modulate coral cover changes. Further validation remains necessary and could be achieved via experimental assays of heat stress resistance 8 in colonies sampled at reefs with different PA HEAT . This approach would also enable disentangling of the possible confounding role of acclimatization in heat stress adaptive responses 12 , 33 . Another important aspect to consider in future studies is the resolution of remote sensing datasets used for predictions. Here, we worked at a resolution of ~ 5 km for thermal variables and ~ 8.5 km for sea current data. While the overall environmental patterns appeared consistent with those characterized in previous studies, it is likely that small scale phenomena were neglected. For instance, reef heat stress exposure can vary substantially under the fine-scale (< 1 km) of a seascape 13 . The same applies to connectivity, since the use of high resolution (≤ 1 km) hydrodynamic models could improve the characterization of coral larvae fine-scale dispersal 39 , 40 . A third limitation of our approach concerns the generalization of the biological and ecological characteristics of a reef. Here we assumed that the reef system of New Caledonia was a single homogenous ecological niche, hosting an “average” species with an “average” heat stress adaptive response. This simplification is useful to portray an overall prediction, but might lead to local inaccuracies. This is because the reef types of New Caledonia are variegated and species distributions varies accordingly 41 , 42 . Furthermore, different species have different levels of bleaching sensitivity 43 and reproduce under different strategies 44 . For instance, the propagules of a broadcast spawning coral as A. millepora travel over longer distances, compared with those of brooding species as P. damicornis and P. acuta 45 . Consequently, the goodness-of-fit of models associating population structure and connectivity at the scale of New Caledonia was lower for A. millepora, when compared to the Pocillopora species (Fig. 3 ). Differences in the dispersal range can also modulate adaptive processes, since limited dispersal capabilities magnify the strength of natural selection 46 . The result are sharper gradients of adaptive genotype frequencies that in our study were not observed. Indeed, the accuracy in predicting the expected frequencies of adaptive genotypes did not significantly differ between species (Fig. S1 ), even though this observation might be biased by the unbalanced sample size between species 47 . In future studies, PA HEAT and connectivity predictions should be calibrated to match these biological differences. It is for this reason that seascape genomics studies will become of paramount importance into the future, as they provide species-specific indications on (1) how thermal stress might be translated in probability adaptation, and (2) the biological meaning (e.g. degree of genetic separation) of a cost distance by sea currents 17 , 18 . Conclusions In this study, we combined remote sensing of environmental conditions with genomic data to predict spatial patterns of heat stress adaptation and connectivity for the coral reefs of New Caledonia. We then retrieved field survey data and showed that recent heat stress was associated with a decrease in living coral cover, but also that such association appeared to be mitigated at reefs predicted with (1) high probability of heat stress adaptation and (2) high levels of incoming dispersal. The metrics computed in this work resumes the adaptive potential of corals against heat stress, and therefore represents valuable indices to support spatial planning of reef conservation."
} | 5,131 |
35508975 | PMC9066861 | pmc | 3,340 | {
"abstract": "Background The rising temperature of the oceans has been identified as the primary driver of mass coral reef declines via coral bleaching (expulsion of photosynthetic endosymbionts). Marine protected areas (MPAs) have been implemented throughout the oceans with the aim of mitigating the impact of local stressors, enhancing fish biomass, and sustaining biodiversity overall. In coral reef regions specifically, protection from local stressors and the enhanced ecosystem function contributed by MPAs are expected to increase coral resistance to global-scale stressors such as marine heatwaves. However, MPAs still suffer from limitations in design, or fail to be adequately enforced, potentially reducing their intended efficacy. Here, we address the hypothesis that the local-scale benefits resulting from MPAs moderate coral bleaching under global warming related stress. Results Bayesian analyses reveal that bleaching is expected to occur in both larger and older MPAs when corals are under thermal stress from marine heatwaves (quantified as Degree Heating Weeks, DHW), but this is partially moderated in comparison to the effects of DHW alone. Further analyses failed to identify differences in bleaching prevalence in MPAs relative to non-MPAs for coral reefs experiencing different levels of thermal stress. Finally, no difference in temperatures where bleaching occurs between MPA and non-MPA sites was found. Conclusions Our findings suggest that bleaching is likely to occur under global warming regardless of protected status. Thus, while protected areas have key roles for maintaining ecosystem function and local livelihoods, combatting the source of global warming remains the best way to prevent the decline of coral reefs via coral bleaching. Supplementary information The online version contains supplementary material available at 10.1186/s12862-022-02011-y.",
"conclusion": "Conclusions Collectively, our findings add to the growing evidence that protected status will have little impact for alleviating the effects global stressors such as marine heatwaves which will continue to be exerted on coral reefs. While the implementation of effectively designed MPAs can be beneficial for coral cover and maintaining functional species [ 22 , 25 ], and most critically support communities dependent on coral reefs [ 49 ], they will not mitigate the effects of coral bleaching induced by global warming [ 22 , 30 ]. Consequently, actions targeting the source of rising global temperatures (i.e. greenhouse gas emissions) remains the most effective way to moderate future coral bleaching caused by global warming, and thus mitigating continued global coral reef decline [ 11 , 22 , 39 , 50 ].",
"introduction": "Introduction Rising ocean temperatures and increased frequency and duration of marine heatwaves [ 1 ] are causing the decline of coral reefs at alarming rates via coral bleaching [ 2 , 3 ]—the process whereby photosynthetic endosymbionts are expelled, revealing the coral skeleton [ 4 – 8 ]. Sustained ocean heat stress can lead to mass bleaching events which may result in mortality of entire coral colonies [ 3 , 9 , 10 ]. If lethal bleaching occurs, the loss of coral cover results in habitat homogenisation and consequently reduced biodiversity [ 10 , 11 ]. Ultimately, such reductions in coral reef biodiversity inhibits the ecosystem function of coral reefs, critical for supporting > 25% of marine species [ 12 ] and for providing ecosystem services to over 100 million people circumtropically [ 13 ]. While global warming is unequivocally the predominant driver of mass coral bleaching, a myriad of local scale factors can also induce bleaching of corals. Factors such as turbidity [ 14 , 15 ], eutrophication [ 16 , 17 ], hypoxia [ 16 , 18 ], and sedimentation [ 14 ] have been documented to independently induce coral bleaching. However, pioneering studies identified reduced mortality from coral bleaching under higher levels of sedimentation when exposed to heat stress, likely as a result of reduced solar irradiance [ 14 ]. Yet, bleaching is known to occur under high temperature regimes regardless of irradiance [ 19 ]. Despite convoluted evidence of these interactions influencing bleaching, a widespread expectation that these local stressors interact either additively or synergistically with global warming to exacerbate coral bleaching exists, with field evidence from Mesoamerican reefs [ 20 , 21 ], and French Polynesia [ 17 ]. To mitigate the additive effects of local scale stressors on marine biodiversity overall, Marine Protected Areas (MPAs) have been implemented across different regions of the world, which when effectively designed, are established to enhance regional biodiversity and general ecosystem health [ 22 ]. Large and long-established MPAs are often especially effective for enhancing multiple metrics used for monitoring ecosystem health [ 23 , 24 ], such as coral cover [ 25 ], fish biomass [ 26 ] and biodiversity [ 22 ]. For corals specifically, the role MPAs perform for reducing local stressors intend to enhance coral health through a variety of physiological mechanisms [ 27 ], thereby promoting resistance of reef building corals to disturbance. Furthermore, MPAs have the potential to promote resilience to disturbance events, such as marine heatwaves, disease outbreaks, and hurricanes, via ecological processes [ 28 ]. This enhanced resilience intrinsically promotes resistance to future bleaching by facilitating full recovery from bleaching before the next disturbance event [ 11 ]. Given that marine heatwaves and bleaching events are increasing in frequency and intensity through time [ 1 , 2 , 11 , 29 ], the benefits of MPAs for promoting resilience in reef building corals are subsequently crucial for also enhancing the resistance of corals to future bleaching—i.e. managed resilience [ 22 ]. However, the effects of MPAs for mitigating coral reef decline remain contested. For example, decline in coral cover attributed to thermal stress is not mitigated by MPAs [ 30 ], suggesting that the preservation of coral reefs does not depend significantly on MPAs, but on actions that mitigate the degree of climate warming [ 22 , 31 ]. Furthermore, multiple stressors on coral reefs tend to be antagonistic rather than synergistic, especially interactions between local stressors, and global warming [ 22 , 32 – 35 ]. This is likely owing to co-sensitivity and co-tolerance of coral species exposed to stressors, along with the frightening prospect that climate warming eclipses the potential advantages that could be expected to result from the mitigation of local stressors [ 31 ]. Given both the convoluted relationship between global and local stressors exerted on coral reefs, along with the diversity of primary objectives different MPA’s aim to achieve, it is crucial to discern whether MPA’s have any moderation effect on bleaching under global warming. However, an explicit global scale test to examine the prevalence of bleaching in relation to their protected status remains lacking. To test this hypothesis for coral bleaching specifically, we examine (1) the probability of coral bleaching under thermal stress (quantified as Degree Heating Weeks, DHW) for key MPA attributes—the size and age of MPAs, using a Bayesian Generalised Linear Mixed Model; (2) implement quantitative comparisons of bleaching prevalence on coral reefs within and outside protected regions under different levels of thermal stress; and (3) compare thermal thresholds where the onset of bleaching occurs between protected and non-protected coral reefs based on the gamma distributions of DHWs. To address this hypothesis we utilise a global scale data set containing 8,766 coral bleaching surveys (Fig. 1 ) over a 16 year period. \n Fig. 1 The richness and global scale distribution of Reef Check surveys used to examine the effects of MPAs on coral bleaching. a Represents 5393 surveys which do not fall within an MPA. b Are the 3391 surveys which do fall within the jurisdiction of an MPA",
"discussion": "Discussion Our analyses reveal that MPAs play a negligible role in mitigating the onset of coral bleaching when under climate change related thermal stress. However, weak evidence for moderation under the interaction of DHW with MPA size, and MPA age, in comparison to the sole predictor of DHW does exist (Fig. 2 ). Crucially, however, bleaching is still predicted to occur under these interactions. Given our findings, with no discernible difference in temperatures where the onset of bleaching occurs, we expect that coral resistance to thermally induced bleaching is unlikely enhanced by the implementation of protected status. These findings are in accordance with previous studies investigating loss of coral cover within MPAs under climate change [ 30 ], and further challenge the assumed benefits of managed resilience for promoting resistance in corals to guide reefs through the gauntlet of climate change [ 22 , 31 ]. Given the similar bleaching responses between coral reefs residing within and outside MPAs, our findings add to the growing complexity of the relationship between local and global scale stressors for degrading coral reefs. Comparable levels of bleaching where no temperature stress is present (0 DHW category) indicates no difference in bleaching under ambient conditions, which is likely a result of localised conditions [ 29 ], survey error [ 37 ], and perhaps lack of recovery from a previous disturbance event - i.e. non-branching corals which are able to survive longer while bleached [ 38 ]. Furthermore, an identical thermal threshold where the onset of bleaching occurs suggests there is a not a synergistic relationship between local and global factors which exert stress onto coral reefs. Non-synergistic and antagonistic relationships have been widely reported on coral reefs over the last 10 years [ 32 – 34 ] challenging the previous supposition that stressors exerted onto coral reefs act synergistically [ 39 ]. Our findings could indicate that bleaching is unlikely to be synergistically exacerbated by local stressors [ 35 ], which are assumed to be moderated by MPAs, given the identical bleaching responses between MPA and non-MPA environments (Fig. 4 ). It is likely that the effects of climate change are far eclipsing the role of localised stressors and thus localised mitigation [ 11 , 22 , 40 ]. It should be noted, however, that many MPAs are not adequately managed in many marine regions [ 41 ], and have aims focused on social-economic and biodiversity benefits [ 42 ], thus our findings may also reflect this. Furthermore, owing to the spatial variability of coral bleaching [ 29 ], which is often specific to a wide range of factors such as turbidity [ 43 , 44 ], internal waves [ 45 , 46 ], evolutionary history [ 47 ], and ecological memory [ 48 ], exceptions to the global scale pattern will exist [ 20 , 21 ]. Our findings also identify insufficient evidence to support the managed resilience hypothesis for reef corals, because bleaching responses are similar between MPA and non-MPA sites (Figs. 3 , 4 ). Consequently, our findings suggests that the resistance of reef building corals will not be enhanced through the implementation of MPAs, which aim to mitigate local stressors and ameliorate physiological performance of corals [ 27 ]. However, it is critical to note there are many other benefits of MPAs which ensure food provision, vital for human livelihood, and maintain biodiversity which is critical for ecosystem function around the globe [ 23 , 24 , 42 ]. Yet, the assumption that MPAs will help support coral reefs by preventing impacts of warming (i.e. bleaching) on corals is likely incorrect based on these findings. Rather, continued warming linked to anthropogenic activity will incessantly bleach corals more often through the Anthropocene [ 2 ] regardless of protected status."
} | 2,978 |
37653875 | PMC10223382 | pmc | 3,341 | {
"abstract": "Iron is an essential element for most organisms. Both plants and microorganisms have developed different mechanisms for iron uptake, transport and storage. In the symbiosis systems, such as rhizobia–legume symbiosis and arbuscular mycorrhizal (AM) symbiosis, maintaining iron homeostasis to meet the requirements for the interaction between the host plants and the symbiotic microbes is a new challenge. This intriguing topic has drawn the attention of many botanists and microbiologists, and many discoveries have been achieved so far. In this review, we discuss the current progress on iron uptake and transport in the nodules and iron homeostasis in rhizobia–legume symbiosis. The discoveries with regard to iron uptake in AM fungi, iron uptake regulation in AM plants and interactions between iron and other nutrient elements during AM symbiosis are also summarized. At the end of this review, we propose prospects for future studies in this fascinating research area.",
"introduction": "1. Introduction Iron, as one of the most abundant elements on earth, is an essential element for most organisms since it functions as an indispensable co-factor of many enzymes in various crucial metabolic processes [ 1 ]. In plants, iron deficiency results in reduced chlorophyll synthesis and photosynthesis, and causes chlorosis and dramatic growth defects. To obtain sufficient iron from soil, plants evolved different strategies for effective iron uptake and homeostasis. The first one is the reduction strategy (Strategy I), which is widely used in all non-graminaceous plants. The second one is the chelation strategy (Strategy II), which is applied by graminaceous plants [ 2 ]. Compared with plants, microorganisms engage high-affinity and low-affinity uptake systems for iron uptake [ 3 , 4 ]. The high-affinity uptake pathways include the siderophore-mediated iron uptake pathway and the reductive iron assimilation (RIA) pathway [ 4 ]. The low-affinity uptake pathways include the iron-containing protein (e.g., heme, ferredoxin) uptake pathway and the ferrous iron uptake pathway. In general, the high-affinity uptake pathways are adopted by microorganisms when limited iron is available. In contrast, when iron is sufficient, the low-affinity pathways are applied by microorganisms. Plants and microorganisms in the rhizosphere recruit their own ways to acquire iron from soil until an infection or a symbiosis event takes place between them. In the competition of host plants with pathogens, iron also plays an important role in restricting pathogen growth either by the overaccumulation of iron at the pathogen attack site to induce ROS burst, which leads to the infected cell’s death [ 5 , 6 ], or by withholding iron out of the vicinity of the infection site [ 2 , 7 ]. Symbiosis between a plant and microorganism is a very common phenomenon in nature. In the symbiont, both the plant and microorganism can obtain nutrients from each other, supporting better growth and development. For example, leguminous plants obtain ammonia from symbiotic rhizobia and bacteria obtain carbon compounds from host plants. Similarly, AM fungi supply nitrogen and phosphate to host plants and host plants provide lipids to mutualistic AM fungi [ 8 , 9 ]. Therefore, symbiosis is very important for both mutualistic microorganisms and host plants. In the symbiosis, such as legume–rhizobium and plant–arbuscular mycorrhizal (AM) fungi, iron is coordinated as an important micronutrient for both plants and symbiotic microbes. For legume–rhizobium symbiosis, iron is an essential co-factor for the nitrogenase and the enzymes of the bacterial respiration. A large amount of iron has to be transported from the roots to the bacteroids to support symbiotic nitrogen fixation (SNF). In the last thirty years, many studies focused on this process have been conducted. For the plant–AM fungi symbiosis, recent studies revealed that AM symbiosis can influence the iron uptake of plants. However, the iron transport mechanisms between the plants and AM fungi are still unknown. In this review, we introduce the iron transportation mechanism in the symbiosis and interaction between the plants and symbiotic microbes in terms of the iron uptake, transport and homeostasis."
} | 1,059 |
22214379 | PMC3311593 | pmc | 3,342 | {
"abstract": "Current-generating (exoelectrogenic) bacteria in bioelectrochemical systems (BESs) may not be culturable using standard in vitro agar-plating techniques, making isolation of new microbes a challenge. More in vivo like conditions are needed where bacteria can be grown and directly isolated on an electrode. While colonies can be developed from single cells on an electrode, the cells must be immobilized after being placed on the surface. Here we present a proof-of-concept immobilization approach that allows exoelectrogenic activity of cells on an electrode based on applying a layer of latex to hold bacteria on surfaces. The effectiveness of this procedure to immobilize particles was first demonstrated using fluorescent microspheres as bacterial analogs. The latex coating was then shown to not substantially affect the exoelectrogenic activity of well-developed anode biofilms in two different systems. A single layer of airbrushed coating did not reduce the voltage produced by a biofilm in a microbial fuel cell (MFC), and more easily applied dip-and-blot coating reduced voltage by only 11% in a microbial electrolysis cell (MEC). This latex immobilization procedure will enable future testing of single cells for exoelectrogenic activity on electrodes in BESs.",
"introduction": "Introduction Bioelectrochemical systems (BESs) are based on electron transfer between microbes and an electrode surface. Most investigations into the mechanisms of electron transfer from a microbe to an anode have focused on two microorganisms, Geobacter sulfurreducens (Marsili et al. 2008; Holmes et al. 2006; Strycharz et al. 2010; Inoue et al. 2010; Nevin et al. 2009; Srikanth et al. 2008 ) and Shewanella oneidensis ( Bretschger et al. 2007 ; Gorby et al. 2006 ), where it has been shown that specific genes and proteins are involved in exogenous electron transfer. Further study of current-generating (exoelectrogenic) bacteria and biofilms will benefit from isolating and identifying other microorganisms that are capable of electron transfer to an electrode. Isolation techniques to identify novel exoelectrogens have typically involved dilution-to-extinction in BESs, or isolation on ferric iron agar plates. A U-tube reactor was developed ( Zuo et al. 2008 ) that would allow a single microbe, obtained by serial dilutions, to deposit by sedimentation onto a flat anode surface. This technique was used to identify novel exoelectrogens Ochrobactrum anthropi YZ-1 ( Zuo et al. 2008 ) and Enterobacter cloacae FR ( Rezaei et al. 2009 ). However, the cumbersome process required many serial transfers to obtain these isolates. A microbe related to Clostridium butyricum was isolated from a microbial fuel cell (MFC) using ferric iron agar plates ( Park et al. 2001 ), but this method of isolation does not target all exoelectrogens as some microbes have been isolated that can generate current but not reduce iron ( Kim et al. 2004 ; Zuo et al. 2008 ). In addition to spread-plating techniques, screening of arrays of microorganisms on ferric iron agar plates is possible through printer technology ( Ringeisen et al. 2009 ). This approach can be used to print very small droplets of a cell suspension diluted to contain single microbes. To take advantage of this technology, for example by printing single cells in a grid pattern onto an electrode for isolation, a robust immobilization layer is required to bind the cells to the electrode so that they do not move after application to the electrode surface. This layer should not interfere with the ability of microbes to transfer electrons to an electrode surface, or with the diffusion of substrate to the cells. Latex films were evaluated here to see if they could be used to fulfill these requirements. Latex films have previously been used to entrap microbes on non-conducting surfaces, producing a high density of organisms in a thin film that survived freezing and drying ( Gosse et al. 2007 ; Lyngberg et al. 1999 ; Flickinger et al. 2007 ). We show here effective entrapment of bacteria-sized particles using fluorescent microspheres, and demonstrate that latex entrapped anode biofilms allow exoelectrogenic activity.",
"discussion": "Discussion Latex films were shown be effective in holding individual particles (fluorescent microspheres) or active biofilms on electrically conductive surfaces. Microbes trapped on two different surfaces (carbon paper and graphite block) using different application methods (airbrushing and dip-and-blot) retained most of their exoelectrogenic capability. On both surfaces, and in both MFC and MEC reactors, increasing the amount of latex applied onto the biofilm adversely affected the ability of the anode to recover exoelectrogenic activity to pre-application current levels ( Lyngberg et al. (2001) ). found that effective diffusivity through the latex was highly dependent on layer thickness. Therefore, this decrease in activity was likely due to a reduction in mass transfer to (substrate) and from (protons) the biofilm with thicker layers of latex. The latex coating thickness, measured by dry weight, on the graphite block was less than that of the graphite paper, and the full strength latex coating did not stick well to the block. The coating on the carbon paper when applied by the air brush to the MFC anode or the dip-and-blot method (at 30% strength) to the MEC anode was similar (slightly more than 2 mg/cm 2 /layer). While the MFC regained 100% of its pre-application performance, the MEC was limited to about 89% of its pre-application performance. It is unlikely that there was any decrease in the performance of the MEC in these experiments due to exposure of the biofilm to oxygen during the latex application, as MEC biofilms are routinely exposed to air when it they are refilled (often intentionally to reduce methanogenesis) without adverse affects to current production ( Call and Logan 2008 ). In addition, the biofilm in an MFC is routinely exposed to oxygen in air due to oxygen diffusion through the cathode and into the anode chamber without apparent adverse effects. If desired, the latex film could be applied under strictly anoxic conditions in an anaerobic glove box. Previous work with bio-catalytic films used for hydrogen gas production has shown that the coating itself is not adversely affected by the presence or absence of air, nor is the performance of that biofilm ( Gosse et al. 2007 ). However, it is possible that some strict anaerobes might be affected by oxygen during this procedure, so anaerobic application of the latex biofilm may be of interest in future studies. The ability to immobilize microbes on an electrode using a latex film has two valuable applications for BESs, but for successful application in BESs, immobilization of microbes on electrodes must not interfere with the ability of cells to transfer electrons. Bioelectrochemical features seen in cyclic voltammograms of pectin-entrapped Geobacter biofilms have been shown to be similar to naturally-grown Geobacter biofilms ( Srikanth et al. 2007 ). This suggests that entrapment by itself is not changing the electrical capability of the cells, although they found current was somewhat decreased as observed here as well. One application of an immobilization layer for cells on a BES electrode is isolation of microbes directly on an electrode. This requires immobilization of an array of single cells, without greatly compromising current generation, which our latex overlay achieves. In addition, a biofilm of specific microbes can be developed on an electrode in a controlled setting, immobilized and protected under a latex coating, and then introduced to a more complex, non-sterile environment. Under the coating, these organisms would not have to compete with other microbes for the electron-accepting surface. Exoelectrogenic biofilm activity under a glycerol-amended latex film can be restored to nearly the same levels as pre-application activity, making it a suitable immobilization layer for these applications."
} | 2,005 |
30245550 | PMC6147227 | pmc | 3,344 | {
"abstract": "Graphical processing units (GPUs) can significantly accelerate spiking neural network (SNN) simulations by exploiting parallelism for independent computations. Both the changes in membrane potential at each time-step, and checking for spiking threshold crossings for each neuron, can be calculated independently. However, because synaptic transmission requires communication between many different neurons, efficient parallel processing may be hindered, either by data transfers between GPU and CPU at each time-step or, alternatively, by running many parallel computations for neurons that do not elicit any spikes. This, in turn, would lower the effective throughput of the simulations. Traditionally, a central processing unit (CPU, host) administers the execution of parallel processes on the GPU (device), such as memory initialization on the device, data transfer between host and device, and starting and synchronizing parallel processes. The parallel computing platform CUDA 5.0 introduced dynamic parallelism, which allows the initiation of new parallel applications within an ongoing parallel kernel. Here, we apply dynamic parallelism for synaptic updating in SNN simulations on a GPU. Our algorithm eliminates the need to start many parallel applications at each time-step, and the associated lags of data transfer between CPU and GPU memories. We report a significant speed-up of SNN simulations, when compared to former accelerated parallelization strategies for SNNs on a GPU.",
"introduction": "1 Introduction 1.1 Neurocomputing on GPUs Early GPUs were initially developed and produced for computer graphics, and in particular for video processing and computer gaming. They were built to maximize the device throughput by computing the same function on large quantities of data in parallel. GPUs can speed up computations by running a single instruction on multiple data points simultaneously (SIMD). As such, GPUs have been shown to accelerate computationally demanding complex problems, ranging from game physics to computational biophysics [ 1 ]. Theoretical neuroscientists have exploited the use of general purpose computing on GPUs, in neural field model computations and spiking neural network simulations [ 2 ]. Using GPUs as vector processors has recently been adopted for SNN simulators, in order to speed up large-scale simulations, such as NeMo [ 3 ], NCS6 [ 4 ], and GeNN [ 5 ]. However, the advancements in general purpose GPU computing is not yet fully adopted by these simulators. Time-driven SNN simulations follow a simple routine at every time-step that can be broken down into three major steps: (i) state update, (ii) spike thresholding, and (iii) spike propagation. The state update changes the time-dependent variables of all neurons in the network, according to a set of differential equations, in which each neurons membrane potential is computed on the basis of its internal dynamics, synaptic inputs and externally applied currents. Spikes are detected from the updated membrane potentials: if a neurons membrane potential exceeds its spiking threshold, it is reset to its resting state, and a spike event is stored in memory. The spike-propagation step calculates the post-synaptic effect of each spike on the connected neurons. Usually, this step is implemented by a weight-matrix multiplication to the synaptic input values of the post-synaptic neurons. Parallel computing can vastly accelerate the calculations, when these processes are carried out simultaneously. In the optimal scenario, the calculated variables are independent of each other. For SNN simulations, the membrane-potential update and the spike thresholding steps are so-called embarrassingly parallel problems. The state-update and thresholding functions ( kernels ) can therefore readily run in parallel for individual neurons with different input values or parameters that specify each neurons biophysical properties. However, synaptic communication across the network is considered to be the bottleneck in parallelization [ 6 , 7 ], as it requires a pass through all synapses of the network to update the effect of spikes on the post-synaptic neurons. Different parallelization strategies have been designed for GPUs (reviewed in [ 8 ]) with the aim to vectorize these calculations: across neurons [ 9 ], or across spikes and synapses [ 3 ]. However, these strategies all have in common that they run many obsolete operations in each time-step, as they typically include also the silent (non-spiking) neurons in the network. Especially, since spikes are relatively infrequent events compared to the size of the network and to the number of time-steps, most computations in existing algorithms introduce substantial additional idle time that merely keeps the computing cores busy. The same problem exists in spiking neural network simulations on other parallel computing architectures [ 10 ]. This problem has partly persisted as a result of technical limitations in GPU programming. General-purpose GPUs have become common for large-scale computational problems. Yet, they pose limitations on the implementation of parallel algorithms as a consequence of the hardware architecture. In particular, memory-handling on the GPU differs from the serial applications that run on the central processing unit (CPU). As GPUs have their own memory, they require that all the data, used for the computations, are available on the devices memory. Even though the GPU (device) parallelizes the computations, the CPU (host) manages the applications, such as the data transfer between host and device, memory initialization on the device, the initiation of new parallel processes, and the synchronization between parallel processes. This task requires either the device-to-host memory transfer of the spiking neuronsâ;; indices at each time-step, and to initiate the synaptic update kernels for spikes, or to check all synapses in the network to update the spike effects, in case there was a presynaptic spike. CUDA (Compute Unified Device Architecture) allows the implementation of dynamic parallelism [ 11 ], which allows a CUDA kernel to create nested parallel processes on the GPU. When applied to a SNN, this would allow the start of a new parallel operation to update the synaptic values of post-synaptic neurons, only if a neuron emitted a spike. In this way, it would potentially speed-up the simulations, by eliminating idle calculations. Here, we test an implementation of dynamic parallelism, applied to spike propagation across a SNN. We demonstrate a significant speed-up from dynamic parallelism in a pulse-coupled network of Izhikevich neurons [ 12 ]. The network consists of randomly connected excitatory and inhibitory neurons, which are driven by stochastic input. The same network has recently been used as a benchmark to test the SNN simulator GeNN [ 5 ] on different GPU devices. 1.2 Parallel computing on GPUs A GPU comprises of a GPU chip, and a synchronous graphics RAM (SGRAM, Fig. 1A ). The GPU chip contains organized sets of streaming multiprocessors, coupled with on-chip registers and read-only texture memories that are private to each processor. The shared memory can be read and written by all processors belong to the same multiprocessor. The SGRAM is used for processor-specific local memory, and for global memory to which each processor has access rights. The access speed and allotted size of these memories will differ. While global memory has the largest space, it has the narrowest bandwidth. Yet, the host can only access the global memory on the SGRAM. General purpose GPUs typically use C-language programming with application programming interfaces (APIs). Commonly used APIs are NVIDIA CUDA and OpenCL. Here, we will focus on CUDA terminology, for consistency. CUDA provides a set of extension functions to allow the programmer to use computing and memory resources of the GPU. These helper functions allow programmers to allocate memory on the device, transfer memory between device and host, and manage the parallel execution of kernels written in C++. Parallel computing follows SIMD parallelism (single-instruction multiple data points), where the individual processors run the same instructions on different data points. The instruction code is termed a kernel , as it is the building block of a parallel application. A kernel executes its code simultaneously across a set of parallel threads. A threading structure consists of the arguments and data addresses on the device that will be used by the kernel, and determines a hierarchy of grids of blocks ( Fig. 1B ) that run in parallel. Each thread runs the same kernel, with its unique id, which is used to access and manipulate unique elements in an array or matrix. A thread block is a set of threads that can cooperate through barrier synchronization and access a shared memory (private to that block). A grid is a set of thread blocks that can be executed independently, and only share access to the global memory. Different thread blocks can be executed independently, in arbitrary order. However, within each block, 32 threads ( warps ) run in parallel, and multiprocessors regulate their execution. When a warp is stuck, the multiprocessor can quickly switch to another available warp to reduce idle time. The GPU scheduler will map the thread blocks onto the multiprocessors, based on the threading structure, and it maintains task efficiency by keeping busy as many cores as possible at any given time [ 13 ]. These conceptual differences introduce new challenges that affect programming style. For instance, a race condition arises when concurrent threads need to write to the same memory address. Hypothetically, both may read the same value at the same time, do their own computations on the data, and write one after another to the same location ( Fig. 1C ). In this case, the result from the thread that wrote last will survive, and the computations by earlier threads will be discarded, leading to erroneous results. Such conflicts should be foreseen during code development; writing into a given memory location should thus be sequenced. CUDA API provides atomic operations and memory locks to handle such often-encountered programming problems. Coalesced memory access refers to combining multiple memory accesses into a single transaction ( Fig. 1D ). When data is organized in the global memory such that the concurrent threads in a warp access contiguous memory locations, then, the whole chunk of memory can be called at once for all threads in a warp. While on earlier GPUs the computing capabilities required aligned and sequential memory calls from a warp (128 bytes for 32 threads), for coalesced memory access, compute capability 3.0 also supports non-sequential accesses if they are aligned ( Fig. 1D , bottom). Unaligned access patterns do not benefit from memory coalescing for efficient memory calls. Further, coalesced memory access may not always be applied for all algorithms, while un-coalesced access may not be critical for enhanced performance. Yet, especially the algorithms that require repetitive memory accesses will benefit from coalesced memory accesses to improve performance. In the optimal scenario, (1) the calculated variables would be independent of each other, (2) the data size handled by each processor, and the computational load on the functions (kernels) that process the data, would be balanced, (3) memory access within the device, and memory transfers between device and host would be optimized. 1.3 Parallel synaptic updating schemes We propose a novel parallelization strategy, which utilizes dynamic parallelism for synaptic updating in SNN simulations. To evaluate performance of our algorithm, we compared it to two earlier applied parallel updating algorithms ( Fig. 2 ): (1) parallelization across neurons, in which the synaptic currents are calculated for individual neurons in parallel [N-algorithm; Fig. 2A ; 9 , 14 ], and (2) parallelization across synapses, which updates the synaptic currents for each synapse in parallel [S-algorithm; Fig. 2A ; 15 ]. In contrast, our new algorithm updates all post-synaptic currents for each action potential in parallel (AP-algorithm; Fig. 2B ). We compared the performance of the three algorithms for different network sizes, by varying the number of neurons ( N ), and the number of synapses per neuron ( S ) in the network, and for different spiking regimes, by varying the activity states in the networks. Each algorithm updates the neural states by N threads. Based on the total current acting on a neuron at a time-step, membrane potential is updated by the differential equation describing the neuron model. If the membrane potential crosses spiking threshold, the spike is recorded to be propagated to the postsynaptic connections. While N- and S-algorithms update synapses at a separate step after state updates are finished for all the neurons, AP-algorithm starts nested processes ( Fig. 2 ). This paradigm difference already decreases computation time, because the neural state update computations must be completed for all neurons to continue with spike propagation in N- and S-algorithms. The threads which complete their calculations earlier wait for the rest of the threads to finish. Therefore, synchronization between neural state update and synaptic update steps hurts throughput. However, the main novelty of the AP-algorithm is the use of dynamic parallelism for spike propagation and decreasing number of running threads per time-step. Both the N-algorithm and the S-algorithm parallelize the matrix multiplication for synaptic updates. They both calculate an update for each existing synapse in the network ( Fig. 2A ). The N-algorithm starts N threads (across neurons), which each iterate over S synapses to update postsynaptic currents for the neurons that elicit a spike. The S-algorithm recruits N × S threads (across synapses), which each updates the postsynaptic current if there was a presynaptic spike. It is apparent that these two algorithms allot the work in different ways to individual threads. Yet, both algorithms check if there was a presynaptic spike at a connection, and update the postsynaptic current for each synapse with a presynaptic spike. The difference is; the N-algorithm updates the postsynaptic currents with fewer threads, but with more computations per thread, when compared to the S-algorithm. Therefore, the computation duration increases with the number of synapses. The AP-algorithm combines neuron state update and postsynaptic update steps. It utilizes dynamic parallelism to update all postsynaptic currents from a neuron, whenever it produces an action potential. Each time a neurons membrane potential crosses the spiking threshold, a new set of children threads are triggered ( Fig. 2B ). Postsynaptic updates are delivered by S threads, each updating one synaptic end. Therefore, the number of spikes become the main determinant of the number of calculations to be done. AP-algorithm starts S × (# of spikes) threads in total per time-step. Each thread updates a postsynaptic current as in S-algorithm. Compared to the N- and S-algorithms, the AP-algorithm combines spike thresholding with synaptic updating, and thus eliminates the overhead synchronization delays as well. AP-algorithm executes synaptic updates as the spikes occur. We will demonstrate that each algorithm will have its own optimal performance conditions. As we define algorithm performance by the computation time needed to update the postsynaptic currents, the fastest algorithm is considered the best. The execution time of each time-step is determined by two factors: (i) the time needed for a thread to complete its task, and (ii) the occupancy of GPU multiprocessors. A threads runtime depends on the computational load of its kernel; when a kernel must perform many calculations and memory accesses per time-step, it increases processing time. The occupancy of GPU multiprocessors deduces to how well the task is distributed over the streaming cores to increase throughput. Since the threads are mapped onto the multiprocessors by the GPU scheduler, the more threads there are, the longer it takes for the network to finish.",
"discussion": "4 Discussion In this paper, we quantified the performance of three different parallelization algorithms for the simulation of spike propagation within spiking neural networks on a GPU. We showed that the simulation runtimes were highly susceptible to the number of synapses for simulations with the N- and S-algorithms, whereas the spike count was the prominent determinant of simulation runtime for the AP-algorithm. As a result, the AP-algorithm outperforms the other two algorithms when the spike occurrence is sparse in relation to the network size (the total number of neurons and synapses), and to the number of simulation time-steps. We employed a network architecture of pulse-coupled Izhikevich neurons for the SNN simulations [using the same implementation on CUDA as in 12 ], because this approximate network model allows for easy scalability by varying the number of neurons ( N ) and synapses ( S ), while preserving sufficient complexity and variation of different neural states within the network, and easy control of the total spike counts. However, the simulations had a relatively poor time-resolution (time-steps at 1 ms intervals), while at the same time this simple neuronal model had already been computationally optimized [ 12 ] to explain a variety of complex physiological behaviors of neurons under different input and biophysical conditions. The network is thus able to capture different states of synchrony within populations of randomly connected neurons (as coupled nonlinear oscillators). Note that alternative neural models, which require much higher time precision, will result in many more computations per thread for the neural-state updating steps. This would happen, for instance, when the research question demands more computations per time-step, by including ion-channel-specific computations as in Hodgkin–Huxley model neurons [ 4 , 16 ], or when considering current propagation through geometrically complex dendritic trees [ 17 , 18 ]. Such architectures and models would require more computations per time-step simply because of the increasing complexity of the models to update neural states or synaptic propagation. Accounting for spike-time-dependent plasticity [ 19 ], or when modeling the high-frequency bursting behavior of neurons in the midbrain Superior Colliculus [ 20 , 21 ] would also require additional computations or fine-grained time resolutions, and thus more computations and performance. Also the new class of evolving SNNs require additional computations per time-step [ 22 ] and multiple network classes. As long as the spike propagation follows delivery of discrete pulses to a subset of the all neuron population in the network, dynamic parallelism would accelerate GPU based simulations. Because, also under these more demanding dynamic requirements, spikes would be elicited more sparsely during the whole simulation. Because the AP-algorithm eliminates the need to compute synaptic updates for neurons that do not elicit a spike, it will readily speed-up such more demanding simulations. However, this is only valid for spiking neural network implementations. Most of the other neural network modelling frameworks for deep neural networks and machine learning applications are already utilizing GPUs (Torch [ 23 ], Tensorflow [ 24 ], supported by CUDA cuDNN library in the backend talking to GPU devices [ 25 ]). We explored the idea of dynamic parallelism for synaptic updating in SNN simulations, by comparing its performance to the two parallelization strategies that are currently available in the literature. However, it should be noted that the actual simulation durations for all three algorithms were longer than reported here because of the considerable time needed for the random number generations, and memory transfers prior to, and following the main simulation loops. The generation of random numbers to initialize the neural parameters and their connectivity within the network introduced considerable latencies, and depended strongly on the number of neurons and synapses in the network. Furthermore, the random number generators that were used for each time-step to provide the time-varying stochastic input current to each neuron, occupied a large portion of the device memory. However, since here we focused on performance differences between the three algorithms, we merely considered the execution time of each time-step from the start of the state updates until all synaptic currents had been calculated for the next time-step. Our proposed algorithm can readily speed up the computer simulations on GPU where the spike propagation is the limitation factor. Also, the simulation code can be further improved by optimizing the use of device memory during the simulations. However, in this simple network implementation, the comparative performance of the different algorithms would not be affected, since an ongoing thread reads the connectivity matrix element, and writes the synaptic input current only once. Using shared memory and coalesced memory access will potentially accelerate the simulations for repetitive computations on the same data point. This would be the case when GPUs are used to speed-up the neuro-computational simulations with more computations at each synapse updating step, for instance, under synaptic plasticity calculations [ 19 ], or for current propagation within complex dendritic tree geometries [ 17 ]. For computationally demanding SNN simulations, different GPU-based simulation frameworks have been introduced: CARLsim [ 26 ], Nemo [ 15 ], NC6 [ 4 ], and GeNN [ 27 ]. The GeNN simulator was developed to implement different SNN architectures with the least amount of code on a GPU [ 5 ]. The simulator contains a code-generation process: the user defines a network model, and specifies the neural parameters by a set of predefined functions, upon which the simulator generates and compiles the associated C++/CUDA code for a GPU. Memory usage and access on the device are optimized for various example cases. The GeNN simulator is independent of the operating system and of the GPU device model, and can also be used to generate C++ code for the same network configuration on CPUs. These characteristics make GeNN a versatile simulation tool. However, it limits the user friendliness in easy extensions with new neuron models, in manually specifying the neural dynamics, or in changing the simulator source code. In addition, the GeNN simulator can be optimized by utilizing dynamic parallelism for its synaptic updates. All GPU devices produced from 2013 onward support dynamic parallelism as described in this study, and thus allow developers to employ this programming paradigm to overcome various programming problems. In terms of spiking neural network simulations, dynamic parallelism substantially accelerates the massive neural computations, by implementing the spike-triggered calculations at each synaptic updating step. In previous parallel SNN implementations, this step was considered to be the bottleneck of the simulations, because the developed algorithms kept running obsolete calculations for spike propagation, even when the presynaptic neuron did not elicit any spike. Especially, the simulations of densely connected neurons operating under sparse spiking regimes (like observed experimentally in the cerebral cortex, or when simulating the neural dynamics at a high temporal resolution) benefit from the considerable speed up via dynamic parallelism. We therefore foresee that spike propagation will no longer be the major determinant of simulation duration of large-scale dynamic neural networks. The premise of parallel computing is: parallelization accelerates computations. However, parallelization is only possible if the same exact computations are performed again and again on different data points; and these computations are not dependent on each others results. Modern GPU’s can run millions of threads in parallel, therefore millions of neural state update and synaptic update can be parallelized. However, the computations can be parallelized only if the calculations are exactly the same, even if with different parameters. Therefore, N- and S-algorithms require to finish all neural state updates to start synaptic propagation. If the neural network architecture requires many small sets of different neuron types, whose behaviors are defined by different equations, GPU utilization would decrease. That would mean, not many calculations are done in parallel and many processors are waiting to be assigned to a calculation. Such scenario would not optimize throughput, thus the architecture of the network is also a consideration for GPU. For full utilization of GPU in calculations, the number of calculations running in parallel should cover the number of threads started at a parallel block."
} | 6,284 |
36651189 | PMC10154605 | pmc | 3,346 | {
"abstract": "Abstract Glucuronoyl esterases (GEs) are microbial enzymes able to cleave covalent linkages between lignin and carbohydrates in the plant cell wall. GEs are serine hydrolases found in carbohydrate esterase family 15 (CE15), which belongs to the large α/β hydrolase superfamily. GEs have been shown to reduce plant cell wall recalcitrance by hydrolysing the ester bonds found between glucuronic acid moieties on xylan polysaccharides and lignin. In recent years, the exploration of CE15 has broadened significantly and focused more on bacterial enzymes, which are more diverse in terms of sequence and structure to their fungal counterparts. Similar to fungal GEs, the bacterial enzymes are able to improve overall biomass deconstruction but also appear to have less strict substrate preferences for the uronic acid moiety. The structures of bacterial GEs reveal that they often have large inserts close to the active site, with implications for more extensive substrate interactions than the fungal GEs which have more open active sites. In this review, we highlight the recent work on GEs which has predominantly regarded bacterial enzymes, and discuss similarities and differences between bacterial and fungal enzymes in terms of the biochemical properties, diversity in sequence and modularity, and structural variations that have been discovered thus far in CE15.",
"introduction": "Introduction Lignin–carbohydrate complexes and plant cell wall recalcitrance The plant cell wall is a complex network mainly consisting of polysaccharides. Cellulose is typically the most abundant polysaccharide and it coalesces via strong hydrogen bonding into crystalline fibres that in turn are coated and cross-linked by different heteropolysaccharides [ 1 ]. The cell wall can be further reinforced by lignin, where lignin monomers polymerize in radical coupling reactions. In order to use the plant cell wall polymers as a nutrient source, microorganisms need to produce an arsenal of different hydrolytic and oxidative enzymes to tackle this recalcitrant matrix [ 2 ]. Likewise, full utilization of renewable biomass by enzymatic processing in biorefineries requires a variety of enzymatic activities, usually formulated in so-called enzyme cocktails. A feature that is often overlooked is that during lignification, covalent bonds are formed not only between the lignin monomers but also between lignin and the exposed carbohydrates of the cell wall, particularly xylan, forming so-called lignin–carbohydrate complexes (LCCs) [ 1 , 3 ]. It has been estimated that virtually all lignin in softwood, and a major fraction of lignin also in hardwood, can be found covalently bound to carbohydrates [ 4 ]. Correspondingly, a significant proportion of the plant cell wall carbohydrates can be bound to lignin, as in beechwood, where around a third of the glucuronic acid (GlcA) moieties are estimated to participate in LCCs [ 5 ]. LCCs greatly add to the recalcitrance of the cell wall, and while these structures are difficult to study, various lignin–carbohydrate bonds have been proposed, including benzyl ethers, benzyl esters, γ-esters, phenyl glycosides and ferulate esters ( Figure 1 ) [ 3 ]. While ferulate-mediated cross-links to lignin can indirectly be cleaved by feruloyl esterases that cleave bonds between feruloyl and arabinofuranosyl moieties, when it comes to direct enzymatic cleavage of LCCs, the only known enzymes with this ability to date are the glucuronoyl esterases (GEs) which hydrolyse the ester bonds between GlcA moieties in glucuronoxylan and lignin. The importance of GlcA moieties for cell wall recalcitrance has recently been highlighted [ 6 ] and indeed points to these residues as being key in forming the LCC. Here, we summarize the current literature on GEs, with a focus on their activities, modularity and structure. Figure 1 Lignin–carbohydrate complexes involving xylan ( A ) Lignin can bind covalently to xylan in direct ester linkages to glucuronic acid (GlcA) moieties (often 4-O-methylated) or via feruloylated side chains. The xylose units are coloured orange, GlcA blue, and arabinofuranose green. ( B ) The ester bonds between (4-O-Me)GlcA and lignin has been identified in two configurations, either α-linked (benzyl) or γ-linked."
} | 1,061 |
28191902 | PMC5340623 | pmc | 3,347 | {
"abstract": "Metabolic engineering of microorganisms to produce desirable products on an industrial scale can result in unbalanced cellular metabolic networks that reduce productivity and yield. Metabolic fluxes can be rebalanced using dynamic pathway regulation, but few broadly applicable tools are available to achieve this. We present a pathway-independent genetic control module that can be used to dynamically regulate the expression of target genes. We applied our module to identify the optimal point to redirect glycolytic flux into heterologous engineered pathways in Escherichia coli , resulting in 5.5-fold increased titres of myo- inositol and titers of glucaric acid that improved from unmeasurable quantities to >0.8 g/L. Scaled-up production in benchtop bioreactors resulted in almost 10-fold and 5-fold increases in titers of myo- inositol and glucaric acid. We also used our module to control flux into aromatic amino acid biosynthesis to increase titers of shikimate in E. coli from unmeasurable quantities to >100 mg/L.",
"discussion": "Discussion We report the engineering of tunable genetic circuits using parts from a bacterial QS system to exercise autonomous, dynamic control over target metabolic genes and redirect pathway fluxes. These circuits were built from pathway-independent parts, and were applied to regulate metabolic fluxes and achieve substantial increases in titers of various products. Previous studies of dynamic regulation have proposed strategies to sense and respond to specific intermediates 34 , 35 , cell states 9 or medium compositions 36 . Although these strategies can be effective, they are specific to the pathway for which they are developed. Using nutrient starvation is a well-established regulatory control strategy 36 but our attempts to boost MI titres with a circuit that responds to phosphate depletion suggested that nutrient perturbations result in unknown global metabolic effects, limiting industrial use ( Supplementary Note 2 , Supplementary Fig. 11 ). As endogenous gene expression is often low and highly-regulated, tight control during both ON and OFF states is required. Transcription of the target gene can be abrogated by our QS circuit, but cellular protein pools must also be depleted to observe phenotypic changes. We altered natural degradation rates by appending degradation tags to target proteins. Strong tags were required to deplete GFP and Pfk-1 pools, whereas a weaker tag was needed to ensure sufficient AroK levels in the ON state. Fluorescence profiles of a subset of strains in Figure 1C with untagged GFP confirmed that degradation tags are needed to deplete these stable proteins ( Supplementary Fig. 12 ). Precise circuit tunability was achieved through a chromosomal library of EsaI expression levels, revealing that circuit switching times were optimal at the lowest EsaI expression levels. This highlights the sensitivity of circuit-triggering time to AHL production rate and underscores the fact that endogenous gene expression only needs to be slightly perturbed to substantially affect production of heterologous compounds. Our attempts to use a reverse QS-circuit configuration in which an activating promoter was driving expression of SspB, an SsrA-dependent degradation protein targeted to Pfk-I, failed as even leaky expression completely suppressed growth ( Supplementary Note 3 , Supplementary Fig. 13 and 14 ). Our system is tunable and fully autonomous, and does not require external inducer addition. A library of EsaI circuits that produce the ‘trigger molecule’ at variable rates resulted in a series of strains that provide different switching rates, making it possible to find the optimal circuit for any pathway. Despite ample evidence that circuits developed for product synthesis often fail to translate from the laboratory to industry 27 , robustness of synthetic biology devices is often overlooked. Quorum sensing relies on extracellular signals which can vary upon mixing 37 , so it is vital to scale studies up into bioreactors to prove they are translatable to industrial contexts. We evaluated our QS circuits in various media and found that with richer, industrially-relevant medium, dynamic regulation prevented overflow metabolism and unwanted acetate production. Performance of our circuit in shake flasks and bioreactors was consistent, and revealed how carbon flux in central metabolism can be wasted by excess acetate and biomass production. Dynamic regulation of pathway fluxes has emerged as a new frontier in metabolic engineering 38 – 40 . The QS system we have developed enables precise tunability of an engineered pathway with minimal upfront effort in any growth environment. As production strategies become more complex, host genetic backgrounds become more cumbersome to engineer. The strategies we report here exemplify the next stage in dynamic metabolic engineering, with standardized and streamlined engineering methods."
