Synthetic microbial ecosystems: an exciting tool to understand and apply microbial communities

Imbalance in Carbon and Nitrogen Metabolism in Comamonas testosteroni R2 Is Caused by Negative Feedback and Rescued by L-arginine

The collapse of Comamonas testosteroni R2 under chemostat conditions and the aerobic growth of strain R2 under batch conditions with phenol as the sole carbon source were investigated using physiological and transcriptomic techniques. Phenol-/catechol-degrading activities under chemostat conditions gradually decreased, suggesting that metabolites produced from strain R2 accumulated in the culture, which caused negative feedback. The competitive inhibition of phenol hydroxylase and catechol dioxygenase was observed in a crude extract of the supernatant collected from the collapsed culture. Transcriptomic analyses showed that genes related to nitrogen transport were up-regulated; the ammonium transporter amtB was up-regulated approximately 190-fold in the collapsed status, suggesting an increase in the concentration of ammonium in cells. The transcriptional levels of most of the genes related to gluconeogenesis, glycolysis, the pentose phosphate pathway, and the TCA and urea cycles decreased by ~0.7-fold in the stable status, whereas the activities of glutamate synthase and glutamine synthetase increased by ~2-fold. These results suggest that ammonium was assimilated into glutamate and glutamine via 2-oxoglutarate under the limited supply of carbon skeletons, whereas the synthesis of other amino acids and nucleotides was repressed by 0.6-fold. Furthermore, negative feedback appeared to cause an imbalance between carbon and nitrogen metabolism, resulting in collapse. The effects of amino acids on negative feedback were investigated. L-arginine allowed strain R2 to grow normally, even under growth-inhibiting conditions, suggesting that the imbalance was corrected by the stimulation of the urea cycle, resulting in the rescue of strain R2.

Leveraging Experimental Strategies to Capture Different Dimensions of Microbial Interactions

Microorganisms are a fundamental part of virtually every ecosystem on earth. Understanding how collectively they interact, assemble, and function as communities has become a prevalent topic both in fundamental and applied research. Owing to multiple advances in technology, answering questions at the microbial system or network level is now within our grasp. To map and characterize microbial interaction networks, numerous computational approaches have been developed; however, experimentally validating microbial interactions is no trivial task. Microbial interactions are context-dependent, and their complex nature can result in an array of outcomes, not only in terms of fitness or growth, but also in other relevant functions and phenotypes. Thus, approaches to experimentally capture microbial interactions involve a combination of culture methods and phenotypic or functional characterization methods. Here, through our perspective of food microbiologists, we highlight the breadth of innovative and promising experimental strategies for their potential to capture the different dimensions of microbial interactions and their high-throughput application to answer the question; are microbial interaction patterns or network architecture similar along different contextual scales? We further discuss the experimental approaches used to build various types of networks and study their architecture in the context of cell biology and how they translate at the level of microbial ecosystem.

Eco-Evolutionary Dynamics in Microbial Communities from Spontaneous Fermented Foods

Eco-evolutionary forces are the key drivers of ecosystem biodiversity dynamics. This resulted in a large body of theory, which has partially been experimentally tested by mimicking evolutionary processes in the laboratory. In the first part of this perspective, we outline what model systems are used for experimental testing of eco-evolutionary processes, ranging from simple microbial combinations and, more recently, to complex natural communities. Microbial communities of spontaneous fermented foods are a promising model system to study eco-evolutionary dynamics. They combine the complexity of a natural community with extensive knowledge about community members and the ease of manipulating the system in a laboratory setup. Due to rapidly developing sequencing techniques and meta-omics approaches incorporating data in building ecosystem models, the diversity in these communities can be analysed with relative ease while hypotheses developed in simple systems can be tested. Here, we highlight several eco-evolutionary questions that are addressed using microbial communities from fermented foods. These questions relate to analysing species frequencies in space and time, the diversity-stability relationship, niche space and community coalescence. We provide several hypotheses of the influence of these factors on community evolution specifying the experimental setup of studies where microbial communities of spontaneous fermented food are used.

Environmental fluctuations reshape an unexpected diversity-disturbance relationship in a microbial community

Environmental disturbances have long been theorized to play a significant role in shaping the diversity and composition of ecosystems. However, an inability to specify the characteristics of a disturbance experimentally has produced an inconsistent picture of diversity-disturbance relationships (DDRs). Here, using a high-throughput programmable culture system, we subjected a soil-derived bacterial community to dilution disturbance profiles with different intensities (mean dilution rates), applied either constantly or with fluctuations of different frequencies. We observed an unexpected U-shaped relationship between community diversity and disturbance intensity in the absence of fluctuations. Adding fluctuations increased community diversity and erased the U-shape. All our results are well-captured by a Monod consumer resource model, which also explains how U-shaped DDRs emerge via a novel 'niche flip' mechanism. Broadly, our combined experimental and modeling framework demonstrates how distinct features of an environmental disturbance can interact in complex ways to govern ecosystem assembly and offers strategies for reshaping the composition of microbiomes.