} | 1,234 |
39898181 | PMC11787994 | pmc | 3,348 | {
"abstract": "Abstract Microbial perception of spatial electromagnetic fields is essential for navigation and communication on Earth's surface system, but current understanding of this phenomenon is limited. At present, cable bacteria of the Desulfobulbaceae family have the longest known range of electron transport. In fact, the flow of electrons along these long filamentous bacteria generates an external electrostatic field, suggesting a potential for electromagnetic induction mirroring that of metallic wires. In this study, we measured the responses of cable bacteria to externally applied electric waves. We noted the formation and disappearance of square waves caused by a pair of spatially variable electric fields, generating negative and positive mirror-symmetric inductions (±1.20 mV in marine sediment) along the horizontally filamentous bacterial layer. Both seawater Candidatus Electrothrix and freshwater Ca. Electronema exhibited this electric induction. The distinct spatial boundary of bacterial induction was strictly confined within 12.5 mm below the surface of the seawater sediment. The results of this study open further avenues of research into understanding how bacteria sense and respond to spatial electromagnetic information.",
"introduction": "Introduction The ability of microorganisms to perceive electromagnetic fields is crucial for their navigation and communication on Earth's surface. However, our current understanding of this process is limited to 2 specific scenarios: magnetotactic bacteria that use extracellular magnetite ( 1–6 ) to detect the Earth's magnetic field ( 2 , 3 , 7–9 ) and ion channels in microbial membranes that generate potentials in response to electric stimuli ( 10–13 ). Evidence in the literature has been sparse concerning conductive filamentous bacterial structures analogous to metal wires. These structures may actually be capable of inducing significant spatial electromagnetic fluctuations. In this study, we confirmed that cable bacteria, which grow widely in both marine and freshwater sediments, can sense electromagnetic oscillations. This evidence may provide new perspectives regarding the sensing of wireless electromagnetic information by microorganisms ( 14–17 ). The first report of cable bacteria came from Nielsen et al. in 2010 ( 18 ), and cable bacteria have been defined as a group of filamentous bacteria from the Desulfobulbaceae family that are capable of centimeter-long electron transport ( 19 ). By coupling the oxidation of H 2 S ( 20 ) or acetate ( 21 ) in deeper sediment to the reduction of O 2, NO 3 − , or Fe 3+ at the surface ( 21–28 ), electrons can be transported over conductive periplasmic fibers to form an internal circuit used to equilibrate external reactions ( 29 ). The conductive fibers in cable bacteria extend over the whole filament of up to 10,000 cells, as an interconnected electrical network with conductivities of >10 S·cm −1 and electron mobilities in the range of 0.1 cm 2 ·V −1 ·s −1 ( 30 ). Their highly linear current-voltage characteristics, as well as their resistive impedance characteristics, indicate that cable bacteria behave as classical conductive nanowires ( 22 , 30 ). Efforts to understand the function of electron transport in cable bacteria have identified roles related to physiological adaptation ( 31 ) and elemental geochemistry ( 32–35 ). Nevertheless, whether this electron-conducting system supports the type of electrical induction similar to that present in inorganic metal wires remains unclear. Therefore, this type of biological induction may present new evidence concerning biological communication beyond the known applications related to physiological adaptation and elemental geochemistry in cable bacteria ( 36 ). All conductors that rely on the directional motion of electrons are theoretically capable of electromagnetic induction. The spatial static electric field caused by electrons flowing along filamentous cable bacteria has been measured previously using electrostatic potential (EP) microsensors and has been reported to increase by ∼0.6 mV within 1.4 cm below the surface of the sediment ( 17 , 37 , 38 ). Evidence from conductivity tests and electrostatic field measurements around cable bacteria led us to hypothesize that cable bacteria respond to electromagnetic oscillations similarly to inorganic metal wires. In the present study, we successfully enriched and cultured a marine strain of Candidatus Electrothrix and a freshwater species of Ca. Electronema bacteria, developed a set of new sensor/electrodes, and employed them to meticulously measure the electromagnetic induction responses of filamentous cable bacteria to spatial electromagnetic fluctuations.",
"discussion": "Discussion Comparison with magnetotactic bacteria Our findings demonstrated that the electron-conducting system in cable bacteria facilitates electromagnetic induction that mirrors the well-known phenomenon similarly in inorganic metallic conductors. This ability to sense electromagnetic fields was also reminiscent of a similar property in magnetotactic bacteria, which rely on both intra- and extracellular magnetite ( 1–5 ) to sense the Earth's magnetic field ( 2 , 3 , 7 , 8 ). However, in this study, we did not observe magnetite in or near our cable bacteria. Furthermore, an additional potential scenario can likewise be eliminated. It has been previously reported that iron exists in layers of cable bacteria, mainly as the ferrous (II) ion, at concentrations far lower (<50 μmol Fe 2+ ·kg −1 ) than the values found in deeper sediment layers (∼70–150 μmol·kg −1 at a depth of 4–6 cm the sediment surface) ( 46 ). As a result, the electric induction observed in this study was only found to occur in the cable bacteria layer, and was not present in the iron-rich layer of the deeper sediment, excluding the possibility of electric induction occurring in the major iron species in the sediments. Our results therefore suggest that the induction signals that occurred in the cable bacteria layer were independent of the metal-containing minerals present in the sediment and represent a novel form of bioelectric induction caused by an interaction between the filamentous cable bacteria and our oscillating electromagnetic field. Equivalent model of electric induction To characterize this form of bioelectric induction, we constructed an equivalent model for electrical induction (Extended Data Fig. S7 ). According to the right-hand rule in electromagnetism, a periodic square-wave potential with a high rate of fluctuation (+0.350 V·μs −1 ) induces a magnetic field around the line connecting the poles of the electrode carrying the signal. In the fluctuating magnetic field produced by our emitting electrode, the filamentous bacterial conductor produced a negative electrical signal based on Lenz's law (Extended Data Fig. S7 , right). Similarly, a periodic square-wave potential with a low rate of fluctuation (−0.442 V·μs −1 ) also induced a magnetic field, generating a positive electrical signal in the filamentous bacteria (Extended Data Fig. S7 , right). This model thus accurately explains how the two induction signals in our layer of cable bacteria were triggered by our oscillating electric fields. We further simplified this model by replacing the layer of filamentous cable bacteria with a bare conductive copper wire (Extended Data Fig. S7C ). We observed that the time lags between the two induction signals matched the square-wave widths of the spatial square waves (0.2, 0.4, 0.6, 0.8, 1.0, 1.2, 1.4, 1.6, 1.8, and 2.0 ms) (Fig. 2 C). The electromagnetic induction patterns in the copper wire (Extended Data Fig. S7D ) matched those noted in the cable bacteria layer (Fig. 2 C). This result further confirmed that cable bacteria can react to external electric fields similarly to inorganic metallic conductors, following the laws of electromagnetic induction ( 41 ). Vertical component of bioelectrical induction in the cable bacteria layer According to our proposed equivalent model, we hypothesized that no induction signal would be measurable between the upper and lower layers of cable bacteria as the electric field was moved along the horizontal axis (Fig. 1 A) because the induced signals would have been oriented horizontally, according to Lenz's law and the right-hand rule ( 41 ). This hypothesis was tested by measuring the vertical component of the induced signals in the cable bacteria layer. We used a receiving electrode with 2 bare platinum tips spaced 0.5 cm apart to detect the vertical component, using the same square-wave source detailed in Fig. 1 A. Our results (Extended Data Fig. S8 ) revealed that when both tips of the receiving electrode were submerged either in the seawater (case 1 in Extended Data Fig. S8B and C ) or the mineral sediment without cable bacteria (case 3 in Extended Data Fig. S8B and C ), only the background signal from the square waves (7.2 ms) and the capacitance effect were detected. Conversely, when the two tips were embedded in the cable bacteria layer, a small and sharp negative induction signal at 7.2 mV was superimposed near the background signal, but no positive induction signal was found. Theoretically, this weak superimposed induction signal was hypothesized to vanish if the line between the receiving electrode tips was perpendicular to the line between the tips of the emitting electrode. However, this ideal geometric arrangement was not feasible in practice, and the slightly superimposed signal could not be completely eliminated without the persistence of a geometric transverse spacing component between two tips of the receiving electrode. Nevertheless, the absence of a pair of opposite and equal induction signals suggests that the differences in the induction signals between the upper and lower layers of the cable bacteria were negligible. Potential biological-geological-environmental implications The presence of this bioelectric induction phenomenon in both sea- and freshwater sediments may carry a substantial geoenvironmental significance. It indicates that electromagnetic oscillations may be detectable by the filamentous “antennas” of cable bacteria communities, broadcasting the information through biofilms or biological mats in and on sediments, allowing the bacterial populations to perceive spatial electromagnetic information. Additionally, similar electronic signaling structures may also be present in certain migratory animals such as pigeons and cetaceans, allowing them to travel to precise locations worldwide ( 14–17 , 47 ) as the motions of their conductive fibers relative to the generally static magnetic field of the Earth likely mirror the electromagnetic oscillations we used in our experiments. The results of this study may therefore generate other general insights that extend beyond the field of bacterial microbiology as well."
} | 2,724 |
21526386 | null | s2 | 3,349 | {
"abstract": "Microorganisms have become an increasingly important platform for the production of drugs, chemicals, and biofuels from renewable resources. Advances in protein engineering, metabolic engineering, and synthetic biology enable redesigning microbial cellular networks and fine-tuning physiological capabilities, thus generating industrially viable strains for the production of natural and unnatural value-added compounds. In this review, we describe the recent progress on engineering microbial factories for synthesis of valued-added products including alkaloids, terpenoids, flavonoids, polyketides, non-ribosomal peptides, biofuels, and chemicals. Related topics on lignocellulose degradation, sugar utilization, and microbial tolerance improvement will also be discussed."
} | 193 |
36557161 | PMC9788529 | pmc | 3,351 | {
"abstract": "As a new membrane technology, forward osmosis (FO) has aroused more and more interest in the field of wastewater treatment and recovery in recent years. Due to the driving force of osmotic pressure rather than hydraulic pressure, FO is considered as a low pollution process, thus saving costs and energy. In addition, due to the high rejection rate of FO membrane to various pollutants, it can obtain higher quality pure water. Recovering valuable resources from wastewater will transform wastewater management from a treatment focused to sustainability focused strategy, creating the need for new technology development. An innovative treatment concept which is based on cooperation between bioelectrochemical systems and forward osmosis has been introduced and studied in the past few years. Bioelectrochemical systems can provide draw solute, perform pre-treatment, or reduce reverse salt flux to help with FO operation; while FO can achieve water recovery, enhance current generation, and supply energy sources for the operation of bioelectrochemical systems. This paper reviews the past research, describes the principle, development history, as well as quantitative analysis, and discusses the prospects of OsMFC technology, focusing on the recovery of resources from wastewater, especially the research progress and existing problems of forward osmosis technology and microbial fuel cell coupling technology. Moreover, the future development trends of this technology were prospected, so as to promote the application of forward osmosis technology in sewage treatment and resource synchronous recovery",
"conclusion": "3. Conclusions and Prospects Forward osmosis (FO) technology has been developed to treat wastewater. The water flow in FO flows naturally from medium with high water concentration to medium with low water concentration [ 54 ]. The water treatment process consists of a semi permeable membrane that allows water to pass through and expel solutes. FO has attracted much attention due to its excellent energy efficiency and salt discharge capacity, as well as its low scaling tendency and saltwater discharge. Therefore, the synergy of microbial fuel cells and FO can potentially eliminate the dependence on fossil fuels, as well as provide better waste management. One technology to achieve this result is the OsMFC [ 55 ]. It can potentially be used in many processes, such as wastewater treatment facilities, where clean water can be produced and extracted, and in water desalination facilities where salt can be removed from water and used for water reuse. OsMFCs seems to be more effective than conventional MFC in terms of energy generation and water extraction, due to the presence of FO membrane in OsMFC. It also leads to more power generation than conventional MFC and provides an opportunity to extract water through the anode chamber. Because of the many positive characteristics of OsMFC, they can be applied to many processes in practice. However, the FO membrane fouling remains a major challenge for these internal configurations, as it is difficult to apply in situ membrane cleaning. All the above problems related to OsMFC will eventually lead to operation in a short time [ 56 ]. This is why OsMFCs long-term continuous operation has not been well studied in previous studies. Based on these facts, more research is needed to better understand the combination of MFC and FO. In general, the research of OsMFCs is still in its infancy, but the huge prospect of MFC and FO as separate technologies in resource recovery and progress will accelerate the development of OsMFCs technology. More efforts must be invested to identify application areas, understand energy issues, alleviate membrane pollution, and expand OsMFCs to the transition stage.",
"introduction": "1. Introduction to Forward Osmosis (FO) 1.1. Principle of Forward Osmosis Forward osmosis is a separation process that uses the osmotic pressure difference between feed solution (FS) and draw solution (DS) on both sides of the forward osmosis membrane as the driving force without external pressure to make water flow spontaneously from the feed solution (low osmotic pressure) to the drawn solution (high osmotic pressure) as shown in Figure 1 . In this process, the FO membrane selectively penetrates water molecules to intercept and remove pollutants and ions in water. Forward osmosis (FO) is based on the natural phenomena of osmotic processes and can extract clean water from wastewater [ 1 ]. Compared with other membrane systems, FO has many advantages, such as high energy efficiency, high salt discharge rate, low membrane pollution, and low salt water discharge. Therefore, once FO becomes advantageous, determine the appropriate DS based on different wastewater types. The pore diameter of the second FO membrane is only 0.3–0.5 nm, allowing a high solute rejection rate, making it an ideal choice for desalination, removal of heavy metals, and removal of micro pollutants, such as cell inhibitory drugs and endocrine disruptors. In addition, FO does not require pre-treatment of wastewater. Another key advantage of the FO process is its low pollution tendency [ 2 ]. Reversible fouling is the most common type of membrane fouling and can be repaired using simple hydraulic cleaning. Seawater is one of the most commonly used DS, which has been diluted and can be safely discharged back to the sea without any treatment. The concentrated FS can be produced by anaerobic digestion. 1.2. Development of Forward Osmosis(FO) The development of FO technology and membrane materials has mainly gone through three stages: Stage 1: A new process for desalination of seawater based on the principle of FO membrane was proposed for the first time. However, at this stage, a special FO membrane was not developed, but the reverse osmosis membrane was used for FO research. Due to the dense support layer of the reverse osmosis membrane, serious internal concentration polarization was caused when it was applied to FO, resulting in low FO performance [ 3 ]. Stage 2: Started to explore a semi permeable membrane more suitable for the FO process. HTI Company of the United States used polyester mesh to replace the RO membrane support layer, developed an asymmetric cellulose triacetate FO membrane (CTA membrane) with better performance, and realized commercial application in the field survival water purification equipment and food concentration. However, compared with the RO process, FO water flux is still at a low level. Moreover, the mass transfer mechanism of FO process and the study of extraction solution are still not in-depth. Stage 3: Further development has been made in exploring FO mass transfer mechanism and model, developing efficient extraction solutions, and developing high-performance FO membranes. The researchers successfully prepared polyamide composite membrane (TFC) through interfacial polymerization, which improved the water flux and salt rejection of the FO process, and had a wider pH application range than CTA membrane. Different from the traditional membrane separation process, the forward osmosis process uses the osmotic pressure difference between two solutions to drive water through the semi permeable membrane, without additional pressure, so it has the advantage of low energy consumption [ 4 ]. The biggest feature of FO technology is osmotic pressure driving, which is essentially different from other membrane separation processes. Therefore, compared with traditional pressure driven membrane separation processes (such as reverse osmosis and nanofiltration), FO technology has the following advantages. ◾ \n Low energy consumption \n No hydraulic pressure is required in the operation process, so the FO process has the advantage of low energy consumption, especially in applications where the extract does not need to be recycled, such as the diluted fertilizer extract, directly used for agricultural irrigation, and the diluted seawater extract, directly discharged, which can obviously reflect the low energy consumption advantage of FO process [ 5 ]. ◾ \n Light membrane pollution and high reversibility \n No hydraulic pressure can prevent pollutants on the membrane surface from being compacted, resulting in light FO membrane pollution and high reversibility. ◾ \n High pollutant retention rate and good effluent quality \n The pore diameter of FO membrane is very small (about 0.25–0.3 nm), which has an excellent removal effect on ions and micro pollutants in water. Therefore, FO technology with low energy consumption, low pollution, and high retention has a very broad application prospect [ 6 ]. 1.3. Concentration Polarization Concentration polarization is a common phenomenon in all membrane separation processes, and the forward osmosis process is no exception. Concentration polarization is due to the fact that during the membrane separation process of water and solute, the solute of the feed solution accumulates on the membrane surface layer, and one side of the draw solution is diluted by water, resulting in the phenomenon that the effective osmotic pressure of the membrane layer is far less than the osmotic pressure difference of the solution itself on both sides [ 7 ]. Concentration polarization not only reduces osmotic driving force, thereby reducing water flux and increasing solute diffusion, but also aggravates membrane pollution. Due to the asymmetric structure of the forward osmosis membrane, external concentration polarization and internal concentration polarization are prone to occur. The outer concentration polarization occurs on the membrane surface and can be reduced or eliminated by hydraulic conditions [ 8 ]. The inner concentration polarization occurs in the support layer of the membrane, which seriously affects the performance of the forward osmosis membrane. In the process of forward osmosis, there are two commonly used operation modes: FO mode or AL-FS mode. The active layer of the feed solution towards the membrane. PRO mode or AL-DS mode. The active layer of the absorption solution towards the membrane. Different membrane orientation will lead to different dilution or concentration polarization. Figure 2 describes the concentration polarization diagram of FO and PRO modes [ 9 ]. In the AL-FS mode, the water molecules of the feed solution enter the absorption solution side through the membrane, while the solute gradually accumulates in the active layer of the membrane, making the concentration of the solute on the membrane surface greater than its concentration in the solution, forming a concentrated external concentration polarization. At the same time, the water permeates the active layer with gradually diluting the extract of the support layer and then the diluted internal concentration polarization occurs. In AL-DS mode, the solute in the feed solution gradually accumulates in the membrane support layer and the concentrated inner concentration polarization occurs [ 10 ]. The absorption solution near the active layer is diluted by the transferred water, which reduces the concentration and polarizes the diluted external concentration difference. Therefore, regardless of the membrane orientation, the concentration polarization will reduce the osmotic pressure, resulting in a decrease in water flux. In the process of forward osmosis, the internal concentration polarization occurs in the support layer and cannot be removed through optimization of hydraulic conditions, which is the main reason for the decline of water flux [ 11 ]. 1.4. Membrane Fouling Membrane fouling involves solutes and/or particles on the membrane surface and in the membrane hole or the feed spacer is blocked. This may cause dirt, scaling, or damage of the membrane. The main pollutants in natural and damaged water bodies are microorganisms, organic substances, and inorganic substances (scaling). When wastewater is used, due to the existence of microorganisms and the secretion of extracellular polymeric substances (EPS) to establish biofilm integrity, biological scaling may be the most limiting factor [ 12 ]. Biological scaling is affected by influent water quality, membrane physical and chemical properties and operating conditions. In a FO-MBR study, biological deposition had little effect on water permeability, but the mass transfer coefficient was seriously reduced and ICP was enhanced. In seawater FO, silica scaling or membrane biological scaling may occur through transparent outer polymer particles (TEP). Organic pollution varies depending on the water supply used. The wastewater consists of mobile organic matter (EfOM), including soluble microbial products and natural organic matter (NOM). NOM has been found to be a serious pollutant in many membrane processes, including FO [ 13 ]. Therefore, it is important to simulate the behavior of these complex feeds to include all or the most important dirt. Model fouling, using, e.g., sodium alginate or alginate, bovine serum albumin (BSA), and Aldrich humic acid (AHA), has been used to test the severity of NOM fouling on FO membrane. Alginic acid is related to the hydrophilic part of EfOM, AHA represents humic acid, and BSA represents protein part [ 14 ]. Immediate fouling detection ensures and restores membrane performance. Determining the scaling potential of the feed can help predict scaling, However, once fouling occurs on the membrane surface, off-line methods may be required for future preventive measures. Non invasive visual online methods can detect early signs of fouling in real time, such as flow decline, solute rejection, and NPD change operating parameters (temperature, feed TDS, penetrant flow, recovery). Figure 3 summarizes the fouling detection technology in which feed and FO membrane contamination are involved [ 15 ]. 1.5. Application of FO Technology The idea of wastewater treatment has changed from the original “pollutant removal up to standard discharge” to the idea of “resource and energy recycling”, which can realize water resource regeneration, energy production, and value-added product output [ 16 ].The advantages of FO technology, such as low energy consumption, light pollution and high interception rate, make it widely used and researched in wastewater treatment, specifically including water resource regeneration and nitrogen and phosphorus nutrient recovery [ 17 ]. ◾ \n Water resources regeneration \n Due to the high interception of FO membrane, most of the pollutants in wastewater can be removed, and high-quality effluent can be obtained to realize the regeneration and reuse of water resources. The FO wastewater treatment and resource recovery unit is composed of two parts, namely the FO treatment system and extraction liquid recovery water purification system. Zhang et al. studied the treatment effect of FO membrane on the effluent of the secondary sedimentation tank and used solar radiation to drive electrodialysis to recover the diluted extract, which can meet the drinking water standard [ 18 ]. ◾ \n Recovery of nitrogen and phosphorus nutrients \n Wastewater contains rich nutrients, such as nitrogen and phosphorus. If discharged directly, it will not only reduce the effluent quality, but also cause eutrophication of the water body. Recycling nitrogen, phosphorus, and other nutrients as fertilizers is an urgent need for sustainable development of wastewater treatment. The dense membrane pore of FO membrane can effectively intercept and concentrate ammonia, nitrogen, and phosphate in wastewater for subsequent crystallization and recovery [ 13 ]. At present, it is successfully used for concentration and recovery of nitrogen and phosphorus resources in anaerobic digestion liquid and urine shown in Figure 4 . In addition, using the reverse diffusion characteristics of the FO draw solution, with the salt solution of magnesium bivalent as the extracting solution, nitrogen and phosphorus in the synthetic urine are recovered by FO technology [ 19 ]. After FO treatment, magnesium ions entering the concentrated solution form struvite precipitation with phosphorus. The diluted extracting solution of recovered urea is used for the direct irrigation of green walls, parks, or urban agriculture."
} | 4,056 |
25168789 | null | s2 | 3,352 | {
"abstract": "Sessile marine mussels must \"dry\" underwater surfaces before adhering to them. Synthetic adhesives have yet to overcome this fundamental challenge. Previous studies of bioinspired adhesion have largely been performed under applied compressive forces, but such studies are poor predictors of the ability of an adhesive to spontaneously penetrate surface hydration layers. In a force-free approach to measuring molecular-level interaction through surface-water diffusivity, different mussel foot proteins were found to have different abilities to evict hydration layers from surfaces-a necessary step for adsorption and adhesion. It was anticipated that DOPA would mediate dehydration owing to its efficacy in bioinspired wet adhesion. Instead, hydrophobic side chains were found to be a critical component for protein-surface intimacy. This direct measurement of interfacial water dynamics during force-free adsorptive interactions at solid surfaces offers guidance for the engineering of wet adhesives and coatings."
} | 253 |
36376336 | PMC9663567 | pmc | 3,353 | {
"abstract": "We present a Brownian dynamics study of a 2D bath of active particles interacting among each other through usual steric interactions and, additionally, via non-reciprocal avoidant orientational interactions. We motivate them by the fact that the two flagella of the alga Chlamydomonas interact sterically with nearby surfaces such that a torque acts on the alga. As expected, in most cases such interactions disrupt the motility-induced particle clustering in active baths. Surprisingly, however, we find that the active particles can self-organize into collectively moving flocks if the range of non-reciprocal interactions is close to that of steric interactions. We observe that the flocking motion can manifest itself through a variety of structural forms, spanning from single dense bands to multiple moderately-dense stripes, which are highly dynamic. The flocking order parameter is found to be only weakly dependent on the underlying flock structure. Together with the variance of the local-density distribution, one can clearly group the flocking motion into the two separate band and dynamic-stripes states.",
"introduction": "Introduction The interdisciplinary field of active matter 1 – 5 , situated at the crossroad of physics, chemistry, biology and engineering, examines individual and collective behavior of units capable of autonomous motion. The units can be diverse, including, for instance, bacteria that use body appendages to swim in viscous media, active colloids that exhibit propulsive motion by generating flow around their surfaces by means of self-phoresis, bird flocks and sheep herds. Many interesting properties of these systems can be captured already with simple models which do not account explicitly for the medium surrounding active units. Instead, on the coarse-grained level the medium serves as a source of fluctuations and drag forces acting on the units. Typically, active units are modeled as particles moving with a roughly constant speed along an orientation vector attached to them 6 , which can change its direction due to rotational diffusion and inter-particle interactions. On one side of the spectrum, there are models with pairwise interactions. Possibly the simplest example within this class of models involves isotropic active particles interacting with each other via steric interactions, which can lead to the phenomenon of motility-induced phase separation 7 – 10 (MIPS) between dense particle clusters and dilute regions of freely moving particles. In a nutshell, MIPS takes place when active particles are sufficiently fast and numerous 11 , 12 , increasing chances that free particles join existing clusters compared to chances that particles within clusters escape them as a result of rotational diffusion. On the other side, there are models with social interactions 13 , 14 . The most notable example within this class is the Vicsek model 15 , incorporating alignment with average particle orientation of all neighbors situated within some fixed radial distance, which can result in coherent flocking motion 16 – 19 : particles spontaneously form traveling bands propagating along a common direction. Models fusing both type of interactions 20 are also found in literature. Furthermore, different types of orientational interactions have been introduced 21 – 28 . In this article we introduce a specific form of orientational interactions, which are non-reciprocal and avoidant. We demonstrate how they influence the collective dynamics of our model active particles. The orientational interactions are motivated by the fact that the two flagella of the alga Chlamydomonas interact sterically with nearby surfaces such that the alga experiences a torque, which rotates it away from the surface. If pairwise interactions stem from a potential, they are reciprocal due to Newton’s action-reaction principle. However, the reciprocity can be broken if the pairwise interaction originates in some non-equilibrium mechanism 29 . Numerous examples exist in literature, including carpets of microfluidic rotors 30 , droplets exhibiting predator-prey interactions driven by non-reciprocal oil exchange 31 , neural networks 32 , 33 and many others 34 . An eminent example of non-reciprocal interactions from the realm of active matter is found in binary mixtures of active colloids with phoretic interactions 35 – 38 . In essence, colloids with two distinct hemispheres, immersed in a solution containing an appropriate chemical solute, can produce and maintain a local chemical concentration gradient by means of, for instance, self-diffusiophoresis or self-thermophoresis. The chemical gradient implies a hydrodynamic flow of the surrounding solvent, which in turn propels the colloid forward so that the entire system remains force free. Two populations of different active colloids will exhibit a different response to self-generated chemical gradients, leading in general to non-reciprocal interactions, the strength of which can be controlled by varying colloidal mobilities and activities. Interestingly, it has been reported that interplay of hydrodynamics and boundaries can also lead to non-reciprocal interactions 30 . In this article we study the collective motion of a 2D low Reynolds number suspension of self-propelled particles displaying non-reciprocal pairwise interactions. The particles perform active Brownian motion with a constant swim speed v and translational and rotational diffusion constants D 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}$$D_{\\mathrm {R}}$$\\end{document} D R . Two types of pairwise interactions are present in the system as we describe in more detail in the “ Methods ” section. Firstly, the particles interact with each other via repulsive steric forces with a typical interaction range \\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}$$\\sigma$$\\end{document} σ , which can be interpreted as an effective particle diameter. In the absence of other kind of interactions, the active suspension would be described by two dimensionless parameters: the area fraction \\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}$$\\Phi$$\\end{document} Φ of active particles and the Péclet number \\documentclass[12pt]{minimal}\n\t\t\t\t\\usepackage{amsmath}\n\t\t\t\t\\usepackage{wasysym} \n\t\t\t\t\\usepackage{amsfonts} \n\t\t\t\t\\usepackage{amssymb} \n\t\t\t\t\\usepackage{amsbsy}\n\t\t\t\t\\usepackage{mathrsfs}\n\t\t\t\t\\usepackage{upgreek}\n\t\t\t\t\\setlength{\\oddsidemargin}{-69pt}\n\t\t\t\t\\begin{document}$$\\text {Pe} = v\\sigma /D$$\\end{document} Pe = v σ / D . The \\documentclass[12pt]{minimal}\n\t\t\t\t\\usepackage{amsmath}\n\t\t\t\t\\usepackage{wasysym} \n\t\t\t\t\\usepackage{amsfonts} \n\t\t\t\t\\usepackage{amssymb} \n\t\t\t\t\\usepackage{amsbsy}\n\t\t\t\t\\usepackage{mathrsfs}\n\t\t\t\t\\usepackage{upgreek}\n\t\t\t\t\\setlength{\\oddsidemargin}{-69pt}\n\t\t\t\t\\begin{document}$$\\text {Pe}$$\\end{document} Pe number is the ratio of characteristic times \\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}$$\\sigma ^2/D$$\\end{document} σ 2 / D 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}$$\\sigma /v$$\\end{document} σ / v that the active particle needs to respectively diffuse and swim its own size \\documentclass[12pt]{minimal}\n\t\t\t\t\\usepackage{amsmath}\n\t\t\t\t\\usepackage{wasysym} \n\t\t\t\t\\usepackage{amsfonts} \n\t\t\t\t\\usepackage{amssymb} \n\t\t\t\t\\usepackage{amsbsy}\n\t\t\t\t\\usepackage{mathrsfs}\n\t\t\t\t\\usepackage{upgreek}\n\t\t\t\t\\setlength{\\oddsidemargin}{-69pt}\n\t\t\t\t\\begin{document}$$\\sigma$$\\end{document} σ . In this study we fix \\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}$$\\Phi = 0.24$$\\end{document} Φ = 0.24 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}$$\\text {Pe} = 80$$\\end{document} Pe = 80 such that the system is in the regime where MIPS occurs. In addition, the particles exhibit pairwise orientational interactions of short range R , which manifest themselves as torques acting on the particles. Motivated by the avoidant torque, the alga Chlamydomonas experiences close to a surface as explained below, we have formulated the orientational interaction of Eq. ( 5 ) in the “ Methods ” section. If the distance \\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}$${\\mathbf {r}}_{ij}$$\\end{document} r ij between the particles i and j is smaller than a cutoff distance R , they are subjected to torques of the amplitude \\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}$${\\mathscr {T}}_0$$\\end{document} T 0 . In the general case, the orientational interaction is non-reciprocal, meaning that the torques \\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}$$\\pmb {{\\mathscr {T}}}_{ij}$$\\end{document} T ij 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}$$\\pmb {{\\mathscr {T}}}_{ji}$$\\end{document} T ji acting on the particles are not equal and opposite, \\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}$$\\pmb {{\\mathscr {T}}}_{ij} \\ne -\\pmb {{\\mathscr {T}}}_{ji}$$\\end{document} T ij ≠ - T ji . This stems from the form of Eq. ( 5 ) where the torque exerted on particle i depends on its orientation \\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}$${\\mathbf {u}}_i$$\\end{document} u i and the normalized separation vector \\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}$${\\mathbf {r}}_{ij}/|{\\mathbf {r}}_{ij}|$$\\end{document} r ij / | r ij | , but not on the orientation of particle j . The interactions are predominantly avoidant in nature. For example, interaction of such form can be motivated by looking at the dynamics of alga Chlamydomonas reinhardtii 39 . Chlamydomonas propagates itself through the fluid by breaststroke beating of a pair of frontal flagella 40 such that its far-field flow topology resembles that of a puller 41 : the flow is inward along the main body axis and outward in the perpendicular direction. Recent experiments have demonstrated that Chlamydomonas scatter off solid surfaces primarily due to contact interactions 42 between their flagella and the surface, while later investigations reveal that hydrodynamic interactions are needed for a complete quantitative description of how algae interact with cylindrical obstacles 43 . The contact interactions, on which we concentrate here, generate torques 44 that avert the algal body from a collision with the surface. To capture this type of interaction, we propose the model described by Eq. ( 5 ), in which case \\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}$$\\pmb {{\\mathscr {T}}}_{ij} \\equiv \\pmb {{\\mathscr {T}}}_{i}$$\\end{document} T ij ≡ T i would stand for the torque exerted on the particle 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}$${\\mathbf {r}}_{ij} \\equiv {\\mathbf {r}}_i$$\\end{document} r ij ≡ r i for the distance vector of the particle i from the surface. It is now reasonable to suppose that an analog contact interaction through flagella exists among two algae situated close to each other. Since there are no useful experimental insights concerning such interactions between algae, we propose the torque of Eq. ( 5 ) as a first approach for describing these interactions, which certainly needs to be refined in future work for a quantitative description. Thus, as the flagellum of one Chlamydomonas touches the cell body of the other, and vice versa, the torques exerted on the algae will be non-reciprocal in the general case. Some typical examples of the encounter of two algae modeled by Eq. ( 5 ) are illustrated in Fig. 1 , where the orientation of alga i is fixed and eight orientations of alga j are chosen. The directions of the torques acting on both algae and their strengths are indicated by curved red arrows. In particular, the avoidant torque on particle j is maximal if its orientation vector \\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}$${\\mathbf {u}}_j$$\\end{document} u j is perpendicular to the distance vector to particle 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}$${\\mathbf {u}}_j \\perp {\\mathbf {r}}_{ij}$$\\end{document} u j ⊥ r ij ) and, by symmetry, zero for \\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}$${\\mathbf {u}}_j \\Vert {\\mathbf {r}}_{ij}$$\\end{document} u j ‖ r ij . The torque in Eq. ( 5 ) can be viewed as a simple and generic form of an avoidant non-reciprocal orientational interaction and, therefore, in the following we explore how it influences the collective motion of active Brownian particles. Figure 1 A schematic of the encounter between two Chlamydomonas . Their current unit orientation vectors \\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}$${\\mathbf {u}}_i$$\\end{document} u i are depicted in light black, while their directions of rotation upon interactions modeled by non-reciprocal torques from Eq. ( 5 ) are displayed in red. As an illustration eight different examples are shown. The torques are non-reciprocal in the general case (hinted by different thicknesses of the red arrows). We describe active particle motion by a set of coupled overdamped stochastic equations, which are presented in the “ Methods ” section. Starting from an active suspension exhibiting MIPS as a reference state, we introduce non-reciprocal orientational interactions ( 5 ) and using the method of Brownian dynamics conduct a detailed parameter study of collective motion of the resulting active bath as a function of torque amplitude \\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}$${\\mathscr {T}}_0$$\\end{document} T 0 and interaction range R . As the orientational interactions are predominantly avoidant, one expects disruption of MIPS for strong enough torques \\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}$${\\mathscr {T}}_0$$\\end{document} T 0 , because active particles at the edge of a cluster turn away from neighboring particles and leave the cluster. Even though the disordered state is indeed the most common outcome for strong torques, as the state diagram in Fig. 2 shows, surprisingly, we find that there exists a narrow region in the state diagram, characterized by short interaction range R and moderate torques \\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}$${\\mathscr {T}}_0$$\\end{document} T 0 , where a transition to ordered collective motion occurs. In the ordered state, the particles move in flocks which can take a variety of structures spanning from a compact dense band to a single very dynamic porous band and multiple bands. This is the main result of our study. Figure 2 State diagram of the system as a function of the non-reciprocal interaction range R and interaction amplitude \\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}$${\\mathscr {T}}_0$$\\end{document} T 0 . The \\documentclass[12pt]{minimal}\n\t\t\t\t\\usepackage{amsmath}\n\t\t\t\t\\usepackage{wasysym} \n\t\t\t\t\\usepackage{amsfonts} \n\t\t\t\t\\usepackage{amssymb} \n\t\t\t\t\\usepackage{amsbsy}\n\t\t\t\t\\usepackage{mathrsfs}\n\t\t\t\t\\usepackage{upgreek}\n\t\t\t\t\\setlength{\\oddsidemargin}{-69pt}\n\t\t\t\t\\begin{document}$${\\mathscr {T}}_0$$\\end{document} T 0 axis is presented in the logarithmic scale and includes data over the range of five orders of magnitude. Apart from the dispersed state, three ordered states are observed, which we term MIPS, flocking (band) and flocking (dynamic). State boundaries have been sketched by using simulation data, represented by circles of different colors. The system is characterized by \\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}$$\\Phi = 0.24$$\\end{document} Φ = 0.24 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}$$\\text {Pe} = 80$$\\end{document} Pe = 80 . The states of the snapshots presented in Fig. 3 are indicated by enlarged circles. The article is organized as follows. In the “ Results ” section we analyze different states appearing in our system and construct the corresponding state diagram in the parameter space 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}$${\\mathscr {T}}_0$$\\end{document} T 0 and R . We elaborate the implications of our findings, suggest possible future experiments, and offer our conclusions in the “ Discussion ” section. Lastly, the equations of motion of active particles and details of Brownian dynamics simulations are presented in the “ Methods ” section. Figure 3 Simulation snapshots of typical states appearing in the system for different interaction strength \\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}$${\\mathscr {T}}_0$$\\end{document} T 0 and range \\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}$$R/\\sigma$$\\end{document} R / σ as indicated by enlarged circles in the state diagram of Fig. 2 . Top left panel: MIPS ( \\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}$${\\mathscr {T}}_0/k_{\\mathrm {B}}T = 0.1$$\\end{document} T 0 / k B T = 0.1 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}$$R/\\sigma = 2^{1/6}$$\\end{document} R / σ = 2 1 / 6 ) and top right panel: dispersed state ( \\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}$${\\mathscr {T}}_0/k_{\\mathrm {B}}T = 1$$\\end{document} T 0 / k B T = 1 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}$$R/\\sigma = 2^{1/6}$$\\end{document} R / σ = 2 1 / 6 ). Middle panel: Flocking (band). Two snapshots of a coherently moving band of active particles ( \\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}$${\\mathscr {T}}_0/k_{\\mathrm {B}}T = 10$$\\end{document} T 0 / k B T = 10 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}$$R/\\sigma = 2^{1/6}$$\\end{document} R / σ = 2 1 / 6 ) are shown, with a time 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}$$3D_{\\mathrm {R}}^{-1}$$\\end{document} 3 D R - 1 in between them. Bottom panel: Flocking (dynamic). Left: Motion of a moderately dense and dynamically varying stripe of particles ( \\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}$${\\mathscr {T}}_0/k_{\\mathrm {B}}T = 100$$\\end{document} T 0 / k B T = 100 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}$$R/\\sigma = 1.15$$\\end{document} R / σ = 1.15 ). Right: Motion of several dynamically varying stripes ( \\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}$${\\mathscr {T}}_0/k_{\\mathrm {B}}T = 30$$\\end{document} T 0 / k B T = 30 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}$$R/\\sigma = 2^{1/6}$$\\end{document} R / σ = 2 1 / 6 ). Red arrows denote the direction of coherent motion. In all cases \\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}$$\\Phi = 0.24$$\\end{document} Φ = 0.24 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}$$\\text {Pe} = 80$$\\end{document} Pe = 80 .",
"discussion": "Discussion To summarize, we studied a system of active particles interacting with each other via conventional steric interactions; besides, we introduced the additional non-reciprocal avoidant orientational interactions. The latter were motivated by an example of flagellum–body interactions which are present in an encounter of two algae (cf. Fig. 1 ). We showed that motility-induced active particle clustering is disturbed already for moderately low non-reciprocal interaction amplitudes \\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}$${\\mathscr {T}}_0$$\\end{document} T 0 and that the active bath finds itself in most instances in a dispersed state, characterized by numerous and unstable smaller clusters. However, the dispersed state is not the only possible outcome. Remarkably, if the non-reciprocal interaction range R is close to the steric interaction range, we demonstrated that the active system displays coherent flocking motion for a finite range of amplitudes \\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}$${\\mathscr {T}}_0$$\\end{document} T 0 (cf. Fig. 4 ). The polar order is found to decrease with increasing R , and is largely independent on the underlying flock structure. Together with the variance of the local-density distribution, we can group the flocking motion into band and dynamic stripe states. The occurrence of a band of flocking particles can at least qualitatively be understood as follows. When they all move in the same direction, the torques acting on each particle from its neighbors cancel. Now, whenever a particle orientation deviates from the direction of the moving band, the particle moves towards its direct neighbor and experiences the avoidant torque back to the moving direction. The same happens when the close-by neighbor on the other side is approached. Thus the parallel orientations of all the particles are stabilized by the avoidant orientational interactions with the neighbors; however, only when the torque amplitude exceeds \\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}$$k_{\\mathrm {B}}T$$\\end{document} k B T so that thermal orientational motion is irrelevant. If the interaction range R is too large, a particle experiences the avoidant torques from all the neighbors simultaneously. The torques cancel each other and the particle’s orientation is not turned back to the common direction. Thus, the band disintegrates. Interestingly, it is also not stable for large torques and the reason for this instability under increased “orientational tension” requires further explanation. Thus, fully uncovering the microscopic mechanisms of the observed behavior will be one direction of our future efforts. Collective behavior of Chlamydomonas algae has recently been the focus of experimental studies 45 . Importantly, the flocking motion observed in our simulation work has not been reported in the experiments so far. We hope that our work may stimulate future investigations aimed at establishing a connection between our parameters \\documentclass[12pt]{minimal}\n\t\t\t\t\\usepackage{amsmath}\n\t\t\t\t\\usepackage{wasysym} \n\t\t\t\t\\usepackage{amsfonts} \n\t\t\t\t\\usepackage{amssymb} \n\t\t\t\t\\usepackage{amsbsy}\n\t\t\t\t\\usepackage{mathrsfs}\n\t\t\t\t\\usepackage{upgreek}\n\t\t\t\t\\setlength{\\oddsidemargin}{-69pt}\n\t\t\t\t\\begin{document}$${\\mathscr {T}}_0$$\\end{document} T 0 and R and interaction parameters of real systems. A possible experimental setup could be perhaps realized either through biological engineering (manipulating the length and mechanical properties of algal flagella) or by manufacturing artificial microswimmers following prescribed non-reciprocal interactions. The non-reciprocal avoidant torque of Eq. ( 5 ) has a very generic form, which one can modify. In particular, there is a symmetry in the torque values for a particle oriented towards or away from its neighbor. One can break this symmetry and make the avoidant torque larger when the particle is oriented towards its neighbor. Such a modification might, for example, be interesting to describe the social interaction of a prey turning away from a predator (Supplementary Videos 1 – 4 )."
} | 8,044 |
22367118 | null | s2 | 3,357 | {
"abstract": "Reconstructed microbial metabolic networks facilitate a mechanistic description of the genotype-phenotype relationship through the deployment of constraint-based reconstruction and analysis (COBRA) methods. As reconstructed networks leverage genomic data for insight and phenotype prediction, the development of COBRA methods has accelerated following the advent of whole-genome sequencing. Here, we describe a phylogeny of COBRA methods that has rapidly evolved from the few early methods, such as flux balance analysis and elementary flux mode analysis, into a repertoire of more than 100 methods. These methods have enabled genome-scale analysis of microbial metabolism for numerous basic and applied uses, including antibiotic discovery, metabolic engineering and modelling of microbial community behaviour."
} | 202 |
29950589 | PMC6021390 | pmc | 3,359 | {
"abstract": "Microbial aromatic catabolism offers a promising approach to convert lignin, a vast source of renewable carbon, into useful products. Aryl- O -demethylation is an essential biochemical reaction to ultimately catabolize coniferyl and sinapyl lignin-derived aromatic compounds, and is often a key bottleneck for both native and engineered bioconversion pathways. Here, we report the comprehensive characterization of a promiscuous P450 aryl- O -demethylase, consisting of a cytochrome P450 protein from the family CYP255A (GcoA) and a three-domain reductase (GcoB) that together represent a new two-component P450 class. Though originally described as converting guaiacol to catechol, we show that this system efficiently demethylates both guaiacol and an unexpectedly wide variety of lignin-relevant monomers. Structural, biochemical, and computational studies of this novel two-component system elucidate the mechanism of its broad substrate specificity, presenting it as a new tool for a critical step in biological lignin conversion.",
"introduction": "Introduction Lignin is a heterogeneous, aromatic biopolymer found in abundance in plant cell walls where it is used for defense, structure, and nutrient and water transport 1 . Given its prevalence in plant tissues, lignin is the largest reservoir of renewable, aromatic carbon found in nature. The ubiquitous availability of lignin in the environment, coupled to its inherent structural heterogeneity and complexity, has led to the evolution of microbial strategies to break lignin polymers down to smaller fragments using powerful oxidative enzymes secreted by rot fungi and some bacteria 2 – 4 . These lignin oligomers can be further assimilated as carbon and energy sources, through at least four known catabolic paradigms 5 . The most well understood aromatic catabolic mechanism, mainly studied in aerobic soil bacteria, relies on the use of non-heme iron-dependent dioxygenases to oxidatively ring-open structurally diverse, lignin-derived aromatic compounds 5 , 6 . These dioxygenases act on central intermediate substrates, such as catechol, protocatechuate, and gallate, either in an intra- or extra-diol manner. Lignin is primarily based on coniferyl (G) and sinapyl (S) alcohol subunits, which exhibit one or two methoxy groups on the aromatic ring, respectively. Nearly all lignin-derived compounds must therefore be O -demethylated to diols before they can be oxidatively cleaved to generate ring-opened compounds, which are ultimately routed to central carbon metabolism (Fig. 1 ) 7 . More recently, the same aromatic-catabolic pathways have been invoked as a potential means to convert lignin to useful products in biorefineries 4 , 7 – 11 . O -demethylation is therefore a critical reaction for assimilating lignin-derived carbon in both natural carbon cycling as well as in emerging biotechnology applications. Fig. 1 O -demethylation in aromatic catabolism. a \n O -demethylation provides a central role in the upper pathways of aromatic catabolism 5 , 6 , 76 – 80 . G- and S-lignin, the primary units in lignin, are O -demethylated to form central intermediates. These are then cleaved by intradiol (red lines) or extradiol (blue lines) dioxygenases. b Coupled reactions catalyzed by GcoA and GcoB. por, porphyrin The importance of O -demethylation has motivated substantial efforts toward the discovery and characterization of enzymes capable of demethylating the methoxy substituents of diverse lignin-derived substrates 12 – 20 . For example, Ornston et al. described the VanAB O -demethylase in Acinetobacter baylyi ADP1, which converts vanillate to the central intermediate, protocatechuate, via a Rieske non-heme iron monooxygenase mechanism 14 , 15 . VanAB, which is common in many aromatic-catabolic soil bacteria, is active on vanillate analogs, but to our knowledge, has not been reported to be active on other lignin-derived compounds. Masai and colleagues first described LigX 18 from Sphingobium sp. SYK-6, a model bacterium for aromatic catabolism 7 . LigX also employs a Rieske non-heme iron monooxygenase mechanism to demethylate a biphenyl compound representing a common lignin linkage. Masai et al. additionally reported, in SYK-6, two tetrahydrofolate-dependent O -demethylases, LigM and DesA. LigM primarily demethylates vanillate and 3- O -methylgallate, whereas DesA principally demethylates syringate with very weak activity on vanillate 16 , 17 . Earlier reports from Eltis et al. and Bell et al. described cytochrome P450-based demethylation of aromatic compounds; though either the full gene sequences were not reported until recently 13 , 21 , or the para -substituted substrate (4-methoxybenzoate) was of limited interest for the lignin degradation problem 22 , 23 . Similarly, Dardas et al. found evidence of a P450 in Moraxella GU2 responsible for the O -demethylation of guaiacol and guaethol; however, neither the gene sequence nor identity of the P450 or its reductase partner was isolated 24 . The relatively narrow substrate specificities elucidated to date for aryl- O -demethylation, coupled to the potentially broad distribution of structurally distinct, methoxylated lignin products found in nature, prompted us to search for alternative mechanisms for this key reaction. Because G-unit monomers constitute a majority of plant-derived lignin, we initially focused on O -demethylation of guaiacol (2-methoxyphenol), which in turn represents the simplest G-unit monomer derivable from lignin. As reported in a companion study 21 , we isolated a cytochrome P450-reductase gene pair, gcoAB , from Amycolatopsis sp. ATCC 39116 (encoding proteins with accession numbers WP_020419855.1 and WP_020419854.1). Introduction of this pair via plasmid-based expression into Pseudomonas putida KT2440, a robust aromatic-catabolic bacterium, was sufficient to confer growth on guaiacol 21 . Here, we report a comprehensive structural, biochemical, and computational description of this new cytochrome P450-based mechanism for aryl- O -demethylation. Unlike other known tetrahydrofolate- or non-heme iron-dependent demethylases, which are fairly substrate specific, the P450-reductase pair characterized here (GcoAB) demethylates diverse aromatic substrates, potentially providing an important advantage in both natural and biotechnological contexts. The results presented here suggest a remarkably flexible active site that may promote promiscuous substrate usage.",
"discussion": "Discussion Recent efforts from multiple groups have attempted to harness aromatic catabolism for productively utilizing lignin 8 – 10 , 18 , 39 – 44 . As a single microbe is unlikely to have the full complement of necessary catabolic enzymes for lignin bioconversion, a key component of such synthetic biology strategies is the introduction of foreign catabolic genes to expand substrate specificities of the host microbe. Bacterial enzymes that catalyze the demethylation of lignin-derived aryl-methoxy substrates are of particular interest, as the demethylation reaction presents a bottleneck for the conversion of lignin into desirable products. Currently, Rieske non-heme iron monooxygenases 14 , 15 , 18 and tetrahydrofolate-dependent O -demethylases 16 , 17 , offer two well-known paradigms for aryl- O -demethylation. This study presents a detailed characterization of a third, cytochrome P450-based enzymatic strategy that could fill a critical gap for engineering applications. From a metabolic engineering standpoint, the GcoAB system offers a number of potential advantages. First, the native substrate of GcoA, guaiacol, is a major breakdown product of plant lignin. Demethylation of guaiacol yields catechol, which can be ring-opened via either intra- or extra-diol cleavage catechol dioxygenases. Second, compared to other known O- aryl-demethylases, the substrate preferences of GcoA are intrinsically broad, admitting a variety of guaiacol analogs that are also known lignin breakdown products. Third, we anticipate a P450 system to be amenable to further tuning using directed evolution techniques 45 . A prior report of a closely related cytochrome P450 that can demethylate 4-methoxybenzoate 12 suggests that the GcoA active site may be modified to admit larger, more hydrophilic, lignin-derived substrates such as ferulate or vanillate. Indeed, genes encoding putative homologs to the two-component GcoA and GcoB system described here are predicted in the genomes of several bacterial species belonging to the genera Rhodococcus , Streptomyces , and Gordonia , among others, and the substrate preferences for this diverse group remain unclear, but offer a promising platform for further exploration and engineering. Moreover, work from Bell et al. revealed an unrelated Rhodopseudomonad cytochrome P450 can also demethylate 4-methoxybenzoate and be productively engineered to accommodate 4-ethylbenzoate. While retaining a classical P450 fold, this CYP199A4 system exhibits an alternative binding mode in terms of both substrate positioning relative to the heme, and steric selectivity with an alternative set of aromatic residues lining the active site pocket, further demonstrating the diversity within this class of enzymes. Fourth, a heme-based P450 may offer a simpler alternative for aromatic demethylation compared to tetrahydrofolate-dependent O -demethylases, given the relative ubiquity of P450s and robust heme biosynthetic pathways in potential bacterial hosts. Finally, distinct from most P450 systems, the GcoB reductase is encoded as a single polypeptide rather than two. Close examination of the GcoA-guaiacol active site shows that substrate binding involves interactions between the peptide backbone and the substrate hydroxyl (ring C1) and methoxy groups (C2). The ring C3 position has a relatively close (3.8 Å) interaction with the porphyrin-γ -meso carbon that bridges the propionate-substituted pyrrole rings. However, the remaining ring positions are not directly occluded by backbone/porphyrin atoms. Reactivity studies showed that guaiacol analogs with substitutions at C4, C5, and C6 remained substrates with comparable efficiencies ( k cat / K M ) to guaiacol itself. Even substitutions at C1 and C2 (ethoxy- for methoxy-) are permitted. Comparison of the structures of the guaiacol, guaethol, vanillin, and syringol ligand-bound GcoA structures shows that all assume a similar binding mode with only subtle reorganization of the surrounding active site residues. MD simulations suggest that the active site opens and closes in response to substrate binding. This flexibility in the active site, in which several side chains (e.g., Phe75, Phe169, and Phe395) reorganize to accommodate the bound ligand, may be partly responsible for the observed substrate promiscuity of GcoA. Though the active site is flexible, potential substrates must be able to maintain the closed state of the active site in order to prevent the uncoupling of NADH oxidation from substrate hydroxylation. The same simulations also suggest that the active site constrains the binding mode of guaiacol, so that the methoxy group points toward and the hydroxyl group is oriented away from the heme iron. This may forestall the lower-energy cyclization reaction pathway predicted for guaiacol by DFT calculations. Together, the structural, biochemical, and computational data presented here suggest a GcoA active site that is sufficiently accommodating to turnover a range of substrates that each react in the desired fashion to release an aldehyde product. We hypothesize that the substrate range and consequently the utility of GcoA may be extended even further, to accommodate important G- and S-type lignin subunits, by protein engineering or directed evolution. Tests of this hypothesis are the subject of ongoing work."
} | 2,952 |
38327460 | PMC10847661 | pmc | 3,361 | {
"abstract": "Platinum group metals (PGMs) assume an important role within the chemistry and chemical engineering due to their exceptional chemical stability in high temperatures and various environmental conditions. Their unique attributes make them highly demanded materials across an array of industries. Nevertheless, the gradual depletion of PGM reserves underscores necessitates of recycling PGM-containing waste as a means to ensure the reasonable utilization of resources. Recycling of catalytic waste, in particular, presents a more cost-effective and environmentally sustainable approach acquiring these metals, in contrast to the conventional practice of mining from natural ores. Of particular importance are spent automotive catalysts, which represent a valuable source of platinum group metals, featuring substantially higher PGM concentrations than their naturally occurring counterparts. Conventionally, the recovering of PGMs from waste materials predominantly employs hydrometallurgical and pyrometallurgical processes. Unfortunately, these established techniques entail the utilization of potent oxidizing acidic solutions, including aqua regia and hydrochloric acid with chlorine gas, which exert adverse ecological consequences. In recent years, there has been a growing focus on the development of alternative methodologies that are both environmentally friendly and economically viable for the recovery of PGMs from spent catalysts. Notable among these emerging techniques are solvometallurgy, molecular recognition technology, and magnetic separation. This comprehensive review endeavors to study and assess the latest advancements in the recovery of platinum group metals from spent catalysts, meticulously evaluating their respective advantages and disadvantages. Through an analysis, this review aspires to identify the most promising method - one that combines environmental friendliness and economic feasibility.",
"conclusion": "7 Conclusion Innovative methods are crucial for extracting platinum group metals (PGMs) from ores, driven by the challenging procedures involved. Recycling catalytic waste, especially from automotive catalytic converters, has become essential. Two primary recycling techniques, hydrometallurgy and pyrometallurgy, are prominent. Hydrometallurgy involves treating catalytic waste to eliminate organic residues. Catalysts like Pt/γ-Al 2 O 3 and Pd/γ-Al 2 O 3 can be dissolved in sulfuric acid, concentrating platinum (Pt) and palladium (Pd). However, limitations such as subpar extraction rates for rhodium, high reagent costs, hazardous waste generation, and prolonged processing hinder its advancements. Pyrometallurgy involves fusion and chlorination, resulting in an auxiliary metal-PGM alloy, purified to extract PGMs. Despite effectiveness, challenges include equipment corrosion expenses and environmental risks from gases like carbon monoxide and chlorine. To address these challenges, solvometallurgy and molecular recognition technology offer environmentally friendly alternatives with high selectivity and swift reaction kinetics. Another promising approach involves magnetic concentration directly from catalytic converter waste, using ferromagnetic iron deposition onto PGM particles. This scalable method requires minimal energy and emits no harmful substances. These innovative approaches, including solvometallurgy, molecular recognition technology, and magnetic concentration, provide advantages in selectivity, reaction speed, and environmental sustainability. The resulting catalytic systems have diverse applications in industries such as chemicals, energy, petroleum, jewelry, and healthcare. The continuous evolution of efficient methodologies is vital for the sustainable utilization of these valuable metals.",
"introduction": "1 Introduction The platinum group metals (PGMs), which include platinum, palladium, rhodium, ruthenium, osmium, and iridium, have held a long-standing allure and have ascended to eminence across various industrial sectors. Historical accounts reveal that the discovery of significant PGM reserves in nations such as Russia, the USA, Canada, and South Africa between the 18th and 20th centuries served to establish the important role of platinum in the global industrial landscape [ 1 ]. Over the course of the past two centuries, platinum has showcased its remarkable versatility, finding utility not only in jewelry craftsmanship but also as a catalyst with wide-ranging applications [ 2 ]. Within the automotive industry, platinum group metals (PGMs) have found extensive utilization as catalysts for exhaust gas treatment, a practice that has gained prominence since the 1970s [ 3 ]. This surge in PGM application is primarily caused by the necessity to meet strict environmental requirements, exemplified by regulations like the Euro standards [ 4 ]. Conventional PGM extraction from ores involves labor-intensive processes, underscoring the need for more ecologically sustainable, convenient methodologies for obtaining catalytic systems. Consequently, the recycling of catalytic waste, including components like catalytic converters, has emerged as a highly promising approach. This article is dedicated to a comprehensive examination of recent breakthroughs in the development and implementation of techniques geared towards the recycling of catalytic converters, with the goal of obtaining functional catalyst systems. The remarkable chemical stability exhibited by platinum group metals (PGMs) under extreme temperatures and various environmental conditions makes them exceptionally well-suited for industrial applications ( Fig. 1 ), mainly as catalysts. These PGMs are instrumental in acceleration of chemical reactions and facilitating the selective advancement of particular chemical processes. They occupy a position of significant importance within the chemistry and chemical engineering [ 1 ]. Fig. 1 – Net demand for Pt (178 tons), Pd (303.5 tons) and Rh (29.5 tons) for various industries (2023) [ 5 ]. Fig. 1 In summary, this review focuses on the important role of platinum group metals (PGMs) within the chemistry and chemical engineering. It accentuates their historical significance, expansive utility across various areas, and high attention directed toward the recycling of catalytic waste as a means to acquire valuable catalyst systems. Their most notable application lies in their role as catalysts, orchestrating chemical reactions and, in scenarios involving multiple concurrent reactions, selectively promoting the most critical ones [ [6] , [7] , [8] , [9] , [10] , [11] , [12] , [13] , [14] ]. PGMs function as catalysts in important processes, including ammonia and ammonium nitrate production [ [15] , [16] , [17] , [18] ], catalytic converters [ 1 , 12 , 19 , 20 ], hydrogen fuel cells [ [21] , [22] , [23] , [24] , [25] ] and various other areas of significance. PGM catalysts constitute an category of mixed oxide catalysts, allowing for a comprehensive analysis of their chemical surface and catalytic properties under conditions equivalent to those experienced by operative oxide catalysts [ 8 ]. Within PGM catalysts, rhodium assumes the role of a reduction catalyst, palladium serves as an oxidation catalyst, and platinum functions as a redox catalyst [ 26 ]. The synthesis of PGMs involves a diverse array of methodologies, typically yielding microstructures and nanostructures with a rich spectrum of shapes, including spheres, pyramids, cubes, and dumbbells [ 27 ]. Of particular note, platinum catalysts have attracted significant attention due to their remarkable activity in catalyzing CO oxidation reactions. The industrial market presents a significant demand for platinum, palladium, and rhodium, as illustrated in Fig. 2 [ 1 ]. Fig. 2 Net demand in tons for PGM for the industrial sector, in 2023. Fig. 2 Table 1 showcases the wide array of industrial applications where PGM catalysts find extensive use. Table 1 Applications of PGM catalysts. Table 1 Catalyst Reaction References Pt/Al 2 O 3 /SiO 2 Disproportionation of toluene to benzene [ 28 ] Pd/H–Y-Zeolite Obtaining fuel by cracking of vacuum distillates [ 29 , 30 ] Pt/Zeolite Xylene isomerisation [ 31 ] Pt/Pd/Rh Industrial exhaust [ [32] , [33] , [34] ] Pt, Pd/oxide supports Volatile organic compounds removal [ [35] , [36] , [37] ] Pt Hydrodesulphurisation [ 38 ] Pt/Zeolite Naphtha reforming [ 39 ] Pd Caprolactam synthesis [ 40 , 41 ] Pd/supported oxides Telomerisation of 1,3-dienes [ 42 ] Pd Production of toluene diisocyanate [ 43 ] Pd suspension Production of H 2 O 2 [ 40 ] Pd Bio-oils hydrogenation [ 44 , 45 ] Pt/Pd/Rh Oxidation of ammonia [ 46 ] Pt, Pd Ketones/aldehydes to alcohol [ 47 ] Pt/Pd/Rh Production of nitric acid [ 40 ] Rh, Pd/SiO 2 Acetic acid synthesis [ 40 ] Rh Production of citronella PdCl 2 Acetaldehyde synthesis [ 40 ] Pd 2,5-dichloropyridine amidocarbonylation [ 48 ] Pt Hydrogenation [ 45 , 49 ] PdCl 2 Substituted alcohol carbonylation [ 50 ] Pd Aldehydes and Ketones amination [ 51 ] Pd Production of 1-octene [ 52 ] Within the realm of fine chemicals, various applications necessitate high selectivity despite producing relatively modest product volumes. Pharmaceutical production accounts for over 50 % of this sector, with agriculture making up 25 %, and the remaining 25 % distributed among flavors, dyes, pigments, and food additives [ 45 ]. Within this spectrum, hydrogenation reactions constitute a significant portion, spanning approximately 10–20 % of the product range. These reactions include the hydrogenation of nitro compounds, asymmetric catalysis, and the selective hydrogenation of double bonds. Predominantly, Pd catalysts are deployed in these processes, although other catalysts may also find applicability. One pivotal hydrogenation reaction pertains to the reduction of nitrobenzene, which plays a crucial role in the production of aniline dyes, explosives, and pharmaceuticals. Furthermore, a significant asymmetric reaction revolves around the production of menthol, which is facilitated by the utilization of an Rh catalyst. In a study [ 53 ], it has been established that a catalyst containing just one percent rhodium supported on a mixed cerium-zirconium oxide (1 % Rh/Ce 0.75 Zr 0.25 O 2 ) demonstrates high activity over an extended period, maintains its purity, and facilitates conversion of C 2+ -hydrocarbons into CH 4 , CO 2 and H 2 at relatively low temperatures (300–400 °C). An interesting feature of rhodium catalysts lies in their unique ability to generate minimal amounts of ethane. This study underscores the potential of rhodium as an alternative to nickel due to its superior catalytic activity and stability. Importantly, rhodium catalysts can be deployed without the need for pretreatment in a reducing environment, enhancing their practicality and efficiency."
} | 2,708 |
28781576 | null | s2 | 3,363 | {
"abstract": "Coral reefs worldwide are shifting from high-diversity, coral-dominated communities to low-diversity systems dominated by seaweeds. This shift can impact essential recovery processes such as larval recruitment and ecosystem resilience. Recent evidence suggests that chemical cues from certain corals attract, and from certain seaweeds suppress, recruitment of juvenile fishes, with loss of coral cover and increases in seaweed cover creating negative feedbacks that prevent reef recovery and sustain seaweed dominance. Unfortunately, the level of seaweed increase and coral decline that creates this chemically cued tipping point remains unknown, depriving managers of data-based targets to prevent damaging feedbacks. We conducted flume and field assays that suggest juvenile fishes sense and respond to cues produced by low levels of seaweed cover. However, the herbivore species we tested was more tolerant of degraded reef cues than non-herbivores, possibly providing some degree of resilience if these fishes recruit, consume macroalgae, and diminish negative cues."
} | 267 |
24358717 | null | s2 | 3,364 | {
"abstract": "Ecological networks of two interacting guilds of species, such as flowering plants and pollinators, are common in nature, and studying their structure can yield insights into their resilience to environmental disturbances. Here we develop analytical methods for exploring the strengths of interactions within bipartite networks consisting of two guilds of phylogenetically related species. We then apply these methods to investigate the resilience of a plant-pollinator community to anticipated climate change. The methods allow the statistical assessment of, for example, whether closely related pollinators are more likely to visit plants with similar relative frequencies, and whether closely related pollinators tend to visit closely related plants. The methods can also incorporate trait information, allowing us to identify which plant traits are likely responsible for attracting different pollinators. These questions are important for our study of 14 prairie plants and their 22 insect pollinators. Over the last 70 years, six of the plants have advanced their flowering, while eight have not. When we experimentally forced earlier flowering times, five of the six advanced-flowering species experienced higher pollinator visitation rates, whereas only one of the eight other species had more visits; this network thus appears resilient to climate change, because those species with advanced flowering have ample pollinators earlier in the season. Using the methods developed here, we show that advanced-flowering plants did not have a distinct pollinator community from the other eight species. Furthermore, pollinator phylogeny did not explain pollinator community composition; closely related pollinators were not more likely to visit the same plant species. However, differences among pollinator communities visiting different plants were explained by plant height, floral color, and symmetry. As a result, closely related plants attracted similar numbers of pollinators. By parsing out characteristics that explain why plants share pollinators, we can identify plant species that likely share a common fate in a changing climate."
} | 535 |
27786309 | PMC5082368 | pmc | 3,365 | {
"abstract": "With the increasing anthropogenic CO 2 concentration, ocean acidification (OA) can have dramatic effects on coral reefs. However, the effects of OA on coral physiology and the associated microbes remain largely unknown. In the present study, reef-building coral Acropora gemmifera collected from a reef flat with highly fluctuating environmental condition in the South China Sea were exposed to three levels of partial pressure of carbon dioxide ( p CO 2 ) (i.e., 421, 923, and 2070 μatm) for four weeks. The microbial community structures associated with A. gemmifera under these treatments were analyzed using 16S rRNA gene barcode sequencing. The results revealed that the microbial community associated with A. gemmifera was highly diverse at the genus level and dominated by Alphaproteobacteria. More importantly, the microbial community structure remained rather stable under different p CO 2 treatments. Photosynthesis and calcification in A. gemmifera , as indicated by enrichment of δ 18 O and increased depletion of δ 13 C in the coral skeleton, were significantly impaired only at the high p CO 2 (2070 μatm). These results suggest that A. gemmifera can maintain a high degree of stable microbial communities despite of significant physiological changes in response to extremely high p CO 2 .",
"conclusion": "Conclusions In this study, the tropical fast-growing coral A. gemmifera from a shallow habitat with natural pH/ p CO 2 fluctuations was selected as a representative species and was exposed to a 4-week CO 2 treatment. The microbial communities and skeletal isotopic compositions were examined simultaneously. We found that the microbial communities in A. gemmifera remained remarkably stable. In contrast, neither photosynthesis nor calcification in the coral were impacted under medium p CO 2 but were both negatively affected under extremely high p CO 2 , as demonstrated by an enrichment of δ 18 O and increased depletion of δ 13 C in the skeleton under extremely high CO 2 stress. The present findings indicate that some reef-building corals may be more tolerant to OA in pH/ p CO 2 fluctuating environments and have a high degree of host-symbiont fidelity, despite the observed impairment of host physiological processes in response to high CO 2 stress. This study also contributes to our understanding of the variability of OA resistance among coral-microbial associations. Because coral reefs are facing other environmental stresses in addition to OA, the synergistic effects of multiple stressors on the coral microbiome must be carefully examined to understand the persistence of the coral holobiont and coral reefs in the future ocean.",
"discussion": "Results and Discussion Overview of the microbial communities After quality filtering, 308,591 reads were used for the downstream analyses. The number of operational taxonomic units (OTUs), Chao1 estimation of species richness, and Shannon index were obtained at a dissimilarity of 3% ( Table 1 ). The rarefaction analyses revealed that the sequencing effort for each sample was sufficient to reflect the microbial diversity, and the rank-abundance curve showed that most OTUs had an abundance lower than 0.1%, which demonstrated that the microbial communities were occupied by rare species (see Supplementary Fig. S2 ). The prevalence of rare species has been widely demonstrated elsewhere, yet the ecological and functional roles of these rare species remain unknown 31 . There were no significant differences in beta diversity among the p CO 2 treatments, which is in contrast to the findings of a previous report showing an increase in coral microbial diversity with decreasing pH, possibly caused by an intermediate disturbance 16 . In total, 24 bacterial and 2 archaeal phyla were detected in the coral and seawater samples, including Proteobacteria, Actinobacteria, Bacteroidetes, Cyanobacteria, Firmicutes, Thaumarchaeota and Euryarchaeota (see Supplementary Fig. S3 ). The relative abundance of archaea made up less than 0.1% of the seawater samples, with most OTUs belonging to autotrophic ammonia-oxidizing archaea (AOA) within the phylum Thaumarchaeota, which was even less abundant in the coral samples. It has been suggested that archaea may play prominent roles in corals and reefs 5 , although their abundance in both corals and reef water is much lower than that of bacteria 32 . Notably, the bacterial communities in both A. gemmifera and seawater were dominated by Proteobacteria and the most abundant class was Alphaproteobacteria (56–80%), among which the majority were assigned to the family Brucellaceae in the order Rhizobiales ( Fig. 1 ) followed by Gammaproteobacteria (9–26%). Both Alphaproteobacteria and Gammaproteobacteria are commonly highly abundant in corals, but their relative abundance varies among species 33 . Taxonomic assignment at the genus level was summarized, and genera with an abundance of greater than 1% in at least one sample are shown in a heat map ( Fig. 2 ). In the present study, the unclassified Brucellaceae (>24%), Acinetobacter (>9%) and Pannonibacter (>5%) were the most abundant genera in coral, regardless of the p CO 2 treatment. Diazotrophs within the order Rhizobiales have been found in other coral species and were considered to be important for coral holobiont in nitrogen-limited waters 5 . It has been shown that copiotrophic taxa including Brucellaceae were enriched in algal-dominated environment 34 . Diverse algal communities on the Luhuitou fringing reef 35 might contribute to the dominance of unclassified Brucellaceae in A. gemmifera . Acinetobacter spp. have also been commonly reported in bleached and healthy corals 36 . Therefore, it is reasonable to suggest that the dominant genera, including Acinetobacter and the unclassified Brucellaceae, play critical roles in A. gemmifera . Interestingly, the putatively endosymbiotic Endozoicomonas 37 was detected at a very low level in all coral samples (<2%). The photosynthetic Cyanobacteria assigned to the genus Synechococcus have been reported in sponge and coral 21 and were also detected at a very low abundance (0.2%) in A. gemmifera . However, the functions of bacteria and archaea and their interactions in the coral holobiont remain largely unclear. Stability of microbial communities in A. gemmifera As estimated by Adonis analysis at all taxonomic levels (Adonis test, p > 0.05) and nMDS ordination (see Supplementary Fig. S4 ), there were no significant differences in microbial community compositions in A. gemmifera among the different p CO 2 treatments even after a 4-week exposure. Additionally, results from the SIMPER analysis showed that the dissimilarity of microbial communities among p CO 2 treatments was very small (see Supplementary Fig. S5 ). Taken together, these findings suggest that the A. gemmifera microbiome was not significantly affected by elevated p CO 2 and could remain relatively stable ( Fig. 2 ). This result is inconsistent with the findings of some previous studies in which the coral microbiome shifted under higher p CO 2 or lower pH treatments over treatment periods ranging from days to months 16 38 . However, our finding is consistent with some other studies. For example, there were no differences in the microbial community structure in coral between pH 7.7 ( p CO 2 = 1187 μatm) and 7.5 ( p CO 2 = 1638 μatm) whereas a significant difference was observed between pH 8.1 ( p CO 2 = 464 μatm) and 7.9 ( p CO 2 = 822 μatm) after 6 weeks of CO 2 exposure 18 . Moreover, Meron et al . 19 observed no significant changes in microbial communities associated with two Mediterranean coral species that were transplanted along natural pH gradients. A recent study reported that the microbial communities of two Pacific coral species were tolerant to reduced pH 7.9 ( p CO 2 738–835 μatm) 20 . These inconsistent results might reflect that some coral-microbial associations are more resistant to increases in p CO 2 /decreases in pH than others, but these findings could also be partially attributed to differences in the experimental conditions (e.g., field vs laboratory, p CO 2 or pH level, among others), and the exposure duration. In most cases, microbial communities are dynamic and can rapidly respond to OA in seawater 39 , biofilms 40 and other associated systems 41 . The genus Acropora is among the most sensitive coral to environmental change 42 . The potential for coral acclimatization or adaptation to climate change has been studied 43 , and the physiological and molecular mechanisms responsible for OA resistance have recently been proposed 8 . Although there is limited evidence for biological adaptation to climate change in coral microbial symbionts, the adaptive power to climate change has been well documented in the photosymbiotic Symbiodinium 10 11 44 . The shallow habitat of the coral A. gemmifera sampled in the present study has been experiencing regular large diurnal and seasonal variations in pH/ p CO 2 (see Supplementary Table S1 ), which are mainly driven by biological activities of the reef 28 29 30 . Therefore, it is most likely that microbial communities harbored by the natural population of A. gemmifera are resistant to the increased p CO 2 , due to long-term acclimatization/adaptation to the highly dynamic pH conditions within the reef flat. Thus, there may be a resilient relationship between coral and microbial partners that can help corals overcome the fluctuations in seawater pH/ p CO 2 . However, we note that the stability of the coral microbiome is based on only one species colleting from a fluctuating environment. The application of variable p CO 2 conditions and controls from stable pH/ p CO 2 environments in highly replicated culture experiments with consideration of tank effects could further confirm this assumption in future studies. A recent study supports this interpretation. Morrow et al . 21 found that microbial communities associated with coral and sponge originally from natural volcanic CO 2 seeps were distinct from the nearby control sites, reflecting the acclimatization of the host-symbiont to the high p CO 2 environment. Local acclimatization/adaptation to environmental variations in p CO 2 , temperature and nutrients, among others, has revealed the capabilities of marine organisms including reef-building corals and symbiotic algae, to adapt to future climate change 8 24 25 44 45 . However, in general, the species-specific response of marine organisms to OA remains poorly understood 1 23 46 . Thus, it is rather premature to conclude whether we can extrapolate the adaptive power of coral and its associated microbes documented in the present study to other coral species living in highly fluctuating reef environments. Skeletal isotopic response to ocean acidification During our experiments, all blocks of A. gemmifera exposed to the different p CO 2 treatments grew, survived and formed new skeleton (see Supplementary Fig. S6 ), even at the high p CO 2 (pH reduced to 7.47). When the fast-growing coral A. gemmifera skeletal δ 13 C and δ 18 O were compared among the different p CO 2 treatments, the skeletal δ 13 C values in A. gemmifera were significantly different between any two p CO 2 treatments except between the control and the medium ( Fig. 3 ). Skeletal δ 13 C values were depleted by 1.10‰ and 1.04‰ for the control vs. high p CO 2 and for the medium vs. high p CO 2 , respectively (one-way ANOVA, Tukey test, p < 0.05). Skeletal δ 18 O values in A. gemmifera were enriched with increased p CO 2 ; they were 0.55‰ and 0.38‰ heavier in response to high p CO 2 than those in the control and medium, respectively (one-way ANOVA, Tukey test, p < 0.05). Compared with the previous data 47 , skeletal δ 18 O values revealed greater depletion in fast-growing coral A. gemmifera , while the skeletal δ 13 C values remained within range. In addition, the relationship between skeletal δ 13 C and δ 18 O in the non-photosynthetic coral Tubastrea sp. deviated the most from those both in the photosynthetic corals A. gemmifera and Pavona sp. ( Fig. 3 ). The isotopic composition of the coral skeleton can be affected by metabolic isotope effects (e.g., photosynthesis and respiration) and kinetic isotope effects (e.g., the calcification process) 48 . The coral skeletal δ 13 C and δ 18 O were generally used as an effective proxy to study photosynthesis, respiration and calcification processes 48 49 . In general, photosynthesis and calcification can enrich skeletal δ 13 C but deplete skeletal δ 18 O due to isotope fractionation 47 49 . Compared non-photosynthetic ( Tubastrea sp.) and photosynthetic ( Pavona sp.) corals 47 , the relationship of δ 13 C vs. δ 18 O in Pavona sp. and A. gemmifera was different from that in Tubastrea sp. (non-photosynthetic coral) due to active photosynthesis. In addition, more δ 18 O deviation was observed in A. gemmifera than Tubastrea sp. and Pavona sp., mostly due to the highest growth rate in A. gemmifera ( Fig. 3 ). Skeletal δ 13 C values in A. gemmifera were significantly depleted at the high p CO 2 , suggesting that the photosynthetic rates were much lower at the high p CO 2 than at the control p CO 2 . The variation in skeletal δ 18 O values of A. gemmifera was consistent with the findings of a previous study demonstrating an enrichment of δ 18 O in the coral skeleton in response to elevated p CO 2 49 . The coral calcification rate decreases under reduced pH conditions 9 , which corresponds to heavier skeletal δ 18 O, whereas low p CO 2 and higher pH lead to species with lighter δ 18 O because HCO 3 − is isotopically heavier than CO 3 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 . Consequently, the significantly enriched δ 18 O and more depleted δ 13 C in A. gemmifera observed herein may reflect slight reductions in photosynthesis and calcification at the high p CO 2 . It should be noted that A. gemmifera skeletal δ 13 C and δ 18 O values did not vary significantly at the medium p CO 2 , potentially because this stress level did not exceed its acclimatization range. These findings indicate that the coral A. gemmifera is able to acclimate to an acidifying ocean, even in the presence of a dramatically increasing atmospheric CO 2 concentration. Although the mechanisms by which extremely high p CO 2 induces decreased photosynthesis and calcification efficiencies in A. gemmifera are unknown, several potential mechanisms have been proposed, such as photoinhibition and suppression of the carbon concentrating process 3 9 . Photosynthesis, calcification and other physiological processes in reef-building corals can be influenced by their microbial partners or vice versa under OA 17 . However, the microbial communities associated with A. gemmifera remained unchanged as a consequence of host physiological changes, further supporting our hypothesis that highly stable microbial associations are likely driven by local acclimatization/adaptation to the fluctuating environment. Alternatively, host physiological costs might result from a potentially increasing energy demand to maintain stable microbial assemblages at the extremely high p CO 2 that exceeds its tolerance level. It has also been proposed that physiological differences among symbiotic algal phylotypes may influence the stable isotopic composition of coral skeleton 50 . Furthermore, the distinct mechanisms used to concentrate carbon by different Symbiodinium phylotypes and their physiological responses to OA are phylotype- specific 51 . For example, Symbiodnium community shifts may occur in response to environmental stresses 10 11 . In the present study, we did not investigate Symbiodinium phylotypes associated with A. gemmifera . A recent study found no changes in Symbiodinium phylotypes associated with corals among different pH conditions 19 , suggesting the presence of stable Symbiodinium assemblages in corals in response to OA. In general, a stable microbial partnership to maintain key metabolic functions can improve coral holobiont acclimatization or adaptation to environmental stresses 5 . However, the interactions between microbial communities and coral physiology remain far from clarified."
} | 4,111 |
36697422 | PMC9877027 | pmc | 3,366 | {
"abstract": "Despite the recognized importance of mycorrhizal associations in ecosystem functioning, the actual abundance patterns of mycorrhizal fungi belowground are still unknown. This information is key for better quantification of mycorrhizal impacts on ecosystem processes and for incorporating mycorrhizal pathways into global biogeochemical models. Here we present the first high-resolution maps of fine root stocks colonized by arbuscular mycorrhizal (AM) and ectomycorrhizal (EcM) fungi (MgC ha−1). The maps were assembled by combining multiple open-source databases holding information on root biomass carbon, the proportion of AM and EcM tree biomass, plot-level relative abundance of plant species and intensity of AM and EcM root colonization. We calculated root-associated AM and EcM abundance in 881 spatial units, defined as the combination of ecoregions and land cover types across six continents. The highest AM abundances are observed in the (sub-)tropics, while the highest EcM abundances occur in the taiga regions. These maps serve as a basis for future research where continuous spatial estimates of root mycorrhizal stocks are needed."
} | 286 |
40241745 | PMC12002618 | pmc | 3,368 | {
"abstract": "Summary Despite advances in coral restoration science, challenges imposed by rapid environmental change impede progress. Here, we report mortality from disease and bleaching in an introduced nursery-reared population of the staghorn coral Acropora aspera, in Guam, Micronesia. We present disease progression, incidence, synergies between stressors, and response of the coral microbiome. Microbiome composition in nursery vs. outplanted corals indicated dysbiosis induced by the transition to poorer water quality. However, among outplants, there were no differences between diseased tissues, visually healthy tissues on the same infected colony and tissues from non-infected colonies, suggesting that outplanting into a stressful environment may have compromised coral immune response, increasing susceptibility to disease and bleaching. Our study highlights that outplanting is inherently physically stressful, thus underscoring the need for understanding the microbiome’s role in the coral transplantation stress response. We suggest workflows to minimize stress and improve restoration in the face of environmental challenges.",
"introduction": "Introduction As coral reef decline continues worldwide, coral restoration must develop rapidly as a science to provide substantial benefits as a conservation and management option. 1 While significant progress has been made to develop and test methods, 2 , 3 , 4 define and quantify “success”, 5 incorporate genetic diversity as a success metric, 6 and facilitate climate resilience, 7 , 8 the shifting baseline caused by rapid environmental change continues to challenge restoration efforts. The increasing intensification of tropical storms, 9 warming waters, and disease prevalence 10 has made these shifting baselines more evident in conservation efforts and continues to undermine progress with restoration. The process of restoring coral can expose colonies to multiple shifts in their environmental contexts, particularly if a nursery phase is included. One of the most targeted genera for restoration, Acropora spp., are broadcast spawners that must acquire their endosymbionts (e.g., Symbiodiniaceae algae and bacteria) horizontally at a very early juvenile stage from their surrounding environment. 11 While this attribute generally confers high symbiotic flexibility in responding to environmental change, 12 , 13 these generalist corals are stress sensitive and often described as ecological ‘losers’. 14 , 15 A symbiotic flexibility can also compound stress in outplanted or source colonies if the recipient site is characterized by environmental conditions that are an extreme contrast to their previous site or beyond eco-physiological limits. 16 Impacts of stress exposure on the coral holobiont include heightened susceptibility to infections 17 , 18 or bleaching, 19 which can also interact synergistically to increase mortality. 20 An effective management strategy to reduce the risk of infectious disease in coral restoration requires a multi-faceted approach to understanding how stress manifests from outplanting through the post-outplant acclimation period 21 , 22 and developing protocols to reduce the risk of disease exposure and spread among outplants. Unlike bleaching, infectious diseases are a direct cause of the disruption of the integrity of a coral holobiont’s microbiome, i.e., microbiome dysbiosis as a result of an external influence. 22 , 23 Disease outbreaks in key community structurers have increased in severity and frequency, e.g., among corals (stony coral tissue loss disease 24 , 25 ; sea stars (sea star wasting disease 26 ) and seagrasses (seagrass wasting disease 23 ), a trend often linked with accelerated environmental deterioration. 27 , 28 , 29 , 30 , 31 This association highlights the urgent need for improved disease management and risk reduction in conservation and restoration. Climate change impacts to nearshore communities are often exacerbated by local stressors and it is often beyond the capacity of restoration efforts to address these issues, as they require considerable political collaboration and coordination. 32 Thus, managing disease and stress in a restoration project is most likely to be accomplished by an increased understanding of species-specific resilience and trade-offs to known stressors, and close matching of species requirements with outplant site characteristics. In Guam, White syndromes (WS) are the most prevalent diseases impacting corals 33 and is a term applied to a group of acute tissue loss diseases with a broad host range. Causal agents have not been identified to date, 34 , 35 though bacteria attributed to Vibrio spp. have been implicated in certain outbreaks. 36 , 37 The onset, pattern, and rate of tissue loss may vary widely among host coral taxa and the diseases may manifest as acute outbreaks or chronic infections. Among Guam staghorn Acropora , WS prevalence is generally low though it often appears as an acute outbreak, during or after summer bleaching events. 38 Lesion onset begins at the base of a branch, progressing upward at a mean rate of 15 mm/week, and circumscribing a branch (Raymundo, unpublished data). Total colony mortality can result, which can have a greater impact on highly clonal thicket-forming species such as staghorns. Coral restoration in Guam was initiated in 2015 in response to repeated mortality events beginning in 2013. From 2013 to 2017, multiple bleaching events, extreme low tide exposures, and disease outbreaks resulted in island-wide coral mortality and decline. 39 , 40 Among the worst-impacted taxa were staghorn Acropora , which suffered an estimated 59% decline between 2013 and 2021. 40 , 41 Limited to the shallow reef flats in Guam, these communities exist near their upper thermal limits and are known to have low resistance to bleaching and high susceptibility to tissue loss diseases. 42 , 43 , 44 This sensitivity to environmental stressors is also reflected in their life history strategies; as ‘r-selected’ species, they much energy in fast, expansive growth and high reproductivity capacity. 45 , 46 At present, five of the eight described morphospecies (i.e., species identified by morphological characteristics) from Guam are limited to a single wild population and are thus at a high risk of local extinction, 41 making them a critical focus of Guam’s initial restoration efforts. 42 All eight species are currently grown in two nurseries: Piti Bomb Holes Marine Preserve (13°28′16.33″N, 144°42′06.38″E), and Cocos Lagoon (13°15′29.77″N, 144°39′39.27″E) ( Figure 1 A). 41 Each nursery consists of 12 midwater PVC “trees”, housing 144 fragments suspended on monofilament which are regularly pruned and outplanted into selected sites supporting existing staghorn populations. Figure 1 Map of the study area (A) Map of Guam highlighting Guam’s Marine Preserves (blue areas), locations of coral nursery sites (yellow stars), outplant site (red dot), and the wild population (green dot); (B) location of the remaining wild population of Acropora aspera; and (C) the outplant site within Tumon Bay Marine Preserve. Control plots refer to unrestored substrate; Reference plots refer to high coral cover areas. Photo credit: D. Burdick and M. Andersen. Here, we report a mortality event within an outplanted population of the staghorn coral Acropora aspera . Recent bleaching events have reduced A. aspera to a single remaining wild population, comprising a 4-ha thicket on the Achang Reef Flat ( Figure 1 B) with an estimated mean live coral cover of 38.6%. 41 Fragments from this population were collected and established in two ocean nurseries in 2017, and outplanting was initiated in 2019 to re-establish populations near the nursery sites ( Figure 1 A). 41 A third site, Tumon Bay Marine Preserve, was selected for outplanting as it is an iconic site supporting an extensive population of a congener, Acropora pulchra. In February 2022, nursery-grown fragments were introduced into four plots within Tumon Bay ( Figure 1 C). Outplants showed 100% survival, positive growth, and absence of disease or bleaching for the first three months. However, during the fourth month post-outplant (May), a disease and bleaching event developed coinciding with an algal bloom and seasonal summer elevated sea surface temperatures. As the entire population of outplants was mapped and georeferenced, it provided a unique opportunity to investigate the dynamic nature of this event quantitatively, look for evidence of resistance to disease or bleaching among individual fragments, and document disease incidence and potential recovery within our outplants. This paper reports our investigative process to document these stress impacts on our restoration effort and discusses the implications of infectious disease and stress events on restoration success.",
"discussion": "Discussion In this case study, we report restoration challenges encountered in our first attempt to introduce a key habitat structuring staghorn species threatened with local extinction in Guam, A. aspera , into a marine protected area that currently supports extensive stands of a closely related staghorn species, A. pulchra . Initial responses of A. aspera to this site were favorable, suggesting that reintroduction might be successful. However, three months post-outplant, our fragments developed rapid tissue loss lesions characteristic of Acropora white syndrome (WS) simultaneously with an algal bloom that impacted water quality. As a rapid response to investigate the trajectory and potential etiology of the WS disease outbreak, we initiated an investigation that included both ecological and microbial sampling over time. Subsequent to the onset of the disease outbreak, we observed bleaching that progressed from slight paling to severe bleaching within two weeks. The timing of bleaching and its absence in A. pulchra stands on the same reef (noted during surveillance snorkels around our study area) suggested that bleaching may have been exacerbated by the presence of disease; a response documented by Muller et al. 20 in a close Western Atlantic relative, Acropora cervicornis . This series of physiological disturbances resulted in complete mortality of our reintroduced colonies. We posit that this devastating result was triggered by compounded environmental stressors that included summer extreme low tides and warming temperatures, exacerbated by algal blooms and high bacterial loads. While the recipient site, Tumon Bay, supports a healthy and vital reef community, we speculate that the poor performance of our outplants was significantly impacted by the instability and shifts in their microbiome that may have compromised their immune function. Our results suggest this instability may have initiated in the coral nursery phase (the source of our outplants) and offer a potential explanation for observed ‘transplantation stress’. 18 This highlights the importance of recipient site acclimation as a key event in restoration success and considers the role of the microbiome in this acclimation process. While it is reasonable to assume that organisms are not equally resistant to all potential stressors, growing evidence suggests that multiple stressors acting simultaneously can have synergistic effects on organisms, leading to much greater impacts to health. Knowlton et al. 42 noted a prolonged die-off of staghorn Acropora after a devastating hurricane, postulating that corallivore populations spiked after the storm, causing persistent mortality among corals. In our surveys to document surviving populations after repeated bleaching events, we noted that at least two populations surveyed during the bleaching year of 2017 had completely died out by 2020 despite the absence of bleaching after 2017. 41 We speculate that disease events may have wiped out these remaining populations after they had survived multiple bleaching years. Muller et al. 20 suggested a potential mechanism for this observation: normally white band disease (WBD)-resistant A. cervicornis outplants became more susceptible to WBD after they had bleached. However, a trade-off between bleaching vs. disease resistance was not demonstrated, illustrating that the severe disease impact observed was not Symbiodiniaceae -related. Bleaching and microbial diseases can thus work synergistically; stress caused by one can decrease the host coral’s capacity to resist the other when subsequently exposed. 47 , 48 As a complex meta-organism, the coral holobiont’s response to environmental stress is controlled by a tight association between the host and its mutualistic assemblage of diverse functional groups of microorganisms. The total mortality we observed among our 162 outplants suggests a lack of stress-resistant genotypes in the hologenome of our outplanted population, though our initial objective at the onset of the outbreak was to track all colonies for potential differential resistance. A recent population genetic analysis of the remaining A. aspera wild population (our original fragment source) indicated high clonality (Combosch and Torrado, unpublished data), thus precluding the likelihood of genetically-based differential stress resistance within the population. The lack of genetic diversity is well-recognized as a factor promoting disease spread in agriculture 49 , 50 but has also recently been addressed in the coral restoration literature. 51 Brown et al. 52 report one of the first studies testing the role of genetic diversity in population-level disease resistance in a closely related species, A. cervicornis; higher genetic diversity increased disease resistance among nursery-reared colonies. This poses a challenge to the conservation of A. aspera in Guam: what is the best restoration approach with a species reduced to a single highly clonal population? Assisted sexual propagation not being an option, our current strategy is to plant populations in multiple sites with differing environmental attributes to determine optimal site preferences, and we are also exploring establishing multi-species plots; i.e., polyculture. The Symbiodiniaceae algal community is established as an essential part of the coral holobiont resistance and innate immune system. 53 , 54 , 55 We did not observe a difference in algal community composition between diseased vs. visually healthy tissue parts of the corals vs. visually healthy corals. It was represented in all samples by two closed ITS2 profiles belonging to genus Cladocopium C40 radiation. This high fidelity with Cladocopium and the absence of the stress-tolerant genus Durusdinium has been observed for several congeneric staghorn species (e.g., A. pulchra, A. virgata ) in different reefs along Guam’s coastline 56 (Andersen et al., unpublished data; Rouzé et al., unpublished data), which may help to explain the high predisposition for disease, low tolerance to bleaching, and lack of differential responses to these two stressors within the population. 37 , 53 However, the evidence of an association between Symbiodiniaceae species identity and coral host disease susceptibility is still not well studied and requires further investigation. 20 , 57 , 58 Similarly, the composition of bacterial communities between apparently healthy and diseased tissues of outplanted corals did not present evidence for: (1) distinct microbiomes as previously reported for other Acropora species 22 , 59 , 60 , 61 , 62 or (2) specific pathogens (often belonging to the genus Vibrio ) 36 , 37 , 63 , 64 as causative agents of the WS outbreak. What we did observe was a clear shift to dysbiosis in the bacterial community structure between May (initiation of WS), and June (WS plus bleaching) in both visually disease-free (though bleaching) and diseased tissues. This supports the findings of Pantos and Bythell 59 of a colony-wide impact of disease in White Band Disease-infected A. palmata; bacterial communities differed distinctly between healthy tissues on diseased colonies vs. those from healthy colonies physically distant from diseased colonies. The high clonality and small population size of our outplants may have further influenced the lack of distinction between healthy and diseased microbiomes from within this population. The loss of dominant bacteria from Pseudomonales (ASV1- Litoricolaceae ) and Flavobacteriales (ASV2- Cryomorphaceae , ASV8- Flavobacteriaceae ) in June communities suggest our corals were experiencing two consecutive events of stress (disease onset and bleaching onset), as both groups of bacteria have been previously described with particular role in coral health: Pseudomonales belong to a dominant group present in healthy but not bleached corals, 65 , 66 while Flavobacteriales have been reported to be involved in other coral diseases such as WBD. 67 This loss most likely promoted a new ecological niche favorable for opportunistic bacteria, explaining the increase in community diversity characteristic of diseased states. 17 , 35 , 36 , 68 Interestingly, Desulfovibrionales, a group of bacteria implicated in Black Band Disease pathogenesis, through the production and accumulation of sulfide 69 , 70 was also detected at low relative abundance in May when the WS outbreak started. These results support the hypothesis of the complex and poorly understood etiology of White Syndromes, influenced by abiotic stressors. 71 We conclude that the mass mortality event we documented was the consequence of a stress phase from outplanting, and synergisms between multiple stressors: anthropogenically high nutrient, bacterial loads within Tumon Bay, 28 , 72 repeated algal blooms, and seasonal sea surface warming. These acted in concert to trigger dysbiosis, increasing the susceptibility to opportunistic bacterial invasion. As the summer progressed, we observed other WS hotspots within the Bay affecting closely-related A. pulchra colonies, suggesting that the prolonged period of multiple stressors was impacting resident communities as well and that a waterborne pathogen may be involved. While we have no pre-outbreak microbiome samples from the original outplanted corals, distinct community compositions were detected between nursery corals and outplanted corals ( Figure 5 B). Interestingly, even with a limited sample size ( n = 5), the bacterial communities of nursery corals showed a high alpha diversity and heterogeneity and were not characterized by a strong core microbiome signature similar to those detected in wild populations for other congeneric staghorn Acropora species. Within conspecific ( A. aspera : Anthony et al., unpublished data) and congeneric healthy wild populations investigated in their natural reef conditions, Endozoicomonas is a dominant component, consistent with what has been found in other species ( A. pulchra 73 ; A. cf. muricata : Andersen et al., unpublished data); in A. aspera outplants, we found this in very low relative abundances (∼4%; Figure 5 B). Our understanding of the role of this dominant genus in coral health and nutrition regulation is growing 74 , 75 , 76 and there is evidence that this genus codiversifies with its hosts. 77 While Endozoicomonas are characterized by intraspecific variability in their capacity to respond to changes in local conditions, 76 , 78 they often exhibit dramatic reductions in relative abundance in stressed, bleached or diseased corals. 79 , 80 We hypothesize that transfer of A. aspera fragments from the wild population to the coral nursery may have triggered an as-of-yet undescribed shift in their microbiome. This could have been caused by the change from a close association with the limestone substrate to the coral nursery trees where they are suspended in the water column. 81 This change in their environment could conceivably alter the core microbiome, potentially with the loss of dominant Endozoicomonas . Instability in holobiont microbial communities could, in theory, be caused by an extreme and sudden environmental change (thermal, nutrient, pH, light irradiance), 81 , 82 resulting in stress to the host. Recent work has documented distinct free-living microbial communities between the coral’s ecosphere and the seawater column over the reef. 77 , 83 , 84 Thus, while this is a novel application within the field of coral restoration, the phenomenon is supported by recent studies. Strudwick et al. 85 , 86 reported a shift over time in bacterial communities associated with Acropora millepora in response to the transfer from the source site to a nursery. However, the same study reported no bacterial community shift in Pocillopora verrucosa , possibly a consequence of the distinct microbiomes transfer mode of Acropora corals (horizontal, from the water column, leading to high flexibility) vs. Pocillopora (maternal, leading to high co-evolution and low flexibility). 85 , 87 Together, these results highlight the importance of understanding the changes that coral holobionts experience during both nursery culture and introduction to restoration sites and suggest areas of future research to improve the success of sustainable coral restoration. While the science of coral restoration is developing rapidly, the consideration of infectious disease in this context is relatively unexplored. This is a critical gap which must be addressed, and lessons learned from aquaculture may provide a starting point. Aquacultured organisms are frequently grown in high densities with low genetic diversity. This can increase susceptibility to – and transmission of – infectious disease (reviewed in Moriarty et al. 88 ). Transport of cultured organisms provides opportunities for introduction or transfer of pathogens as well. Thus, quarantine practices have been developed to prevent the transfer of disease within cultured populations and between cultured and wild populations. 89 , 90 In the present study, we considered whether our nursery fragments may have had latent disease that was not visually observable when they were outplanted. However, we saw neither bleaching nor disease in the wild population of A. aspera , in our outplanted populations in other locations, or in our nurseries simultaneous with what we observed in Tumon Bay. However, as we mention in a previous paragraph, a white syndrome outbreak did occur within A. pulchra , at multiple sites within the Bay during our observed outbreak, though no bleaching was observed. Thus, we ruled out the possibility that outplanted fragments were latently diseased when introduced. Considerations for improved restoration and conservation approaches In applying our observations on shifts in the microbiome communities between nursery and outplanted environments, we identify an objective for improving restoration science: determining how we might facilitate preserving a healthy microbiome in outplanted corals. While transplantation stress is a commonly observed phenomenon, visually observed in corals by paling or bleaching, depressed growth rates, increased disease, and tissue loss, the physiological basis for this response is poorly understood. It is reasonable to speculate that a loss of bacterial species integral to coral health, with a shift to potentially opportunistic species, may factor heavily in this response. In this study, we noted a significant difference between nursery (a water column environment) and outplant (a substrate environment) microbiomes and highlighted the low abundances of the beneficial Endozoicomonas bacteria in both treatments. While it is not clear why wild A. aspera is dominated by Endozoicomonas bacteria (which may function as congeners), we would still expect a core microbiome and homogeneity among colonies within nursery treatments. 85 , 86 This heterogeneity highlights a potentially unstable microbiome, despite >2 years of acclimation in the nursery environment, and raises concerns about the physiological constraints of culturing corals in the water column (e.g., changes in energetic allocation strategies). Therefore, adding a transitional step between nursery and outplanting for thicket-forming coral such as Acropora may be beneficial. We propose moving outplants from midwater trees to near reef substrate within the nursery prior to recipient site outplanting, while sampling midwater and substrates for their bacterial communities. This period may prove necessary to recovering key bacteria for microbiome homeostasis and promoting immune functions observed in adjacent healthy colonies. Alternatively, testing the effect on microbiome communities of nursery structures positioned closer to the substrate may prove useful for morphologies that grow as discrete colonies attached to hard substrate. Both of these concepts require additional testing and development prior to introducing them as best practices for nursery culture. This highlights the need to better monitor and investigate environmental conditions and related microbiome function and dynamics through the whole restoration process from wild to nursery to targeted outplant site. Data on the population structure of the surviving wild population were not available when we initially outplanted, though we have now confirmed that the remaining wild population of A. aspera is almost clonal, with little genetic structure (Combosch and Torrado in prep). Hence, while we initially hoped to observe differential responses to disease and bleaching, suggesting the presence of multiple genotypes of differing resilience, 51 we had no genetic diversity within the population. While we thus have few options to increase local genetic diversity for this species, our options for the persistence of A. aspera in the Mariana Islands may rest with efforts to establish populations in more habitats and determine the most beneficial sites, to reduce local extinction risk. Options to manage a disease outbreak within a limited introduced population must also be developed. We initially considered culling diseased colonies, though we suspected a waterborne pathogen based on the pattern of disease spread in one plot, and the fact that no diseased colonies were in physical contact. Previous outbreaks of WS revealed that progression often stops prior to whole colony mortality (Raymundo and Lozada, unpublished data 2007). Previous observations of WS outbreaks in staghorn Acropora indicate that it is relatively short-lived and thus, may not kill larger colonies. Use of probiotics, such as the introduction of beneficial species such as Endozoicomonas , may be possibility with high-value and vulnerable species in an early stage of introduction, 91 , 92 but tools for their application need development. Antibiotic “band aids” may be applied to individual lesions and may be a strategy for ex-situ -cultured corals at risk but the introduction of antibiotics into wild sites is controversial at best. 93 , 94 Restoration efforts often cannot be carried out in the most pristine sites; Guam, for instance, does not house any coastline area that can be considered truly unimpacted by human activity. Given the seasonal water quality issues driving coral decline in Tumon Bay, the current restoration challenge is to determine which staghorn species may be resilient to summer conditions and whether these conditions vary within the Bay, identifying areas that may be more suitable for introduction. While addressing the issue of warming sea surface temperatures is beyond the capacity of the local government, managing inputs that reduce water quality is within local control and should be addressed, as this has implications for both marine ecosystems and human health, i.e., the One Health concept. 95 , 96 Ultimately, restoration success will be limited if political will for tackling anthropogenic inputs is lacking. An increasingly common thread among tropical island nations is that the popularity and success of the tourism industry is intrinsically linked with coral reef health, yet there is a lack of commitment to ensuring the health and continuity of these systems. In conclusion, our study illustrates the importance of considering risks of infectious disease in restoration efforts and suggests new perspectives to be explored to improve the performance of coral outplants. Failure to consider the impacts of stress will lower the success of restoration and speaks directly to the importance of thoughtful site selection. The nature of the coral immunodefense response to stress has made much progress in recent decades. Now it is time to apply this knowledge to the science of restoration to improve the performance of corals introduced for the goal of conservation and management. Limitations of the study Ideally, when examining shifts or differences in the microbiome, we would have sampled from the wild population and the outplanted population on the first day of outplanting as well. Logistically, however, this was not feasible. As disease and bleaching progressed, it was challenging for field assistants to distinguish between WS and bleaching, which may have resulted in underestimates of the number of diseased colonies counted during later censuses. LR and HR were the most practiced at field assessments but could not census all plots in a single survey."