An efficient and scalable top-down method for predicting structures of microbial communities

Modern applications involving multispecies microbial communities rely on the ability to predict structures of such communities in defined environments. The structures depend on pairwise and high-order interactions between species. To unravel these interactions, classical bottom-up approaches examine all possible species subcommunities. Such approaches are not scalable as the number of subcommunities grows exponentially with the number of species, n. Here we present a top-down method wherein the number of subcommunities to be examined grows linearly with n, drastically reducing experimental effort. The method uses steady-state data from leave-one-out subcommunities and mathematical modeling to infer effective pairwise interactions and predict community structures. The accuracy of the method increases with n, making it suitable for large communities. We established the method in silico and validated it against a five-species community from literature and an eight-species community cultured in vitro. Our method offers an efficient and scalable tool for predicting microbial community structures.

Bacteria-driven phthalic acid ester biodegradation: Current status and emerging opportunities

The extensive use of phthalic acid esters (PAEs) has led to their widespread distribution across various environments. As PAEs pose significant threats to human health, it is urgent to develop efficient strategies to eliminate them from environments. Bacteria-driven PAE biodegradation has been considered as an inexpensive yet effective strategy to restore the contaminated environments. Despite great advances in bacterial culturing and sequencing, the inherent complexity of indigenous microbial community hinders us to mechanistically understand in situ PAE biodegradation and efficiently harness the degrading power of bacteria. The synthetic microbial ecology provides us a simple and controllable model system to address this problem. In this review, we focus on the current progress of PAE biodegradation mediated by bacterial isolates and indigenous bacterial communities, and discuss the prospective of synthetic PAE-degrading bacterial communities in PAE biodegradation research. It is anticipated that the theories and approaches of synthetic microbial ecology will revolutionize the study of bacteria-driven PAE biodegradation and provide novel insights for developing effective bioremediation solutions.

Evolving Interactions and Emergent Functions in Microbial Consortia

Microbial communities are constantly challenged with environmental stressors, such as antimicrobials, pollutants, and global warming. How do they respond to these changes? Answering this question is crucial given that microbial communities perform essential functions for life on Earth. Our research aims to understand and predict communities' responses to change by addressing the following questions. (i) How do eco-evolutionary feedbacks influence microbial community dynamics? (ii) How do multiple interacting species in a microbial community alter evolutionary processes? (iii) To what extent do microbial communities respond to change by ecological versus evolutionary processes? To answer these questions, we use microbial communities of reduced complexity coupled with experimental evolution, genome sequencing, and mathematical modeling. The overall expectation from this integrative research approach is to generate general concepts that extend beyond specific bacterial species and provide fundamental insights into the consequences of evolution on the functioning of whole microbial communities.

Co-culturing microbial consortia: approaches for applications in biomanufacturing and bioprocessing

The application of microbial co-cultures is now recognized in the fields of biotechnology, ecology, and medicine. Understanding the biological interactions that govern the association of microorganisms would shape the way in which artificial/synthetic co-cultures or consortia are developed. The ability to accurately predict and control cell-to-cell interactions fully would be a significant enabler in synthetic biology. Co-culturing method development holds the key to strategically engineer environments in which the co-cultured microorganism can be monitored. Various approaches have been employed which aim to emulate the natural environment and gain access to the untapped natural resources emerging from cross-talk between partners. Amongst these methods are the use of a communal liquid medium for growth, use of a solid-liquid interface, membrane separation, spatial separation, and use of microfluidics systems. Maximizing the information content of interactions monitored is one of the major challenges that needs to be addressed by these designs. This review critically evaluates the significance and drawbacks of the co-culturing approaches used to this day in biotechnological applications, relevant to biomanufacturing. It is recommended that experimental results for a co-cultured species should be validated with different co-culture approaches due to variations in interactions that could exist as a result of the culturing method selected.

Engineering Cooperation in an Anaerobic Coculture

Over the past century, microbiologists have studied organisms in pure culture, yet it is becoming increasingly apparent that the majority of biological processes rely on multispecies cooperation and interaction. While little is known about how such interactions permit cooperation, even less is known about how cooperation arises. To study the emergence of cooperation in the laboratory, we constructed both a commensal community and an obligate mutualism using the previously noninteracting bacteria Shewanella oneidensis and Geobacter sulfurreducens Incorporation of a glycerol utilization plasmid (pGUT2) enabled S. oneidensis to metabolize glycerol and produce acetate as a carbon source for G. sulfurreducens, establishing a cross-feeding, commensal coculture. In the commensal coculture, both species coupled oxidative metabolism to the respiration of fumarate as the terminal electron acceptor. Deletion of the gene encoding fumarate reductase in the S. oneidensis/pGUT2 strain shifted the coculture with G. sulfurreducens to an obligate mutualism where neither species could grow in the absence of the other. A shift in metabolic strategy from glycerol catabolism to malate metabolism was associated with obligate coculture growth. Further targeted deletions in malate uptake and acetate generation pathways in S. oneidensis significantly inhibited coculture growth with G. sulfurreducens The engineered coculture between S. oneidensis and G. sulfurreducens provides a model laboratory system to study the emergence of cooperation in bacterial communities, and the shift in metabolic strategy observed in the obligate coculture highlights the importance of genetic change in shaping microbial interactions in the environment.IMPORTANCE Microbes seldom live alone in the environment, yet this scenario is approximated in the vast majority of pure-culture laboratory experiments. Here, we develop an anaerobic coculture system to begin understanding microbial physiology in a more complex setting but also to determine how anaerobic microbial communities can form. Using synthetic biology, we generated a coculture system where the facultative anaerobe Shewanella oneidensis consumes glycerol and provides acetate to the strict anaerobe Geobacter sulfurreducens In the commensal system, growth of G. sulfurreducens is dependent on the presence of S. oneidensis To generate an obligate coculture, where each organism requires the other, we eliminated the ability of S. oneidensis to respire fumarate. An unexpected shift in metabolic strategy from glycerol catabolism to malate metabolism was observed in the obligate coculture. Our work highlights how metabolic landscapes can be expanded in multispecies communities and provides a system to evaluate the evolution of cooperation under anaerobic conditions.

Intestinal fermentation in vitro models to study food-induced gut microbiota shift: an updated review

In vitro gut fermentation models were firstly introduced in nutrition and applied microbiology research back in the 1990s. These models have improved greatly during time, mainly over the resemblance to the complexity of digestion stages, the replication of experimental conditions, the multitude of ecological parameters to assay. The state of the science is that the most competitive models shall include a complex gut microbiota, small working volumes, distinct interconnected compartments and rigorous bio-chemical and ecological settings, controlled by a computer, as well as a free-hands accessibility, not to contaminate the mock microbiota. These models are a useful tool to study the impact of a given diet compound, e.g. prebiotics, on the human gut microbiota. The principal application is to focus on the shift of the core microbial groups and selected species together with their metabolites, assaying their diversity, richness and abundance in the community over time. Besides, it is possible to study how a compound is digested, which metabolic pathways are triggered, and the type and quantity of microbial metabolites produced. Further prospective should focus on challenges with pathogens as well as on ecology of gut syndromes. In this minireview an updated presentation of the most used intestinal models is presented, basing on their concept, technical features, as well as on research applications.

Deconstructing and Reconstructing Cheese Rind Microbiomes for Experiments in Microbial Ecology and Evolution

Cheese rind microbiomes are useful model systems for identifying the mechanisms that control microbiome diversity. Here, we describe the methods we have optimized to first deconstruct in situ cheese rind microbiome diversity and then reconstruct that diversity in laboratory environments to conduct controlled microbiome manipulations. Most cheese rind microbial species, including bacteria, yeasts, and filamentous fungi, can be easily cultured using standard lab media. Colony morphologies of taxa are diverse and can often be used to distinguish taxa at the phylum and sometimes even genus level. Through the use of cheese curd agar medium, thousands of unique community combinations or microbial interactions can be assessed. Transcriptomic experiments and transposon mutagenesis screens can pinpoint mechanisms of interactions between microbial species. Our general approach of creating a tractable synthetic microbial community from cheese can be easily applied to other fermented foods to develop other model microbiomes. © 2019 by John Wiley & Sons, Inc. Basic Protocol 1: Isolation of cheese rind microbial communities Support Protocol 1: Preparation of plate count agar with milk and salt Basic Protocol 2: Identification of cheese rind bacterial and fungal isolates using 16S and ITS sequences Basic Protocol 3: Preparation of experimental glycerol stocks of yeasts and bacteria Basic Protocol 4: Preparation of experimental glycerol stocks of filamentous fungi Basic Protocol 5: Reconstruction of cheese rind microbial communities in vitro Support Protocol 2: Preparation of lyophilized and powdered cheese curd Support Protocol 3: Preparation of 10% cheese curd agar plates and tubes Basic Protocol 6: Interaction screens using responding lawns Support Protocol 4: Preparation of liquid 2% cheese curd Basic Protocol 7: Experimental evolution Basic Protocol 8: Measuring community function: pH/acidification Basic Protocol 9: Measuring community function: Pigment production Basic Protocol 10: RNA sequencing of cheese rind biofilms.