} | 7,345 |
38470769 | PMC10934599 | pmc | 3,369 | {
"abstract": "Owing to their excellent elasticities and adaptability as sensing materials, ionic hydrogels exhibit significant promise in the field of intelligent wearable devices. Nonetheless, molecular chains within the polymer network of hydrogels are susceptible to damage, leading to crack extension. Hence, we drew inspiration from the composite structure of the human dermis to engineer a composite hydrogel, incorporating dopamine-modified elastic fibers as a reinforcement. This approach mitigates crack expansion and augments sensor sensitivity by fostering intermolecular forces between the dopamine on the fibers, the hydrogel backbone, and water molecules. The design of this composite hydrogel elevates its breaking tensile capacity from 35 KJ to 203 KJ, significantly enhancing the fatigue resistance of the hydrogel. Remarkably, its electrical properties endure stability even after 2000 cycles of testing, and it manifests heightened sensitivity compared to conventional hydrogel configurations. This investigation unveils a novel method for crafting composite-structured hydrogels.",
"conclusion": "4. Conclusions In this study, we designed a composite hydrogel sensor by integrating modified elastic fibers and a hydrogel to augment the interfacial synergy between the components and refine the properties of the hydrogel. We selected modified fibers as a reinforcement, enhancing the mechanical performance of the sensor and endowing remarkable sensing capabilities to the DPF hydrogel. Relative to pure hydrogel, the fiber-composite hydrogel demonstrated markedly heightened sensitivity. The incorporation of fibers not only elevated the sensor’s fracture energy from 35 kJ to 203 kJ but also extended the detection range to 640%. Its electrical attributes remained stable over 2000 test cycles, with a response time of only 50 ms. Consequently, this sensor displays considerable promise for use in applications such as electronic skin, human health monitoring, and motion detection. This study describes a potential strategy for use in amplifying the sensing and mechanical attributes of hydrogel sensors via composite modifications, enabling innovative research and applications in related fields.",
"introduction": "1. Introduction Wearable sensors, which are emerging as novel electronic devices, have considerable potential for development across diverse fields, including motion detection [ 1 , 2 ], healthcare [ 3 , 4 ], electronic skin [ 5 , 6 ], soft robotics [ 7 , 8 ], and human–machine interfaces [ 9 , 10 ]. Among these sensors, skin-like wearable sensors may convert mechanical signals to electrical signals by mimicking the softness and adaptability of human skin, which can profoundly affect human–computer interactions and motion monitoring applications [ 11 , 12 ]. Ionic hydrogels, comprising a network of covalently and/or non-covalently crosslinked hydrophilic polymers and solvents, represent promising skin-like wearable sensors. These hydrogels, serving as multifunctional sensing materials, demonstrate remarkable capabilities in bending, stretching, and deformation. In comparison to conventional flexible sensors, hydrogel sensors offer distinct advantages, including adaptability to diverse curved surfaces, lightweight construction, and a broad sensing range. Ion-doped hydrogels exhibit modulus and elasticity akin to human skin, thus holding significant potential in the realms of electronic skin and robotics and garnering considerable attention from researchers [ 13 ]. Hydrogels, an elastic substance comprising a polymer matrix and water molecules, derive their physical attributes governing high elasticity and exceptional conformity to the human body. The ion hydrogel, employed in sensor fabrication, features a three-dimensional cross-linked hydrophilic polymer network immersed in a matrix rich in water content. Within these hydrogels, ions manifest fluidity. When subjected to external forces, the gel undergoes deformation, inducing alterations in its electrical signal and thereby realizing sensing functionality. Currently, the preparation methods of hydrogels for strain sensing applications mainly include physical cross-linking [ 14 ] or chemical cross-linking [ 15 ]. Physical gels materialize through physical phenomena such as electrostatic interactions, hydrogen bonding, and chain entanglement, rendering the internal three-dimensional scaffold susceptible to impairment. Conversely, hydrogels synthesized via chemical cross-linking boast heightened robustness, elasticity, and resilience owing to the presence of covalent links among molecules. Despite the mechanical superiority of ion hydrogels produced through chemical cross-linking over those crafted via physical means, their resilience remains relatively wanting. Particularly under external pressures, the three-dimensional polymer framework of chemically cross-linked hydrogels tends to undergo stress concentration, precipitating irreversible fractures [ 16 ] and compromising the structural integrity of their sensing mechanisms. This limitation presents a barrier to meeting the protracted operational requisites of smart wearable technologies. Consequently, in order to fulfill the exigencies of flexible sensors, the optimization of ion hydrogels is imperative to augment the efficacy of hydrogel-based sensors. Therefore, to satisfy the demands of flexible sensors, the ionic hydrogel should be designed by introducing other substances [ 17 , 18 ] and increasing the toughness of the structure [ 19 , 20 ], etc., to enhance the use of hydrogel sensors. The introduction of other polymer materials or reinforcers into the hydrogel matrix may effectively enhance the comprehensive performance of the hydrogel. To improve the durability of flexible hydrogel sensors, Yang et al. [ 21 ] introduced a dual-network hydrogel ionic conductor that combined the physical cross-linking of agar with the chemical cross-linking of polyacrylamide. This innovative approach yielded excellent mechanical properties, with an elongation at break of up to 1600%. Certain researchers have engineered a composite architecture of flexible hydrogel sensors inspired by biomimicry. The human dermal tissue comprises a supple protein matrix and sturdy collagen fiber scaffolding. This intricate arrangement bestows exceptional anti-fatigue toughness upon human skin, allowing it to endure millions of deformation cycles annually. Through the utilization of elastic microfibers to emulate the collagen fiber framework and hydrogels to replicate the protein matrix, the mechanical attributes of the resultant composite flexible sensors are substantially bolstered. Consequently, their flexibility as composite materials is markedly improved. The fatigue resistance of the hydrogel sensor experiences a significant enhancement. Wang et al. [ 22 ] successfully fabricated a composite ion sensor by combining a hydrogel with fibers. This blend effectively enhanced the robustness of the hydrogel, increased its fatigue fracture threshold to 2950 J/m 2 , and significantly improved its resistance to crack extension. The prevailing body of research predominantly emphasizes the incorporation of fibers into hydrogel formulations for reinforcement, but the influences of the structural and functional modifications of the fiber surface within ionic gels are notable oversights. The failure to establish an interface between untreated fibers and the hydrogel can significantly diminish the finishing properties of the composites. To further enhance the durability and sensing capabilities of flexible hydrogel sensors, attention can be directed toward fortifying the interfacial effect between the hydrogel and its reinforcement within the realm of composites. Indeed, feeble interfacial interactions between the hydrogel and its reinforcement may precipitate the deterioration of the mechanical properties of the composites, posing a threat to structural integrity. Overcoming this challenge necessitates a pivotal improvement in the surface characteristics of fibers serving as reinforcements, directly contributing to the comprehensive performance of the sensors. In this study, we developed a hydrogel composite by combining water-based gel with dopamine-modified polyurethane fibers, namely the dopamine-modified polyurethane fiber hydrogel (DPF hydrogel). Initially, we fabricated ultra-fine and exceedingly elastic polyurethane fibers (PFs) through the electrospinning process. These fibers underwent subsequent modification via dopamine, resulting in dopamine-modified polyurethane fibers (DPFs), wherein dopamine intricately anchors itself onto the fiber’s surface. Post-modification, these fibers are intricately combined with the hydrogel precursor, culminating in the ultimate manifestation of the DPF hydrogel, as elucidated in Figure 1 a. The inherent functional groups of dopamine augment the interfacial effect between the fiber and hydrogel (as shown in Figure 1 b). This composite material, marrying hydrogel nanofibers with hydrogels, seamlessly integrates the functional attributes of a hydrogel with the structural merits of nanofibers [ 23 ]. The amalgamated structure of these fibers and hydrogels ingeniously emulate human dermal tissue, conferring notable fatigue resistance and heightened sensitivity and rendering it eminently suited for flexible sensors. Moreover, the tailored modification of these fibers amplifies the overarching performance of the composite material. This amalgamation not only elevates the mechanical properties of the hydrogel, augmenting its modulus and strength but also fortifies its resilience. This substantial enhancement significantly prolongs the sensor’s operational longevity, thereby amplifying its pragmatic worth. Our empirical observations reveal a noteworthy escalation in tensile fracture work, increasing from 35 kJ in the hydrogel to a commendable 203 kJ in the DPF hydrogel. This provides evidence of a remarkable fortification in strength, effectively mitigating crack propagation within the internal fibers. The sensor’s expansive detection range spans 640%, coupled with an impressive stimulus-response time of 50 milliseconds. Functioning as a monitoring instrument, this composite hydrogel sensor exhibits exemplary human–machine performance, proficiently overseeing movements across diverse regions of the human body, thereby underscoring its tremendous potential in practical applications."
} | 2,604 |
27819039 | PMC5091355 | pmc | 3,370 | {
"abstract": "A hybridized self-powered textile for simultaneously collecting solar energy and random body motion energy was demonstrated.",
"conclusion": "CONCLUSION In summary, we demonstrate the concept of a hybridized self-charging power textile system with the aim of simultaneously collecting outdoor sunshine and random body motion energies and then transferring them to an energy-storing cell to sustainably operate mobile or wearable electronics. For a single F-DSSC unit, a V OC of 0.74 V and a J SC of 11.92 mA cm −2 were achieved, corresponding to an overall power conversion efficiency of 5.64%. The F-TENG can take advantage of human motions, such as jogging, to deliver an output current of up to 0.91 μA. The F-SC unit with the excellent pseudocapacitance of the as-synthesized RuO 2 ·xH 2 O exhibits a promising specific capacitance (1.9 mF cm −1 ), which makes it an effective and flexible electronic energy storage device. Because of the all–fiber-based shape in each device, our proposed hybridized self-charging textile system can be easily woven into electronic textiles to fabricate smart clothes to operate wearable electronic devices. This work presents a welcome advancement for self-powered systems in wearable technology, which will initiate promising improvements in self-powered flexible displays and wearable electronics, among others. A more complicated design is possible because all of the textiles started from 1D building blocks.",
"introduction": "INTRODUCTION Wearable electronics fabricated on lightweight and flexible substrate are widely believed to have great potential for portable devices ( 1 – 3 ). Several promising applications, for example e-skin, smartwatches, and bracelets, have been successfully achieved for the replacement of conventional electronic gadgets ( 4 – 6 ). Lightweight and wearable power supply modules with high energy storage performance are desirable for wearable technology. One strategy is to directly integrate a conventional rechargeable energy storage device, such as a battery or a supercapacitor (SC), into fabrics ( 7 – 10 ). This self-powered system is a favorable power platform to be integrated into wearable electronic systems. Fu et al . ( 11 ) designed a new type of integrated power fiber by incorporating a dye-sensitized solar cell (DSSC) and a solar cell for harvesting solar energy and storage to realize a self-powered system for driving a commercial light-emitting diode (LED). Du et al . ( 12 ) also proposed self-powered electronics by integration of flexible graphene-based SCs into perovskite hybrid solar cells. However, a photovoltaic cell works only under sufficient light illumination, and solar energy is not always available, strongly depending on the weather, working conditions, and so on. The intermittent and unpredictable nature of solar energy is an inevitable challenge for its expansion as a reliable power supply system in wearable electronics. The question of how to scavenge alternative energy from the environment with different types of energy harvesters, to compensate for the insufficient part of the solar energy, is urgent. To develop a practical strategy to simultaneously scavenge multiple types of energies from the environment, the concept of a hybridized energy harvester incorporating two kinds of conversion cells for concurrently scavenging solar and mechanical energies was proposed, so that the energy resources could be effectively and complementarily used ( 13 – 18 ). Tribolectric nanogenerators (TENGs), are based on the coupling effect of contact electrification and electrostatic induction, and these have now been widely studied to harvest different mechanical energies from the environment ( 19 – 23 ). By using TENGs as the power supply, different types of self-powered systems were successfully demonstrated and realized, such as wireless sensors, chemical sensors, electrochemical reactions, home appliances, and security detection systems ( 24 – 28 ). Furthermore, to expand the practical applications of a TENG-based self-powered system, various structure types of flexible TENGs have been designed for harvesting ambient mechanical energy and, more adequately, for integration into wearable electronic devices ( 29 – 31 ). The high operating voltage of SCs can be directly achieved by charging them using a single TENG unit without additional in-series connection, which compensates for insufficient solar energy ( 32 , 33 ). Here, we present a prototype of a fabric-hybridized self-charging power system not only for harvesting solar energy from ambient light but also for gathering mechanical energy from human motion. Both of the harvested energies can be easily converted into electricity by using fiber-shaped DSSCs (F-DSSCs) (for solar energy) and fiber-shaped TENGs (F-TENGs) (for mechanical energy) and then further stored as chemical energy in fiber-shaped SCs (F-SCs). Our proposed hybridized self-charging textile not only achieves reasonable energy conversion and storage capacity but also is inexpensive and can be easily fabricated. In addition, because of the all–fiber-based shape in each device, our proposed hybridized self-charging textile system can be easily woven into electronic textiles to fabricate smart clothes which operate wearable electronic devices.",
"discussion": "RESULTS AND DISCUSSION The double-layer structure of our proposed hybridized self-charging power textile is schematically illustrated in Fig. 1 . Three kinds of functional devices, including F-DSSCs, F-SCs, and F-TENGs, can be integrated spontaneously into a conventional textile structure. First, the top layer of the hybridized self-charging power textile is the F-DSSC–based textile, which is woven of several F-DSSC units for harvesting solar energy. Here, DSSC is chosen from numerous photovoltaic cells because DSSC materials and dyes can be tuned for optimization in a variety of lighting conditions, making it suitable for indoor and outdoor applications. Also, DSSCs can also be applied to a variety of substrates that are favorable for constructing the TENG structure. The F-SC–based textile acts as the bottom layer for storing the harvested energies. Meanwhile, each F-DSSC and F-SC unit is connected to one another, forming a single F-TENG unit; this F-TENG–based textile system is built to simultaneously scavenge body motion energy. Transparent and flexible ethylene vinyl acetate (EVA) tubing was used to build the basic unit of the self-charging power textile. Before the concurrent operation of the textile, the characterization of each functional device was carried out individually to evaluate its performance. Fig. 1 Schematic of the self-charging power textile. Scheme of a fiber-based self-charging power system, which is made of an F-TENG, an F-DSSC as an energy-harvesting fabric, and an F-SC as an energy-storing fabric. Initially, a single F-DSSC unit with a length of ~10 cm is constructed using N719 dye–sensitized TiO 2 nanotube arrays on a Ti wire as a working electrode and a Pt-coated carbon fiber as a counter electrode (CE), which is sealed into Cu-coated EVA tubing containing an I − /I 3 − -based electrolyte. Cu-coated EVA tubing acts not only as the holder for fabricating an F-DSSC but also as one electrode for F-TENG, which will be discussed later. The wire structure of the F-DSSC unit is schematically illustrated in detail in Fig. 2A . A photograph of a single F-DSSC unit is also presented in Fig. 2B . Figure 2C shows a low-magnification scanning electron microscopy (SEM) image of a Ti wire with a diameter of ~200 μm after anodic oxidation. A top-view high-magnification SEM image presented in Fig. 2D shows that the vertically oriented array of one-dimensional (1D) TiO 2 nanotubes is well grown on the Ti wire surface via electrochemical anodization, with a similar diameter of ~50 nm. Furthermore, the crystalline phases of the as-prepared TiO 2 nanotubes were examined by x-ray diffraction (XRD) patterns, as shown in fig. S1. Peaks corresponding to (101), (103), (004), (200), (105), and (211) of the TiO 2 anatase phase are observed ( 34 ). On the other hand, the SEM images of the Pt-coated carbon fiber and the bare carbon fiber are shown in fig. S2. It can be observed that the diameter of a single fiber (for both the Pt-coated carbon fiber and the pure carbon fiber) is ~10 μm. Homogeneous Pt nanoparticles were well dispersed on the surface of the carbon fiber, as a result of a thermally decomposed process. Afterward, the current-voltage ( I - V ) characteristic of a single F-DSSC unit was evaluated under standard illumination (100 mW cm −2 ; AM1.5). Figure 2E shows the photocurrent density–voltage ( J - V ) curve of a single F-DSSC. The single F-DSSC unit exhibits a short-circuit current density ( J SC ), an open-circuit voltage ( V OC ), and a fill factor (FF) of 11.92 mA cm −2 , 0.74 V, and 0.64, respectively, corresponding to an overall power conversion efficiency of 5.64%. The dark current is also added in the figure as the reference. The performance of a single F-DSSC with bare carbon fibers is also examined for comparison, as shown in fig. S4. The performance of a single F-DSSC unit at different incident light angles is shown in fig. S5, and a detailed discussion can be found in the Supplementary Materials. A nonvolatile I − /I 3 − -based electrolyte was used in our study to enhance the long-term stability of the F-DSSC unit. The inset to Fig. 2E shows the electrochemical impedance spectra of a single F-DSSC unit for evaluating the charge transfer resistance in the device, which was measured under V OC with an alternating current (ac) amplitude of 10 mV in the 100 kHz to 10 MHz frequency range. The ohmic series resistance ( R S ) of a single F-DSSC unit can be determined in the high-frequency region of a Nyquist plot where the phase is zero. The first semicircle in the Nyquist plot at the high-frequency range corresponded to the impedance at the CE/electrolyte interface ( R ct1 ) for the reduction reaction of I 3 − ions, whereas the second semicircle at the middle frequency range corresponded to the charge-transfer impedance at the TiO 2 /dye/electrolyte interface ( R ct2 ). The above results provide solid evidence that F-DSSCs had been successfully prepared for harvesting solar energy. To further apply F-DSSCs in our proposed self-charging power textile, the output performance of the F-DSSC at different bending angles should be considered. Figure 2F shows the normalized current density of a single F-DSSC at different bending degrees (from 0° to 180°) under a constant incident light intensity, where the value of the current density (~12 mA cm −2 ) rarely changed under various bending angles, showing the stability of the photovoltaic device. Fig. 2 Structural design of an F-DSSC. ( A ) Schematic diagram and ( B ) photograph (scale bar, 1 cm) of a single F-DSSC, consisting of N719 dye–adsorbed TiO 2 nanotube arrays on a Ti wire as a working electrode and a Pt-coated carbon fiber as a CE in an I − /I 3 − -based electrolyte. ( C ) Low-magnification and ( D ) high-magnification SEM images of the TiO 2 nanotube arrays on the Ti wire [scale bars, 100 μm (C) and 100 nm (D)]. ( E ) J - V curve of a single F-DSSC (inset shows the Nyquist plot of an F-DSSC, which is measured under V OC with frequencies ranging from 100 kHz to 10 MHz). ( F ) Normalized current density of the single F-DSSC at different bending angles (0° to 180°) (insets show the photograph of a single F-DSSC at different bending angles). F-SCs are introduced in the self-charging power textile as the energy storage unit for F-DSSCs. A single F-SC unit with a length of 10 cm is symmetrically assembled with two carbon fibers coated with RuO 2 ·xH 2 O in the H 3 PO 4 /PVA [poly(vinyl alcohol)] electrolyte and packaged into the polydimethylsiloxane (PDMS)–covered Cu-coated EVA tubing, as schematically shown in Fig. 3A . PDMS-covered Cu-coated EVA tubing acts not only as the holder for fabricating an F-SC but also as one electrode for F-TENG, which will be discussed later. Two bundles of carbon fibers were separated by a cellulose-based paper septum. A photograph of a single F-SC is shown in Fig. 3B . Here, long-ordered carbon fibers without any binders were directly used as the substrate for fabricating the F-SC owing to their excellent chemical stability and outstanding conductivity ( 35 ). RuO 2 ·xH 2 O was synthesized on carbon fiber bundles by using a vapor-phase hydrothermal method to form binder-free fiber electrodes ( 36 ). A low-magnification SEM image of the as-synthesized RuO 2 ·xH 2 O–coated carbon fibers reveals that several carbon fibers were assembled into a bundle, as shown in Fig. 3C . Figure 3D shows a high-magnification SEM image of RuO 2 ·xH 2 O coated on a single carbon fiber with a diameter of ~10 μm; it presents the typical “cracked mud” morphology on the surface of carbon fibers. Moreover, the crystalline phase of the as-synthesized fibers is confirmed by XRD patterns (fig. S5), and the peaks for each XRD pattern can be assigned to a typical amorphous RuO 2 ·xH 2 O with a partly rutile crystalline structure, which is an essential phase to simultaneously obtain high ion and high electron conductivity ( 37 ). The electrochemical capacitance properties of a single F-SC unit were further evaluated by cyclic voltammetry (CV) and galvanostatic charging/discharging (GCD) techniques. To evaluate the fast charge/discharge ability of the F-SC, we examined CV at different scan rates (from 10 to 100 mV s −1 ), as shown in Fig. 3E . It can be observed that the CV curves do not distort significantly as the scan rate increases, indicating their good capacitive behavior and high-rate capability. Figure 3F shows the charge/discharge curves of the F-SC at different current densities (from 100 to 1000 μA), with the potential ranging from 0 to 1.2 V. The symmetrically triangle-shaped GCD curves of the F-SC under various current densities can be observed. Moreover, no obvious IR -drop phenomenon can be found even at a short discharging time of 23 s, which reconfirms the outstanding capacitance behavior and the promising charging/discharging performance of the F-SC. As a comparison, the energy storage performances of the carbon fiber without incorporating RuO 2 were also measured, as shown in fig. S6. Because the mass-specific capacitance (F g −1 ) is not suitable for F-SC, the length-specific capacitance (F cm −1 ) was evaluated and then calculated in this study. Our results reveal that the specific capacitance of 1.9 mF cm −1 can still be retained at a high level under a high current density of 1000 μA, and its energy density is up to 1.37 mJ cm −1 , both of which demonstrate a fast charging/discharging ability and a reasonable energy density. The cycling stability of SC is also a critical issue that should be considered. The cycling performance of a single F-SC unit was investigated, as shown in Fig. 3G . No obvious capacitance change can be observed after 5000 cycles at a charging/discharging current of 1000 μA. The PVA/H 3 PO 4 gel electrolyte has also demonstrated excellent cycling stability in our previous work ( 34 ). Finally, the capacitance of a single F-SC at different bending angles (from 0° to 180°) was also examined, as shown in Fig. 3H . All of the CV curves for a single F-SC unit with various bending angles exhibit typical and almost overlapping rectangle-like curves, indicating that it is a reliable platform for storing harvested energies with excellent flexibility and promising stability under various bending conditions. Fig. 3 Structural design of an F-SC. ( A ) Schematic diagram and ( B ) photograph (scale bar, 1 cm) of a single F-SC, consisting of two carbon fibers coated with RuO 2 ·xH 2 O in the H 3 PO 4 /PVA electrolyte. ( C ) Low-magnification and ( D ) high-magnification SEM images of the RuO 2 ·xH 2 O–coated carbon fiber electrode [scale bars, 100 μm (C) and 5 μm (D)]. ( E ) CV of the single F-SC at different scanning rates (10 to 100 mV/s). ( F ) GCD curve of a single F-SC at different current densities (100 to 1000 μA). ( G ) Cycling performance of a single F-SC unit. ( H ) CV curves of the single F-SC at different bending angles (0° to 180°). As mentioned before, a pair of single F-TENG units can be built by pairing the F-DSSC with Cu-coated EVA tubing and the F-SC with PDMS-covered Cu-coated EVA tubing. A schematic diagram and a digital photograph of a pair of single F-TENG units are shown in Fig. 4 (A and B, respectively). To elucidate the working mechanism in a simplified model, the relative motion of the two fiber tubes can be simplified as the contact-separation process that occurs between Cu and PDMS, as illustrated in Fig. 4C . In the original state (i), the PDMS surface was charged with negative electrostatic charges and the Cu 1 electrode produced positive charges, due to the electrostatic induction and conservation of charges. When the F-TENG was pressed (ii), a shrinkage of the gap between the Cu 2 electrode and PDMS would result in induced positive charges accumulating in the Cu 2 layer because of the electrostatic induction. Accordingly, free electrons in Cu 2 would flow to the Cu 1 layer to balance the field. This process produces an instantaneous positive current. It is necessary to note that the charges on PDMS will not be annihilated even when it makes contact with the Cu 2 electrode (iii), because the electrostatic charges are naturally impregnated into the insulator PDMS. In the reverse case, when the F-TENG was released (iv), it would recover back to its original state (i) and the internal gap would be increased. Thus, an instantaneous negative current could be produced. Therefore, a contact-separation process of the F-TENG will generate an ac through the load ( 38 – 41 ). The output performance of power generation for a pair of single F-TENG units with a length of ~10 cm was systematically studied via the periodic motion of contacting and separating under controlled frequencies. To analyze the output capability of the F-TENG, we used a linear motor to trigger the pair of single F-TENG units, wherein the maximum distance between the two tubing systems was purposely set at 10 mm. As shown in Fig. 4D , when motion frequencies vary from 1 to 5 Hz, the V OC and transferred charges ( Q SC ) remain constant (~12.6 V and ~4.5 nC, respectively). The short-circuit current ( I SC ) increases from ~0.06 to ~0.15 μA, revealing a clear increasing trend with the increase in frequency. In other words, the increase in frequency is favorable for the magnitude of I SC . Furthermore, three kinds of F-TENG–based textile with knitting patterns of 1 × 1, 3 × 3, and 5 × 5 nets are fabricated and then characterized under various motion frequencies (1 to 5 Hz), as shown in Fig. 4 (E and F, respectively). It indicates that the values of Q SC and I SC at 5 Hz increase with the increase in braided density from 1 × 1 nets (5.4 nC and 0.21 μA) to 3 × 3 nets (11.6 nC and 0.68 μA) and 5 × 5 nets (20.8 nC and 0.91 μA), as a result of the further enlargement of its conductive surface area for electrostatic induction. The V OC remains almost constant because of the unchanged motion distance, as shown in fig. S7. As for wearable energy-harvesting textiles, the capability of F-TENG to withstand harsh bending or deformation is an essential requirement. Therefore, a flexibility test was performed, as shown in Fig. 4E and movie S1. No apparent change in resistance could be observed when a single Cu-coated EVA tubing was bent at different angles (from 0° to 180°). The photograph of the Cu-coated EVA at different bending angles is also shown as insets. Fig. 4 Structural design of an F-TENG. ( A ) Schematic diagram and ( B ) photograph (scale bar, 1 cm) of a pair of single F-TENG units, consisting of a Cu-coated EVA tube and a PDMS-covered Cu-coated EVA tube. ( C ) Schematic illustration of the working mechanism of the F-TENG under parallel contact-separation motion. ( D ) Electrical outputs of a pair of F-TENG units, which included V OC , I SC , and Q SC , at various motion frequencies (1 to 5 Hz). ( E ) Photograph of the wearable self-charging powered textile with knitting patterns of 1 × 1, 3 × 3, and 5 × 5 nets (all scale bars, 1 cm). ( F ) Triboelectric output performance of the three network textiles. ( G ) The electric resistance of the Cu-coated EVA tube at different bending angles (0° to 180°) (insets show the photograph of the Cu-coated EVA tube at different bending angles). To construct the hybridized self-charging power textile, several F-DSSC and F-SC units were woven into an individual fabric as the textile structure with in-series/parallel connection. An F-TENG–based textile system can be built after connecting both textiles. Figure 5 (A to C) shows a tester who wore our designed hybridized self-charging power textile attached to a T-shirt, which harvests light energy and motion energy based on the tester’s daily outdoor and indoor activities, respectively. It is also worth noting that the DSSC can efficiently generate electric power under weak light ( 42 ). The equivalent circuit of the hybridized self-charging power textile is shown in Fig. 5D . A bridge rectifier is used to convert the generated current of F-TENG from ac to direct current before charging the F-SC, a diode is used to block the current of F-TENG that goes through an F-DSSC, and all the switches are used to control the circuit. Although the rectifier, diode, and switches are not flexible, it is possible to design them into either a logo or a button, considering their small size. To simply demonstrate the performance of the as-prepared hybridized self-charging power textile, we design the textile structure in a 3 × 3 network, meaning that each fabric was connected to three individual F-DSSC or six F-SC units in series and then woven separately. Figure 5E shows the characteristics of the self-charging behavior by harvesting solar and mechanical contact-separation motion energies via the as-prepared hybridized self-charging power textile. Turning the switch S0 on to connect the F-SC to the circuit, while switch S1 is on and switch S2 is off, will linearly increase the voltage of the F-SC (which takes about 69 s to charge from 0 to 1.8 V), indicating the stable output of F-DSSCs. The top left corner inset in Fig. 5E shows the enlarged curve during the charging period of the F-DSSCs. The I-V curve of three F-DSSCs with in-series connection is shown in fig. S8. However, the F-SCs remained at 1.8 V because the low output voltage of the F-DSSCs limits their reliability and practicability, as shown in the light blue–shaded area. One effective method to solving this problem is to mimic the in-series structure of F-SCs for electrocytes in the electric eel to produce high working voltages, as reported by Sun et al . ( 43 ). Here, we introduced the TENG with a high voltage output to directly charge the electrochemical capacitors to a high level, which compensates for the weakness of the DSSC. After turning the switch S2 on, the F-SCs can be charged continuously by the F-TENGs to a higher voltage. The corresponding charging curve is plotted in the light red–shaded area. The bottom right corner inset in Fig. 5E shows the rectified I SC of three-series F-TENGs. It should be noted that further improvement in the charging efficiencies can be achieved by obtaining impedance matching among DSSCs, TENGs, and SCs, because the internal impedance of TENGs is generally several orders of magnitude higher than that of DSSCs and SCs. Traditional electronic devices, such as LEDs, digital watches, and a variety of sensors for temperature, pressure, or medical diagnosis, can be easily powered. We believe that, after large-scale fabrication and further improvement, high-power electronic devices—for example, smart bracelets and portable MP3 players—could be charged by our novel self-powered textile in the near future. Last, the durability of the hybridized self-charging power textile was examined under continuous bending motion for 1000 cycles by the linear motor, as shown in Fig. 5F and movie S2. Normalized Q SC values of F-TENGs, I SC values of F-DSSCs, and capacitances of F-SCs were recorded after every 100 times of bending. The insets also display photographs of the textile bent from 0° to 180°. As shown in Fig. 5F , on the basis of their performance, each device showed no significant degradation in performance, confirming their excellent flexibility and stability. The increasing demand for lightweight, highly flexible, stretchable, and washable power modules is one of the critical challenges for the progress of self-powered wearable textiles. Fig. 5 Demonstration of the self-charging powered textile and its operation under outdoor and indoor conditions. Photograph of the self-charging power textile woven with F-TENGs, F-DSSCs, and F-SCs under outdoor ( A ), indoor ( B ), and movement ( C ) conditions. ( D ) Circuit diagram of the self-charging powered textile for wearable electronics (WE). ( E ) Charging curve of the F-DSSC and the F-TENG, where the light blue–shaded area corresponds to the charging curve of the F-DSSC and the light red–shaded area corresponds to the charging curve of the F-DSSC–F-TENG hybrid. The top left corner inset shows an enlarged curve during the F-DSSC charging period, and the bottom right corner inset shows the rectified I SC of F-TENGs. ( F ) Normalized Q SC values of F-TENGs, I SC values of F-DSSCs, and capacitances of F-SCs bent between 0° and 180° for 1000 cycles. Insets show the photographs of the two final bending statuses (both scale bars, 1 cm). a.u., arbitrary units."
} | 6,446 |
34493336 | PMC8425128 | pmc | 3,372 | {
"abstract": "Background To create an ideotype woody bioenergy crop with desirable growth and biomass properties, we utilized the viral 2A-meidated bicistronic expression strategy to express both PtrMYB3 ( MYB46 ortholog of Populus trichocarpa , a master regulator of secondary wall biosynthesis) and PdGA20ox1 (a GA20-oxidase from Pinus densiflora that produces gibberellins) in wood-forming tissue (i.e., developing xylem). Results Transgenic Arabidopsis plants expressing the gene construct DX15::PdGA20ox1-2A-PtrMYB3 showed a significant increase in both stem fresh weight (threefold) and secondary wall thickening (1.27-fold) relative to wild-type (WT) plants. Transgenic poplars harboring the same gene construct grown in a greenhouse for 60 days had a stem fresh weight up to 2.6-fold greater than that of WT plants. In a living modified organism (LMO) field test conducted for 3 months of active growing season, the stem height and diameter growth of the transgenic poplars were 1.7- and 1.6-fold higher than those of WT plants, respectively, with minimal adverse growth defects. Although no significant changes in secondary wall thickening of the stem tissue of the transgenic poplars were observed, cellulose content was increased up to 14.4 wt% compared to WT, resulting in improved saccharification efficiency of the transgenic poplars. Moreover, enhanced woody biomass production by the transgenic poplars was further validated by re-planting in the same LMO field for additional two growing seasons. Conclusions Taken together, these results show considerably enhanced wood formation of our transgenic poplars, with improved wood quality for biofuel production. Supplementary Information The online version contains supplementary material available at 10.1186/s13068-021-02029-2.",
"conclusion": "Conclusions The resulting DX15::PdGA20ox1-2A-PtrMYB3 poplars showed enhanced biomass production in both quantity and quality with sustained growth, which was evaluated in a field tests covering the entire active growth-dormancy cycle. Thus, our biotechnological tool can be expanded to various woody crops for production of desired multi-purpose biomass feedstock. Moreover, DX15::PdGA20ox1-2A-PtrMYB3 poplars represent a useful genetic background into which many useful traits may be stacked in order to produce a designer biomass feedstock.",
"discussion": "Discussion To improve the wood and growth performance of poplars for biomass production, we expressed PtrMYB3 in a developing xylem (DX) tissue-specific manner together with PdGA20ox1 , bicistronically. Overexpression of PtrMYB3 under the 35S promoter in both Arabidopsis and poplar results in ectopic secondary wall thickening through upregulation of the biosynthesis of cellulose, xylan, and lignin [ 39 , 40 ]. As a proof-of-concept experiment, we created transgenic Arabidopsis plants expressing the DX15::PdGA20ox1-2A-PtrMYB3. The resulting transgenic Arabidopsis plants showed a significant increase in secondary wall thickening in the interfascicular fibers (up to 1.27-fold) compared to WT plants (Fig. 1 d, e). In addition, expression of this construct increased the fresh weight of the stem by up to threefold (Fig. 1 c). These results demonstrated the efficacy of our strategy of bicistronic gene expression of PtrMYB3 and PdGA20ox1 , further confirming our previous findings [ 41 ]. As shown in Fig. 2 , the growth of the DX15::PdGA20ox1-2A-PtrMYB3 poplars exceeded that of WT considerably, with a 2.6-fold increase of stem fresh weight of the poplars grown in the growth room for 60 days. Next, we attempted to validate the growth room performance of the transgenic poplars under LMO field conditions after 3 months of active growth in spring and summer. The stem height and diameter of the DX15::PdGA20ox1-2A-PtrMYB3 poplars were 1.7- and 1.6-times greater, respectively, than those of WT poplars with minimal growth defects (Figs. 3 and 4 ). Finally, we confirmed enhanced woody biomass production by the DX15::PdGA20ox1-2A-PtrMYB3 poplars by re-planting them in the same LMO field for two years (from May 2019 to Mar. 2021) (Additional file 1 : Fig. S3), resulting in 1.46- and 1.77-fold greater than those of WT plants in stem height and fresh weight, respectively (Fig. 6 a, b). This is significant in that the growth room performance of the transgenic poplars was validated in actual field conditions. It is notable that we could not find any significant histological changes in secondary wall formation in DX15::PdGA20ox1-2A-PtrMYB3 poplars, including secondary wall thickening of stem tissue (Additional file 1 : Fig. S4), in light of the finding that the transgenic Arabidopsis plants expressing the same construct had increased secondary wall thickening of their interfascicular fiber cells (up to 1.27-fold) (Fig. 1 d, e). However, in cell wall composition analysis, the cellulose content of the DX15::PdGA20ox1-2A-PtrMYB3 poplars was 14.4 wt% greater than that of WT poplars (Fig. 7 a). Thus, we hypothesized that the higher content of cellulose may contribute to the increase of saccharification efficiency. However, it is not known yet why only the cellulose content was increased. Additional studies are needed to address the possibility of post-transcriptional regulation of the biosynthesis of the other cell wall components. Nonetheless, it is noteworthy that transgenic rice plants with increased cellulose content had significant increase in saccharification efficiency regardless of the changes in the other cell wall components [ 49 ]. Survival and productivity of temperate perennial woody plants depend on proper timing of dormancy onset and release, which is largely regulated by a plant hormone, GA, in many woody plants [ 45 – 48 ]. GA20ox1 expression in Populus spp. is regulated by day length, and levels of bioactive GAs are downregulated by SD condition, by which mechanism ensures a rapid cessation of growth for bud set and dormancy establishment [ 11 ]. Indeed, hybrid aspens overexpressing Arabidopsis GA20ox1 were unable to arrest growth even under SD conditions [ 31 ]. Previously, we reported transgenic poplars with enhanced wood formation due to constitutive or developing xylem-specific expression of the PdGA20ox1 gene, which encodes a key enzyme involved in GA biosynthesis [ 19 , 22 , 41 ]. However, no intensive study has been conducted on the growth performance of them under the field condition for the entire period covering active growth-dormancy cycle. In this study, we used three transgenic poplars, namely, 35S::PdGA20ox1, DX15::PdGA20ox1, and DX15::PdGA20ox1-2A-PtrMYB3 poplars, and their WT counterparts for evaluation of their growth performance in the LMO field condition that expands to two-growing seasons. As expected, the timing of bud dormancy onset and release (e.g., bud flush) was significantly different among these poplars (Fig. 5 ). The 35S::PdGA20ox1 and DX15::PdGA20ox1 poplars showed delayed bud set before winter but early bud flush the next spring compared to WT and DX15::PdGA20ox1-2A-PtrMYB3 poplars (Fig. 5 ). It is highly probable that the altered bud dormancy phenology was due to differences in the GA content among genotypes caused by the different PdGA20ox1 expression. We speculate that the DX15::PdGA20ox1-2A-PtrMYB3 poplars may have adequately increased level of GA due to the significantly reduced PdGA20ox1 transcripts in the stem tissues compared to the 35S::PdGA20ox1 poplars (Additional file 1 : Fig. S1) and the DX15::PdGA20ox1 poplars. It should be noted that both the 35S::PdGA20ox1 and the DX15::PdGA20ox1 poplars were reported to have very high levels of PdGA20ox1 expression in the stem tissues [ 22 ]. Interestingly, the significantly reduced PdGA20ox1 expression was also found in our previous study with transgenic poplar lines expressing DX15::PdGA20ox1-2A-PtrMYB221, and the winter survival rate of this poplar was also similar to that of WT poplar [ 41 ]. For temperate perennial woody plants, timely bud set is an important protection mechanism to increase the probability of survival over winter, which is characterized by cold temperatures and abiotic stresses [ 13 , 50 ]. In spring, the temperature difference between night and day is large, and the timing of bud flush has a strong influence on plant survival [ 51 ]. Our transgenic hybrid poplars, especially the 35S::PdGA20ox1 poplars, showed altered bud dormancy phenology, which might have contributed to their lower over-winter survival rate (Fig. 5 d). However, the DX15::PdGA20ox1-2A-PtrMYB3 poplars showed a 100% over-winter survival rate with increased biomass up to 77% compared to WT poplars (Fig. 6 ), further validating our bicistronic expression strategy."
} | 2,179 |
37985370 | PMC10711711 | pmc | 3,374 | {
"abstract": "The ever-increasing demand for self-powered systems such\nas glucose\nbiosensors and mixed reality devices has sparked significant interest\nin triboelectric generators, which hold large potential as renewable\nenergy solutions. Our study explores new methods for integrating energy-harvesting\ncapabilities into smart textiles by developing strong and efficient\nyarns that can convert mechanical energy into electrical energy through\na triboelectric effect. Specifically, we focused on Nylon-11 (PA11),\na material known for its crystalline structure well-suited for generating\na powerful triboelectric response. To achieve this, we created triboelectric\nyarns by electrospinning PA11 fibers onto conductive carbon yarns,\nenabling energy-harvesting applications. Extensive testing demonstrated\nthat these yarns possess exceptional durability, surpassing real-life\nusage requirements while experiencing minimal degradation. Additionally,\nwe developed a prototype haptic device by interweaving tribopositive\nPA11 and tribonegative poly(vinylidene fluoride) (PVDF) triboelectric\nyarns. Our research has successfully yielded durable and efficient\nyarns with strong energy-harvesting capabilities, opening up possibilities\nfor integrating smart textiles into practical scenarios. These technologies\nare promising steps to achieve greener and more reliable self-powered\nsystems.",
"conclusion": "Conclusions In this work, we fabricated highly reproducible\nPA11 fibers with\nexceptional mechanical properties, rich in polar γ and δ′\nphases and yarns suitable for real-world applications. High mechanical\nstability was obtained by the regulation of RH during electrospinning.\nDSC results showed a highly crystalline structure that was advantageous\nfor the material’s performance. Chemical analysis confirmed\nthe combination of γ and δ′ phases in the fibers,\nwhich was further validated with KPFM, demonstrating the high surface\npotential stability of PA11. Through electrospinning, we fabricated\na novel triboelectric yarn using a conductive CNT core that displayed\noutstanding energy-harvesting performance and durability. After 200,000\nfatigue cycles, the power output of the triboelectric yarn increased\nby 30%, and it withstood over 600 rubbing cycles with high wear resistance.\nThe triboelectric yarn also maintained its coating and power output\nafter repeated washing cycles. By weaving PA11 and PVDF triboelectric\nyarns together, we created an exceptional and functional triboelectric\ntextile with practical applications in the energy-harvesting and human–computer\ninterface.",
"introduction": "Introduction As our use of portable and wearable electronics\ngrows, we must\nrethink current power generation and energy management methods. Among\nthe various technologies designed to harvest energy, triboelectric\nnanogenerators (TENGs) stand out due to their unique ability to turn\nsurrounding mechanical energy into electricity. It is essential when\nconsidering the future of smart textiles: fabrics integrated with\nelectronic components. A TENG functions based on the principle of\ncontact and separation between two dissimilar materials, usually with\ncontrasting electron affinities. When these materials come into contact,\nthey generate electric charges through the transfer of electrons between\nthem. Upon separation, the charge separation leads to a potential\ndifference that generates an electrical current, thereby producing\npower. 1 This cyclic contact and separation\nprocess continually generates electric charges and, when connected\nto an external circuit, facilitates the harvesting of electrical energy.\nIncorporating TENGs into these materials could reduce our reliance\non bulky batteries and lessen the need for frequent charging. 1 Beyond energy generation, TENGs also have the\npotential to function as self-powered sensors, opening up new possibilities\nfor advanced, interactive electronic devices. 2 Triboelectric devices have been mainly fabricated on flexible polymer\nsubstrates, but they can also be made into yarns by coating a conductive\ncore with a triboelectric material. 3 , 4 These yarns\ncan be woven or knitted together to create functional triboelectric\ntextiles. 4 Consequently, it is important\nthat TENGs designed for smart textiles possess the resilience to endure\ntextile manufacturing processes, offer comfort during wear, and remain\nwashable for maintenance-free and seamless integration. 5 Use of carbon nanotube (CNT) yarns offers exceptional\nspecific strength and conductivity, which are vital for ensuring the\nflexibility, robustness, and longevity of triboelectric textiles under\nreal-world conditions. 6 Moreover, CNT yarns\nprovide a unique advantage in facilitating seamless interconnectivity\nbetween yarns and other textile components, eliminating the need for\nconventional rigid joining methods like soldering or conductive epoxy,\nwhich are necessary for solutions with a metallic core. 3 As for the shell material, combining tribopositive\nand tribonegative materials into a textile is ideal for high-energy-harvesting\nperformance. 4 Several tribonegative yarns\nhave been demonstrated, mainly based on poly(vinylidene fluoride)\n(PVDF) and poly(dimethylsiloxane) (PDMS). 6 − 8 However, only\na handful of tribopositive yarns have been reported due to the limited\nnumber of tribopositive synthetic materials ( e.g. , nylons, polypropylene) and their challenging fabrication process. 9 , 10 To facilitate the real-world application of functional triboelectric\ntextiles, it is essential to develop durable, high-power tribopositive\nyarns, as illustrated in Figure 1 . Figure 1 Conceptual schematic of the study on tribopositive yarn\nbased on\nelectrospun PA11 fiber-based coating on a conductive carbon nanotube\n(CNT) core wire for constructing high wear and water resistance energy-harvesting\ndevices. SEM images have faux colors for clarity. Nylon-11 (PA11) is a promising polymer for energy\nharvesting due\nto its mechanical resilience and triboelectric properties. 11 The mechanical properties of PA11 are crucial\nfor ensuring the durability and performance of triboelectric textiles,\nallowing them to withstand the demands of daily use while efficiently\nharnessing energy. However, solution processing of PA11 has been a\nmajor hurdle for film and fiber-based devices. 12 There are several phases of PA11, namely, α, β,\nγ, and δ′, but only highly aligned α and\nδ′ have high polarization needed for high triboelectric\noutput. Complex methods using extremely rapid evaporation rates or\nnanoconfined templates are required to produce aligned α and\nδ′ phases. 13 , 14 Electrospinning offers\na promising fabrication route because of its unique combination of\nrapid evaporation and mechanical stretching. The nonwoven materials\nproduced this way consist of a large network of interconnected fibers,\nproviding a highly developed surface essential for achieving high\ncharge density, a crucial factor for TENGs. 15 Anwar et al. demonstrated that α and δ′ phase\nPA11 fibers can be fabricated by dissolving the PA11 in a trifluoroacetic\nacid(TFA)/acetone solution and adjuring the polymer concentration. 16 Electrospinning is a promising method to fabricate\ntriboelectric yarns because of its scalability, broad range of available\nmaterials, and potential to enhance a material’s triboelectric\nand mechanical performance in a one-step process. 17 − 19 Triboelectric\nyarns can be produced by depositing polymer fibers directly on a conductive\nyarn using a high electric field and tribonegative PVDF-based yarn\nwith high-power output and superior resistance to fatigue, and abrasion\nwas already reported in a previous study. 6 , 7 , 20 In this work, we developed a novel\nhighly tribopositive yarn based\non an electrospun PA11-coating on a conductive carbon nanotube (CNT)\ncore. The resulting yarn displayed remarkable energy-harvesting performance\nand high wear and water resistance. Finally, PA11 tribopositive yarns\nwere woven with PVDF tribonegative yarns to create a triboelectric\ntextile that demonstrated its real-life applicability in energy harvesting\nand sensing, such as in a human–computer interface. The schematic\nshowcasing the core idea and novelty of the study is presented in Figure 1 .",
"discussion": "Results and Discussion Morphology, Mechanical Properties, and Chemical Composition\nof PA11 Fibers The fabrication and real-life use of triboelectric\nyarns necessitates materials with high toughness and stretchability\nbeyond 20% strain. 1 Fibrous meshes, such\nas electrospun PA6, have shown higher toughness and crack resistance\nthan film counterparts, emphasizing the advantage of fibrous meshes\nfor stable triboelectric layers. 21 Polyamides\nare known for high mechanical stability and are widely studied in\nfibrous form. 22 , 23 It is vital to achieve highly\ncrystalline materials to optimize the energy-harvesting properties.\nPA11 can exist in several crystalline phases, including triclinic\nα-phase, monoclinic β-phase, and three hexagonal or pseudohexagonal\nforms (γ-, δ-, and δ′- phases). Fabricating\nPA11 fibers with polar phases, such as aligned γ and δ’,\nis essential to optimize their energy-harvesting properties. 24 , 25 In electrospinning, relative humidity (RH) conditions can significantly\naffect the rate of solvent evaporation. 26 Higher RH levels slow solvent evaporation from the polymer solution\njet, leading to delayed solidification of polymer fibers. This delay\ncauses structural variations in the fibers, impacting their mechanical\nproperties, crystallinity, and other characteristics, ultimately affecting\nthe material’s energy-harvesting capabilities. 26 RH influence on the rate and nature of PA6 formation, fiber\nstructure, and the material’s mechanical properties has been\npreviously reported. 26 − 28 Thus, we conducted experiments under RH conditions\nof 30, 50, and 70% to investigate their influence on the properties\nof self-standing electrospun PA11. The prepared fiber samples were\nlabeled F30, F50, and F70 to reflect the RH at which they were produced. A process that creates uniform, defect-free fibers is essential\nfor a robust mesh. Thus, scanning electron microscopy (SEM) imaging\nwas used to assess the PA11 fibers’ shape and diameters; see Figure S1 . The electrospun mats exhibited a typical\nfibrous morphology under all tested RH conditions. All fibers had\na smooth surface without visible beads. The diameters for all samples\nranged from 100 to 145 nm, with narrow distributions indicating stable\nelectrospinning. The thickness of the mats showed minimal variation.\nSpecifically, for F30, F50, and F70, the thickness measurements were\n34.3 ± 3.7, 37.0 ± 1.7, and 35.5 ± 2.0 μm, respectively.\nSimilarly, the porosity remained consistent across different humidity\nlevels. The values were 40.3 ± 2.8% for F30, 36.7 ± 0.5%\nfor F50, and 37.1 ± 2.1% for F70, indicating a negligible difference.\nThus, varying RH did not affect the morphology, porosity, or fiber\ndiameters in a significant way. Our results align with previous reports\nshowing excellent reproducibility of electrospun PA11 fibers. 24 The tensile test results are presented in Figure 2 a and Table S1 . Fibers fabricated at 30% RH demonstrated\nthe lowest strain at failure, 21.2 ± 2.5%, with a maximum tensile\nstress of 1.79 ± 0.32 MPa. The toughness of fibers produced under\nthese conditions was 28.3 ± 6.7 MPa. An increase in strain at\nfailure to 28.2 ± 1.9% was observed for the fibers prepared at\n70% RH, underlining the influence of the humidity-dependent formation\nprocess on the material’s mechanical characteristics. 29 However, the ultimate tensile stress corresponding\nto this condition was the lowest among the three, registering at 0.97\n± 0.03 MPa. The toughness also decreased to 18.0 ± 0.1 MPa\nat this RH. PA11 fibers produced at 50% RH provided an ideal blend\nof mechanical properties. They exhibited the strain at failure at\n35.5 ± 1.0%, double that observed for PA11 fibers produced under\n30% RH. In addition, maximum tensile stress was measured at 1.02 ±\n0.14 MPa for this condition, and toughness declined slightly to 25.8\n± 0.9 MPa compared to PA11 fibers produced under 30% RH. These\nresults indicate that 50% RH could be an optimal environment, achieving\nthe best strain at failure without compromising toughness. Compared\nto PA6 tested under the same conditions, our PA11 fibers demonstrated\nsuperior mechanical properties, especially for the strain at maximum\nstress and toughness, making them a more suitable option for TENG\napplications. 30 Figure 2 (a) Exemplary stress–strain\nplot of tensile tested self-standing\nPA11 fiber networks, (b) DSC characterization of PA11 fibers, γ\nand δ′ phase films (first heating), (c) XRD characterization\nof PA11 fibers, γ and δ′ phase films, (d) structural\ncharacterization of PA11 fibers and γ and δ′ phases\nusing FTIR with magnified spectra of the 550–900 cm –1 and 1400–1000 cm –1 regions. The dashed\nred line is a visual indicator of the CO–NH skeletal motion\npeak (P1) at 1156 cm –1 . The dashed blue line is\na visual guideline for the δ′ phase amide V band (686\ncm –1 ). The dashed black line serves as a visual\nguideline for the γ phase amide V band (709 cm –1 ). To understand the changes in mechanical properties,\nwe investigated\nthe thermal properties, and crystallinity of PA11 fibers using differential\nscanning calorimetry (DSC) ( Figure 2 b). Melting points ranged from 187.5 °C (γ\nphase) to 190 °C (δ′ phase) for all samples, suggesting\na mixed crystal structure. F30 and F50 fibers displayed an additional\npeak at 181 °C, likely corresponding to the second δ′\nphase melting peak observed at 185 °C in the reference film.\nThis implies a higher fraction of δ′ phase in these fibers\ncompared to the F70 sample. The first melting peaks were utilized\nto determine fiber sample crystallinity. F30 and F50 samples exhibited\na higher crystallinity of 41 ± 1 and 43 ± 4%, in contrast\nto 27 ± 0.3% found in the F70 sample, while γ and δ′\nphase films showed values of 26 ± 2% and 17 ± 2%, respectively.\nThe enhanced crystallinity of electrospun PA11 arises from high elongation\nstrain, shear forces, and a strong electric field during the electrospinning\nprocess. This results in a highly organized fiber structure composed\nof aligned crystallites with amorphous regions filling the gaps. 31 The crystal structure of the fibers was further\nprobed using X-ray diffractometry (XRD) ( Figure 2 c). The F30 and F50 fibers displayed a single\nbroad peak at approximately 21.4°, a combination of the (100)\nreflection of γ phase and the (100) reflection from the δ′\nphase. In contrast, the F70 fiber had a slightly shifted peak center\n(21.6°), suggesting a lower δ′ phase volume fraction\nand a shift toward the γ phase composition, which aligns with\nDSC data. Moreover, the PA11 fiber samples exhibited a more organized\npseudohexagonal structure than films, as evidenced by a smaller full\nwidth at half-maximum of the δ′-phase line, 2.44–2.59\nand 3.8 for fibers and δ′ film, respectively. Similar\ncomposition of PA11 electrospun from hexafluoroisopropanol (HFIP)\nhas been reported, suggesting electrospinning leads to higher amounts\nof beneficial δ′-phase due to high electric field and\nmechanical stretching. 32 Crystal structure\ninvestigation was continued by using Fourier transform infrared spectroscopy\n(FTIR). Figure S2 shows the spectra of\nPA11 fibers compared to those of γ and δ′ phase\nfilms. PA11 has characteristic primary and secondary amide bands that\nappear in the 1500–1800 cm –1 region and are\nassociated with hydrogen-bonded or free amide groups. In addition,\nthe vibrations at 3300 and 1639 cm –1 correspond\nto the N–H and C=O stretching modes. The 2920 and 2850\ncm –1 vibration bands originate from the antisymmetric\nand symmetric CH 2 stretch. 25 Figure 2 d provides\nfurther insight into the RH effects on PA11 fibers. We can observe\nthat increasing humidity affected both peak position and intensity,\nespecially in regions around 700 and 1200 cm –1 wavenumbers.\nAll of the samples had a broad peak around 700 cm –1 , composed of an intense peak at 721 cm –1 (CH 2 rocking) next to a lower intensity peak for the amide V band,\nfound at 709 and 686 cm –1 for the γ and δ′\nphases, respectively. In the F30 and F50 fibers, the amide V band\nwas located at 686 cm –1 , while in the F70 sample,\nthis band shifted toward 709 cm –1 . This indicates\nthat the F30 and F50 samples had a higher fraction of the δ′\nphase compared to the F70 sample. In the CH 2 progression\nbands region (1000–1400 cm –1 ), the CO–NH\nskeletal motion peak (P1) was found at 1153 and 1161 cm –1 for the γ and δ′ phase films, respectively. The\nP1 peak was located at 1161 cm –1 for F30 and F50\nsamples but shifted to 1157 cm –1 in the F70 sample.\nThis further shows that the F30 and F50 samples have a higher δ′\nphase content compared with the F70 counterpart. Based on the shifts\nin the characteristic amide V bands (709 and 686 cm –1 for γ and δ′ phases, respectively) as well as\nthe shift toward the γ phase in the 1100–1200 cm –1 region, the data confirms the presence of both γ\nand δ′ phases. These results suggest that the PA11 fibers\nare highly crystalline and contain a mixture of both γ- and\npolar δ′ phases, which aligns with XRD and DSC results.\nFurthermore, the presence of a metastable δ′ phase indicates\nextremely high evaporation of solvents during electrospinning. 25 In summary, all produced fibers met the\nabove 20% strain at failure\ncriteria, with the 50% RH condition found to be optimal for making\nhighly mechanically stable fibers. This disparity in mechanical properties\nwas driven by changes in the crystalline structure of the obtained\nfibers. 33 The DSC analysis revealed that\nall samples had a mixed crystal structure composed of γ and\nδ′ phases. Notably, F30 and F50 exhibited an additional\nδ′ phase melting peak at 181 °C, indicating a higher\nδ′ phase fraction compared to F70. In the XRD analysis,\nthe F30 and F50 fibers displayed a broad peak at 21.4°, representing\nboth γ and δ′ phase reflections. Confirming DSC\nresults, the F70 sample had a peak centered at 21.6°, suggesting\na shift toward a greater amount of γ phase in the composition.\nFTIR spectra further confirmed our findings and showed notable differences\nin the amide V band. F30 and F50 samples exhibited this band at 686\ncm –1 , while F70 had it at 709 cm –1 , indicating higher δ′ phase content in the former.\nBecause formic acid and water readily form hydrogen bonds, it is probable\nthat different humidity levels influenced the evaporation rate of\nformic acid, subsequently impacting the crystalline structure of the\nelectrospun material. 27 Our results are\nanalogous to research carried out on PA6 by Giller et al. 27 in which fast and slow solvent evaporation resulted\nin distinct changes in the phase composition of the prepared fibers.\nThus, the influence of RH has been confirmed to affect more than one\ntype of polyamide. The presented research outcomes\nunderscore that careful control of preparation conditions can effectively\ntailor the mechanical stability and phase structure of PA11, demonstrating\nthe advantages of electrospinning. 34 Energy Harvesting and Surface Potential of PA11 Fibers To understand RH’s influence on the energy-harvesting capability\nof triboelectric generators, we assembled several devices and tested\ntheir power output; see Figure 3 a. We recorded the power output for the F30 sample with 2.87\nand 3.34 μW across a 500 MΩ resistor, respectively. In\nthe F50 device, as it produced a maximum power output of 1.18 and\n0.99 μW across a 500 MΩ load resistance. The power output\ndrastically dropped for F70, having a maximum power output of 0.21\nμW across a 300 MΩ load resistance. The results showed\nthat RH strongly influenced the power output of the devices. Lower\nRH led to an increase in the power output of the triboelectric devices.\nSuch a result correlated with the increase in crystallinity and amount\nof the polar δ′ phase as characterized by DSC, XRD, and\nFTIR. While all samples had similar thickness, fiber diameters, and\nporosities, ruling out variations in the contact area as a factor,\nwe observed that the F30 sample delivered a higher power output than\nthe F50 despite having comparable degrees of crystallinity. This disparity\ncan be attributed to variations in the ratio of the γ and δ′\nphases in the fibers, as suggested by DSC and XRD profile fitting\nresults. The significant variation observed in the F30 sample suggests\ninstability and the potential for degradation over extended periods,\nraising doubts about its suitability for real-world applications.\nThis instability is reflected in the tensile testing results, where\nthe F30 sample performed the worst, barely exceeding 20% elongation\nat the breaking point. Therefore, lower mechanical performance of\nthe F30 sample leads to rapid degradation during triboelectric testing.\nIn TENG, stability and flexibility are essential. Thus, we decided\nto focus our further characterization efforts exclusively on the F50\nsample, as it demonstrated the best combination of mechanical properties\nand triboelectric performance. Figure 3 (a) RMS power output measured across several\nload resistances of\nPA11 fibers produced with different RH and (b) surface potential plot\nof PA11 fibers compared to ITO glass background. Kelvin probe force microscopy (KPFM) measurements\nwere carried\nout to test the spread of the surface potential between individual\nfibers, which might indicate differences in the structure and potential\ninstabilities. Exemplary atomic force microscope (AFM) topography\nscan and the accompanying surface potential map are shown in Figure S3 . All tested fibers exhibited similar\nsurface potentials with an average of 336 ± 10 mV ( Figure 3 b). Such a small standard deviation\nindicates high homogeneity of the surface potential of all prepared\nfibers. Thus, we conclude that all produced fibers possess similar\nproperties and chemical composition. A similar value of approximately\n510 mV was already reported for δ′ phase-rich PA11 nanowire\nfilms. 11 A high positive surface potential\nmakes PA11 fibers an excellent candidate for TENG with a negative\npair such as PVDF, which has reported negative voltage potential (as\nmeasured with KPFM) in the range of around −100 to −400\nmV depending on the processing conditions. 35 , 36 Yarn Fabrication and Characterization To demonstrate\nthe PA11 potential for real-world applications, a triboelectric yarn\nwas fabricated by electrospinning PA11 fibers directly onto a carbon\nnanotube (CNT) yarn, creating a core–shell structure. 6 Based on the results from previous sections,\nwe have chosen fibers electrospun at 50% RH (F50) as the coating as\nthey displayed the optimum balance between mechanical properties and\ntriboelectric performance. In this process, the CNT yarn was placed\nperpendicular to the electrospinning nozzle, which was scanned along\nthe length of the CNT yarn to deposit the PA11 fibers. The yarn schematic\nwith SEM images of the end product is shown in Figure 1 . The yarns had an average diameter of 713\n± 51 μm and were coated with PA11 to a thickness of approximately\n440 μm. The coating surface exhibited relative uniformity, with\noccasional creases along the length of the yarn. At the individual\nfiber level, the surface of the PA11 fibers was smooth, and their\naverage diameter was 124 ± 21 nm ( Figure S4 ). Notably, the formation of PA11 fibers was unaffected by\nmodifications to the electrospinning setup or the use of a CNT yarn\nas a collector compared to standard electrospinning procedures used\nearlier in this study. Energy-Harvesting Performance and Stability of Yarns The energy-harvesting performance combined with the mechanical stability\nof the tribopositive PA11 triboelectric yarn was characterized by\ntapping the yarn against a poly(tetrafluoroethylene) (PTFE) film as\nthe tribonegative material. The working principles of PA11 triboelectric\nyarns and a difference in working principle to self-standing meshes\nare shown in Figure S5 . The working principle\nof the PA11 yarn was nearly identical to that of the previously reported\nPVDF yarn. 6 As the yarn contacts the PTFE\nfilm, charges are transferred from the PA11 fibers to the PTFE film.\nThe PA11 fibers become positively charged, and the PTFE film accumulates\nnegative surface charges. When the yarn and film are separated, a\npotential difference develops and the charges on the surface of each\nmaterial induce an electron flow in the respective electrode. The results in Figure 4 showed that the yarn initial power output was 31.7 nW and it increased\nto 41.2 and 40.9 nW after 50,000 and 200,000 cycles. After the test,\nthe yarn surface was inspected using SEM. The images showed that the\nyarn diameter increased from 757 to 837 μm after 200,000 tapping\ncycles, but no coating failure was observed. Furthermore, the PA11\nfibers deformed into a film-like structure, lowering the fiber network\nporosity from 34.1 ± 2.6 to 20.7 ± 3.0%. Irregularities\non the yarn coating such as creases were flattened due to repeated\nmechanical deformation. The increase in total contact area with fatigue\ncycles (10% larger yarn diameter and 40% reduction in fiber network\nporosity) is linked to a 30% increase in the yarn power output. Similar\nfatigue behavior was reported for electrospun triboelectric yarns. 20 It is challenging to directly compare the power\ndensity of the triboelectric yarn with previously reported yarns because\nof the lack of standardized testing parameters ( e.g. , counter material, force, and contact area) and the challenges in\nquantifying the yarn contact area (due to fiber network porosity).\nHowever, a qualitative comparison was performed by estimating the\ncontact area (7.3 mm 2 ), and the results showed that after\n200,000 fatigue cycles, the peak power density obtained from the triboelectric\nPA11 yarn was 121 mW m –2 across a 500 MΩ resistor.\nThe results showed that the PA11 triboelectric yarn had a relatively\nlower power output compared to previously reported electrospun triboelectric\nyarns when subjected to similar mechanical excitation. 6 However, this was expected, considering that the PA11 yarn\nhad a lower contact area due to a smaller yarn diameter. Nevertheless,\nthe triboelectric power output of the tribopositive PA11 yarn was\ncomparable to previously reported tribonegative yarns. 37 Figure 4 Energy-harvesting performance and durability of the PA11\ntriboelectric\nyarn. (a) RMS power output of the triboelectric yarn across different\nresistors during fatigue testing with SEM images of the same triboelectric\nyarn as fabricated and after 200,000 tapping cycles. The wear resistance of a triboelectric yarn is\nrarely evaluated\ndespite being a crucial parameter to demonstrate its suitability to\nthe industrial manufacturing process and real-life applications. Abrasion\ntesting of the PA11 triboelectric was conducted by repeatedly rubbing\nthe yarn with a steel ball while measuring the electrical resistance\nbetween the CNT core and the steel ball ( Figure 5 ). The drop in resistance over time was attributed\nto the progressive damage of the PA11-coating. Figure 5 Schematic of friction\nmeasurement with an SEM image of the triboelectric\nyarn after the wear resistance test. The dashed circles show the exposed\nCNT yarn. The figure has been partially adapted from an already existing\nwork. 6 Figure 6 shows the\nelectrical resistance between the CNT yarn and steel ball during the\nrubbing cycles. Three samples were tested, which started failing after\napproximately 600, 900, and 1600 cycles. The PA11 triboelectric yarn\nshowed remarkable wear resistance, considering the applied stress\nof 6 MPa. The postexperiment images showed that the PA11 fibers were\ndeformed into a film-like structure, and multiple rupture points were\nvisible in the coating. The PA11 triboelectric yarn showed comparable\nwear resistance to previously reported electrospun triboelectric yarns. 6 , 20 On average, the PA11 yarn failed after a lower number of cycles\nthan the PVDF fiber-based yarns, most likely because of differences\nin the individual fibers as well as in the fiber network. The Young’s\nmodulus of bulk PVDF is approximately twice that of bulk PA11 (2.4\nand 1.2 GPa, respectively). 38 Furthermore,\nthe PVDF fiber-based yarns had a roughly 30% thicker coating and 10\ntimes larger individual fiber diameter compared to the PA11 yarn.\nThe high fatigue and wear resistance of the PA11 triboelectric yarn\nwere linked to the bonding between the CNT yarn and the PA11 fibers.\nRaman spectroscopy was used to investigate whether chemical bonding\nbetween the CNTs and PA11 fibers had occurred. The data in Figure S6 are without any significant peak shift,\ndisplaying no evidence of chemical bonding between the CNT yarn and\nthe PA11 fibers on the triboelectric yarn. Therefore, mechanical interlocking\nbetween the CNT yarn and PA11 fibers is the main bonding force. The\nresults are consistent with Raman data of the previously reported\nPVDF triboelectric yarn. 6 Figure 6 Resistance measurements\nbetween the triboelectric yarn and the\nsteel ball were taken across friction cycles. The dashed line highlights\nthe failure point where the coating begins to delaminate. The effect of water on the PA11 triboelectric yarn\nwas investigated\nby testing its power output after 5 and 10 washing cycles. Figure S7 shows that the power output of the\ntriboelectric yarn was not affected by washing. SEM images of the\nyarn displayed a slight increase in the yarn diameter (4%), but no\nsigns of coating damage. The results demonstrate that PA11 fibers\ndid not undergo degradation via hydrolysis and that\nthe washing cycles did not significantly affect the triboelectric\nyarn power output. The slight increase in the yarn diameter is related\nto repeated tapping, as seen in the fatigue tests. Exposure to water\nis known to damage nylons, reducing their mechanical and electrical\nproperties. 39 However, PA11 is more water-resistant\nthan lower number PAs ( e.g. , PA6 and PA7). 39 Furthermore, δ′ phase PA11 has\nbeen reported to have higher water resistance than α phase PA11. 40 PA11 has good resistance to alkaline solutions;\nhence, detergents are unlikely to damage the triboelectric yarn. 41 The PA11 triboelectric yarn showed similar water\nresistance (after 10 washing cycles) as other high-performance triboelectric\nyarns. 42 , 43 Energy-Harvesting and Human–Computer Interface Applications Triboelectric textiles can be used as self-powered force and touch\nsensors and more generally in haptic devices for the human–computer\ninterface. The working principle of a textile-based triboelectric\ndevice is shown in Figure 7 . Figure 7 Operating principle of the triboelectric textile comprised of two\ncore–shell yarns, tribonegative PVDF and tribopositive PA11. PA11 triboelectric yarns were woven with PVDF triboelectric\nyarns\nto create a functional triboelectric textile ( Figure 8 a). The PVDF yarns were prepared using procedures\nreported earlier. Three yarns of each kind were woven using a plain\nweave configuration, where the weft thread passed over the warp in\nan “over and under” sequence. The triboelectric textile\nwas pressed down by using an aluminum block at 2 N and 2 Hz. During\ncontact, the PA11 yarns were pressed against the PVDF yarns at the\ncrossover points, as shown in Figure 8 a, where a textile-based touchpad demonstrating practical\nuse is presented. The touchpad worked by measuring the V oc of each yarn and combining the signals to determine\nthe position of the touch. The V oc of\nthe individual yarns during a single touch is shown in Figure 8 b. Subsequently, it is possible\nto create a spatial map by multiplying together the V oc values of different yarns ( Figure 8 c). The spatial map results showed a clear\ncorrelation with the location of the touch, showcasing the potential\nof the triboelectric textile as a haptic device. For example, the\nproof-of-concept triboelectric textile could be integrated into garments\nor upholstery to enable a more seamless and immersive interface to\nmixed and virtual reality. The V oc value\nof the triboelectric yarn is directly related to the applied force.\nTherefore, the force sensing capability of the triboelectric textile\nwas investigated ( Figure 8 d). The results showed a nearly linear relationship between\nforce and V oc until 10 N, with a coefficient\nof 50 ∼mVN –1 . Beyond 10 N, the response became\nnonlinear and plateaued after 15 N, demonstrating the upper limit\nof the triboelectric textile force sensing capabilities. Figure 8 Energy-harvesting\nand sensing applications of a triboelectric textile.\nEach set of yarns ( i.e. , PVDF and PA11) is connected\nin parallel and is connected to a multimeter lead. (a) Photograph\nof the triboelectric textile made by weaving PVDF and PA11 yarns together\nwith touch sensing capabilities. (b) Demonstration of touch sensing\ncapabilities: P1–3 describe PVDF yarn and N1–3 describe\nPA11 yarns. V oc signal of the respective\nyarn during touch. The voltage of each yarn was filtered and smoothed\nfor easier signal detection, and each yarn was configured in a single-electrode\nmode. (c) Spatial map of the signal of the triboelectric textile during\ntouching. The pixel color refers to the normalized intensity of V oc produced between the respective yarns. (d)\nPeak power density of the triboelectric textile. (e) Force sensing\nmeasurement of the triboelectric textile using open-circuit voltage\n( V oc ) . A load cell was\nused to measure the applied force. The dotted line shows the linear\nfit from which the force and V oc coefficient\nwere calculated. (f) Capacitor charging curves using the triboelectric\ntextile of three different capacitors. A full-bridge rectifier was\nused to rectify the output. The energy-harvesting properties of the triboelectric\ntextile were\ncharacterized by measuring the power output and capacitor charging\ntime. All yarns with the same coating (PVDF or PA11) were connected\nin parallel to maximize the power output. Figure 8 e shows that the triboelectric textile had\nan estimated maximum peak power density of 172 mW m –2 across a 150 MΩ load resistance (contact area: 0.9 mm 2 , mechanical input: 2 N at 2 Hz). Despite being a proof-of-concept\ndevice, the triboelectric textile showed 1.8 times higher peak power\ndensity than previously reported woven electrospun yarns (∼93\nmW m –2 , mechanical input: 200 N and 3 Hz). 3 The capacitor charging test showed that the triboelectric\ntextile was able to charge a 1 μF capacitor to 5 V in approximately\n30 s ( Figure 8 f)."
} | 8,651 |
28642744 | PMC5462947 | pmc | 3,376 | {
"abstract": "Acid mine drainage (AMD) and mine tailing environments are well-characterized ecosystems known to be dominated by organisms involved in iron- and sulfur-cycling. Here we examined the microbiology of industrial soft coal slags that originate from alum leaching, an ecosystem distantly related to AMD environments. Our study involved geochemical analyses, bacterial community profiling, and shotgun metagenomics. The slags still contained high amounts of alum constituents (aluminum, sulfur), which mediated direct and indirect effects on bacterial community structure. Bacterial groups typically found in AMD systems and mine tailings were not present. Instead, the soft coal slags were dominated by uncharacterized groups of Acidobacteria (DA052 [subdivision 2], KF-JG30-18 [subdivision 13]), Actinobacteria (TM214), Alphaproteobacteria (DA111), and Chloroflexi (JG37-AG-4), which have previously been detected primarily in peatlands and uranium waste piles. Shotgun metagenomics allowed us to reconstruct 13 high-quality Acidobacteria draft genomes, of which two genomes could be directly linked to dominating groups (DA052, KF-JG30-18) by recovered 16S rRNA gene sequences. Comparative genomics revealed broad carbon utilization capabilities for these two groups of elusive Acidobacteria, including polysaccharide breakdown (cellulose, xylan) and the competence to metabolize C1 compounds (ribulose monophosphate pathway) and lignin derivatives (dye-decolorizing peroxidases). Equipped with a broad range of efflux systems for metal cations and xenobiotics, DA052 and KF-JG30-18 may have a competitive advantage over other bacterial groups in this unique habitat.",
"introduction": "1. Introduction Mining frequently produces enormous amounts of tailings, which often pose the danger of generating acid mine drainage (AMD) (Rohwerder et al., 2003 ). AMD is a consequence of sulfur- and iron-rich minerals, primarily pyrite (FeS 2 ), being exposed to oxygen and humidity (Druschel et al., 1999 ). Pyrite oxidation leads to the formation of sulfuric acid and ferrous iron. Sulfuric acid lowers the pH and ferrous iron is further oxidized yielding ferric iron. The gradually decreasing pH increases the solubility of ferric iron, which is a stronger oxidant of pyrite than oxygen (Druschel et al., 1999 ). Microbial activity accelerates AMD generation tremendously. Microbial iron and sulfur oxidation are orders of magnitude faster than the abiotic oxidation of these two elements. The microbial activity easily leads to a release of acidic and metal-contaminated discharges. Early studies targeting AMD microbial communities revealed the prevalence of a few taxonomic groups, including Leptospirillum and Acidithiobacillus among the bacteria and Ferroplasma and other Thermoplasma -related groups (A-, E-, and G-Plasma) within the archaea (Baker and Banfield, 2003 ). Metagenomic (Tyson et al., 2004 ; Dick et al., 2009 ; Yelton et al., 2011 , 2013 ), metatranscriptomic (Lehembre et al., 2013 ; Hua et al., 2015 ; Chen et al., 2015 ) and metaproteomic (Denef et al., 2010 ; Mueller et al., 2011 ) studies showed that iron- and sulfur-cycling are the dominating microbial activities in AMD environments. Most AMD studies focused either on tailings as source material (Radeva and Selenska-Pobell, 2004 ; Senko et al., 2008 ; Urbanová et al., 2011 ; Korehi et al., 2014 ) or on AMD discharges as the end product (Baker and Banfield, 2003 ; Tyson et al., 2004 ; Dick et al., 2009 ; Xie et al., 2011 ; Kuang et al., 2013 ). The most common sources of AMD are mine tailings, and iron and coal deposits. Though coal is nowadays almost exclusively mined for its use as fossil fuel, mineral-rich coal is mined to win scarce and precious minerals such as germanium (Arroyo and Fernández-Pereira, 2008 ). In the nineteenth century, sulfur mineral-rich soft coal was mined in Western Germany, in the surroundings of Bonn, to extract these minerals by a smelting-like process (Supplementary Figure 1 ). Among these minerals, especially alum (KAl(SO 4 ) 2 ×12H 2 O) was commonly used as mordant and precipitant in early textile and paper industry. Alum was extracted from soft coal in a four-step process. Soft coal was mined, sheared and subsequently smoldered to enrich present alum. The resulting ash (one third of the original coal, alum content 15%) was leached and the leachate boiled to yield crystalline alum. Overall, alum leaching was a low-yield process. One ton of coal had to be processed to win 50 kg of crystalline alum, thereby leading to 300–400 kg of leached slag as by-product. At peak year level, 500,000 tons of coal were mined, producing 1,250 tons of alum and 150,000–200,000 tons of slag. In the middle of the nineteenth century, the alum extraction plants and soft coal mines in the surroundings of Bonn were the biggest of their kind in former Prussia. Given a mining period of roughly 70 years (1805–1875), tremendous amounts of leached slag were produced and dumped into the environment without precautions and remediation. Here we investigated the microbiology of soft coal slag deposits. Given their industrial history and leached nature, we hypothesized that the slags represent an endpoint AMD environment that is characterized by a unique bacterial community composition. In particular, we were interested in exploring to which extent the remaining alum and other metals affect the genome coding potential of the slag-deposit-inhabiting microbial communities. An additional challenge faced by these communities is the recalcitrant nature of their carbon sources. Our research involved a thorough geochemical analysis, bacterial community profiling, and shotgun metagenomics. In addition to samples from three slag deposit sites, sediment from a drainage pond and nearby undisturbed forest soil were examined for comparison.",
"discussion": "4. Discussion The slag samples contained high amounts of iron and sulfur (Figure 2A ), presumably in mineral form. This was unexpected given the age (150 years) and leached nature of the slags. Assuming a continuous exposure to oxygen and humidity, an oxidation of present sulfide-mineral components was anticipated. Sulfide-rich mine tailings show a zonation over time: a sulfide-depleted zone; an active, transitory oxidation zone; and a primary zone representing the original conditions (Diaby et al., 2007 ; Tan et al., 2008 ; Huang et al., 2011 ). In our study, the slags originated from soft coal with a high content of pyrite. Organic carbon in soft coal and, as a consequence, in the studied slags primarily consists of humic and fulvic acids (Peuravuori et al., 2006 ). Humic acids were repeatedly reported to be efficient in pyrite passivation (Lalvani et al., 1996 ; Belzile et al., 1997 ; Chen et al., 1999 ), either by chelating released ferric iron with their negatively charged functional (carboxylic, phenolic) groups or by direct pyrite adsorption. Both processes may explain why the oxidation of sulfide minerals in the slag deposits was mitigated. This low oxidation level clearly differentiates the Red Hill slag deposits from mine tailings and other AMD environments. Aluminum was found to be a major driver of bacterial community structure in the leached slags (Figures 2B–D ). The high aluminum content highlights the inefficiency of the early-industrial leaching process. Given the low pH (3.4–3.6) of the slags, aluminum was likely present as cations (Supplementary Figure 7 ). Cationic aluminum is highly toxic because of potential interferences with ATP metabolism, lipid metabolism and membrane transport processes (Supplementary Figure 8 ). In soils, aluminum toxicity can be mitigated by clay minerals and organic acids, which act as a buffer system due to their cation exchange capacity (Turpault et al., 1996 ). The chelating capabilities of humic and fulvic acids may lead to the immobilization of aluminum cations as described above for iron-sulfur minerals. Mohan and Chander ( 2006 ) showed that brown coal is an efficient adsorbent for metal cations in AMD discharges. Given a passivation of iron-sulfur minerals and aluminum, their role as drivers for bacterial community structure can be considered indirect, albeit toxic effects of aluminum due to minor releases may occur. Previous research had revealed that the retention of metal cations can alter the accessibility and utilizability of humic and fulvic acids as potential carbon sources for microbes (Jones and Edwards, 1998 ; Jones et al., 2003 ). Considering that humic and fulvic acids are naturally rather inert and recalcitrant carbon sources (Kirk and Farrell, 1987 ), metal complexation would increase the supposed oligotrophic nature of the studied slag deposits. In the leached slags, both microbial biomass and bacterial cell numbers were significantly lower than in the undisturbed forest soil (Supplementary Figure 5 ), but in the range previously determined for sulfidic mine tailings (Korehi et al., 2014 ). Five yet-uncultured subphylum groups were identified to be dominant in the slag deposits. These belonged to Acidobacteria, Actinobacteria, Alphaproteobacteria, and Chloroflexi (Figures 1A,B ). None of the five groups have previously been reported to be highly abundant in AMD systems. Their first detection was in peatlands (DA052, DA111, TM214) (Rheims et al., 1996 ; Felske et al., 1998 ) and uranium waste piles (KF-JG30-18, JG37-AG-4, DA111) (Selenska-Pobell et al., 2001 ; Selenska-Pobell, 2002 ). Phylogenetic analysis of nearly complete 16S rRNA gene sequences also revealed relationships to populations present in acidic, metal-rich, and contaminated soil environments (Supplementary Table 2 ). In accordance with the geochemical differences discussed above, non-occurrence of bacteria known to be involved in iron- and sulfur-cycling again clearly differentiates the slag deposits from AMD systems and mine tailings. Given that cultured representatives are not yet available for the dominant groups identified in the Red Hill slag deposits, their metabolic capabilities remained elusive. Therefore, high abundances of Acidobacteria subdivisions 2 (DA052) and 13 (KF-JG30-18) prompted us to conduct a metagenomic approach in order get first insights into their genetic potential. Acidobacteria are known to be abundant members of terrestrial microbiomes (Janssen et al., 2002 ; Sait et al., 2006 ) and to be phylogenetically highly diverse (Barns et al., 2007 ). A total of 22 genera have been described, which cover only 8 of 26 subdivisions proposed until today. Genome sequences are available for members of 5 subdivisions (1, 3, 4, 8, and 23; Kielak et al., 2016 ). Acidobacteria are believed to have an oligotrophic (K-strategist) lifestyle. This perception, however, may be biased due to the low number of acidobacterial isolates of which most belong to subdivision 1. Members of subdivisions 2 and 13 have repeatedly been detected in higher abundances in U-contaminated environments (Selenska-Pobell et al., 2001 ; Barns et al., 2007 ). The occurrence of subdivision 2 populations in Amazonian forest soils was correlated to the microbial availability of CO 2 , Fe, and Al 3+ . Thus, it was hypothesized that members of subdivision 2 are tolerant to aluminum (Navarrete et al., 2013 ; Catão et al., 2014 ). Adaptation and tolerance to Al 3+ could also be one major reason for the high relative abundance of DA052 in our sampling sites, especially in RH1. Amazonian forest soils are commonly rich in biochar whose chemical characteristics are remotely similar to those of studied soft coal slags. However, a recent study of biochar microbiomes and metagenomes revealed a rather low abundance of Acidobacteria (Noyce et al., 2016 ). Given the limited knowledge of yet uncharacterized Acidobacteria groups, the MAGs obtained for subdivisions 2 (DA052) and 13 (KF-JG30-18) allowed us to infer valuable information on the physiology and metabolic potential of these two Acidobacteria subdivisions. As of November 2016, 27 genome sequences were available for Acidobacteria, with most of them being affiliated with subdivision 1 Acidobacteria. This number has recently more than doubled by deep metagenomic sequencing of an aquifer system (Anantharaman et al., 2016 ). However, to the best of our knowledge, no genomes of Acidobacteria subdivisions 2 and 13 have yet been reported, highlighting the novelty of the draft genomes reconstructed for DA052 (RH1 MAG20) and KF-JG30-18 (RH2 MAG 17b). The genome size of DA052 is comparable to those of subdivision 1 Acidobacteria such as Terriglobus roseus (4.9 Mb, 60% GC) (Rawat et al., 2014 ). The KF-JG30-18 genome is comparably small, being in the range of the only subdivision 23 genome ( Thermoanaerobaculum aquaticum 2.7 Mb)(Stamps et al., 2014 ). Apparently, members of DA052 and KF-JG30-18 are able to utilize polysaccharides such as cellulose and xylan (Figure 4 ). Comparative genomics suggests that the ability of polysaccharide breakdown is widely distributed among the Acidobacteria (Kielak et al., 2016 ), but to date experimental evidence for polysaccharide utilization was obtained only for members of subdivisions 1, 3, and 4 (Dedysh et al., 2012 ; Pascual et al., 2015 ; Garcia-Fraile et al., 2016 ; Jiang et al., 2016 ; Lladó et al., 2016 ). Xylan degradation appears to be a rather common metabolic trait of the Acidobacteria, while cellulose breakdown has been shown only for Telmatobacter bradus (Pankratov et al., 2008 ). Plant cell wall constituents such as cellulose or xylan are commonly identified in soft coal in varying quantities dependent on the degree of coalification (del Río et al., 1994 ; Rumpel et al., 1998 ). The DA052 draft genome RH1 MAG20 contains all the genes required for formaldehyde fixation via the cyclic ribulose monophosphate pathway (Figure 4 ). Thus, members of DA052 may be able to utilize C1 compounds as carbon source. These are present in coal as methyl- and methoxyl-groups or as formate (Stafford, 1988 ; Stout et al., 1988 ; Hatcher and Clifford, 1997 ). A survey of the available Acidobacteria genomes revealed key genes of the ribulose monophosphate pathway (3-hexulose-6-phosphate synthase and 6-phospho-3-hexuloisomerase) in Edaphobacter aggregans and Terriglobus roseus , but both organisms have not yet been shown to utilize C1 compounds (Eichorst et al., 2007 ; Koch et al., 2008 ). In the DA052 representative, we also identified the genetic potential to produce lignin-degrading dye-decolorizing peroxidases. This family of enzymes is of increasing interest as it represents the bacterial counterpart of lignin-cleaving peroxidases and laccases known from fungi (de Gonzalo et al., 2016 ). The ability to utilize rather inert, lignin-derived carbon sources would give DA052 a selective advantage as lignin-derived carbon is assumed to be abundantly present in the studied slags. Although most aluminum in the Red Hill slag deposits is assumed to be immobilized by humic and fulvic acids, some bioavailability cannot be excluded. Both draft genomes, DA052 and KF-JG30-18, contain genes encoding high-affinity phosphate uptake systems, while the potential to form and release polyphosphate was detected specifically for DA052. The intracellular cleavage of polyphosphate and release of phosphate moieties was described for bacteria and archaea (Remonsellez et al., 2006 ; Rao et al., 2009 ; Navarro et al., 2013 ) as a measure to inactivate toxic metal cations by precipitation. Since inorganic phosphate has manifold roles in cellular metabolism, the sole presence of these genes cannot be exclusively attributed to metal resistance. The draft genomes of both DA052 and KF-JG30-18, however, harbor an unexpectedly high number of genes encoding Czc efflux pumps (Figure 4 ). These mediate resistance to cobalt, zinc, and cadmium (Nies, 1995 ; Chen et al., 2015 ). Using InterPro and PFAM, a closer inspection of the encoded proteins revealed that 6 and 5 sequences for, respectively, KF-JG30-18 and DA052 are closely related to acriflavine resistance proteins, which, like Czc efflux pumps, belong to the resistance/nodulation/division superfamily of solute transporters (Table 1 ). Acriflavine resistance proteins are multi-drug efflux systems with a tremendously broad substrate range, including different classes of antibiotics, detergents and small organic molecules (Blair and Piddock, 2009 ; Pos, 2009 ). Acriflavine was first extracted from smoldered coal tar by precipitation with diluted sulfuric acid, a procedure that is reminiscent of the early industrial mineral leaching from soft coal (Supplementary Figure 1 ). Paul Ehrlich found acriflavine to be bacteriocidal (Wainwright, 2001 ; Kumar et al., 2012 ) and intercalation into DNA was identified as its mode of action (Lerman, 1961 ). It has been shown for iron-oxidizing bacteria that the number of acriflavine resistance genes can have a strong effect on their fitness when being exposed to metals, metalloids, or hazardous organic compounds (Emerson et al., 2013 ). It is thus tempting to hypothesize that the presence of such substances in the leached slags selects for acriflavine-tolerant bacteria. In consequence, the presence of multiple genes encoding acriflavine resistance proteins could thus represent a competitive advantage, favoring the colonization of studied slags by DA052 and KF-JG30-18. In summary, our analyses revealed that the microbiology of the studied slags greatly differs from commonly studied AMD and mine tailing environments. The unusual geochemistry, including the proposed mitigation of mineral oxidation and subsequent metal release, increases the oligotrophic nature of the Red Hill slag deposits. Members of the elusive Acidobacteria subdivisions 2 (DA052) and 13 (KF-JG30-18) showed a dominant occurrence not observed in any other previously studied environment. Metagenome-assembled genomes allowed us to identify broad carbon utilization capabilities and, more intriguingly, pronounced metal and xenobiotic detoxification mechanisms. These may explain the dominant occurrence of DA052 and KF-JG30-18. Our findings call for further research into the microbiology of the Red Hill slag deposits, in particular for activity-centered approaches such as metatranscriptomics and -proteomics that allow to link both genome coding potential and actual metabolic activity of identified groups in this unique, early-industrial, man-made habitat."
} | 4,625 |
32010113 | PMC6978639 | pmc | 3,377 | {
"abstract": "Fermentation of gases provides a promising opportunity for the production of biochemicals from renewable resources, which has resulted in a growing interest in acetogenic bacteria. Thermophilic organisms provide potential advantages for the fermentation of, e.g., syngas into for example volatile compounds, and the thermophiles Moorella thermoacetica and Moorella thermoautotrophica have become model organisms of acetogenic metabolism. The justification for the recognition of the closely related species M. thermoautotrophica has, however, recently been disputed. In order to expand knowledge on the genus, we have here genome sequenced a total of 12 different M. thermoacetica and M. thermoautotrophica strains. From the sequencing results, it became clear that M. thermoautotrophica DSM 1974 T consists of at least two different strains. Two different strains were isolated in Lyngby and Ulm from a DSM 1974 T culture obtained from the DSMZ (Leibniz-Institut DSMZ-Deutsche Sammlung von Mikroorganismen und Zellkulturen GmbH, Brunswick, Germany). Phylogenetic analysis revealed a close relationship between all the sequenced genomes, suggesting that the two strains detected in the type strain of the species M. thermoautotrophica could not be distinguished at the species level from M. thermoacetica . Despite genetic similarities, differences in genomic features were observed between the strains. Differences in compounds that can serve as carbon and energy sources for selected strains were also identified. On the contrary, strain DSM 21394, currently still named M. thermoacetica , obviously represents a new Moorella species. In addition, based on genome analysis and comparison M. glycerini NMP, M. stamsii DSM 26217 T , and M. perchloratireducens An10 cannot be distinguished at the species level. Thus, this comprehensive analysis provides a significantly increased knowledge of the genetic diversity of Moorella strains.",
"introduction": "Introduction Interest from the research community and industry in acetogenic bacteria has grown within recent years due to their potential to produce valuable compounds from syngas ( Latif et al., 2014 ). Thermophilic acetogens are of significance, since their use would reduce gas cooling requirements, allow for cost-efficient recovery of products with relatively low boiling point ( Henstra et al., 2007 ; Redl et al., 2017 ), and decrease the risk of contamination. A well-studied syngas-fermenting thermophile is Moorella thermoacetica . The species was isolated from horse feces in 1942 and named Clostridium thermoaceticum ( Fontaine et al., 1942 ). The taxonomy of the genus Clostridium was restructured in 1994 and C. thermoaceticum was transferred to a new genus Moorella as M. thermoacetica ( Collins et al., 1994 ). Several strains originating from the cultures isolated by Fontaine et al. (1942) are deposited in strain collections. The type strain DSM 521 T and the strain ATCC 39073 have primarily served to elucidate the primary metabolism of M. thermoacetica (synonym C. thermoaceticum ): they were used in experiments to study carbohydrate utilization ( Andreesen et al., 1973 ), the acetate kinase ( Schaupp and Ljungdahl, 1974 ), cytochromes and menaquinones ( Gottwald et al., 1975 ), the formate dehydrogenase ( Ljungdahl and Andreesen, 1977 ), and the utilization of CO ( Diekert and Thauer, 1978 ). The genome of the non-type strain ATCC 39073 was sequenced in 2008 ( Pierce et al., 2008 ) and the genome sequence of the type strain DSM 521 T followed in 2015 ( Poehlein et al., 2015 ). A spore sample of the original M. thermoacetica strain isolated in 1942 was deposited by Kerby and Zeikus (1983) as a second representative of the type strain (DSM 2955 T ) in the DSMZ (Leibniz-Institut DSMZ-Deutsche Sammlung von Mikroorganismen und Zellkulturen GmbH, Brunswick, Germany). It was shown to utilize H 2 /CO 2 as substrate and was also adapted to growth on CO ( Kerby and Zeikus, 1983 ). The ability to utilize gaseous substrates was not shown for ATCC 39073 and DSM 521 T until 1990 ( Daniel et al., 1990 ). Another M. thermoacetica strain (Y72) with higher transformation efficiency than ATCC 39073 was described and its draft genome published in 2014 ( Tsukahara et al., 2014 ). Wiegel et al. (1981) described the isolation of strains closely related to the already known C. thermoaceticum ( M. thermoacetica ) strains. The novel strains were shown to grow chemolithotrophically on H 2 /CO 2 and chemoheterotrophically on several carbon sources. At that time, the aforementioned strains of C. thermoaceticum ( M. thermoacetica ) were not known to utilize H 2 /CO 2 and CO. Furthermore, Wiegel et al. (1981) described differences in the cell shape in comparison to M. thermoacetica. In addition to C. aceticum and Acetobacterium woodii , this new strain was the third species known to grow autotrophically using H 2 and CO 2 while producing acetate. Therefore, a new species was proposed and a strain isolated from a Yellowstone hot spring (strain JW 701/3) was deposited as Clostridium thermoautotrophicum DSM 1974 T ( Wiegel et al., 1981 ). C. thermoautotrophicum was later re-classified as Moorella thermoautotrophica in the extensive study of Collins et al. (1994) . In addition to M. thermoautotrophica DSM 1974 T , which is the designated type strain, a second M. thermoautotrophica strain, DSM 7417, is available. This strain (DSM 7417) was first described in Rijssel et al. (1992) when it appeared as a contamination in a continuous culture. The authors based their decision to place the newly described strain in the species of M. thermoautotrophica instead of M. thermoacetica mainly on observations regarding the cell shape ( Rijssel et al., 1992 ). Recently, Kimura et al. (2016) requested an opinion regarding the taxonomic status of M. thermoautotrophica . Based on DNA–DNA hybridization experiments and 16S rRNA gene sequence analysis, Kimura et al. (2016) concluded that the species M. thermoautotrophica should be reclassified as M. thermoacetica . Over time, phenotypic differences between M. thermoacetica and M. thermoautotrophica were described, but often with partly conflicting results ( Cato et al., 1986 ; Das et al., 1989 ; Yamamoto et al., 1998 ; Carlier and Bedora-Faure, 2006 ). Here, we report that M. thermoautotrophica DSM 1974 T is a mixed culture of at least two strains, which we isolated. We sequenced the genome of those two strains as well as the genome of DSM 7417 and nine other M. thermoacetica strains, thereby considerably adding to the genomic information of this group of bacteria. We compared the genomes of the strains with the genome of the M. thermoacetica strain ATCC 39073 ( Pierce et al., 2008 ) and the type strains DSM 2955 T ( Bengelsdorf et al., 2015 ) and DSM 521 T ( Poehlein et al., 2015 ). In addition, we performed genome comparison with all other genomes of the genus Moorella . Furthermore, differences in carbon utilization of the aforementioned strains were characterized. Based on this study, we conclude that the classification of the two strains isolated from DSM 1974 T as a separate species, M. thermoautotrophica , is not justified and that based on the data collected both strains should be reclassified as strains of the species M. thermoacetica . However, a problem arises due to the fact that the designated type strain deposited in the DSMZ, as DSM 1974 T , appears to be a mixture of two strains. The implications of these findings within the context of the rules of the International Code of Nomenclature ( Parker et al., 2019 ) together with the content of the recent Request for an Opinion of Kimura et al. (2016) are discussed.",
"discussion": "Discussion Strains of M. thermoacetica and M. thermoautotrophica have become model organisms of the acetogenic metabolism. Due to the observation of conflicting phenotypic traits that have been connected with the two different species, the scientific community has already questioned the taxonomic status of the two species M. thermoautotrophica and M. thermoacetica ( Carlier and Bedora-Faure, 2006 ; Kimura et al., 2016 ). In addition to the high similarity of the genomes’ 16S rRNA gene sequence, there are further similarities described for M. thermoacetica/thermoautotrophica strains such as a similar fatty acid and peptidoglycan profile ( Yamamoto et al., 1998 ) and presence of the same menaquinone ( Das et al., 1989 ). However, these features are generally conserved in “closely related” taxa and one would not expect significant differences between strains showing such a high degree of genetic similarity (Tindall, unpublished). Until a few years ago, only the sequence of the non-type strains M. thermoacetica ATCC 39079 and M. thermoacetica Y72 were publicly available, but many other strains, including the two type strains of the species (DSM 521 T and DSM 2955 T ), and several other strains are available at the German Collection of Microorganisms and Cell Cultures (DSMZ Brunswick), including strain DSM 1974 T . We wished to broaden knowledge of the genetic diversity of this group of organisms and therefore sequenced the genome of both strains which were derived from the DSM 1974 T culture (DSM 103132 and DSM 103284), as well as the genome of DSM 7417 and the genome of another sub-culture of ATCC 39073 (ATCC 39073-HH). In addition, the genomes of eight different M. thermoacetica strains were sequenced. Comparison of the 16S rRNA gene sequences of the strains, ATCC 39073(-HH), DSM 103132, and DSM 103284, showed a sequence similarity between the strains higher than 99.74%. We used MLSA, gene content analysis, and ANI analysis to get insights into the phylogeny of the genus Moorella . With ANIm values between 98 and 99% compared to the other M. thermoacetica strains DSM 512 T and DSM 2955 T , the strains derived from DSM 1974 T (DSM 103132 and DSM 103284) are clearly M. thermoacetica isolates. Through genome sequencing of different M. thermoacetica and M. thermoautotrophica strains, it was evident that M. thermoautotrophica DSM 1974 T consists of at least two different strains, which are both very closely related to each other and to M. thermoacetica . Since phylogenetic analysis showed that all M. thermoacetica/thermoautotrophica strains described to date belong to the same species, there would appear to be no justification based on the currently available data for considering M. thermoautotrophica to be a separate species. Consequently, the strains DSM 103132 and DSM 103284 (both derived from DSM 1974 T , the designated type strain of M. thermoautotrophica ) must be designated as M. thermoacetica . Based on the current study, the observed phenotypic differences are likely to be due to strain variations within one species, as already indicated by Wiegel et al. (1981) and Cato et al. (1986) . Furthermore, observed differences in carbon source utilization cannot serve as a suitable measure to distinguish species, since the substrate acceptance may be dependent on cultivation conditions. However, the picture is complicated by the fact that DSM 1974 T , the strain which led to the proposal of the new species C. thermoautotrophicum ( Wiegel et al., 1981 ) and was later transferred to the genus Moorella as M. thermoautotrophica ( Collins et al., 1994 ) was consistently shown by genome sequencing to consist of two different strains. The isolation of two different strains that have subsequently been deposited as DSM 103132 and DSM 103284 confirms these observations. However, taking the original data of Wiegel et al. (1981) and comparing them with the data collected in this study for DSM 103132 and DSM 103284 does not show a large number of significant differences in the physiology of the strains. Based on the current data and taking into consideration the methods originally used by Wiegel et al. (1981) it is not possible to determine whether the original strain of Wiegel, JW 701/3, was a mixture of two different strains of the same species, whether the original strain was a pure culture, but a mixed culture was submitted for deposit (that methods used at the time would not have detected), or whether a second strain was introduced into the culture subsequent to accession to the DSMZ. Cross-contamination of strains is one possible explanation: the spores of Moorella species are highly heat-resistant and are not sufficiently inactivated by a standard autoclaving at 121°C ( Fontaine et al., 1942 ). Byrer et al. (2000) for example described the strains JW/DB-2 and JW/DB-4 (ATCC number BAA-48) that show unusually heat-resistant spores. However, given the resolution of methods used at the time, one also cannot exclude with certainty that the original culture did not consist of more than one strain. One interesting aspect is that Wiegel et al. (1981) report that DNA–DNA hybridization supported the recognition of strains JW 701/3 and strain KIVU as members of the same species, but distinct from C. thermoaceticum ( M. thermoacetica ). Kimura et al. (2016) have previously reported a similar problem with the designated type strain of M. thermoautotrophica. Formulated as a Request for an Opinion, this limits any action that can be taken to a formal ruling by that body. However, their work concentrates largely on the interpretation of 16S rRNA gene sequences that appear to have been obtained by both cloning and the isolation of strains from the culture supplied. Representative partial sequences of the 16S rRNA genes of the seven groups obtained by cloning and sequencing of the isolates have been deposited as LC133084–LC133087 and designated in the publication as representing OUT-1 to OUT-4 in that order, respectively. Kimura et al. (2016) concentrate on a single 16S rRNA gene sequence deposited as L09168 (from DSM 1974) and do not mention that additional sequences are available, X58353 and X77849. X58353 (strain JW 701/3; 1155 bases, but with numerous Ns) was deposited in 1990 from the University of Kiel and will not be considered further. X77849 was deposited in 1994 from the University of Reading in co-operation with Dr. Hippe (DSMZ curator of the strain at the time) and is derived from DSM 1974 and presumably directly from stocks held in the DSMZ. L09168 was deposited in 1993 from The University of Queensland. A direct alignment of the two sequences L09168 and X77849 indicates that, ignoring a small number of Ns in X77849, the two are not identical making it difficult to conclude whether either of the two can be considered to be a 100% accurate reflection of the original gene sequences from the same strain. Similarly, a comparison with the 16S rRNA sequences from Kimura et al. (2016) also indicate that neither of the two sequences (X77849 and L09168) ( Supplementary Figure S2 ) show 100% similarity with those obtained by Kimura et al. (2016) . It should also be remembered that the sequences X77849 and L09168 are only one part of the evidence that were not obtained directly when the type strain was originally described and “verification” of X77849 vs. L09168 does not allow one to conclude that one sequence is “correct” and the other in error. If one were to extend the reasoning of Kimura et al. (2016) to other similar cases one would conclude that given the differences between the 16S rRNA gene sequence obtained by direct amplification and that extracted from the genome of M. stamsii that the type strain does not exist. An even more dramatic example is the case of Alterococcus agarolyticus ( Shieh and Jean, 1998 ) that started its taxonomic career as an atypical member of the Enterobacteriaceae ( Shieh and Jean, 1998 ) under the 16S rRNA gene sequence AF075271.1 (deposited 19 th June 1998) that was substituted for by AF075271.2 (deposited 21 st August 2002) and is widely accepted as a member of the Verrucomicrobia . Under these circumstances, the nomenclatural type currently available certainly does not correspond to the 16S rRNA gene sequence originally deposited as AF075271.1 and one would have to conclude that the type strain no longer exists. However, put in context other data in the original publication clearly indicates that Alterococcus agarolyticus was an atypical member of the Enterobacteriaceae and that the original 16S rRNA gene sequence AF075271.1 is in error and should have been verified. In the case of M. thermoautotrophica , comparison with the 16S rRNA gene sequence deposited as X77849 and L09168 also needs to be treated with caution if the original source culture (DSM 1974 T ) was not a pure culture or where the quality/accuracy of gene sequencing technologies may have changed over the decades. No attempt was made to compare the physiological/biochemical properties of the strains studied by Kimura et al. (2016) with the original work of Wiegel et al. (1981) and relies solely on one older gene sequence (L09168) that is not corroborated by another sequence (X77849) obtained at about the same time from the same source culture, DSM 1974 T . Examining the 16S rRNA sequences deposited by Kimura et al. (2016) (LC133084-LC133087) against L09168, X77849 and those extracted from the genomes derived from subcultures of DSM 1974 and ATCC 33924 (including re-deposits as DSM 103132 and DSM 103284), i.e., CP017019.1 (positions 154745–156300 and 147549–149104), CP017237.1 (positions 144877–146432), and VCDX01000030.1 (positions 1667–112) indicates that toward the end of the single primer amplified partial sequences LC133085 and LC133086 gaps are present that are not otherwise present in any of the other sequences in a region that could be considered to be conserved ( Supplementary Figure S2 ). These gaps have, therefore, not been taken into consideration in the analysis here. Kimura et al. (2016) do not provide alignments of sequences in support of their work and make it impossible to determine why they consider “none of the sequences were similar to M. thermoautotrophica DSM 1974T (L09168),” when in fact they show only minimal differences in the alignments presented here. Although alignments are critical steps in the evaluation of sequence-based data (both nucleotide and amino acid based) they are rarely given, contrary to recommendations ( Tindall et al., 2010 ), making the direct verification of the resulting interpretation via this critical step impossible and are therefore included in Supplementary Figures S1 , S2 . The sequence LC133087 appears to belong to a strain having the most similar 16S rRNA sequence to M. humiferrea strain 64_FGQ T (GQ872425) and will not be considered further. In the alignment shown, CP017019.1 (positions 154745–156300), CP017019.1 (positions 147549–149104), VCDX01000030.1 (positions 1667–112), and LC133086.1 have a “T” at position 280 (alignment numbering, Supplementary Figure S2 ) while CP017237.1 (positions 144877–146432), LC133084.1, and LC133085.1 have a “C” at the same position. LC133086.1 differs from CP017019.1 (positions 154745–156300), CP017019.1 (positions 147549–149104), and VCDX01000030.1 (positions 1667–112) in having a “T” position 435 rather than a “C” that is present in all other sequences ( Supplementary Figure S2 ). LC133084.1 appears to be identical in the aligned bases to CP017237.1 (positions 144877–146432), but LC133085.1 has an “A” at position 745 rather than a “G” that is present in all other sequences ( Supplementary Figure S2 ). Based on these observations, the only organism recovered in this study and that of Kimura et al. (2016) is that represented by LC133084.1 and CP017237.1 (DSM 103284). While this demonstrates the care that has to be taken in evaluating the interpretation of the data used by Kimura et al. (2016) , the major problem that arises centers on the fact that the strains isolated by Kimura et al. (2016) have not been deposited in a culture collection and comparison with the original physiological and biochemical data published by Wiegel et al. (1981) cannot be made. Based on an evaluation of the 16S rRNA sequences determined previously and those determined here it is not possible to conclude that the type strain no longer exists, since it was deposited as DSM 1974 and ATCC 33924 and the 16S rRNA sequences deposited as X77849 and L09168 do not appear to be fully accurate. The Request for an Opinion of Kimura et al. (2016) also misinterprets the wording of Rule 18c and draws incorrect conclusions. Tindall (2016) provided a detailed discussion of the incorrect interpretation of Rule 18c that was also applied by Kimura et al. (2016) . Based on the evidence presented by Kimura et al. (2016) and that obtained in this work one cannot conclude that the nomenclatural type no longer exists, but rather there may be an issue with the purity of the culture deposited/currently available. The current study covers the physiological/biochemical properties of strains isolated from DSM 1974 T and expands on the genomic characterization of the strains studied. While it is clear that DSM 103132 and DSM 103284 (both derived from DSM 1974 T , the designated type strain of M. thermoautotrophica ) are more appropriately considered to be members of the species M. thermoacetica , there is a formal nomenclatural issue that also needs to be addressed that requires reference to be made to the International Code of Nomenclature of Prokaryotes ( Parker et al., 2019 ). Typically, the nomenclatural type of a species as defined in Rule 18a is an axenic culture, but there are instances where one component part of a syntrophic co-culture has been named and the co-culture accepted as the nomenclatural type (type strain). However, when mixed cultures or consortia are considered (see Rule 31a and 31b) and these are treated as a “single” biological entity, the names associated with them are not validly published and could be applied to M. thermoautotrophica . In the case of DSM 1974 T and ATCC 33924 T , although the strains currently in circulation appear to be a mixed culture, there is no unambiguous evidence that the parent culture, strain JW 701/3, was also a mixed culture. In contrast to the study of Kimura et al. (2016) , it has been possible to study in greater detail pure cultures of strains isolated from DSM 1974 T (that is the parent deposit for all other culture collection strains) and subsequently deposited as DSM 103132 and DSM 103284. In both cases, the strains appear to be members of the species M. thermoacetica . One possible solution would be to designate one of them as a neotype, although based on the physiological and biochemical data presented here neither of the two strains (DSM 103132 or DSM 103284) can unambiguously be shown to be more similar in its properties than the other to the data originally published by Wiegel et al. (1981) . Irrespective of which course of action is taken, it is clear that the culture of DSM 1974 T made available to the current authors contains strains that should be classified in the species M. thermoacetica leading to the logical conclusion that DSM 103132 and DSM 103284 should be assigned to that species. This nomenclatural conclusion is inescapable, irrespective of whether one follows the arguments of Kimura et al. (2016) , where the name M. thermoautotrophica would eventually be rejected, declared to not have been validly published, or whether one considers the names M. thermoacetica ( Fontaine et al., 1942 ; Collins et al., 1994 ) and M. thermoautotrophica ( Wiegel et al., 1981 ; Collins et al., 1994 ) to be heterotypic synonyms. In the latter case, priority is governed by Rule 23a, 38 and 42 where the dates of valid publication of the epithets are taken into consideration, i.e., thermoacetica \n Fontaine et al. (1942) has priority over thermoautotrophica \n Wiegel et al. (1981) . This also leads to the use of the name M. thermoacetica ( Fontaine et al., 1942 ; Collins et al., 1994 ) and recognition of M. thermoautotrophica ( Wiegel et al., 1981 ; Collins et al., 1994 ) as the later heterotypic synonym when their respective nomenclatural types are considered to members of the same taxon. The current authors favor the latter course of action, but the Judicial Commission may also decide otherwise. Also, M. thermoautotrophica DSM 7417 should be reclassified as M. thermoacetica as well. In addition to resolving the M. thermoacetica/thermoautotrophica problem, this comprehensive analysis of the genus Moorella by the study of a significant number of novel genome sequences and knowledge of phenotypic differences led to two other important conclusions. First, strain DSM 21394, currently still named M. thermoacetica , clearly does not belong to this species. Reclassification and renaming as a new species are required. Secondly, M. glycerini NMP, M. stamsii DSM 26217 T , and M. perchloratireducens cannot be distinguished at species level. Furthermore, M. glycerini NMP has been wrongly assigned as M. glycerini as this strain shows an ANIm value of 94% similarity compared to the type strain DSM 11254 T and is clearly a different species despite the high 16S rRNA gene sequence pairwise similarity of 99.7%. Based on the data presented here, M. glycerini NMP, M. stamsii DSM 26217 T , and M. perchloratireducens are all members of the same species. Although reclassification of these three strains may be required, caution needs to be exercised when one considers differences between the data reported here and that previously reported in the literature ( Slobodkin et al., 1997 ; Balk et al., 2008 ; Alves et al., 2013 ), especially with regards to the 16S rRNA gene sequences and the genomic similarity inferred from DNA–DNA hybridization experiments vs. in silico comparisons."
} | 6,480 |
25455858 | null | s2 | 3,378 | {
"abstract": "Widespread quorum-sensing (QS) enables bacteria to communicate and plays a critical role in controlling bacterial virulence. However, effects of promiscuous QS crosstalk and its implications for gene regulation and cell decision-making remain largely unknown. Here we systematically studied the crosstalk between LuxR/I and LasR/I systems and found that QS crosstalk can be dissected into signal crosstalk and promoter crosstalk. Further investigations using synthetic positive feedback circuits revealed that signal crosstalk significantly decreases a circuit's bistable potential while maintaining unimodality. Promoter crosstalk, however, reproducibly generates complex trimodal responses resulting from noise-induced state transitions and host-circuit interactions. A mathematical model that integrates the circuit's nonlinearity, stochasticity, and host-circuit interactions was developed, and its predictions of conditions for trimodality were verified experimentally. Combining synthetic biology and mathematical modeling, this work sheds light on the complex behaviors emerging from QS crosstalk, which could be exploited for therapeutics and biotechnology."
} | 291 |
20024685 | PMC2855437 | pmc | 3,379 | {
"abstract": "Microbial fuel cell (MFC) systems employ the catalytic activity of microbes to produce electricity from the oxidation of organic, and in some cases inorganic, substrates. MFC systems have been primarily explored for their use in bioremediation and bioenergy applications; however, these systems also offer a unique strategy for the cultivation of synergistic microbial communities. It has been hypothesized that the mechanism(s) of microbial electron transfer that enable electricity production in MFCs may be a cooperative strategy within mixed microbial consortia that is associated with, or is an alternative to, interspecies hydrogen (H 2 ) transfer. Microbial fermentation processes and methanogenesis in ruminant animals are highly dependent on the consumption and production of H 2 in the rumen. Given the crucial role that H 2 plays in ruminant digestion, it is desirable to understand the microbial relationships that control H 2 partial pressures within the rumen; MFCs may serve as unique tools for studying this complex ecological system. Further, MFC systems offer a novel approach to studying biofilms that form under different redox conditions and may be applied to achieve a greater understanding of how microbial biofilms impact animal health. Here, we present a brief summary of the efforts made towards understanding rumen microbial ecology, microbial biofilms related to animal health, and how MFCs may be further applied in ruminant research.",
"conclusion": "Conclusions Ruminant production systems are faced with a variety of challenges. Chief among them are the need to: (1) improve the efficiency by which grains and forages are converted to food and fiber to meet increasing global demand; (2) complete the conversion of natural resources into consumable products in a sustainable manner with limited environmental impact; and (3) achieve these goals while supporting and improving animal health and well-being. Microbial communities play an integral role in all of these challenges such that the health, efficiency, and environmental impact of a ruminant cannot be distinguished from that of its inherent microbial community. For these reasons, it is essential to develop methods for characterizing complex microbial communities and their associated dynamics. Research to date has largely focused on a narrow proportion of ruminant microbes, in part due to limitations of culture-based methods in microbiology. These limitations have further contributed to an inability to fully characterize microbial diversity and how it may change in time or in response to nutrient composition and concentration. The capacity to examine linkages between ruminants and microbial communities in ecological contexts will be necessary to derive the next evolution of interventions that may enhance production and mitigate environmental impacts. Developing tools for improving ruminant production systems will have a positive impact on global society. The direct relationship between increased nutrient utilization efficiency and decreased enteric CH 4 production creates the opportunity to define solutions for this dual purpose, which would have significant benefit to mitigating global warming and increasing global food supplies. For example, the US Environmental Protection Agency estimated that the enteric CH 4 resulting from livestock production accounted for 32% of the global, non-CO 2 , agricultural emissions in the year 2000; and this level is expected to increase by more than 30% by the year 2020. Further, CH 4 is approximately 21 times more powerful at warming the atmosphere than CO 2 over a 100-year period. Fortunately, CH 4 is also known to only have a 12-year chemical lifetime in the atmosphere (relative to CO 2 , which has a 100-year lifetime). The immediate decrease of anthropogenic emissions of CH 4 has therefore become a feasible near-term target for the mitigation of global warming [ 128 ]. Decreasing enteric CH 4 emissions during ruminant production would have the added benefit of increasing feed efficiency, therefore, requiring fewer animals to produce the same protein resource. The Food and Agriculture Organization of the United Nations (FOA) has reported that diets in developing countries are changing as incomes rise, contributing to an increased consumption of meat and dairy products. Between 1964–1966 and 1997–1999, per capita meat consumption in developing countries rose by 150%, and by 2030, per capita consumption of livestock products could rise by another 44% [ 129 ]. The FOA further speculates that demand for livestock products will grow faster than production in developing countries, creating a growing trade deficit. Meat products are expected to rise steeply, from 1.2 million tons a year (1997–1999) to 5.9 million tons in 2030, and it is reported that the increasing share of livestock production will likely come from industrial enterprises. In recent years, production from this sector has grown twice as fast as that from more traditional mixed farming systems and more than six times faster than from grazing systems [ 129 ]. Given the predicted increase in global industrial livestock production, it will be essential to develop interventions for preventing disease among the increasing ruminant population. As has been discuss previously, microbial biofilm-related infections such as BRD and bloat have an enormous impact on ruminant health and production economics. The development of new interventions to prevent and treat such diseases is yet another benefit that can be realized from understanding microbial ecology as it relates to ruminants. Recent advances in molecular and microbiological platforms are beginning to facilitate alternative research approaches that contribute to more comprehensive understanding of the phylogenetic and functional diversity in microbial communities and the consequences of perturbations within these systems. As has been discussed, MFCs and related technologies are an example of an emerging platform that contributes to a greater understanding of microbial ecology and complex microbial systems. Several examples of how these systems may apply to ruminant research have been proposed within this review. MFCs have been widely utilized to isolate microbes that have unique energy metabolisms and thrive in extreme environments; therefore, it is easy to consider that these systems may be additionally exploited to study the complex microbial relationships that exist in the rumen. For example, Archaeal populations have been among the microbial constituents targeted in MFC research and are more thoroughly addressed here with respect to environmental impacts and nutrient inefficiency in production attributed to carbon loss through enteric CH 4 production. MFC or BES systems could be utilized to explore the Archaeal populations that exist in the rumen, and perhaps even be designed as in situ devises to specifically enrich for microbial consortia that will increase feed efficiency and decrease methanogenesis. However, one of the more immediate benefits that MFCs could provide is the ability to cultivate and study biofilms under defined redox environments that may be set to mimic the rumen or conditions that may arise during an infection. The applications of MFCs and the ability to cultivate targeted microbial populations that are described here are by no means comprehensive and cannot be considered feasible without incorporating advanced tools for characterizing the molecular diversity of mixed microbial communities. The coupling of metagenomic and metatranscriptomic techniques with new cultivation strategies and research methodologies has been described elsewhere, and a full discussion is outside the scope of this manuscript [ 52 , 130 , 131 ]. However, it is exciting to consider how MFCs may complement the growing arsenal of advanced tools that contribute to a greater understanding of the microbial world. The research opportunities provided by MFC technology extend beyond the generation of electricity and represent a unique opportunity to study and control the impact of microbial ecology and physiology on complex systems such as those found in ruminant biology.",
"introduction": "Introduction Contemporary livestock production is distinctly linked to a variety of microbial processes that directly impact: (1) the efficiency by which ruminants convert available feedstuffs into energy for maintenance and growth; (2) the health of ruminants within production systems; and (3) the environmental consequences of ruminant production. Microbial communities in the gastrointestinal tract influence the efficiency of nutrient utilization through microbial digestion of fiber, starch, and protein in the rumen and the persistence and shedding of pathogenic bacteria and food safety pathogens such as Salmonella enterica and Escherichia coli O157:H7 in the hindgut. Ecology of viral and bacterial pathogens in the respiratory tract influences the incidence of respiratory disease, the most economically significant disease of ruminants [ 1 ]. Finally, the impacts of ruminant production on the environment are largely dictated by complex microbial communities related to enteric methane (CH 4 ) production, emissions of hydrogen sulfide (H 2 S), and ammonia (NH 3 ) from intensive production environments and dispersion of relevant human and ruminant pathogens in the production ecosystem. A variety of therapeutic and preventive measures are available to address specific bacteria and viruses that pose a threat to the well-being of the animal or the safety of food derived for human consumption. However, considering the role of these pathogens independent of their environment, and/or their synergistic interactions within a respective microbial community, may limit the success of any applied interventions. Knowledge regarding the specific ecological niches of constituents within these complex microbial communities and microbial interactions associated with shifts in microbial diversity or the onset of infectious and metabolic disease is largely limited to those organisms that can be isolated in monoculture using available microbiological methods. Estimates suggest that less than 1% of all microbial species have been identified in culture and less than 10% of all rumen microbes have been identified using routine methods. Alternative technological platforms must be employed to illuminate more subtle shifts in microbial populations relevant to ruminant production and interactions therein. Microbial fuel cells (MFCs) are an additional tool that can facilitate study of the physiological roles of microbes in complex ecosystems [ 2 ]. To date, there has been limited application of MFCs in ruminant health and production research [ 3 ]. In this review, we present an overview of MFCs and identify several potential applications of this technology to advancing knowledge of ruminant microbial ecology particularly as it relates to animal health, production, and environmental impact. Microbial Fuel Cells Microbial fuel cells are a developing technology that has been utilized for studying microbial physiology in terms of electron (and proton) transfer [ 4 – 6 ]. They provide a medium for the study of complex microbial systems like those encountered in ruminant production, as well as the opportunity for developing novel approaches to altering the dynamics within those systems. When combined with molecular approaches including genomics and metagenomics, MFCs have the potential to profoundly expand the existing body of knowledge regarding phylogenetic and functional diversity in complex microbial communities. Microbial fuel cell systems have been explored for identifying organisms that have unique metabolic functions within mixed consortia sampled from different environments [ 7 – 10 ] and to divert energy away from methanogenesis in favor of other forms of anaerobic respiration [ 11 – 13 ]. Microbial fuel cells also offer another cultivation strategy that enables the simultaneous exploration of biofilm and planktonic populations [ 2 , 14 , 15 ]. Biofilms are formed by individual bacterial species and/or consortia of species that lead to densely packed microbial populations densely contained within a protein and polysaccharide matrix secreted by its bacterial constituents [ 16 – 19 ]. As such, biofilms represent one of the most complex and dynamic microbial architectures. The ability to study biofilms in concert with planktonic communities is a particularly intriguing advantage when studying rumen microbial ecology, given that mixed populations of microorganisms may have varied community structures throughout the rumen and at different times during digestion [ 19 – 22 ]. Biofilms form naturally, or artificially, on MFC components [ 23 ]. Microbial fuel cells exploit the energy metabolism of microbes that electrically interact with the conductive surfaces in the system called electrodes (Fig. 1 ). The electrical interaction is facilitated by direct contact with the electrode surface in the form of an electrochemically active biofilm or may also occur by way of extracellular chemical electron shuttles (or mediators) that are reduced by cells in the medium and re-oxidized at the electrode surface. Microbes within a biofilm or planktonic culture will enzymatically extract electrons from organic components, or in some cases H 2 [ 24 ] and/or H 2 S [ 25 ], in the surrounding media and transfer them to the electrode, which serves as an electron acceptor for biological respiration and/or maintenance. Completion of the MFC reaction takes place in a physically separate but electronically and ionically linked compartment where different bacterial biofilms use the cathode electrode as a source for energy during the reduction of oxidants such as nitrate, sulfate, fumarate, or oxygen [ 26 – 30 ].\n Figure 1 Microbial fuel cell schematic for wastewater management operating with microbes as catalysts for fuel oxidation at the anode electrode and oxidant reduction at the cathode electrode. If sludge is used as the fuel and oxygen as the oxidant, then the net reaction, without nitrification, is: C 18 H 19 O 9 N + H + → 8H 2 O + 18CO 2 + NH 4 + [ 132 ] \n Microbial fuel cells facilitate a redox environment that can be precisely controlled by electron flow and may serve as ideal tools for cultivating microorganisms as biofilms and/or active planktonic cultures. The redox potentials recorded within an environment correspond to the thermodynamic parameters that govern specific chemical and biological reactions [ 31 ]. A schematic representation of redox potentials and microbial processes is shown in Fig. 2 . Microbial energy metabolism is impacted by redox potential because growth is limited by the amount of energy that can be gained through the coupling of oxidation and reduction reactions [ 32 ]. The greater difference between the oxidation and reduction potentials, the more energy an organism can gain to facilitate growth and/or maintenance. However, microorganisms have adapted to nearly every redox environment corresponding to both high and low energy yields. Therefore, to gain insights relative to microbial energy metabolism in different environments, it is critical to understand the mechanisms of energy flow and transformation in reactive biofilms and suspended cultures. Current flow in a MFC can affect the redox energy available for microbial growth and begin to affect the metabolic activity of the microbial community [ 6 ]. In the case of rumen microbial ecology, it may be desirable to employ MFC systems that can facilitate carbon dioxide (CO 2 ) reduction and H 2 oxidation, conditions that are ideal for the competitive consumption of H 2 in the rumen (Fig. 2 ). In this way, MFC systems may be utilized to select for existing consortia of microorganisms that can outcompete methanogens during H 2 consumption [ 13 ]. Manipulating the redox environment of rumen microorganisms may be achieved by operating the MFC with external loads, i.e., increasing or decreasing the electron flow rates (current); or by applying a constant potential to the system such that the electron acceptor, or donor, available to the reactive community does not fluctuate. In the case of applied potentiostatic conditions, the system is no longer being operated as a dynamic MFC; however, precision control of the redox environment can be achieved. The engineered devices that can facilitate potentiostatic operations are more generally referred to as bioelectrochemical systems (BES) [ 5 , 33 – 35 ]. Bioelectrochemical systems provide highly controlled environments that enable experimental analysis of microbial energy metabolism [ 36 – 40 ]. Utilizing BES, researchers can explore enrichment techniques to cultivate desirable microbes for improving rumen efficiency and also investigate potential electrochemical interventions to treat pathogenic biofilms.\n Figure 2 Redox energy and MFC schematic [ 31 ]"
} | 4,251 |
29522747 | null | s2 | 3,380 | {
"abstract": "Spatial organization is a hallmark of all living systems. Even bacteria, the smallest forms of cellular life, display defined shapes and complex internal organization, showcasing a highly structured genome, cytoskeletal filaments, localized scaffolding structures, dynamic spatial patterns, active transport, and occasionally, intracellular organelles. Spatial order is required for faithful and efficient cellular replication and offers a powerful means for the development of unique biological properties. Here, we discuss organizational features of bacterial cells and highlight how bacteria have evolved diverse spatial mechanisms to overcome challenges cells face as self-replicating entities."
} | 174 |
29522747 | null | s2 | 3,381 | {
"abstract": "Spatial organization is a hallmark of all living systems. Even bacteria, the smallest forms of cellular life, display defined shapes and complex internal organization, showcasing a highly structured genome, cytoskeletal filaments, localized scaffolding structures, dynamic spatial patterns, active transport, and occasionally, intracellular organelles. Spatial order is required for faithful and efficient cellular replication and offers a powerful means for the development of unique biological properties. Here, we discuss organizational features of bacterial cells and highlight how bacteria have evolved diverse spatial mechanisms to overcome challenges cells face as self-replicating entities."
} | 174 |
27801908 | PMC5270565 | pmc | 3,382 | {
"abstract": "The hydrothermal vent mussel Bathymodiolus azoricus lives in an intimate\nsymbiosis with two types of chemosynthetic Gammaproteobacteria in its gills: a\nsulfur oxidizer and a methane oxidizer. Despite numerous investigations over the\nlast decades, the degree of interdependence between the three symbiotic\npartners, their individual metabolic contributions, as well as the mechanism of\ncarbon transfer from the symbionts to the host are poorly understood. We used a\ncombination of proteomics and genomics to investigate the physiology and\nmetabolism of the individual symbiotic partners. Our study revealed that key\nmetabolic functions are most likely accomplished jointly by B. azoricus \nand its symbionts: (1) CO 2 is pre-concentrated by the host for carbon\nfixation by the sulfur-oxidizing symbiont, and (2) the host replenishes\nessential biosynthetic TCA cycle intermediates for the sulfur-oxidizing\nsymbiont. In return (3), the sulfur oxidizer may compensate for the host's\nputative deficiency in amino acid and cofactor biosynthesis. We also identified\nnumerous ‘symbiosis-specific' host proteins by comparing\nsymbiont-containing and symbiont-free host tissues and symbiont fractions. These\nproteins included a large complement of host digestive enzymes in the gill that\nare likely involved in symbiont digestion and carbon transfer from the symbionts\nto the host.",
"conclusion": "Conclusion Our proteogenomic anaylsis of the deep-sea mussel B. azoricus and its\ntwo uncultured symbionts provided detailed insights into the molecular\nmechanisms and strategies that underpin this symbiosis, which is otherwise\ndifficult to access by cultivation-based approaches. The ability of the B.\nazoricus symbionts to use an extensive range of energy sources\nincluding sulfide, thiosulfate, methane and hydrogen to fuel chemosynthesis may\nenable the host to exploit a wide range of environmental conditions.\nComplementing metabolic pathways between the host and its symbionts point to\nmetabolic interdependence between the individual partners, which may\nnevertheless enhance the metabolic efficiency of the consortium as a whole.\nParticularly, the inability of the thiotrophic symbiont to replenish its\noxaloacetate and succinate pools and the high abundance of chaperones in their\nproteome may indicate that this bacterium could be on the verge of becoming an\nobligate symbiont. The potential integration of host and symbiont metabolism at\nthe level of TCA cycle intermediates furthermore raises some intriguing\nquestions on how this metabolic interconnection evolved and if it provides a\nmechanism for the host to exert control on symbiont metabolism. Our study forms\na comprehensive basis for future investigations to examine how obligate\nassociations could evolve from facultative symbiotic partnerships.",
"introduction": "Introduction Life at deep-sea hydrothermal vents is powered by chemosynthetic bacteria, many\nof which live in symbiosis with animals. Hydrothermal vents of the Mid-Atlantic\nRidge (MAR) are home to the mytilid bivalve Bathymodiolus azoricus ,\nwhich harbours two types of gammaproteobacterial endosymbionts ( von Cosel et al. , 1999 ; Van Dover, 2000 ; Duperron et al. ,\n2006 ). Unlike other vent symbioses, such as the giant tube worm\n Riftia pachyptila and the clam Calyptogena spp., which\ndisplay extreme dependence on their chemoautotrophic endosymbionts for\nnourishment ( Childress and Fisher, 1992 ), B.\nazoricus are mixotrophs: They possess a functional gut and feeding\ngroove for filter feeding in addition to the chemosynthetic symbionts in their\ngills ( Page et al. , 1991 ; Gustafson et al. , 1998 ; von Cosel et al. , 1999 ; Riou et\nal. , 2010 ). Filter-feeding may supplement the symbiotic\ndiet of the host with particulate and organic matter from their surroundings\n( Le Pennec et al. , 1990 ) and may\nalso enable them to survive without symbionts for limited periods of time\n( Colaco et al. , 2011 ). However,\naposymbiotic B. azoricus in laboratory aquaria display an overall\nreduction in their fitness and health ( Raulfs et\nal. , 2004 ; Kádár\n et al. , 2005 ), suggesting that despite their\nnutritional flexibility, B. azoricus mussels depend on their symbionts\nfor long-term sustenance. B. azoricus maintains a stable symbiotic partnership with two distinct\ngammaproteobacterial phylotypes living within its gills ( Figure 1 ). The co-occurrence of a thiotrophic symbiont, which\noxidizes reduced sulfur compounds, and a methanotroph, which oxidizes methane\n( Fiala-Médioni et al. , 2002 ),\nenables B. azoricus to simultaneously tap the energy from two of the\nmost abundant reductants in the MAR vent fluids. The symbionts are housed in\nvacuoles within specialized gill epithelial cells called bacteriocytes. The\nbacteriocytes face the apical side of the gill filament, which is in contact\nwith the vent fluids ( Figure 1 ; Distel et al. , 1995 ). The physical proximity of the\nbacteriocytes to the ambient vent fluids facilitates direct exchange of\ndissolved gases and substrates ( Childress and Fisher,\n1992 ) and may also allow quick responses of symbionts to changes\nin environmental conditions. The host presumably acquires nutrients from the\nsymbionts by digesting them using lysosomal degradation enzymes ( Streams et al. , 1997 ; Fiala-Médioni et al. , 2002 ; Kádár et al. , 2008 ). The symbionts' location within host bacteriocytes allows for intricate\nmetabolic interactions between the host and the symbionts. So far, only a\nhandful of whole gill-based ‘omics' studies have examined this\ncomplex association, most of them focusing on the physiology of the host\n( Bettencourt et al. , 2010 ; Company et al. , 2011 ; Petersen et al. , 2011 ; Sayavedra\n et al. , 2015 ). The fact that the symbionts are\nuncultivable as yet and the mussels can only be maintained temporarily under\ncontrolled laboratory conditions ( Kádár\n et al. , 2005 ) has rendered detailed physiological\ninvestigations difficult. We therefore conducted a culture-independent\nproteogenomic study, which – for the first time – provided a\ndetailed and comprehensive picture of host–symbiont interaction dynamics\nand metabolic interdependencies in B. azoricus . To detect host proteins\npotentially involved in symbiosis-specific functions, we compared protein\nexpression patterns between symbiont-containing and symbiont-free host\ntissues.",
"discussion": "Results and discussion Enhanced protein identification following density gradient enrichment\nin B. azoricus We used a multistep centrifugation technique to physically separate host\ncomponents and thiotrophic and methanotrophic symbiont cells of B.\nazoricus . This enrichment substantially enhanced the rate of\nspectral identifications for the respective individual organisms, as\ncompared to plain, unenriched tissue. Our centrifugation procedure involved\ndifferential pelleting of host nuclei followed by rate-zonal density\ngradient centrifugation for symbiont enrichment ( Figure\n2a ). We analysed the resulting fractions with CARD-FISH and\nDAPI staining to identify fractions where either host material or symbiont\ncells were enriched ( Figure 2b ). Relative cell\ncounts revealed that 93% of the cells in the gradient pellet were\nthiotrophic and methanotrophic endosymbionts and that 97% of the\nsolid material in the supernatant consisted of host nuclei and host cell\nfragments (see Supplementary Figure S1 ).\nThis enrichment was clearly reflected in our proteomic results, where we\nfound a 17.7% increase in symbiont-associated spectral\nidentifications (NSAF) in the symbiont-enriched gradient pellet, and a\n15% increase in host spectral identifications in the host-enriched\nsupernatant, as compared to the gill tissue ( Figure\n2c ). The enhanced spectral identification rate enabled better\nquantification of the identified proteins and substantially improved the\nproteome coverage: The number of identified proteins in enriched samples\nincreased by 7.4% (host proteins) and 9.3% (symbiont proteins)\ncompared to those from unenriched tissues ( Supplementary Table S2C , see Supplementary Results and Discussion for absolute numbers of\nidentified proteins). Grouping of the most abundant proteins (in terms of\nNSAF%) of the symbiotic partners into metabolic categories allowed us\nto trace the metabolic network of the B. azoricus consortium\n( Figure 3 ). The B. azoricus symbiosis is fuelled by a versatile array of\nenergy sources Thiosulfate oxidation In the thiotrophic B. azoricus symbiont, thiosulfate as an\nenergy source seems to play a more prominent role than in other\nchemoautotrophic symbioses. We found the thiotroph's SoxYZ\nproteins for thiosulfate oxidation (Sox) to be more abundant than the\ndissimilatory sulfite reductase (Dsr) enzymes DsrAB for hydrogen sulfide\noxidation: With 1.104 OrgNSAF% (SoxYZ) and 0.894 OrgNSAF%\n(DsrAB), the enzyme complexes were present in a DsrAB:SoxYZ ratio of\n0.81 (soluble protein fraction of gradient pellet samples, Velos\nanalysis, see Supplementary Table S3 ).\nIn contrast, the sulfur-oxidizing symbionts of R. pachyptila \nand Olavius algarvensis express DsrAB at much higher levels\nthan SoxYZ. The DsrAB:SoxYZ ratio in the Riftia symbiont was\n2.5 ( n =3; S. Markert, unpublished results), and 5.2 in\nthe Olavius Gamma 1 symbiont ( Kleiner\n et al. , 2012b ). In addition to the Sox enzyme\ncomplex, we identified two sulfur/thiosulfate carrier protein\nhomologs, a TusA domain-containing protein (Rhd1,\nBazSymB_scaffold00007_23) and a Rhodanese-like domain-containing protein\n(Rhd2, BazSymB_scaffold00002_24) in the B. azoricus thiotroph\n( Supplementary Figure S2A ). In fact,\nRhd1 was one of the most abundant proteins in the thiotroph's\nmembrane proteome (membrane OrgNSAF% from gradient pellet,\n Supplementary Table S3 ). Rhodaneses\ncleave thiosulfate to sulfite and sulfide ( Brune,\n1995 , Supplementary Figure\nS2A ), while TusA has been shown to mediate thiosulfate\ntransfer in an acidothermophilic sulfur- and tetrathionate-oxidizing\narchaeon ( Liu et al. , 2014 ).\nBoth rhodanese proteins together constituted 2.11 OrgNSAF% in the\nthiotrophic B. azoricus symbiont (for comparison: the\n Riftia symbiont's rhodanese proteins make up only\n0.15 OrgNSAF %, n =3; S. Markert, unpublished).\nThe B. azoricus thiotroph clearly oxidizes sulfide, as\nindicated by the detection of most components of the rDSR-APS-Sat\npathway (see Supplementary Results and\nDiscussion ). However, the relatively high expression of\nthiosulfate-metabolizing and -transfer enzymes (compared to the\nsulfur-oxidizing symbionts of other host animals) indicates that\nthiosulfate oxidation may be particularly important for the B.\nazoricus symbiosis in its specific habitat. This is in\nagreement with previous studies, in which thiosulfate was observed to\nstimulate carbon fixation much more than sulfide in the thiotrophic\nsymbionts of related Bathymodiolus species ( Belkin et al. , 1986 ; Fisher\n et al. , 1987 ). Thiosulfate is more stable than sulfide and is less toxic to aerobic\nrespiration ( Harada et al. ,\n2009 ). In other symbiotic species such as vestimentiferan\ntubeworms and vesicomyid clams, sulfide is transported in a less harmful\nform, bound to the host's hemoglobin ( Arp\n et al. , 1984 , 1987; Doeller et al. , 1988 ). However, no dedicated\nhost proteins for sulfide transport are known in Bathymodiolus \nmussels ( Powell and Somero, 1986 ). High\nconcentrations of thiosulfate (0.178 m M in gills\nversus 0.079 m M in other tissues) in the closely\nrelated B. thermophilus led Fisher et\nal (1988) to propose that the host may detoxify\nsulfide from the environment to the less toxic thiosulfate.\nHost-mediated thiosulfate production as a means of sulfide\ndetoxification was recently also suggested for B. brevior \n( Beinart et al. , 2015 ). If\n B. azoricus uses a similar mechanism of sulfide\ndetoxification, then its symbionts would be exposed to thiosulfate\nconcentrations that are much higher than those in the environment. This\nmay stimulate higher expression of thiosulfate-metabolizing enzymes in\nthe B. azoricus thiotroph as compared to other symbionts, whose\nhosts do not produce thiosulfate as a means of sulfide\ndetoxification. Hydrogen oxidation In addition to its capacity for thiotrophy, the B. azoricus \nthiotroph is also capable of using hydrogen (H 2 ) as an\nelectron acceptor ( Petersen et al. ,\n2011 ). Genes for hydrogen oxidation were clearly\nexpressed, but at lower abundance compared with enzymes involved in\nsulfide or thiosulfate oxidation. H 2 oxidation may therefore\nnot be as important as the oxidation of reduced sulfur compounds for the\nthiotroph under the conditions prevailing at the sampling site in this\nstudy (see Supplementary Figure S2A and\n Supplementary Results and\nDiscussion ). Methane oxidation The energy-generating methane oxidation process is the most prominent\nmetabolic pathway in the methanotrophic B. azoricus symbiont.\nIts key enzymes, the particulate methane monooxygenase PmoCAB and the\nmethanol dehydrogenase XoxF that catalyze the oxidation of methane to\nformaldehyde, constituted 28.6% of the membrane OrgNSAF in the\ngradient pellet samples and 2.4% of the gill OrgNSAF,\nrespectively ( Supplementary Figure S2B ,\n Supplementary Results and\nDiscussion ). Considering the high catalytic efficiency of\nboth enzymes ( Chan et al. , 2013 ;\n Keltjens et al. , 2014 ),\nthese high expression levels likely correspond to very high methane\noxidation rates in the B. azoricus methanotroph. As indicated\nby our results, the symbiont can accomplish the subsequent\nenergy-producing oxidation of formaldehyde to formate and CO 2 \nvia two parallel metabolic routes, that is, the tetrahydrofolate\n(H 4 F) pathway and the dephospho-tetrahydromethanopterin\n(H 4 MPT) pathway (see Supplementary\nFigure S3 and Supplementary Results\nand Discussion for details). We identified enzymes of\nboth pathways in the methanotroph's proteome. The presence of\nmultiple routes for formaldehyde metabolism may offer enhanced metabolic\nflexibility to the symbiont under various environmental conditions.\nAlso, since accumulation of formaldehyde is toxic to the cells, the two\nformaldehyde oxidation pathways may operate as overflow valves for\ncontrolling excess formaldehyde levels, while simultaneously generating\nelectrons and reducing equivalents during the process ( Crowther et al. , 2008 ). Pathways for carbon assimilation are highly expressed in both symbionts\nwhile crucial TCA cycle enzymes are missing in the thiotroph Assimilation of C1 compounds In the proteomes of both the thiotrophic and the methanotrophic B.\nazoricus symbiont, carbon fixation pathways were highly\nabundant, reflecting their importance in the symbiotic association. The\nthiotroph uses the Calvin-Benson-Bassham cycle for autotrophic fixation\nof CO 2 (see Supplementary Results and\nDiscussion and Figure 4a ).\nAll Calvin-Benson-Bassham pathway enzymes were highly abundant in the\nthiotroph. The large subunit of ribulose bisphosphate\ncarboxylase/oxygenase (RuBisCO form I, CbbL,\nBazSymA_Acontig00018_18), the key enzyme of the Calvin-Benson-Bassham\ncycle, was consistently the most abundant enzyme of the\nthiotroph's carbon metabolism in all samples analysed in our study\n( Figures 3 and 4a , Supplementary Table\nS3 ). The methanotroph expressed a complete ribulose\nmonophosphate (RuMP) pathway for the assimilation of carbon from\nformaldehyde, as well as parts of a second carbon assimilation pathway,\nthe serine cycle (see Figure 4b , Supplementary Figure S3 and Supplementary Results and Discussion ). The\nhigh abundance of the two RuMP pathway key enzymes hexulose-6-phosphate\nformaldehyde lyase (Hps, BAZMOX_41472_2) and 3-hexulose-6-phosphate\nisomerase (Hpi1, BAGiLS_016202) indicates that the methanotroph\nprimarily uses this pathway for formaldehyde assimilation. The serine\ncycle seems to play a minor role in carbon assimilation as compared to\nthe dominant RuMP pathway under the conditions in this study (see\n Supplementary Results and\nDiscussion ). Incomplete TCA cycle in the thiotroph The thiotrophic symbiont of B. azoricus appears to be unable to\nreplenish the crucial carbon metabolism intermediates oxaloacetate and\nsuccinate. As expected in an obligate autotroph, the thiotroph lacks the\ntricarboxylic acid (TCA) cycle enzyme 2-oxoglutarate dehydrogenase (Odh;\n Wood et al. , 2004 ; Kleiner et al. , 2012a ). The absence\nof Odh effectively prevents wasteful re-oxidation of autotrophically\nfixed organic carbon, while still allowing for the production of carbon\nprecursors for amino acid biosynthesis and other anabolic pathways.\nIntermediates of this ‘horse shoe' TCA cycle are usually\nreplenished by anaplerotic pathways such as the glyoxylate bypass.\nSurprisingly, our proteogenomic analysis revealed that not only the gene\nencoding Odh is missing in the thiotroph, but also the genes for the TCA\ncycle enzymes malate dehydrogenase (Mdh) and succinate dehydrogenase\n(Sdh, Figure 4a ). Moreover, the thiotroph\napparently lacks all known genes encoding anaplerotic enzymes for the\nreplenishment of the essential TCA cycle intermediates oxaloacetate and\nsuccinate (see Supplementary Results and\nDiscussion ), although it expresses enzymes involved in\noxaloacetate and succinate consumption ( Figure\n4a ). Oxaloacetate is an important precursor for\nbiosynthesis of essential amino acids of the aspartate family, while\nsuccinate, or rather its derivative succinyl-CoA, is required for the\nbiosynthesis of porphyrins and amino acids. Replenishment of\noxaloacetate and succinate is therefore crucial for cellular metabolism\nand alternate mechanisms for refilling both intermediates must exist\n(see below). Complete TCA cycle in the methanotroph Unlike the thiotrophic symbiont of B. azoricus , the methanotroph\nhas a complete set of genes encoding TCA cycle enzymes, including\n odh (BAZMOX_25028_0). Odh, Mdh and Sdh were, however, not\ndetected in the methanotroph's proteome ( Figure\n4b ). In the facultative methylotroph Methylobacterium\nextorquens AM1, odh expression is repressed during\ngrowth on C1-compounds ( Chistoserdova et\nal. , 2003 ). It is therefore possible that the\nmethanotrophic symbiont of B. azoricus expresses a complete,\nenergy-producing TCA cycle during growth on multicarbon compounds when\nthe preferred carbon source methane is not available, and an incomplete\nversion of the TCA cycle that produces anabolic intermediates when\nmethane is plentiful ( Zhao and Hanson,\n1984 ; Chistoserdova et al. ,\n2003 ; Wood et al. ,\n2004 ; Dedysh et al. ,\n2005 ). In the absence of methane, cellular storage\npolymers such as glycogen may serve as readily available multicarbon\ncompounds for energy generation. This idea is supported by the detection\nof glycogen synthesis enzymes in the methanotroph's proteome\n( Figure 4b , Supplementary Table S3 , Supplementary Results and Discussion ). Some metabolic tasks are accomplished jointly by the symbiotic\npartners CO 2 concentration by carbonic anhydrase in\ngills In the B. azoricus gill metaproteome, host-derived carbonic\nanhydrase (CA) is one of the most abundant proteins expressed ( Figures 3 and 4a ,\n Supplementary Table S3 ,\nBAGiLS_000922). The enzyme was ~10 times more abundant in gills and ~19\ntimes more abundant in the supernatant, respectively, as compared to\nsymbiont-free foot tissue ( Table 1 ),\nsuggesting a symbiosis-specific role for the host CA in B.\nazoricus. In marine invertebrates such as anemones, corals,\ntubeworms and clams harbouring carbon-fixing bacteria, the ubiquitous\nenzyme CA facilitates the reversible conversion of bicarbonate, the\ndominant form of seawater carbon, to CO 2 for transport to\nsymbiont-bearing tissues ( Kochevar and Childress,\n1996 ). The B. azoricus CA therefore likely\nrepresents a CO 2 -concentrating mechanism, which provides\nelevated levels of inorganic carbon for fixation by the thiotrophic\nsymbiont ( Figure 4a ). High activity and\nprotein expression of host CA was also described in gills of\n Bathymodiolus mussels hosting only methanotrophic\nsymbionts, where CA may be involved in the elimination of CO 2 \nproduced as an end product of methane oxidation ( Hongo et al. , 2013 ). In addition to the host CA,\nwe also found the CAs of the thiotroph and of the methanotroph expressed\n(BAT01672, BAZMOX_02303_3), albeit in very low abundances. It is unclear\nwhether either of the CAs from host, methanotroph or thiotroph\nparticipate in the elimination of methanotroph-derived CO 2 .\nWe speculate that in B. azoricus this methanotroph-derived\nCO 2 , instead of being eliminated, may be recycled by the\nthiotrophic symbiont for CO 2 fixation ( Nelson and Fisher, 1995 ). Biosynthesis of amino acids and vitamins/cofactors in B.\nazoricus Only seven genes associated with amino acid biosynthesis were found in\nthe B. azoricus host EST library, of which four were identified\nas proteins ( Supplementary Figure S5 ).\nIn contrast, the genome of the thiotrophic symbiont contains essentially\ncomplete gene sets for the biosynthesis of all 20 proteinogenic amino\nacids and of 11 vitamins and cofactors. Ninety-five per cent of the\nthiotroph's amino acid synthesis-related genes (that is, 63 of 66)\nand 43% (26 out of 60) of the genes associated to cofactor\nbiosynthesis were identified as proteins ( Supplementary Figure S5 ). In the methanotroph, 43 amino\nacid synthesis genes and 30 cofactor synthesis genes were detected in\nthe genome, of which 30 (70%) and 11 (37%), respectively,\nwere detected at the protein level ( Supplementary\nFigure S5 ). As amino acids are indispensable for protein\nbiosynthesis in the host, the sparse presence of amino acid\nsynthesis-related genes in B. azoricus (even when considering\nthe incompleteness of the available transcriptome information) may\nindicate that the bivalve depends on its symbionts for supply with amino\nacids and cofactors. This putative deficiency in amino acid biosynthetic\nenzymes seems to be uncommon in non-symbiotic marine mussels as several\nspecies are capable of de novo synthesizing most amino acids\nfrom TCA pathway intermediates ( Ellis et\nal. , 1985 ). Bathymodiolus mussels can\nacquire amino acids by direct uptake from seawater or from breakdown of\norganic matter ingested through filter feeding ( Riou et al. , 2010 ). But whether this can satisfy\nall of their nutritional requirements is unclear ( Martins et al. , 2008 ), particularly given the\nunsteady availability of organic nutrients in the dynamic vent habitats.\nOur results suggest that the B. azoricus symbionts are capable\nof providing their host with all required amino acids and prosthetic\ngroups, a scenario that was previously also suggested for the\nthiotrophic vesicomyid symbioses of Calyptogena magnifica and\n C. okutanii ( Newton et al. ,\n2008 ). Amino acids that are synthesized by the B.\nazoricus symbionts may be made available to the host through\nintracellular symbiont digestion, as indicated by the detection of\nabundant host-derived digestive enzymes in the gill tissue (see\nbelow). Replenishment of oxaloacetate and succinate As mentioned above, the thiotroph seems not to be able to restore its\noxaloacetate and succinate pools autonomously, as several TCA cycle\nenzymes are missing in its genome, and potential anaplerotic routes that\ncould replace the missing enzymes are not encoded ( Figures 4a and 5a , see\n Supplementary Results and Discussion \nfor details). The required intermediates may instead be provided by the\nhost, as suggested by the results of our proteome analysis: The host\nenzyme phosphoenolpyruvate carboxykinase (PckA, BAGiLS_012326) was\nabundantly expressed in the B. azoricus gill metaproteome and\nits expression was 3.7 fold higher in the gill as compared to the\nsymbiont-free foot tissue (calculated from host gill and foot\nOrgNSAF% Supplementary Table S3 ).\nPckA mediates the reversible carboxylation of phosphoenolpyruvate to\noxaloacetate ( Prichard and Schofield,\n1968 ; Moon et al. ,\n1977 ; Lee, 2002 ) and may\nthus provide oxaloacetate for import into the thiotroph in B.\nazoricus ( Figure 5a and b ). This\nwould effectively mean that a part of the carbon fixation is done on the\nhost side. Such an intimate metabolic integration of host and symbiont\non the level of central carbon metabolism would provide the host with a\ndirect way to control symbiont metabolism. Oxaloacetate could furthermore be converted to malate or aspartate before\ntransfer from host to thiotroph ( Figure 5a ),\nas indicated by high concentrations of host Mdh (BAGiLS_010003,\n0.55% gill OrgNSAF) in the gill metaproteome. The host's\naspartate transaminase AspC (CAD42721.2) was also expressed, although at\nlower abundance (0.012% gill OrgNSAF; Figures\n5a and b , Supplementary Table\nS3 ). Succinate/succinyl-CoA might be produced or\ninterconverted to fumarate before transfer to the thiotroph by the two\nhost enzymes fumarate reductase/succinate dehydrogenase, Sdh\n(BAGiLS_010531, Figure 5a ), and\ndihydrolipoyllysine-residue succinyltransferase component of\n2-oxoglutarate dehydrogenase, Odh (BAGiLS_005913). Both proteins showed\nsignificantly elevated expression levels in the symbiont-enriched\ngradient pellet as compared to the host-enriched supernatant in our\nstudy ( Table 1 ). Uptake of malate or succinate by the thiotrophic symbiont requires the\npresence of the TRAP-type C4 dicarboxylate transporter complex DctQMP,\nwhereas aspartate can be imported through the glutamate/aspartate\nABC transporter complex, GltIJKL, respectively ( Figure 5a ). Complete gene sets for both these transporter\ncomplexes are encoded in the thiotrophic symbiont's genome. The\nsolute receptor component DctP (BazSymB_scaffold00004_53), a component\nof the TRAP-type C4 dicarboxylate transporter complex, and the\nperiplasmic binding component GltI (BazSymA_Acontig00019_5) of the\nglutamate/aspartate ABC transporter complex were also identified in\nthe thiotroph's proteome ( Figure 5b \nand Supplementary Table S3 ).\nTransporters for oxaloacetate are rare in bacteria, but a citrate\ntransporter (BazSymA_Acontig02368_3), which is encoded in the\nthiotroph's genome, shows promiscuity towards oxaloacetate as its\nsubstrate and may therefore be used for oxaloacetate uptake in the\nthiotroph ( Pudlik and Lolkema, 2011 ).\nOxaloacetate may furthermore also be imported through the\nabove-mentioned TRAP-type C4 dicarboxylate transporter, which is poorly\ncharacterized with respect to its specificity. Is the thiotroph turning into an obligate symbiont? The mdh and sdh genes, which are missing from the\nthiotroph's genome, are present in a single gene cluster in the\nsymbiont's free-living relative SUP05 ( Walsh\n et al. , 2009 ; Figure\n5c ). This might indicate a selective loss of these genes\nduring the thiotroph's transition from a free-living to a\nsymbiotic lifestyle, possibly driven by the presence of functional\nsubstitutes in the host (as demonstrated in our study). The thiotrophic\nsymbiont may hence even be obligately dependent on the host for its\nmetabolic needs. The fact that no active free-living stage of the\nthiotrophic B. azoricus symbiont has ever been detected in the\nvent environment might support this speculation. However, as the\n mdh gene (but not the sdh gene) is also absent\nfrom the recently published genome of the free-living SUP05 member\n‘ Candidatus Thioglobus autotrophica' ( Shah and Morris, 2015 ), the possibility of an\nobligate symbiosis in B. azoricus remains hypothetical. It\nmight be speculated that a putative free-living stage of the thiotroph\n– if there is one – may rely on the uptake of oxaloacetate\nor other small organic molecules from the environment, circumventing the\nneed for the missing TCA cycle enzyme functions. Adaptations to a symbiotic lifestyle To identify candidate genes and proteins that are potentially involved in\nsymbiosis-specific functions we pursued two complementary approaches: (i) We\ncompared symbiont genomes and proteomes with those of their free-living\nrelatives. This approach revealed that chaperones and DNA-binding proteins\nare extraordinarily abundant in both symbionts (see below). It furthermore\nshowed the unexpected presence of genes and proteins involved in CRISPR-Cas\nand restriction-modification systems in the thiotrophic B. azoricus \nsymbiont, which may hint at a yet to be determined role of these proteins in\nhost-symbiont interactions (see Supplementary Results\nand Discussion for details). (ii) We compared protein\nexpression in symbiont-enriched B. azoricus samples versus\nsymbiont-free samples, and in symbiont-containing tissue versus\nsymbiont-free tissue to identify host proteins involved in interactions with\nthe symbionts (see Methods for details and Supplementary Table S4 for a comprehensive list of putative\nsymbiosis-relevant proteins identified in our analysis). With this approach\nwe identified a broad repertoire of digestive enzymes, which are likely\ninvolved in symbiont digestion (see below). We also detected 23\nimmune-related host proteins, of which seven had significantly higher\nexpression levels in symbiont-containing samples, and whose exact function\nin the symbiosis is unclear (see Supplementary Results\nand Discussion ). High expression of digestive enzymes in gill tissue In our proteome analysis, we identified 58 host proteins with putative\nproteolytic and carbohydrate-degrading functions ( Supplementary Table S3 ), of which 12 were significantly\nmore abundant in symbiont-containing samples (whole gills and gradient\npellet) compared to symbiont-free (foot tissue) and host-enriched\nsamples (host-enriched supernatant, Table\n1 ). These abundant host enzymes are likely involved in the\ndigestion of the symbionts. In chemoautotrophic invertebrate symbioses,\ntwo modes of nutrient transfer from symbiont to host have been proposed:\n(i) direct digestion of symbionts by the host, and/or (ii)\ntranslocation of nutrients from symbiont tissue to the host cells,\ntermed ‘milking' ( Streams et\nal. , 1997 ). Although previous observations\nindicated that symbiont digestion might be the major mode of nutrient\ntransfer in B. azoricus ( Fisher and\nChildress, 1992 ; Streams et\nal. , 1997 ; Fiala-Médioni et al. , 2002 ), no direct\nevidence existed so far. Seven of the host proteins with significantly higher abundances in\nsymbiont-containing samples were putative proteases and peptidases.\nAmong them were lysosomal proteases such as saposin B (BAGiLS_000621)\nand cathepsin (BAGiLS_003294), which showed >80 fold and ~13 fold\nhigher abundance, respectively, in gills compared to foot samples\n( Table 1 ). Lysosomes have been\nimplicated in symbiont digestion in gills of B. azoricus \n( Fiala-Médioni et al. ,\n2002 ) and other bivalves ( Boetius and\nFelbeck, 1995 ) and our results further corroborate the\nidea that lysosomal host proteases may facilitate the degradation of\nsymbiont proteins during symbiont digestion. We furthermore identified\ntwo glycosidases (glycoside hydrolases), which were significantly\nenriched in the gills ( Table 1 ):\nBAGiLS_012512 was most abundant in the gill membrane fraction,\nindicating a possible involvement in the hydrolysis of bacterial\ncell-surface polysaccharides ( Davies and Henrissat,\n1995 ; see Supplementary Table\nS3 ). During symbiont digestion, some of the particularly\nabundant host glycosidases in the gill tissue may also target the\nmethanotrophic symbiont's glycogen reserves (see above). Abundant chaperones and bacterial nucleoid proteins in B.\nazoricus symbionts Our proteome data revealed remarkably high expression levels of molecular\nchaperones in both symbionts and of histone-like DNA-binding proteins in\nthe thiotrophic symbiont: The chaperones GroEL, GroES, DnaJ and DnaK\ntogether constituted 3.02% and 7.16% (gill OrgNSAF) of the\ntotal protein abundance in the thiotroph and in the methanotroph,\nrespectively (Velos analysis, see Supplementary\nTable S3 and Supplementary Results\nand Discussion ). Bacterial nucleoid-associated proteins,\nsuch as the histone-like bacterial DNA-binding protein (Hns) and the\nDNA-binding protein HU beta (HupB), constituted 16.87% (gill\nOrgNSAF) in the thiotroph, the latter being the most abundant protein of\nthe entire gill metaproteome ( Figure 3 ,\n Supplementary Table S3 ). In the\nthiotroph, GroEL and HupB were even more abundant than the most abundant\nsulfur oxidation-related protein DsrH and the carbon-fixing RuBisCO.\nHigh expression levels of chaperones and DNA-binding proteins have also\nbeen observed in other symbionts ( Baumann et\nal. , 1996 ) and in pathogenic bacteria ( Neckers and Tatu, 2008 ), indicating that these\nproteins might have a symbiosis-specific function in the B.\nazoricus symbionts. As the thiotroph might be evolving into an\nobligate symbiont (see above), enhanced mutation rates and corresponding\nincreased protein misfolding might be a possible explanation for the\nobserved high chaperone concentrations (see Supplementary Results and Discussion for details)."
} | 8,260 |
38982749 | PMC11253715 | pmc | 3,383 | {
"abstract": "Abstract Ciliates are a diverse group of protists known for their ability to establish various partnerships and thrive in a wide variety of oxygen-depleted environments. Most anaerobic ciliates harbor methanogens, one of the few known archaea living intracellularly. These methanogens increase the metabolic efficiency of host fermentation via syntrophic use of host end-product in methanogenesis. Despite the ubiquity of these symbioses in anoxic habitats, patterns of symbiont specificity and fidelity are not well known. We surveyed two unrelated, commonly found groups of anaerobic ciliates, the Plagiopylea and Metopida, isolated from anoxic marine sediments. We sequenced host 18S rRNA and symbiont 16S rRNA marker genes as well as the symbiont internal transcribed spacer region from our cultured ciliates to identify hosts and their associated methanogenic symbionts. We found that marine ciliates from both of these co-occurring, divergent groups harbor closely related yet distinct intracellular archaea within the Methanocorpusculum genus. The symbionts appear to be stable at the host species level, but at higher taxonomic levels, there is evidence that symbiont replacements have occurred. Gaining insight into this unique association will deepen our understanding of the complex transmission modes of marine microbial symbionts, and the mutualistic microbial interactions occurring across domains of life."
} | 355 |
33638170 | PMC9292320 | pmc | 3,384 | {
"abstract": "Summary \n Arbuscular mycorrhizal fungi (AMF) are keystone symbionts of agricultural soils but agricultural intensification has negatively impacted AMF communities. Increasing crop diversity could ameliorate some of these impacts by positively affecting AMF. However, the underlying relationship between plant diversity and AMF community composition has not been fully resolved. We examined how greater crop diversity affected AMF across farms in an intensive agricultural landscape, defined by high nutrient input, low crop diversity and high tillage frequency. We assessed AMF communities across 31 field sites that were either monocultures or polycultures (growing > 20 different crop types) in three ways: richness, diversity and composition. We also determined root colonization across these sites. We found that polycultures drive the available AMF community into richer and more diverse communities while soil properties structure AMF community composition. AMF root colonization did not vary by farm management (monocultures vs polycultures), but did vary by crop host. We demonstrate that crop diversity enriches AMF communities, counteracting the negative effects of agricultural intensification on AMF, providing the potential to increase agroecosystem functioning and sustainability.",
"conclusion": "Conclusions Through investigating the response of AMF communities to greater crop diversity, we have demonstrated that plant host diversity shifts the available AMF community into richer and more diverse communities while soil properties structure AMF community composition. Our on‐farm approach focused on the role of polycultures – the dominant form of agriculture across many regions in the world, especially among smallholder farmers (Altieri, 1999 ; Brooker et al ., 2015 ) – allowing us to elucidate the important role that plant host diversity plays on AMF communities without the confounding reciprocal process (i.e. AMF communities influence plant communities), a common obstacle in observational studies of natural systems. Specifically, we show that polycultures doubled AMF richness in comparison to monocultures. We further find that AMF colonization is dependent on crop host identity. Together, the positive relationship between plant diversity and AMF community composition highlights the fact that vegetative diversity is essential to harnessing AMF functional diversity. Therefore, we conclude that plant diversity is key to enriching AMF communities, and that enhancing crop diversity locally on farms may allow multifunctionality to be re‐established via AMF communities in agricultural landscapes.",
"introduction": "Introduction Arbuscular mycorrhizal fungi (AMF) are a key component of the soil microbial community that contribute to the development of healthy soils and agricultural sustainability (Bender et al ., 2016 ). Arbuscular mycorrhizal fungi establish associations with the majority of land plants, including most crops, and provide many ecosystem services to agriculture (Rillig et al ., 2016 ; Bender et al ., 2016 ; Thirkell et al ., 2017 ). However, agricultural intensification, characterized by high nutrient input, low crop diversity and high tillage frequency, reduces the diversity of AMF taxa in agricultural soils (Helgason et al ., 1998 ; Verbruggen & Toby Kiers, 2010 ; Rillig et al ., 2016 ; Hontoria et al ., 2019 ), compromising the potential functions and benefits of AMF in agricultural landscapes (Gottshall et al ., 2017 ; Manoharan et al ., 2017 ; Xu et al ., 2017 ; de Graaff et al ., 2019 ). In natural systems, a positive relationship between plant and AMF community composition has been well documented (Landis et al ., 2004 ; Hiiesalu et al ., 2014 ; Martínez‐García et al ., 2015 ; Chen et al ., 2017 ) but the underlying mechanisms are still unclear (Kokkoris et al ., 2020 ). Plant communities could filter AMF (Šmilauer et al ., 2020 ) or AMF could be driving plant community composition (Tedersoo et al ., 2020 ). If plant communities can positively shape AMF communities in agricultural systems (Verbruggen & Toby Kiers, 2010 ), depauperate AMF communities could be bolstered by increasing crop diversity in intensive agricultural landscapes dominated by large areas of monocultures. Understanding whether increasing crop diversity can bolster AMF communities that could benefit sustainable agricultural systems requires a thorough investigation of the underlying mechanisms between crop and AMF diversity in agricultural landscapes. Intensive agricultural production has often come at high environmental cost to soils, including increased soil erosion, greater nutrient leaching and lower water‐holding capacity (Foley et al ., 2005 ). Ensuring agricultural sustainability requires strategies that prioritize multiple ecosystem services rather than just maximizing production (Kremen & Merenlender, 2018 ). Arbuscular mycorrhizal fungi are plant symbionts that are an important source of ecosystem services in agricultural landscapes (Gianinazzi et al ., 2010 ; Thirkell et al ., 2017 ; Rillig et al ., 2019 ). Beyond nutrient acquisition (Smith & Read, 2008 ), AMF are helpful in pathogen protection (Veresoglou & Rillig, 2012 ; Jung et al ., 2012 ), herbivore resistance (Middleton et al ., 2015 ), drought tolerance (Leigh et al ., 2009 ), nutrient cycling (van der Heijden, 2010 ) and soil formation and aggregation (Rillig & Mummey, 2006 ; Wilson et al ., 2009 ). In this way, while AMF are not always tightly linked to increasing crop productivity (Ryan & Graham, 2018 ; but see Zhang et al ., 2019 ), they are important to overall agroecosystem multifunctionality via ‘system performance and sustainability’ that can reduce negative external inputs (Rillig et al ., 2019 ). Enhancing agroecosystem multifunctionality through AMF will depend in part on the composition of the AMF community (Verbruggen & Toby Kiers, 2010 ). Multiple aspects of intensive agriculture adversely alter AMF communities. For example, intensively tilled agricultural soils tend to select for a less diverse, more ruderal AMF community, which includes taxa thought to have fewer mutualistic traits (Chagnon et al ., 2013 ). Intensive tillage and bare fallows also decrease AMF colonization of crops by disrupting hyphal networks and leaving AMF without hosts, respectively (Bowles et al ., 2017 ). Heavy fertilization can create less mutualistic and abundant AMF associations (Johnson et al ., 1997 ; Johnson, 2010 ) and suppress colonization of roots by AMF. Specifically, high nutrient availability via fertilization decreases the dependency of plant hosts on AMF but selects for AMF that are more aggressive competitors for plant carbohydrates, leading to a net cost to plant hosts (Johnson, 2010 ; Thirkell et al ., 2017 ). Farm management also influences AMF community composition indirectly via changes in other soil properties, such as soil pH and soil organic carbon (Vályi et al ., 2016 ). For example, adding fertilizer acidifies soils (Geisseler & Scow, 2014 ) and tilling reduces soil organic carbon, both of which can drive changes in AMF communities (Fitzsimons et al ., 2008 ; Bouffaud et al ., 2016 ; Oehl et al ., 2017 ). Apart from tillage, fertilization and other practices that change soil properties, agricultural soils may also have low numbers of AMF taxa because of the extremely low diversity of plant hosts when crops consist of monocultures in space and/or over time (Burrows & Pfleger, 2002 ; Oehl et al ., 2003 ; Johnson et al ., 2004 ; Strom et al ., 2020 ). By contrast, polycultures, which are more similar to biodiverse natural systems, have the potential to positively impact AMF communities by providing a more diverse set of plant hosts. While agriculture continues to shift towards monocultures, polycultures have traditionally been the dominant form of agriculture across many regions in the world (Altieri, 1999 ; Brooker et al ., 2015 ) and have been promoted as a way to remedy the negative environmental impacts that intensive monoculture agriculture has had on soils (Power, 2010 ; Li et al ., 2014 ; Iverson et al ., 2014 ; Altieri et al ., 2015 ), especially through AMF associations (Orrell & Bennett, 2013 ; Brooker et al ., 2015 ). Yet surprisingly little is known about how AMF respond to polycultures (Verbruggen & Toby Kiers, 2010 ). More generally, the underlying mechanism driving the relationship between AMF and plant diversity in managed or natural ecosystems has not been fully resolved. Observational studies in natural ecosystems cannot differentiate whether AMF diversity supports greater plant diversity or AMF diversity is dependent on plant composition (Lekberg & Waller, 2016 ; Kokkoris et al ., 2020 ). While AMF are generalists, there is a degree of selectivity in AMF associations with plant hosts (Bainard et al ., 2014 ; Davison et al ., 2016 ; Sepp et al ., 2019 ; Davison et al ., 2020 ), and thus plant hosts could filter AMF communities directly (Šmilauer et al ., 2020 ). Alternatively, plant hosts could impart changes in the soil environment (e.g. pH, carbon, composition) that alter AMF communities indirectly (Vályi et al ., 2016 ; Lekberg & Waller, 2016 ). Because the suite of plant hosts is carefully managed in agricultural systems, studies in agroecosystems might help to clarify the mechanism underlying the relationship between plant diversity and AMF communities. Therefore, we sought to understand how AMF communities respond to greater crop diversity (i.e. polycultures) in an intensively managed agricultural landscape. Our study compared AMF communities (richness, diversity and composition) in soil, the legacy of previous management, as well as AMF colonization in roots in monoculture vs polyculture fields. Our experimental design allowed us to investigate the filtering effect of crop diversity (monoculture vs polyculture) on AMF communities, as well as how AMF communities could be influenced by soil properties. To reduce confounding effects of management practices on AMF, all field sites studied used similar tillage regimes and fertilizers, allowing us to focus on management differences in crop diversity (monoculture vs polyculture). Specifically, we asked: how does greater crop diversity via polyculture and its management legacy affect AMF richness and diversity relative to monoculture cropping; to what extent does AMF community composition differ between polyculture and monoculture field sites; how does AMF root colonization differ between crop plants grown in monoculture vs polyculture field sites; and, ultimately, do soil properties impact AMF community composition (richness, diversity, and composition) and colonization? We predicted that despite the legacy of intensive agricultural practices on soils in our study region, greater crop diversity would have a positive effect on richness and diversity. We also expected that the more diverse plant community in polycultures may foster more beneficial, host‐specific AMF taxa, which, in turn, lead to greater AMF root colonization for a given crop host when planted in polyculture rather than monoculture fields (Johnson et al ., 2004 ). Based on previous literature, we also anticipated that soil properties would have an overriding effect on AMF community composition, but that crop diversity still plays an important role in shifting the AMF community. In this way, our study aims to increase our understanding of the relationship between plant diversity and AMF communities and to investigate whether greater crop diversity could support more sustainable agriculture systems via AMF communities.",
"discussion": "Discussion Our study demonstrates that greater crop diversity in intensive agricultural systems drives a richer and more diverse AMF community. We observed nearly twice as many AMF taxa in polycultures than in monocultures, while accounting for variation in soil properties that also significantly affected AMF richness. The AMF community composition in polyculture sites was also distinct from that in monoculture field sites, but soil properties played a stronger role in structuring the AMF community. Contrary to our expectations, we also show that AMF colonization of roots is probably driven by plant host identity rather than farm management practices (monoculture vs polyculture). For both AMF diversity and colonization responses, soil properties were important factors that influenced the outcomes, but did not dominate relative to the important effect of higher crop diversity. Overall our findings indicate that managing for crop diversity in agricultural landscapes can strongly influence AMF community composition, including richness and diversity, across heterogeneous soils. Further, our results support the notion that plant diversity is key to belowground biodiversity, which in turn could support multifunctional agroecosystems (Bender et al ., 2016 ; Isbell et al ., 2017 ), including those that have been intensively managed in the past. We show that polyculture fields harbor a richer and more diverse AMF community than do monoculture fields, suggesting that polyculture plantings may promote recovery of AMF richness following a long period of monoculture farming, which is known to be associated with decreased AMF diversity (Helgason et al ., 1998 ; Daniell et al ., 2001 ). Our polyculture sites were formerly farmed intensively as monocultures, as recently as 7 yr before sampling, and thus were likely to have had a depauperate AMF community (Druille et al ., 2013 ; Manoharan et al ., 2017 ; Williams et al ., 2017 ). Soil properties also contributed to explaining some of the variance in AMF richness and diversity, but overall they played a minimal role. While AMF are ubiquitous across landscapes, AMF are obligate symbionts with a degree of host specificity; thus, AMF associations with plant hosts are typically not random (Martínez‐García et al ., 2015 ; Werner & Kiers, 2015 ; Davison et al ., 2016 ; Horn et al ., 2017 ). Variation in plant traits, including phenology, root architecture and other factors, impacts the distribution and composition of AMF (Hart & Reader, 2002 ; Pringle & Bever, 2002 ; Oehl et al ., 2004 ; Maherali & Klironomos, 2007 ), and thus functionally different plants can associate with distinct AMF communities (Davison et al ., 2020 ). In our study, we found evidence that different AMF taxa occur in polycultures vs monocultures. A Rhizophagus taxon was the top indicator of monocultures, whereas the top indicator taxon in polycultures was in the genus Glomus . While research on AMF functional traits is still emerging (e.g. Chagnon et al ., 2013 ), these taxonomic differences (Šmilauer et al ., 2020 ), coupled with greater AMF diversity in polycultures, could indicate differences in AMF community functionality with implications for plant performance and ecosystem processes. Future research should focus on these possible functional differences among AMF taxa. In polycultures, functionally distinct plant hosts are planted across space and time, creating a mosaic of diverse microhabitats, varying in microclimatic and microedaphic properties, as evidenced by our finding that polycultures have a more heterogenous soil environment compared with monocultures. Across polyculture fields in our study system, crop type can be distinct row by row in space, but single rows can also shift from crop to crop at different times throughout the year. For example, annuals and perennial crops are grown together at the same time, grasses and tubers can be grown adjacent to each other, and leafy greens and legumes could be grown sequentially in polyculture fields in this study system. In fact, the presence of perennials (Alguacil et al ., 2012 ) and legumes (Drinkwater et al ., 1998 ; Bünemann et al ., 2004 ; Mathimaran et al ., 2007 ) has been shown to increase AMF diversity. In the polyculture field sites, not only are legumes present, but functionally distinct leguminous species and cultivars are planted (e.g. long beans, faba, peanuts, peas, etc.). Therefore, the likely mechanism that fosters a richer and more diverse AMF community in polycultures is the heterogeneity in plant composition: over space, across time within a space, and as different species or varieties across and within functional types such as legumes. Arbuscular mycorrhizal fungi communities also depend, in part, on the composition and pattern of past plant communities (Bittebiere et al ., 2020 ). This may explain why in polycultures we do not find a more diverse AMF community in the more plant‐rich transects when compared with the single species transects. Instead, the legacy of polyculture management, specifically the temporally, spatially and functionally heterogeneous plant community, leads to an overall richer and more diverse AMF community in polycultures than in monocultures. Polycultures also harbored a distinct AMF community from monocultures. However, AMF communities were quite heterogeneous across both monoculture and polyculture field sites, reflecting a high turnover among sites. The heterogeneity and high turnover of the AMF community are evident in the fact that average site‐level AMF richness is much lower than total AMF richness recorded across all sites: the average AMF richness was c . 5 in monoculture and 10 in polyculture field sites, compared with a total AMF richness in the whole study of 244. Arbuscular mycorrhizal fungi communities tend to be heterogeneous even at fine scales (Pringle & Bever, 2002 ; Vályi et al ., 2016 ; Mony et al ., 2020 ). Our expectation that AMF communities on polyculture farms would be more heterogeneous at a fine scale than those on monocultures was not borne out; specifically, we found no interaction between farm management (monoculture vs polyculture) and transect (within‐row vs across‐row) for composition. This is further evidence that polycultures may impart a legacy effect on AMF communities. Despite possible AMF compositional differences between monocultures and polycultures, our results show that soil properties played a larger role in explaining AMF community composition than farm management, with pH being a significant predictor, consistent with other studies (Fitzsimons et al ., 2008 ; Bouffaud et al ., 2016 ; Davison et al ., 2016 ; Oehl et al ., 2017 ; Van Geel et al ., 2018 ), especially at finer spatial scales (Rasmussen et al ., 2018 ). The greater heterogeneity in soil edaphic properties in polycultures than monocultures suggests that crop diversity may indirectly underlie these edaphic‐driven patterns of AMF community structure. Regardless, these findings suggest a role for soil properties in structuring AMF community composition across farms and a role for farm management in shifting the available AMF community into more or less diverse communities at the site level. The role of plant diversity vs plant host identity on AMF associations was most evident in our measurements of AMF colonization in roots. Our study design allowed us to explore whether crop diversity (polyculture vs monoculture management) impacted AMF colonization in the same crop species, and also whether different crop plant hosts in polycultures play a role in determining AMF colonization. Contrary to our expectation, we found no difference in AMF colonization across the same crop host when planted in polyculture or monoculture fields. In part, this may be explained by fertilizer usage across all farms, which may mask or suppress changes in AMF root colonization as a result of increasing crop diversity because fertilization decreases the dependency of plants hosts on AMF (Johnson, 2010 ). But AMF colonization has been shown to increase in plant host roots within more diverse plant communities (Eriksson, 2001 ; Johnson et al ., 2004 ; but see Burrows & Pfleger, 2002 ), especially when highly mycorrhizal plants are present (Chen et al ., 2005 ). Instead, we found similar degrees of AMF colonization on the focal crop host between polyculture and monoculture farms, but greater degrees of AMF colonization on other crop hosts on polyculture fields. Recent research has found mixed results about the extent to which plant host identity determines the quantity of AMF colonization. Some studies show that plant identity rarely plays a role (Lekberg & Waller, 2016 ; Van Geel et al ., 2018 ), while others, like this study, demonstrate that plant host identity does impact AMF colonization, especially at local scales (König et al ., 2010 ; Davison et al ., 2016 ; Šmilauer et al ., 2020 ). Thus, our study strengthens the body of research showing that AMF colonization is dependent on specific AMF–plant host associations. While this finding could suggest that agricultural systems with higher plant diversity may not benefit from greater AMF colonization, AMF colonization may not actually be the most important indicator of AMF benefits and functions for crops in agricultural systems (Thirkell et al ., 2017 ). Colonization does not indicate the extent of nutrient transfer or the degree of ecosystem services provided by AMF (Chagnon et al ., 2013 ). Instead, there is a growing understanding that AMF composition is an important determinant of the benefits received by ecosystems from AMF communities (Chagnon et al ., 2013 ). A richer and more diverse AMF community could indicate differences in ecosystem functioning between monoculture and polyculture farming, with important implications for agricultural management. Previous research has shown that monocultures contribute to reducing AMF richness and can change community composition to favor less beneficial AMF taxa, in turn contributing to yield declines (Johnson et al ., 1992 ). Although empirical evidence from field studies on AMF remains rare, a positive relationship between AMF diversity and ecosystem functioning is expected because AMF taxa differ in their functions (Powell & Rillig, 2018 ). For example, studies have shown differential plant productivity responses to different AMF taxa or communities (van der Heijden et al ., 1998a , 1998b , 1998a , 1998b , 2003 ; van der Heijden, 2002 ; Klironomos, 2003 ). Other studies have demonstrated that productivity, phosphorus uptake, soil aggregation and pathogen protection increase with AMF diversity (van der Heijden et al ., 1998a , 1998b , 1998a , 1998b ; Sikes et al ., 2009 ; Chen et al ., 2017 ). In short, as AMF taxa are functionally heterogenous (Chagnon et al ., 2013 ), a more diverse community could provide a wider array and/or stability of functions (Loreau et al ., 2003 ; Isbell, 2015 ). Therefore, crops grown in polycultures may benefit from the enhanced and/or stabilized ecosystem functions and services of a richer and more diverse AMF community. Conclusions Through investigating the response of AMF communities to greater crop diversity, we have demonstrated that plant host diversity shifts the available AMF community into richer and more diverse communities while soil properties structure AMF community composition. Our on‐farm approach focused on the role of polycultures – the dominant form of agriculture across many regions in the world, especially among smallholder farmers (Altieri, 1999 ; Brooker et al ., 2015 ) – allowing us to elucidate the important role that plant host diversity plays on AMF communities without the confounding reciprocal process (i.e. AMF communities influence plant communities), a common obstacle in observational studies of natural systems. Specifically, we show that polycultures doubled AMF richness in comparison to monocultures. We further find that AMF colonization is dependent on crop host identity. Together, the positive relationship between plant diversity and AMF community composition highlights the fact that vegetative diversity is essential to harnessing AMF functional diversity. Therefore, we conclude that plant diversity is key to enriching AMF communities, and that enhancing crop diversity locally on farms may allow multifunctionality to be re‐established via AMF communities in agricultural landscapes."
} | 6,069 |
33777686 | PMC7610433 | pmc | 3,386 | {
"abstract": "Photosynthetic organisms evolved different mechanisms to protect themselves from high irradiances and photodamage. In cyanobacteria, the photoactive Orange Carotenoid-binding Protein (OCP) acts both as a light sensor and quencher of excitation energy. It binds keto-carotenoids and, when photoactivated, interacts with phyco-bilisomes, thermally dissipating the excitation energy absorbed by the latter, and acting as efficient singlet oxygen quencher. Here, we report the heterologous expression of an OCP2 protein from the thermophilic cyanobacterium Fischerella thermalis ( Ft OCP2) in the model organism for green algae, Chlamydomonas reinhardtii. Robust expression of Ft OCP2 was obtained through a synthetic redesigning strategy for optimized expression of the transgene. Ft OCP2 expression was achieved both in UV-mediated mutant 4 strain, previously selected for efficient transgene expression, and in a background strain previously engineered for constitutive expression of an endogenous β-carotene ketolase, normally poorly expressed in this species, resulting into astaxanthin and other ketocarotenoids accumulation. Recombinant Ft OCP2 was successfully localized into the chloroplast. Upon purification it was possible to demonstrate the formation of holoproteins with different xanthophylls and keto-carotenoids bound, including astaxanthin. Moreover, isolated ketocarotenoid-binding Ft OCP2 holoproteins conserved their photoconversion properties. Carotenoids bound to Ft OCP2 were thus maintained in solution even in absence of organic solvent. The synthetic biology approach herein reported could thus be considered as a novel tool for improving the solubility of ketocarotenoids produced in green algae, by binding to water-soluble carotenoids binding proteins.",
"introduction": "1 Introduction Photosynthetic organisms need light to drive photosynthetic reactions, producing NADPH and ATP molecules which are essential to satisfy the metabolic demands of the cells. However, in natural environments, these organisms can easily experience rapid changes in light intensity and quality [ 1 ]. High light exposure can cause an overexcitation of the photosynthetic apparatus due to the excessive absorption of photons, that cannot be compensated by the capacity of Calvin-Benson cycle to regenerate ADP and NADP + . This condition is extremely harmful for the cell. Indeed, the excess of absorbed light cannot be properly used for charge separation, thus increasing the probability of energy transfer to oxygen molecules and finally leading to the formation of toxic reactive oxygen species (ROS) [ 1 ]. Excited and highly reactive intermediates, like ROS, have a high oxidative potential that may damage the photosynthetic apparatus, leading to photodamage or even cell death [ 1 ]. To prevent or minimize generation of such oxidizing molecules, photosynthetic organisms have evolved a wide range of photoprotective mechanisms, among which the fastest is the so called non-photochemical quenching (NPQ), which acts through the thermal dissipation of excess energy [ 1 – 3 ]. Cyanobacteria and higher plants show significant differences at the level of their light harvesting systems, despite a conserved structure of the core complex of Photosystems. In cyanobacteria, intramembranous supramolecular assemblies of phycobiliproteins, called phycobilisomes (PBS), act as light harvesting antennae [ 4 ], whereas higher plants evolved transmembrane antenna proteins called Light Harvesting Complexes (LHC), which bind carotenoids and chlorophylls [ 5 , 6 ]. LHC complexes or LHC-like proteins can be found in most of the eukaryotic photosynthetic organism, except for glaucophytes, which retained the cyanobacterial PBS, and red algae, which exploit both PBS and LHC proteins [ 7 , 8 ]. Diversity in light harvesting systems caused also a different evolution of NPQ photoprotective mechanisms. Photosynthetic organisms where LHC or LHC-like proteins are present, require some specific subunits to trigger NPQ, as LHCSR (Light Harvesting Complex Stress-related) or their close relative LHCX (Light Harvesting Complex X) and/or PSBS (Photosystem II Subunit S) proteins [ 9 – 11 ]. Either LHCSR or PSBS subunits contain protonatable residues exposed to the lumen, which are responsible for quenching activation upon lumen acidification [ 12 – 14 ]. Differently, in the case of cyanobacteria, NPQ is triggered by an Orange Carotenoid-binding Protein (OCP) [ 15 – 20 ]. Three paralog families of OCP, called OCP1, OCP2, and OCPX have been identified so far: OCPX and OCP1 share a common ancestor, whereas OCP2 and OCP1 are the result of a second divergence [ 21 , 22 ]. Genomic analysis allowed identifying OCP1 as the most widespread OCP protein with members in almost every phylogenetic subclade of cyanobacteria [ 23 ]. On the contrary OCP2 is less frequently observed in cyanobacteria genomes and in some cases both OCP1 and OCP2 can be found encoded by the same genome [ 22 ]. The third class of OCP proteins, OCPX, is usually present in genomes where OCP1 or OCP2 cannot be found [ 24 ]. OCPX is more frequently observed compared to OCP2 especially in filamentous heterocyst-forming cyanobacteria [ 24 ]. OCP is a water-soluble protein which binds a single carotenoid molecule, senses blue-light, and interacts with PBS. In particular, OCP has a crucial role in the NPQ mechanism of cyanobacteria because the OCP-PBS interaction allows inducing thermal dissipation of excess energy absorbed by the latter [ 25 , 26 ]. 3-Hydroxyechinenone has been reported as the main carotenoid bound by OCP proteins, even if other types of carotenoids and ketocarotenoids, like echinenone, canthaxanthin and zeaxanthin were also found bound to these soluble protein [ 25 ]. Among these ligands ketocarotenoids were specifically reported to be essential for OCP photoactivation and its function in photoprotection [ 25 , 27 ]. Under strong blue-green light, OCP O (orange form) is converted to OCP R (red active form), which can trigger NPQ mechanism [ 28 ]. OCP2 and OCPX red active forms can spontaneously revert to OCP O in the dark [ 22 ], whereas OCP1 needs a Fluorescence Recovery Protein (FRP) to accelerate OCP R -to-OCP O conversion reaction and for detaching from PBSs [ 29 ]. Interestingly, OCP2 and FRP genes were never found in genome where OCP1 was present [ 22 ]. OCP shows a modularity in structure; it contains an effector N-terminal domain (NTD), a sensor C-terminal domain (CTD) and a carotenoid. Both NTD and CTD present homologous gene in the majority of cyanobacteria genomes named helix carotenoid proteins (HCPs) in the case of NTD and CTDHs (CTD-like homologs) in the case of CTD [ 23 ]. The role of these proteins is still not clear at all but it is proposed that these NTD and CTD homologous can mix generating OCP-like protein with different photoprotective properties [ 15 ]. In recent years OCP function and role have acquired an increasing interest, both as a singlet oxygen ( 1 O 2 ) [ 15 ] and energy quencher in living cells, but also as an antioxidant molecule for pharmaceutical and cosmetic applications [ 30 , 31 ]. In biological systems, as plants but also animals or humans, excessive light exposure leads to the formation of ROS, that could damage biomolecules, affecting the integrity and stability of cells and tissues. Pathobiochemistry of several diseases of light-exposed tissues is indeed influenced also by these photooxidative processes [ 32 ]. For these reasons, research toward the discovery of new bioavailable antioxidant molecules is extremely active and requires the use of highly hydrophilic antioxidants. Water-soluble carotenoid binding proteins, in fact, might be suitable to this purpose, as they are able to confer hydrophilic properties to carotenoids, which otherwise would be relatively hydrophobic and embedded in biological membranes. In addition, it was recently reported the higher antioxidant power of OCP compared to vitamin C, tocopherol and isolated carotenoids [ 30 ]. Bourcier de Carbon and co-workers have reported the possibility to produce high amount of holo-OCP protein in Escherichia coli [ 31 ] however, to the best of our knowledge, stable production in green microalgae has not been achieved yet. A “green” alternative to bacteria could indeed be represented by microalgae, which are well known as highly efficient CO 2 -fixing organisms and can be cultivated in a circular economy approach, exploiting nutrients recovered from wastewaters [ 33 , 34 ]. Moreover, the possibility to efficiently manipulate metabolism in microalgae allows redirecting endogenous pathways toward the production of different molecules of interest and high-valuable compounds [ 35 – 38 ]. Recently the model organism for green algae, Chlamydomonas reinhardtii , was engineered to accumulate ketocarotenoids, as canthaxanthin and astaxanthin, suitable for human nutrition or livestock feed [ 36 ]. However, carotenoids are hydrophobic molecules requiring an organic solvent or amphiphilic environment to be maintained in solution. In this work we investigate the expression of OCP2 from Fischerella thermalis ( Ft OCP2) in a microalgal host. OCP2 was chosen among the different OCP subunits due to its previously reported spontaneous ability to revert to OCP O in the dark even in the absence of FRP [ 22 ]. F. thermalis is a thermophile cyanobacterium growing at temperature up to ~60°C presenting in its genome genes for OCP2, HCP2, HCP4 and CTDH subunits [ 22 , 39 ]. Ft OCP2 sequence was preferred to OCP2 subunits from other cyanobacteria being F. thermalis a thermophilic microorganism, suggesting a possible higher stability of the proteins encoded by its genome compared to the case of other mesophilic cyanobacteria. Here, we report the expression and purification of a functional and photoactive Ft OCP2 as a carotenoid carrier in C. reinhardtii , in order to improve carotenoids availability in aqueous solution upon extraction.",
"discussion": "4 Discussion Carotenoids are antioxidant molecules which recently raised interest for their possible use as nutraceuticals for human health [ 52 – 55 ]. Ketocarotenoids as astaxanthin or canthaxanthin are, among carotenoid molecules, those with the highest antioxidant properties, with a high potential for their application in different industrial sectors. Microalgae are primary producers of carotenoids, including ketocarotenoids, being thus considered as potential platform for sustainable production of these molecules [ 52 – 60 ]. Differently from other potential heterotrophic sources of carotenoids, as bacteria or yeasts, microalgae have the important benefit of exploiting the photosynthetic process to sustain metabolism, converting light energy into chemical energy and leading to CO 2 fixation [ 61 , 62 ]. Carotenoids are essentially hydrophobic and require an amphiphilic carrier to be maintained in aqueous solution for industrial production and application. OCP is a small soluble protein able to bind one carotenoid molecule that could be suitable to this purpose, preventing carotenoids precipitation in aqueous environment ( Fig. 4 ) [ 31 ]. OCP proteins in cyanobacteria are responsible for photoprotection, interacting with phycobilisomes and quenching the excess energy to prevent photodamage [ 63 ]. Several successful attempts to purify OCP have been performed in cyanobacteria [ 64 ] and its recombinant expression in bacteria has also been described [ 31 ]. To extend the range of possible platforms to produce carotenoid binding OCP proteins, here we report the overexpression and purification of Ft OCP protein, a member of the OCP2 protein family [ 22 ], in C. reinhardtii. Using C. reinhardtii as a host for OCP expression permits to induce the formation of OCP holoproteins bound to different carotenoids, which are not available in cyanobacteria. Moreover, the powerful synthetic biology tools recently developed in this model organism allow the application of this strategy [ 43 ]. OCP protein was successfully accumulated in Chlamydomonas without any major effect on growth, both in mixotrophy and in autotrophy, even at high light intensity ( Fig. S4 ). OCP protein has been reported to bind mainly ketocarotenoids in cyanobacteria, with 3’-hydroxyechinenone being the main carotenoid bound [ 15 , 23 , 25 , 51 ]. Here we demonstrate that Ft OCP can bind, in absence of ketocarotenoids, also loroxanthin, neoxanthin or lutein. In particular, loroxanthin was the xanthophyll for which Ft OCP showed the highest affinity ( Fig. 3 ). These results were independent of the relative concentration of loroxanthin among C. reinhardtii carotenoids, which is accumulated to a much lower level compared to other pigments, as lutein or β-carotene [ 65 ]. As mentioned above, the use of C. reinhardtii as host for OCP overexpression permit to exploit the synthetic biology tools available for this organism [ 36 , 37 , 43 ]: the expression of Ft OCP in the bkt background allowed accumulating this protein in presence of ketocarotenoids, including astaxanthin ( Figs. 2 , 3 ). The results obtained from Ft OCP expressed in ocp \n 1 - bkt \n 1 confirms that Ft OCP preferentially binds ketocarotenoids ( Fig. 3 ) and for the first time, to the best of our knowledge, demonstrate the possible direct binding of astaxanthin to a OCP2 subunit ( Fig. 3 ). Indeed, while astaxanthin was reported to bind a novel water-soluble carotenoid binding protein, named AstaP, found in an eukaryotic microalgal strain [ 66 ], the affinity of OCP1, OCP2 or OCPX for this ketocarotenoids was not investigated so far. As previously reported, only in the presence of ketocarotenoids, including astaxanthin, recombinant Ft OCP behaved as a photoswitchable protein in presence of blue light ( Fig. 5 ). Astaxanthin or canthaxanthin, or both, are thus able to allow OCP conformational change into the OCP R form. Moreover, the ability to solubilize carotenoids in a water-based solution was confirmed also in the case of ketocarotenoid binding Ft OCP ( Fig. 4 ). Interestingly, neither accumulation of Ft OCP nor ketocarotenoids biosynthesis influenced the biomass production rate of C. reinhardtii ( Fig. S4 ). This result allows considering C. reinhardtii as an optimal host for the expression of OCP, which could act as a carrier of ketocarotenoids in aqueous solution. Metabolic engineering of C. reinhardtii for the production of astaxanthin has been recently reported as a promising step toward efficient and sustainable industrial production of ketocarotenoids for human nutrition, aquaculture or animal feed [ 36 ]. Overexpression of OCP in this strain allows further improvement of C. reinhardtii as ketocarotenoid production platform, opening the possibility to keep astaxanthin and canthaxanthin in aqueous solution upon extraction, for specific application requiring the absence of membranes or organic solvents. However, proper optimization of OCP accumulation and its purification from engineered C. reinhardtii strains are required to make this process feasible at industrial scale. Possibly, other carotenoid binding proteins can be considered as soluble carrier for carotenoids/ketocarotenoids as for instance the C-terminal domain-like carotenoid proteins (CCPs): these subunits are homologs to the C-terminus of the OCP proteins and where recently characterized as a new class of soluble carotenoid binding proteins being able to bind canthaxanthin. Overexpression of CCPs subunits in C. reinhardtii might lead to a further carrier for ketocarotenoids [ 67 ]. It is also important to note that the ability to switch from the inactive to active form of Ft OCP expressed in bkt background could allow the use of this holoprotein as a blue light-dependent molecular switch, to be used upon further engineering steps for regulating and studying gene expression or other cell activities [ 68 ]."
} | 3,986 |
19818022 | null | s2 | 3,387 | {
"abstract": "The initial encounter between a microbe and its host can dictate the success of the interaction, be it symbiosis or pathogenesis. This is the case, for example, in the symbiosis between the bacterium Vibrio fischeri and the squid Euprymna scolopes, which proceeds via a biofilm-like bacterial aggregation, followed by entry and growth. A key regulator, the sensor kinase RscS, is critical for symbiotic biofilm formation and colonization. When introduced into a fish symbiont strain that naturally lacks the rscS gene and cannot colonize squid, RscS permits colonization, thereby extending the host range of these bacteria. RscS controls biofilm formation by inducing transcription of the symbiosis polysaccharide (syp) gene locus. Transcription of syp also requires the sigma(54)-dependent activator SypG, which functions downstream of RscS. In addition to these regulators, SypE, a response regulator that lacks an apparent DNA binding domain, exerts both positive and negative control over biofilm formation. The putative sensor kinase SypF and the putative response regulator VpsR, both of which contribute to control of cellulose production, also influence biofilm formation. The wealth of regulators and the correlation between biofilm formation and colonization adds to the already considerable utility of the V. fischeri-E. scolopes model system."
} | 338 |
28435803 | PMC5374263 | pmc | 3,391 | {
"abstract": "Highlights • The droplet culture of cyanobacteria showed little toxicity using dodecane. • The oil phase protects the medium from drying and increases CO 2 supply. • Single cell encapsulation and culture can be a powerful tool in mutant selection.",
"conclusion": "4 Conclusions In this study, droplet cultures were constructed using dodecane as an oil phase with little observed cytotoxicity. The oil phase resulted in an increased CO 2 supply to the droplet medium, and specific growth rates were higher compared to those observed for liquid cultures grown under normal air conditions. We anticipate that droplet culture can be applied to high-throughput screening for the acquisition of useful mutants, such as high-growth strains and strains resistant to specific metabolic products. In addition to these applications, we hope this method can be applied to single colony isolation for other microalgae that are able to fix CO 2 and are difficult to grow on agar plates due to drying.",
"introduction": "1 Introduction Photosynthetic microorganisms, including cyanobacteria and microalgae, have attracted a growing interest in biofuel production. These organisms are efficient at converting solar energy and recycling CO 2 , and thus, biofuel production does not compete with agriculture for water, fertilizer, and arable land. Estimates suggest that nearly 50% of the global net primary fixation of carbon by photosynthesis occurs in ocean waters dominated by phytoplankton. For these reasons, there is an increasing interest in utilizing photosynthetic microorganisms to fix CO 2 and produce biofuels. Photosynthesis-driven conversion of carbon dioxide to biofuels and biochemicals using genetically modified cyanobacteria has previously been investigated [1] , [2] , [3] , [4] , [5] . For example, ethanol, 1-butanol, and isobutyraldehyde (a precursor to isobutyl alcohol) have been produced directly from CO 2 \n [3] , [4] , [5] . Cyanobacteria are attractive candidates for biofuel production, since genome characterization has facilitated genetic engineering of host cells [6] . To improve biofuel productivity, it is important to develop an effective screening method for the selection of useful mutants. The general approach for mutant screening involves cell isolation following colony formation in agar nutrient media, followed by the identification of target mutants by evaluating their activity after culturing in liquid media. For a long time, “toothpicks and logic” were considered sufficient for screening [7] . However, cell isolation on agar plates cannot be carried out efficiently for organisms with low growth rates and/or low colony-forming ratios. In cyanobacteria, the doubling time for Synechococcus elongatus \n PCC7942 is more than 10 h (with 5% CO 2 bubbling), and the number of colonies formed in a solid medium is less than 10% of the number of cells before plating. A significant amount of time is required for culturing single cells into colonies that are large enough to visualize and select from agar plates. This inherently limits the throughput of mutant screening. To address this problem, some have proposed methods for encapsulating single cells in aqueous droplets [8] , [9] , [10] and agarose microparticles [11] . In this study, encapsulation of cyanobacteria in a droplet culture was investigated for cell screening without colony formation on agar plates. Using glass slides printed with highly water-repellent mark, we conducted micro-compartmentalized cultivation from single cyanobacteria cells by covering microdroplets in an oil phase. This oil phase can protect small volumes of culture medium from drying and increase the transfer of CO 2 from the air to cells, since, it has a higher absorption constant than water. This micro-compartmentalized culture method offers promise for the screening of useful cyanobacteria mutants, such as high growth strains and strains resistant to specific metabolic products, and for single colony isolation for many kinds of microalgae that can fix CO 2 .",
"discussion": "3 Results and discussion 3.1 Selection of oil For the selection of an oil phase for micro-compartmentalized cultivation, S. elongatus in stationary phase were incubated for three days with an overlay of oil. The cell death rate of S. elongatus increased consecutively according to treatments with dodecane, mineral oil, oleyl alcohol, and oleic acid; in the case of oleic acid, dead cells comprised 28% of the sample ( Fig. 2 ). Little toxicity was observed with an overlay of dodecane, with only 2% dead cells. Although both dodecane and mineral oil had low toxicity, dodecane has high CO 2 absorption. The abilities of dodecane and mineral oil to absorb CO 2 are approximately 1.7 and 1.1 times higher than that of water, respectively [14] , [15] . Dodecane, the oil with the lowest recorded cytotoxicity and high CO 2 absorption, was subsequently used for micro-compartmentalized culture. Fig. 2 The percentage of dead cells in the presence of oil. Cyanobacteria in the stationary phase were incubated with an overlay of dodecane, mineral oil, oleyl alcohol, or oleic acid in the presence of light (50 μmol photons m −2 s −1 ). After three days, cells were stained with YO-PRO and the numbers of live and dead cells were estimated by tallying counts of red and green cells, respectively, using fluorescence microscopy. To examine the influence of dodecane on cell growth in test tubes, S. elongatus was cultured with overlaid dodecane supplied with 5% CO 2 . When S. elongatus was cultivated under 5% CO 2 , the specific growth rate increased 2.4-fold compared to that in normal air conditions. The specific growth rate increased a further 3.5-fold when cultivated under 5% CO 2 with an overlay of dodecane ( Fig. 3 ). We assume that the CO 2 supply into the culture medium was enhanced in conditions with an overlay of dodecane. Consequently, an increase in cell growth was observed in cultures grown under 5% CO 2 with overlaid dodecane. Fig. 3 The effect of 5% CO 2 supply and a dodecane layer on growth in test tubes. S. elongatus was cultured by exposing the test tube to air or 5% CO 2 . Furthermore, the strain was cultured with dodecane overlaid in 5% CO 2 . The y -axis shows the relative value of the specific growth rate. Each value was normalized by the specific growth rate without dodecane in air. 3.2 Micro-compartmentalized droplet cultivation Droplet cultures of S. elongatus were investigated using glass slides printed with highly water-repellent marks measuring 1 mm in diameter. To examine the CO 2 concentration of dodecane-overlaid cultures, approximately 15 cells/droplet of S. elongatus were introduced in air (0.04% CO 2 ), 1.8% CO 2 , or 5% CO 2 conditions. Although little increase in cell growth was observed under the 1.8 and 5% CO 2 conditions, cell growth was confirmed when cultured in air ( Fig. 4a ). Cell growth could be observed using fluorescence microscopy. Holes containing divided cells were detected as an enhanced fluorescence signal ( Fig. 4b ). Cell growth increased under 5% CO 2 in test tube cultures. The difference in suitable CO 2 conditions for cultures might be associated with differences in the specific surface area (the ratio of the interfacial area with dodecane to the volume of medium) in the droplet culture and test tube culture. An arrest of cell growth in the droplet culture whose specific surface area was large was considered to be due to a decrease in the pH of the medium following excessive adsorption of CO 2 . When phenol red was added to droplets with an overlay of dodecane, the color of the medium changed from red to yellow (indicating a decrease in the pH below 6.8) in 5% CO 2 conditions. We observed that cell growth in droplet culture with overlaid dodecane did not require CO 2 enrichment in the gas phase. Fig. 4 The growth of S. elongatus at different CO 2 conditions in droplet culture with an overlay of dodecane. (a) The growth ratio of droplet cultures in the air, 1.8% CO 2 and 5% CO 2 . Growth ratios were calculated by dividing number of cells at day 4 by the number of cells at day 0. Approximately 15 cells were in each droplet at the beginning of the experiment. (b) Fluorescence images of droplet cultures in the air. When S. elongatus was cultured in air, the specific growth rate of droplet cultures (0.336 day −1 ) was approximately 1.4 times higher than that of normal liquid cultures without dodecane in 18 mm test tubes (0.240 day −1 ). In other words, the doubling time of droplet cultures and test tube cultures was 50 and 69 h, respectively, without shaking under air conditions. Another conventional method is the use of a solid culture with agar medium, which takes 2 weeks to form colonies. In contrast, the droplet culture requires less than 1 week because temporal observations are possible for evaluating cell growth. In addition to growth improvement, the number of colonies formed in droplet culture was approximately 70% whereas that in solid culture was less than 10% of the number of cells before culture. Therefore, we concluded that micro-compartmentalized droplet cultivation of S. elongatus was successfully conducted using dodecane as the organic solvent phase. 3.3 Single-cell culture of S. elongatus with addition of antibiotics Cell growth was evaluated for cyanobacteria cultured under conditions of 1 cell/droplet using the droplet culture method. S. elongatus was cultured in the presence or absence of chloramphenicol. A concentration of 15 μg/mL chloramphenicol was used; this concentration is sufficient for arresting cell growth in test tube cultures. Fig. 5 shows the population of compartmentalized cells within each droplet. Approximately 30% of droplets contained single cells. The percentage of droplets containing zero, two, or three cells was 8, 23, and 18%, respectively. After culturing droplets for two and four days, cell growth was evaluated using fluorescence microscopy. In cultures without chloramphenicol, we could confirm growth from single cells. We observed changes in the cell population for each droplet. After two days of culturing, 48% of droplets contained five or more cells. After four days of culturing, this number further increased and approximately 72% of droplets contained more than five cells. On the other hand, little growth was observed for cultures grown with chloramphenicol. Following the addition of antibiotics, changes in the cell population for each droplet indicated that the droplet cultivation method could be applied to mutant screening after transformation. Furthermore, daughter cells were observed to divide near parent cells ( Fig. 4 , Fig. 5 ). Therefore, even if all droplets did not contain single cell, cell growth could be continuously observed under the microscope. Fig. 5 The growth of S. elongatus in the presence or absence of chloramphenicol. (a) Fluorescence images of droplet cultures using normal BG11. (b) Fluorescence images of droplet cultures using BG11 with 15 μg/mL chloramphenicol. (c) Changes in the cell populations of each droplet cultured using normal BG11. The cells in each of 27 droplets were counted. (d) Changes in the cell populations of each droplet cultured using BG11 with 15 μg/mL chloramphenicol. The cells in each of 30 droplets were counted."
} | 2,833 |
32995524 | PMC7445765 | pmc | 3,392 | {
"abstract": "Abstract Synthetic biology holds significant potential in biomaterials science as synthetically engineered cells can produce new biomaterials, or alternately, can function as living components of new biomaterials. Here, we describe the creation of a new biomaterial that incorporates living bacterial constituents that interact with their environment using engineered surface display. We first developed a gene construct that enabled simultaneous expression of cytosolic mCherry and a surface-displayed, catalytically active enzyme capable of covalently bonding with benzylguanine (BG) groups. We then created a functional living material within a microfluidic channel using these genetically engineered cells. The material forms when engineered cells covalently bond to ambient BG-modified molecules upon induction. Given the wide range of materials amenable to functionalization with BG-groups, our system provides a proof-of-concept for the sequestration and assembly of BG-functionalized molecules on a fluid-swept, living biomaterial surface.",
"introduction": "1. Introduction Advances in biological engineering and materials science have enabled the creation of new biomaterials capable of integrating with living systems and augmenting their behavior. 1 In contrast to biocompatible materials, which have been utilized for millennia, 2 modern biomaterials are engineered with enhanced functionality. The materials are able to selectively augment living microenvironments such as the tumor ecosystem 3 and local environment surrounding neural implants. 4 With a deepening understanding of cellular biology and material interactions, 5 biocompatible materials such as polyethylene and bio-inert alloys like titanium 6 , 7 have given way to more nuanced bioactive materials such as microbial resistant hydroxyapatite 8 and degradable conductive polymers. 9 , 10 Taken as a whole, biomaterials show great promise in not only medicine, 11–13 but also bioprocessing and drug development. 14 Simultaneously, the field of synthetic biology has given scientists and engineers the ability to selectively control the behavior of living cells. From the foundational genetic toggle switch 15 and repressilator 16 to more intricate circuit topologies such as predator–prey systems, 17–21 the field has developed to include a broad library of genetic circuits and constructs. In the process, synthetic biology has yielded insight into fundamental biological principles 22 while enabling unprecedented bioprocessing 23 and disease diagnostic 24 advances. Furthermore, synthetic biology has allowed scientists and engineers to begin to develop new biomaterials, designed at both a material and genetic level. 25 , 26 These biomaterials show great promise, combining the advantages of self-replicating life with genetically engineered behavior. Deliberate biofilm dispersion 27 and nanoscale material fabrication 28 , 29 are just a few of the exciting new directions for synthetic biology in the creation of self-healing, adaptive or responsive living materials. Here, we report the development of a biomaterial surface coating consisting of living cells capable of sequestering chemicals from their environment. This material is based on a synthetic system for outputting intracellular genetic events through the surface-display of enzymes. The cellular envelope of Escherichia coli is made up of two phospholipid bilayers—the outer surface membrane and cytoplasmic membrane—separated by the periplasmic space. 30 With this structure in mind, we designed and built synthetic components consisting of chimeric fusion proteins that could embed in the cellular envelope and reliably display a functionally active enzyme on the E. coli surface. Although there are many protein structures that span both membranes, we leveraged an existing engineered surface-display anchor that presents protein structures extracellularly, anchors within the cellular envelope and does not interact with the inner plasma membrane. 30 This chimeric fusion protein, lpp-ompA, enables C-terminal fusion and display of large proteins. 31 It was first successfully demonstrated to express β-lactamase on the surface of E. coli , 32 and consists of the first nine N-terminal amino acids of a lipoprotein (lpp) fused to amino acids 46–159 of outer membrane protein A (ompA). We created a new fusion protein based on lpp-ompA, allowing us to express modified human O 6 -alkylguanine DNA alkyltransferase (hAGT), also known as the SNAP-tag, on the surface of Gram-negative bacteria. SNAP is a useful tool in tagging functional proteins in living cells, with capabilities that complement other protein tags such as the polyhistidine tag, GFP or other fluorescent proteins. 33 SNAP forms a covalent bond with benzylguanine (BG) groups in its environment. The SNAP-tag was derived from O 6 -alkylguanine-DNA-alkyltransferase (AGT), a human DNA repair enzyme. 34 AGT’s binding affinity for BG was initially demonstrated in 2003 by Keppler et al. 34 and was later improved in 2006 by Gronemeyer et al. , 35 resulting in an optimized protein (SNAP) with a 50-fold increase in affinity for BG. The SNAP-tag has since been widely utilized in a variety of studies ranging from medical applications, such as tumor targeting 36 , 37 and drug delivery, 38 to basic scientific research on protein network and interactions. 39 , 40 In 2010, E. coli cells expressing SNAP in their cytosol demonstrated successful live labelling with BG-MR121 fluorescent dyes. 41 Beyond this previous study, there has been minimal use of the SNAP-tag technology in bacteria. By fusing SNAP with the lpp-ompA protein, we engineered E. coli with a surface-displayed, BG-binding enzyme. The genetic construct endowed cells with a phenotypic expression platform spatially discrete in comparison to traditional cytosolic fluorescent proteins. Additionally, the construct conferred an inducible ability that enabled cells to be selectively labelled by BG-modified fluorescent chemical dyes while simultaneously upregulating intracellular fluorescent protein (i.e. mCherry) expression. As BG-modified dyes cannot be transported into the bacterial cytosol due to size constraints, the results described in this work confirmed that the SNAP enzyme was transported to the cell’s surface, while providing a new method for selectively discretizing surface and cytosolic genetic outputs in bacteria. In other synthetic biology studies, genetic circuit outputs have been coupled to regulatory gene circuits to probe how regulation dynamics and cellular behavior change over time. 15 , 16 Here, we focused on utilizing the spatial heterogeneity of the cell (i.e. the spatial domains associated with the cytosol and the outer membrane) to engineer synthetic gene constructs to deliberately form a biomaterial.",
"discussion": "4. Discussion The creation of new biomaterials using the tools of synthetic biology has emerged as an important thrust in biomaterials engineering. 26 , 45 Many approaches have focused on engineering living cells to synthesize one or more components of an eventual biomaterial. 46 , 47 Alternatively, cells can be programmed to produce molecules that interfere with biomaterial assembly. 48 In both these synthesis and interference approaches, the cell’s ability to function as a molecular factory is leveraged. In other materials science approaches, cells themselves can be embedded as constituents within the biomaterial. 49 In the results presented here, we have engineered a fluid-swept bacterial surface with an ability to bond to small molecules in its environment upon induction. These results describe a synthetic component, an E. coli surface-displayed SNAP ® enzyme, along with an approach to using this component in microfluidic devices that demonstrates its use as a nucleation point for biomaterials assembly in microfluidic systems. Here, the surface-displayed enzyme bonded to BG-modified fluorescent dye molecules. However, straightforward chemistry and widely available BG-linkers allow a broad range of macromolecules to be BG-linked. Thus, these results potentially can be leveraged by others for inducible sequestration of other BG-modified macromolecules. Although this BG-modification requirement is a limitation of the system presented here, one advantage this system is its robust function under flow conditions in microfluidic devices. Other proteins can be potentially surface-displayed by modifying the synthetic construct reported here, potentially for extracellular chemical catalysis 50 or alternatively, as an antigen nucleation point for biomaterials assembly based on antibody–antigen interactions. 51 Another limitation of this system is the random patterning of living cells in the microfluidic device. The primary focus of the work presented here is the demonstration of an extracellular genetic output that can interact with the cell’s environment. Fortunately, multiple other studies have focused on different approaches to cellular patterning using synthetic biology. 52 , 53 These systems could potentially be combined to create patterned biomaterials with living constituents that bond to extracellular small molecules. The field of synthetic biology has allowed for the programmable control of cellular behaviors through the use of genetic components and their interactions. 54 Most of these components are expressed either in the cytosol or, if cell–cell communication is involved, by the movement of signaling molecules out of the cell where neighboring cells may detect them using quorum-sensing strategies. 17 , 55 In contrast to these approaches, we used the cell’s ability to spatially compartmentalize protein output to enable biomaterial formation. Leveraging synthetic behaviors compartmentalized on the cell surface allowed us to create a nucleation point for molecular assembly that is spatially separated from phenotypic changes in the cell’s cytosol. Through this approach, we were able to form a biomaterial that can sense a small molecule using synthetic machinery in the cytosol while assembling a material using surface-displayed synthetic machinery. Beyond biomaterial formation, this technology could be utilized for other synthetic biology applications. For example, by building upon the BG-binding membrane system, this platform could be used for cell sequestration of a range of species of interest. For example, if BG-functionalized antibodies were introduced to the fluid system, antigens that can be targeted with antibodies could be sequestered from the bulk flow. Furthermore, this tool could be adapted and deployed with cell-free expression technology, an area where there has been successful demonstration of the localization of expressed proteins to the surface of the vesicles, 56 as well as α-hemolysin pore formation on the phospholipid bilayer. 57 The work presented here can serve as an enabling technology for biomaterial synthesis and assembly. By engineering living cells that can sense, respond, and draw molecules from the local environment as the building blocks for a biomaterial, we experimentally validated a strategy for material formation using surface-displayed synthetic biology. Furthermore, by exploiting synthetic gene constructs that enable cytosolic sensing and surface-display-based material formation, we have shown how synthetic biology may leverage spatial compartmentalization for discrete functions in the same cell. We envision our living biomaterial being used in a range of applications from biomaterial formation to biomolecule sequestration."
} | 2,899 |
38292616 | PMC10823519 | pmc | 3,395 | {
"abstract": "Elastomers are widely\nused in textiles, foam, and rubber, yet they\nare rarely recycled due to the difficulty in deconstructing polymer\nchains to reusable monomers. Introducing reversible bonds in these\nmaterials offers prospects for improving their circularity; however,\nconcomitant bond exchange permits creep, which is undesirable. Here,\nwe show how to architect dynamic covalent polydiketoenamine (PDK)\nelastomers prepared from polyetheramine and triketone monomers, not\nonly for energy-efficient circularity, but also for outstanding creep\nresistance at high temperature. By appending polytopic cross-linking\nfunctionality at the chain ends of flexible polyetheramines, we reduced\ncreep from >200% to less than 1%, relative to monotopic controls,\nproducing mechanically robust and stable elastomers and carbon-reinforced\nrubbers that are readily depolymerized to pure monomer in high yield.\nWe also found that the multivalent chain end was essential for ensuring\ncomplete PDK deconstruction. Mapping reaction coordinates in energy\nand space across a range of potential conformations reveals the underpinnings\nof this behavior, which involves preorganization of the transition\nstate for diketoenamine bond acidolysis when a tertiary amine is also\nnearby.",
"conclusion": "Conclusions We find that PDK elastomers address ongoing\nchallenges in the creation\nof highly recyclable yet mechanically stable rubbers that remain thermoformable,\ndue to their dynamic covalent cross-links. Elastomers prepared from\ncommercially available pTHF-diamine soft segments contain exchangeable\nbonds that permit remolding, but their inability to undergo chemical\nrecycling led us to discover that heteroatom proximity to the diketoenamine\nbond is required to enable depolymerization. Covalently attaching\nTREN moieties to the soft segment restored the ability to undergo\nmonomer-to-monomer chemical recycling, and it also produced unexpected\ncreep resistance that could not be achieved with the analogous PDK-monovalent\nformulation. This study advances fundamental insights into the macromolecular\ndesign of high-performance cross-linked elastomers that are amenable\nto circular manufacturing. We anticipate leveraging this platform\nin the future, both to broaden the range of properties exhibited and\nto enable chemical recycling of more complex products featuring circular\nPDK elastomers alongside other materials.",
"introduction": "Introduction Cross-linked elastomers and rubbers have\nbroad commercial and industrial\nuses due to their thermal, chemical, and mechanical stabilities. These\nstabilities make deconstructing them to their original monomers a\npersistent challenge, yet important for a circular plastics economy. 1 , 2 Elastomer networks featuring reversible bonds open the door to chemical\nrecycling. 3 − 9 However, most fail to close the loop upon deconstruction: more often,\nchemical recycling returns fragments of the network rather than monomers. 10 − 14 Chemical recycling to monomer has been most successful when networks\nare cross-linked using dynamic covalent bonds that can be cleaved\nsolvolytically. 15 − 21 However, bond exchange reactions inherent to dynamic covalent elastomers\nalso promote creep and the materials exhibit poor mechanical stability\nin load-bearing environments, particularly at elevated temperature. 22 Controlling viscous flow to minimize or eliminate\ncreep in future generations of circular elastomers therefore requires\nmore careful consideration, not only of the reversible bond but also\nof the network architecture. 23 − 26 Ideally, short-range bond exchange kinetics and long-range\nviscoelastic flow can be uncoupled. Here, we show how to architect\ncircular polydiketoenamine (PDK)\nelastomers and carbon black reinforced PDK rubbers to resist creep\nby tailoring the valency at cross-linking sites associated with flexible\npolyetheramine segments within the network ( Figure 1 ). Notable in our designs, diketoenamine\nbonds retain their ability to participate in short-range bond exchange,\nenabling thermoforming during manufacturing and stress relaxation\nupon strain; however, viscoelastic flow over longer length scales\nis disfavored due to the multiplicity of anchor points to the network,\nwhich render the elastomers exceptionally resistant to creep, even\nat high temperature. Interestingly, we found that the end-group structure\nof the polyetheramine soft segments, herein referred to as macromers,\nalso dictated the rate of PDK depolymerization during chemical recycling:\nwhereas monovalent polyetheramine macromers producing creep-susceptible\nPDK elastomers were slow to depolymerize, multivalent polyetheramine\nmacromers producing creep-resistant PDK elastomers were completely\ndepolymerized within 24 h. This enabled facile recovery of the multivalent\npolyetheramine macromer and triketone monomer in high yields with\nhigh purity, permitting their reuse in subsequent manufacturing cycles.\nTo understand this behavior, we developed a theoretical framework\nto explore reactive conformations along the reaction coordinate in\nPDK hydrolysis. In doing so, we identified the key role played by\na proximal ionized amine, exclusive to the multivalent polyetheramine\nend group, that preorganizes the transition state associated with\nthe rate-limiting step, lowering the standard free energy of activation\n(Δ G ‡ ) by 13 kJ mol –1 for diketoenamine hydrolysis in strong acid. Transition-state preorganization\nemerges with due importance in achieving high efficiency and low-carbon\nintensity in PDK chemical recycling. This work advances macromolecular\ndesign of elastomeric soft segments in chemically recyclable dynamic\ncovalent thermosets that simultaneously enable mechanical stability\nand depolymerization to monomer. Given the vast chemical space available\nto both polyetheramine and triketone monomers, we envision the knowledge\ngleaned in this work can be exploited for codesigning future elastomers\nand rubbers on the basis of both performance and circularity in chemical\nrecycling. Figure 1 PDK elastomer formulation and stress–strain behavior. (A)\nExamples of commercial products that incorporate cross-linked elastomeric\ncomponents that are challenging to recover and recycle. (B) Schematics\nof macromer, monomer, and corresponding polymer network structure\nfor PDK-multivalent and PDK-monovalent. (C) Macromer and monomer structures\nfor multivalent soft segment, poly(tetrahydrofuran)-bis-tris-2(aminoethyl)amine\n(pTHF-bis-TREN); triketone, 2,2′-decanedioyl-bis(5,5-dimethylcyclohexane-1,3-dione)\n(TK-10); monovalent soft segment, poly(tetrahydrofuran)-diamine (pTHF-diamine);\nTREN, tris-2(aminoethyl)amine. (D) Stress–strain plots for\nPDK-multivalent (strain at break = 104%, tensile strength at break\n= 1.14 MPa, toughness = 0.785 MJ m –3 ) and PDK-monovalent\n(strain at break = 268%, tensile strength at break = 0.257 MPa, toughness\n= 0.499 MJ m –3 ).",
"discussion": "Results\nand Discussion PDK Elastomer Synthesis and Formulation PDK resins\nare created from a wide variety of polytopic triketone and amine macromers\nand/or monomers via spontaneous polycondensation (i.e., click) reactions. 27 Until now, our navigation of monomer chemical\nspace has produced exclusively rigid vitrimers, whose glass transition\ntemperatures ( T g ) of 70–150 °C\nprioritized their use to applications requiring strength and structural\nintegrity in that working temperature range. 27 − 29 We hypothesized\nthat, by incorporating flexible amine macromers into the network,\nit would be possible to explore new regions of chemical space to seek\nthe subambient temperature T g and impart\nelasticity to the network architecture. If successful, the circularity\nafforded by PDK materials would extend to a broader range of useful\npolymeric materials, particularly elastomers and reinforced rubbers\n( Figure 1 A). The manner in which flexible amine macromers should be integrated\ninto PDK networks is nontrivial, given the tendency of elastomers\nto creep in polymer networks cross-linked with dynamic covalent bonds. 22 , 30 , 31 We hypothesized that, by increasing\nthe valency of amine end groups in the flexible amine macromer, it\nwould be possible for PDK networks to retain their ability to engage\nin short-range bond exchange reactions; however, long-range viscoelastic\nflow responsible for creep would be disfavored due to the large number\nof anchor points of the amine macromer to the larger network architecture.\nTo test this hypothesis, we designed and synthesized flexible polyetheramine\nmacromers with multivalent amine end groups. Specifically, we transformed\nthe chain ends of polytetrahydrofuran diol (pTHF-diol) to the corresponding\nmesylates prior to reaction with tris(2-aminoethylamine) (TREN) to\nobtain the target macromer, pTHF-bis-TREN. We then prepared cross-linked\nPDK elastomers from pTHF-bis-TREN and a triketone monomer (TK-10)\nseparately synthesized from dimedone and sebacic acid ( Figure 1 B,C). The amine-to-triketone\nmolar ratio was 1.3:1, and solid samples of these multivalent PDK\nelastomers (PDK-multivalent) were obtained within 30 s of polymerization\nat 60 °C in THF. As a control, to understand the impact of PDK\nnetwork architecture and macromer end-group structure on thermomechanical\nproperties and efficiency of recycling circularity, we also prepared\ncross-linked PDK elastomers (PDK-monovalent) from pTHF-diamine (i.e.,\na flexible polyether amine macromer with monovalent amine end groups),\nTREN as the cross-linker, and TK-10. We matched the pTHF weight fraction\nbetween the two formulations as closely as possible (75% w/w for PDK-monovalent\nvs 76% w/w for PDK-multivalent) and again set the total amine-to-triketone\nmolar ratio to 1.3:1 for PDK-monovalent. Polymerized samples were\neasily remolded into defined shapes by pressing in Teflon molds at\n150 °C and 60 psi for 5 min ( Figure S1 ). This method produced a high gel fraction for the monovalent and\nmultivalent formulations (94.1 and 96.3%, respectively). We then performed\ntensile stress–strain measurements as an initial investigation\nof mechanical properties ( Figure 1 D). PDK-multivalent had a lower elongation at break\nrelative to PDK-monovalent (104% vs 268%) yet maintained significantly\nhigher tensile strength (1.14 MPa vs 0.257 MPa) and toughness (0.785\nMJ m –3 vs 0.499 MJ m –3 ). These\nresults suggested a strong dependence between network architecture\nand properties in PDK elastomers, motivating a deeper investigation\ninto their rheological behavior. Soft Segment Chain-End\nStructure Determines Cross-Linking and\nStress Relaxation in PDK Elastomers To test the second part\nof our hypothesis, pertaining to long-range viscoelastic flow, we\nperformed a series of rheology experiments to reveal how amine macromer\nvalency within the PDK network architecture dictates the modulus and\ntransient flow behavior of the materials ( Figure 2 ). To study the interactions between the\nnetwork and reinforcing fillers, we further carried out each PDK polycondensation\nin the presence of 0.5 wt % carbon black, which produced black-pigmented\ncarbon-reinforced PDK rubbers with essentially quantitative incorporation\nof the filler. Similar to the unfilled PDK formulations, the carbon-reinforced\nrubbers were amenable to thermoforming at 150 °C and 60 psi,\nproducing samples that conformed to Teflon molds after 5 min of processing\n( Figure S1 ). This confirmed part of our\ninitial hypothesis in that short-range diketoenamine bond exchange\nremained feasible for all materials in this study. We carried out\nthese experiments between 30 and 150 °C, which is above the temperature\nof all thermal transitions in both PDK elastomers and rubbers, as\nobserved by differential scanning calorimetry (DSC; Figures S2 and S3 ). Figure 2 Rheological characterization of PDK elastomers.\n(A) Frequency sweep,\n(B) amplitude sweep, and (C) stress relaxation measurements for PDK-multivalent\nelastomers. (D) Frequency sweep, (E) amplitude sweep, and (F) stress\nrelaxation measurements for PDK-monovalent elastomers. Frequency sweep measurements quantifying the storage modulus\n( G ′) and loss modulus ( G ″)\nfor PDK-multivalent elastomers showed no crossover point in G ′/ G ″ over the measured frequency\nrange and minimal frequency dependence on the modulus ( Figure 2 A). The modulus of PDK-multivalent\nelastomers was 200 kPa at 30 °C and increased slightly to 210\nkPa at 110 °C. Notably, at 150 °C, the modulus nearly doubled\nto 390 kPa ( Figure 2 B). Our observation of G ′ increasing with\ntemperature is consistent with previous reports for polymer networks\nthat engage in associative bond exchange. 32 , 33 Moreover, we note that this phenomenon in well-described by rubbery\nelasticity theory, 34 which states that\nthe force ( f ) required to deform a network is related\nto temperature and the change in entropy with sample length ( L ) through the equation 1 Since conformational entropy decreases when\na polymer network is\ndeformed, f becomes a positive quantity. We further\nrelate temperature ( T ) to the storage modulus ( G ) as 2 where\nν is network strands\nper unit volume and k B is Boltzmann’s\nconstant, demonstrating the direct proportionality between G and T . 34 Surprisingly,\nhowever, we observed the opposite trend with PDK-monovalent elastomers,\nfor which G ′ decreased monotonically with\ntemperature. Compared to the modulus for PDK-multivalent elastomers,\nthe modulus for PDK-monovalent elastomers showed a strong frequency\ndependence, which indicates relatively shorter network relaxation\ntimes due to higher chain mobility ( Figure 2 D). 35 , 36 We also noted a G ′/ G ″ crossover at 150 °C,\nfurther confirming that, at elevated temperature, chain mobility is\nhigh enough to permit long-range viscous flow. Critical to understanding\nthis trend is the observation that the\nmodulus for PDK-monovalent elastomers at 30 °C (190 kPa) ( Figure 2 E) is comparable\nto that for PDK-multivalent elastomers (200 kPa) ( Figure 2 B) at the same temperature,\ndespite PDK-monovalent elastomers containing less TREN as a cross-linker.\nThis suggests that, at relatively low temperature, noncovalent entanglements\nmanifest in PDK-monovalent networks that increase the apparent cross-link\ndensity (ν). We calculated the cross-linking density for both\nformulations from the equation 3 where 4 Here, ρ is\nbulk density, R is the gas constant, T is absolute temperature,\nand G is the shear storage modulus at 30 °C.\nWe obtain ν = 3.32 × 10 –5 mol g –1 for PDK-monovalent and ν = 3.59 × 10 –5 mol g –1 for PDK-multivalent, confirming comparable\ncross-linking densities for both formulations. As the temperature\nincreases, excess amines can participate in\ndiketoenamine bond exchange reactions to disentangle the linear segments\nwithin the network, allowing it to reach an equilibrium state with\ncomparatively lower ν and thus a lower observed modulus. By\ncontrast, PDK-multivalent elastomers have a higher density of covalent\ncross-links by virtue of the pTHF-bis-TREN multivalent chain-end structure,\nwhich appears to dominate over any loss of noncovalent network entanglements\nassociated with diketoenamine bond exchange. We observed further\nevidence that network reorganization is facile\nfor PDK-monovalent elastomers by comparison with PDK-multivalent elastomers\nin the stress relaxation data for both ( Figure 2 C,F). Stress relaxation in PDK-multivalent\nelastomers did not follow a simple exponential decay, suggesting far\nmore complex behavior associated with its relaxation than conventional\nmodels account for, e.g., extracting the activation energy (Arrhenius)\nor standard free energy of activation (Eyring) for bond exchange. 34 , 37 Instead, we compared the relative rates of relaxation between PDK-multivalent\nand PDK-monovalent elastomers, noting that the characteristic time\nfor PDK-monovalent to relax to a reduced modulus of e –1 is greater than 2 orders of magnitude faster than that for PDK-multivalent.\nWe observe a two-step relaxation process in PDK-multivalent networks\nrepresenting the presence of relatively fast and slow exchanging network\nsegments, 38 compared to a single-step relaxation\nfor PDK-monovalent. This is likely due to the pTHF-bis-TREN end group\nstructure, wherein stress relaxation in PDK-multivalent networks requires\nrearrangement of at least three bonds while PDK-monovalent requires\nonly one bond to rearrange. PDK-monovalent networks feature relatively\nlong linear chains with exchangeable diketoenamine bonds along the\nbackbone which further enables more facile associative bond exchange,\ncompared to PDK-multivalent networks in which all PDK bonds and excess\namines are confined to the cross-linking points. The temperature-dependent\ndata for G ′ and G ″\nindicate a preservation of noncovalent and covalent cross-linking\ndensities in PDK-multivalent elastomers and an apparent lowering of\nthe cross-linking density in PDK-monovalent elastomers. It follows\nthat stress relaxation in PDK-monovalent elastomers is concomitant\nwith a decrease in the noncovalent contribution to network cross-linking\ndensity, since covalent cross-linking density is constant. Moreover,\nthis occurs only in PDK-monovalent elastomers because bond exchange\nirreversibly reduces linear chain entanglement under the applied strain.\nSince the presence of physical entanglements in covalently cross-linked\nrubbery polymers is known to increase fracture toughness, 39 , 40 we can couple the stress relaxation observations with the results\nin Figure 1 D and conclude\nthat permanent entanglements in PDK-monovalent are unlikely to persist\non the time scale of these experiments. Taken together, these observations\ndemonstrate that covalently confining the cross-linking points to\nthe soft segment chain ends produces slower terminal relaxation in\nPDK-multivalent elastomers, while physical entanglements in PDK-monovalent\nelastomers are rapidly lost during bond exchange. Carbon Black\nProduces a Reinforcing Effect in PDK Elastomers We then examined\nhow carbon black as a filler affects PDK elastomer\nrheology. Carbon black is widely used to reinforce commercial rubbers\nand was easily dispersed into the PDK materials with no observable\neffect on polymerization. FTIR spectra for both PDK-multivalent and\nPDK-monovalent showed no changes in vibrational modes when carbon\nblack was added ( Figures S4 and S5 ). Yet,\nwe observed a 40% increase in storage modulus when incorporating only\n0.5 wt % carbon black into PDK-multivalent elastomers ( Figure 3 A,B), possibly due to the formation\nof a bound rubber layer at the elastomer–carbon black interface. 41 , 42 Because of the unique architecture of PDK-multivalent elastomers,\ninteractions with carbon black are more likely to involve the pTHF\nsegments, since potentially coordinating amine functionalities are\nmost often found at sterically encumbered sites within the network.\nIn stark contrast, coordinating amine functionality in PDK-monovalent\nelastomers may be found throughout the network, thus promoting adsorption\non that basis to a greater degree. Consequently, the reduction in\nchain mobility produced a larger reinforcing effect for PDK-monovalent\nelastomers, resulting in a reduced frequency dependence on modulus\nand an absence of G ′/ G ″\ncrossover at any temperature over the range explored ( Figure 3 D). The modulus for PDK-monovalent\nelastomers increased at all temperatures ( Figure 3 E) compared to the unfilled formulation ( Figure 2 E), for example,\n250 kPa at 30 °C and 130 kPa at 150 °C in the carbon black\nfilled formulation compared to 190 kPa at 30 °C and 40 kPa at\n150 °C in the unfilled formulation. While we again observed a\ndecrease in modulus with temperature, the magnitude of the decrease\nwas reduced, particularly at higher temperatures. Thus, microstructural\nattributes of PDK networks, particularly the manner in which excess\namine functionality is presented throughout, strongly influence the\nreinforcing characteristics of carbon black fillers, tying back to\ndifferences in structure and dynamic properties of the polyetheramine\nmacromers at the carbon black interface. Figure 3 Rheological characterization\nof carbon black reinforced PDK elastomers.\n(A) Frequency sweep, (B) amplitude sweep, and (C) stress relaxation\nmeasurements for PDK-multivalent containing 0.5 wt % carbon black.\n(D) Frequency sweep, (E) amplitude sweep, and (F) stress relaxation\nmeasurements for PDK-monovalent containing 0.5 wt % carbon black. These differences in the reinforcing effect also\nimpact stress\nrelaxation behavior for both PDK-multivalent and PDK-monovalent carbon-reinforced\nrubbers ( Figure 3 C,F).\nThe relaxation kinetics for PDK-multivalent rubbers did not change\nappreciably with the inclusion of carbon black, providing further\nevidence that excess amine functionality does not appreciably interact\nwith the filler and that diketoenamine bond exchange permitting relaxation\nis highly localized. Conversely, relaxation in PDK-monovalent rubbers\nwas substantially slower with the inclusion of carbon black, requiring\n>10-fold longer to relax to e –1 compared to the\nunfilled sample. Thus, displaying amine functionality at sterically\nless hindered sites throughout the networks of PDK-monovalent elastomers\npermits their adsorption to filler surfaces, and the relaxation behavior\ntied to that adsorption reflects slower chain dynamics at the filler\ninterface. When taken together, the results for unfilled and filled\nPDK elastomers validate our overarching hypothesis by illustrating\nthat multivalency in the flexible amine macromer is key to the creation\nof cross-linked PDK elastomers and rubbers that resist long-range\nviscous flow yet retain capacity for short-range bond exchange to\nremain mechanically processable during thermoforming. PDK Elastomers\nwith Multivalent Soft Segments Resist Creep While dynamic\ncovalent polymers are a promising platform for producing\nrecyclable thermosets, bond exchange can lead to creep, which diminishes\ntheir use in applications that cannot tolerate material deformation\nunder an applied load. We measured creep in both PDK-multivalent and\nPDK-monovalent elastomer networks under 1 kPa stress and observed\nremarkably low creep for PDK-multivalent, with no sample reaching\ngreater than 1% strain up to 150 °C ( Figure 4 A). By contrast, PDK-monovalent flowed readily,\ndue to high chain mobility, reaching >200% strain at 150 °C\n( Figure 4 B). We calculated\nthe residual strain rate from a linear fit of the last 200 s of the\nstrain versus time data; the strain rate was up to 2 orders of magnitude\nlower for PDK-multivalent elastomers than for PDK-monovalent elastomers,\nwhich reflects an increase in network viscosity. Adding carbon black\nto PDK-multivalent elastomers produced a small decrease in creep relative\nto unfilled materials ( Figure 4 D), with all samples reaching a strain ≤0.7% up to\n150 °C. This behavior continued to stand out, even when we added\ncarbon black to PDK-monovalent elastomers, which reduced creep by\nup to 13-fold relative to unfilled PDK-monovalent—although\nit was clear that continuous deformation could not be avoided at elevated\ntemperature ( Figure 4 E). Figure 4 Creep and residual strain rates in unfilled and reinforced PDK\nelastomers. (A) PDK-multivalent elastomer creep, showing exceptional\ncreep resistance at all temperatures. (B) PDK-monovalent elastomer\ncreep, showing high susceptibility to creep at all temperatures. (C)\nStrain rate (dγ/d t ) versus temperature for\nPDK-multivalent and PDK-monovalent elastomers. (D) PDK-multivalent\ncarbon-reinforced (0.5 wt %) rubber creep, showing exceptional creep\nresistance at all temperatures. (E) PDK-monovalent carbon-reinforced\n(0.5 wt %) creep, showing improved creep resistance at all temperatures.\n(F) Strain rate (dγ/d t ) versus temperature\nfor PDK-multivalent and PDK-monovalent carbon-reinforced (0.5 wt %)\nelastomers. Strain rate was calculated from the last 200 s of the\nstrain versus time data. The residual strain rates\nfor PDK-multivalent elastomers with and\nwithout carbon black were of comparable magnitudes ( Figure 4 C,F), and similar to the unfilled\nsamples, PDK-multivalent elastomers had an approximately order of\nmagnitude lower strain rate than PDK-monovalent elastomers when carbon\nblack was added. Given that the modulus of PDK-multivalent elastomers\nhad been observed to increase with the addition of carbon black, there\nis a clear effect in reducing chain mobility. However, carbon black\nhad little effect on the rate of stress relaxation and the magnitude\nof creep in PDK-multivalent elastomers. Furthermore, PDK-multivalent\nelastomers with and without carbon black had little temperature dependence\non creep below 150 °C. A plausible explanation is that the number\nof bonds that must simultaneously break and re-form to allow long-range\nchain motion is sufficiently high in the unfilled material; carbon\nblack simply increases the entropy penalty of deforming individual\nchain segments, resulting in an increase in modulus. We further conclude\nthat introducing exchangeable bonds into linear segments in PDK-monovalent\nelastomers leads to a reduction in cross-link density at elevated\ntemperature and produces undesirably high creep. From our earlier\nanalysis, this reduction is due to reduced noncovalent entanglements\nenabled by bond exchange and network reorganization. Indeed, recent\nstudies have demonstrated that increasing primary chain length in\nassociative networks can reduce viscoelastic flow through maintaining\nmolecular entanglements 43 and that reducing\nthe number of exchangeable bonds in the linear segment is critical\nto realizing this behavior. PDK Elastomers Exhibit High Thermal Stability Encouraged\nby the mechanical stability of PDK-multivalent at high temperature,\nwe further investigated its thermal stability to evaluate the potential\nfor high service temperature applications without deleterious thermal\ndegradation. We measured <1% mass loss in both PDK-multivalent\n( Figure S6 ) and PDK-monovalent ( Figure S7 ) with or without carbon black after\n10 000 s at 150 °C by TGA, verifying excellent thermal\nstability at the highest temperature in our rheological experiments.\nThe decomposition temperature at 50% mass loss for PDK-multivalent\nwas 419 °C without carbon black and 421 °C with carbon black\n( Figure S8 ), which was slightly higher\nthan but comparable to PDK-monovalent (417 and 418 °C respectively, Figure S9 ), suggesting that the thermal stability\narises from the network chemistry and not necessarily the cross-linking\nstructure. To put these results in the context of thermal performance\nfor conventional polymer formulations, we compared the decomposition\ntemperatures of PDK-multivalent and PDK-monovalent at 50% weight loss\nto published data on polyurethanes that contained pTHF ( M n = 2000 g mol –1 ) as a soft segment. 44 − 47 We assumed that 100% of the polyol content for the published formulations\ncould be derived from biorenewable sources, and we plotted decomposition\ntemperature against the mass fraction of biorenewable content ( Figure S10 ). Our formulation shows a clear improvement\nin thermal stability with a relatively high biorenewable content,\ndemonstrating the feasibility for deploying PDK-based elastomers in\ndemanding environmental conditions. PDK Chemical Depolymerization\nRequires Heteroatom Proximity\nto the Diketoenamine Bond Given the influence of amine macromer\nvalency on the structure and dynamic properties of associated elastomers\nand carbon-reinforced rubbers, we probed whether these architectural\nattributes were in any way influential in their deconstruction behavior.\nWe hypothesized that the higher cross-linking density of PDK-multivalent\nelastomers might slow their deconstruction to starting materials in\nstrong acid. We further hypothesized that achieving high material\nefficiency in starting material recovery for PDK-monovalent elastomers\nmight be compromised when the amine macromers are comprised of a mixture\nof compounds, in this case pTHF-diamine and TREN as the cross-linker.\nTo evaluate the effects of PDK elastomer architecture on depolymerization\nrates, we incubated thermoformed samples in 5.0 M hydrochloric acid\nat ambient temperature for 24 h ( Figure 5 A,B). To our surprise (and invalidating these\ninitial hypotheses), after only 6 h, PDK-multivalent samples both\nwith and without carbon black had depolymerized to starting material,\nwhereas PDK-monovalent samples swelled and softened, but remained\nintact after 24 h ( Figure 5 C). We recovered TK-10 and pTHF-bis-TREN components from depolymerized\nPDK-multivalent elastomers in 90% yield. Both were identical to pristine\nstarting materials by NMR spectroscopy and MALDI-ToF mass spectrometry\n( Figure S11 ). To understand the origins\nof this behavior, we recognized that the end-group structure of pTHF\ndiamine and TREN are inequivalent. Because TREN is known to promote\nfacile PDK deconstruction, and does so expediently for PDK-multivalent\nelastomers when TREN end-caps pTHF-bis-TREN cross-linkers, we hypothesized\nthat the proximity of the tertiary amine to the diketoenamine bond\nmay play an important role in acidolysis and therefore PDK depolymerization\nrates. Figure 5 Chemical depolymerization requires heteroatom proximity to the\ndiketoenamine bond. (A) TK-10 and pTHF-bis-TREN form cross-linked\nelastomers through a condensation polymerization, and they are depolymerized\nback to starting materials in the presence of aqueous HCl. (B) TK-10,\npTHF-diamine, and TREN form cross-linked elastomers through a similar\nmechanism, but the diketoenamine bond formed between TK-10 and pTHF-diamine\nis nondepolymerizable in aqueous HCl. (C) Chemical depolymerization\nof PDK-multivalent and PDK-monovalent elastomers with and without\ncarbon black. Depolymerization experiments were performed in 5.0 M\nHCl at ambient temperature. To test this revised hypothesis, we sought a mechanistic understanding\nof how heteroatom proximity affects depolymerization energetics. We\ncarried out a computational simulation of acid-catalyzed diketoenamine\nhydrolysis using small-molecule surrogates for pTHF-bis-TREN and pTHF-diamine:\nspecifically, diketoenamines featuring either a butyl group or an N , N -dimethylaminoethyl group ( Figure 6 ). The acidolysis\nof both diketoenamines is exergonic and is in fact more favorable\nfor the pTHF-diamine surrogate than the pTHF-bis-TREN surrogate. However,\nthe reaction kinetics ultimately explain why pTHF-bis-TREN is depolymerizable\nwhile pTHF-diamine is not. In the rate-limiting step, water adds to\na protonated iminium intermediate along the reaction coordinate. 28 , 48 Here, we found that the corresponding transition state for the butyl-functionalized\ndiketoenamine has a standard free energy of activation approximately\n13 kJ mol –1 greater than that for the N , N -dimethylaminoethyl-functionalized diketoenamine.\nThis difference in free energy of activation is due to the fact that\nthe tertiary amine of the N , N -dimethylaminoethyl\ngroup stabilizes the transition state via a strong hydrogen bond (2.26\nÅ) with the incoming water, and thus decreases the free energy\nof activation for the N , N -dimethylaminoethyl-functionalized\ndiketoenamine. Thus, the multivalent pTHF-bis-TREN end-group structure,\nin addition to providing for useful and advantaged PDK properties\nas elastomers and rubbers, is also essential for ensuring complete\nand rapid PDK depolymerization to triketone and amine starting materials\nat ambient temperature in strong acid. Figure 6 Computational reaction\ncoordinates for acid-catalyzed diketoenamine\nhydrolysis. (A) Chemical structures of small-molecule analogues of\nPDK-monovalent using acyl dimedone and n -butylamine.\n(B) Chemical structures of small-molecule analogues of PDK-multivalent\nusing acyl dimedone and N , N -dimethylaminoethylamine.\n(C) Computational reaction coordinate of PDK-monovalent (top series\nin green) and PDK-multivalent (bottom series in purple)."
} | 7,995 |
31123251 | PMC6533293 | pmc | 3,397 | {
"abstract": "Growing tissue and bacterial colonies are active matter systems where cell divisions and cellular motion generate active stress. Although they operate in the non-equilibrium regime, these biological systems can form large-scale ordered structures. How mechanical instabilities drive the dynamics of active matter systems and form ordered structures are not well understood. Here, we use chaining Bacillus subtilis , also known as a biofilm, to study the relation between mechanical instabilities and nematic ordering. We find that bacterial biofilms have intrinsic length scales above which a series of mechanical instabilities occur. Localized stress and friction drive buckling and edge instabilities which further create nematically aligned structures and topological defects. We also observe that topological defects control stress distribution and initiate the formation of sporulation sites by creating three-dimensional structures. In this study we propose an alternative active matter platform to study the essential roles of mechanics in growing biological tissue.",
"introduction": "Introduction Biofilm formation is a collective response of bacteria 1 – 6 . Depending on the availability of food and environmental conditions 7 , B. subtilis produces matrix proteins and initiates the formation of a biofilm 2 . During biofilm development, motile bacteria differentiate into an aligned chain of cells. Growing chains further develop fibers and bundles, which shape the overall biofilm morphology 8 – 13 . These distinct aligned structures promote sliding of a colony on a solid surface, where the swimming behavior is not efficient 14 . Aligned cellular structures are also observed in a variety of biological phenomena. During wound healing, migrating cells align and form fingering structures at the leading edge of the tissue 15 . Similarly, cultured cells 16 – 18 and isolated bacteria colonies can form nematic alignment and modulate the cellular density and active stress 19 – 23 . Recent studies have shown that liquid crystal theory can provide a suitable framework to study the dynamics of growing tissue as an active nematic system. Mainly, the dynamics of cellular alignment, topological defects, and edge instabilities have been explored 16 – 20 . During growth, mechanical instabilities also play essential roles by generating a large structural folding. Growing aligned fibers and bundles can accumulate stress and buckle. The dynamics of active nematics (AN) and mechanical properties of growing material are intricately coupled. However, we do not know how the mechanical instabilities drive the dynamics of active nematics and form ordered structures. Here, by investigating the formation of a bacterial biofilm starting from a single bacterium, we study the detailed mechanical instabilities driving the formation of a nematic active matter. We reveal the direct relation between local stress, localized buckling, and edge instabilities. This system provides new mechanical insights to explore the complex dynamics of biological AN 24 – 28 .",
"discussion": "Discussion The theory of active nematics provides a robust framework to explain the coordinated motion of cells and the emergence of large-scale order in biological systems. Our study throws light upon the mechanical aspects of biological active matter systems: first, mechanical instabilities can be simply characterized by a critical length scale. Different types of length scales have previously been defined for various AN systems 24 , 26 . These quantities mainly describe the activity of the system. In contrast, our length scale reflects the elastic properties of the biofilm, which is mainly defined by the competition between elastic deformation of chaining bacteria and the bacteria–agar interactions. Second, the leading edge of the biofilm is not stable. Edge instabilities 15 , 44 , 52 – 54 have received significant attention due to fingering formation during wound healing 15 . Our results revealed the importance of cellular alignment and localized stress-driving instabilities. Finally, we have shown the formation of the defects and their effect on the stress distribution across the biofilm. In growing tissue or bacterial colonies, mechanical stress can easily result in physiological stress. Recent studies have linked the physical forces with the cellular response 16 , and our system could further reveal the importance of stress management across growing tissue 55 . Another benefit of using B. subtilis is the availability of a sophisticated genetic toolbox 56 . Genetic manipulations and control could reveal unexplored dynamics of active matter systems. We believe that our biofilm platform offers new opportunities to study active nematics in living systems."
} | 1,184 |
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