The ecology of wine fermentation: a model for the study of complex microbial ecosystems

The general interest in microbial ecology has skyrocketed over the past decade, driven by technical advances and by the rapidly increasing appreciation of the fundamental services that these ecosystems provide. In biotechnology, ecosystems have many more functionalities than single species, and, if properly understood and harnessed, will be able to deliver better outcomes for almost all imaginable applications. However, the complexity of microbial ecosystems and of the interactions between species has limited their applicability. In research, next generation sequencing allows accurate mapping of the microbiomes that characterise ecosystems of biotechnological and/or medical relevance. But the gap between mapping and understanding, to be filled by "functional microbiomics", requires the collection and integration of many different layers of complex data sets, from molecular multi-omics to spatial imaging technologies to online ecosystem monitoring tools. Holistically, studying the complexity of most microbial ecosystems, consisting of hundreds of species in specific spatial arrangements, is beyond our current technical capabilities, and simpler model systems with fewer species and reduced spatial complexity are required to establish the fundamental rules of ecosystem functioning. One such ecosystem, the ecosystem responsible for natural alcoholic fermentation, can provide an excellent tool to study evolutionarily relevant interactions between multiple species within a relatively easily controlled environment. This review will critically evaluate the approaches that are currently implemented to dissect the cellular and molecular networks that govern this ecosystem. KEY POINTS: • Evolutionarily isolated fermentation ecosystem can be used as an ecological model. • Experimental toolbox is gearing towards mechanistic understanding of this ecosystem. • Integration of multidisciplinary datasets is key to predictive understanding.

Formation, characterization and modeling of emergent synthetic microbial communities

Microbial communities colonize plant tissues and contribute to host function. How these communities form and how individual members contribute to shaping the microbial community are not well understood. Synthetic microbial communities, where defined individual isolates are combined, can serve as valuable model systems for uncovering the organizational principles of communities. Using genome-defined organisms, systematic analysis by computationally-based network reconstruction can lead to mechanistic insights and the metabolic interactions between species. In this study, 10 bacterial strains isolated from the Populus deltoides rhizosphere were combined and passaged in two different media environments to form stable microbial communities. The membership and relative abundances of the strains stabilized after around 5 growth cycles and resulted in just a few dominant strains that depended on the medium. To unravel the underlying metabolic interactions, flux balance analysis was used to model microbial growth and identify potential metabolic exchanges involved in shaping the microbial communities. These analyses were complemented by growth curves of the individual isolates, pairwise interaction screens, and metaproteomics of the community. A fast growth rate is identified as one factor that can provide an advantage for maintaining presence in the community. Final community selection can also depend on selective antagonistic relationships and metabolic exchanges. Revealing the mechanisms of interaction among plant-associated microorganisms provides insights into strategies for engineering microbial communities that can potentially increase plant growth and disease resistance. Further, deciphering the membership and metabolic potentials of a bacterial community will enable the design of synthetic communities with desired biological functions.

De Novo Biosynthesis of Chlorogenic Acid Using an Artificial Microbial Community

Engineering an artificial microbial community for natural product production is a promising strategy. As mono- and dual-culture systems only gave non-detectable or minimal chlorogenic acid (CGA) biosynthesis, here, a polyculture of three recombinant Escherichia coli strains, acting as biosynthetic modules of caffeic acid (CA), quinic acid (QA), and CGA, was designed and used for de novo CGA biosynthesis. An influx transporter of 3-dehydroshikimic acid (DHS)/shikimic acid (SA), ShiA, was introduced into the QA module-a DHS auxotroph. The QA module proportion in the polyculture and CGA production were found to be dependent on ShiA expression, providing an alternative approach for controlling microbial community composition. The polyculture strategy avoids metabolic flux competition in the biosynthesis of two CGA precursors, CA and QA, and allows production improvement by balancing module proportions. The performance of this polyculture approach was superior to that of previously reported approaches of de novo CGA production.

Complex yeast-bacteria interactions affect the yield of industrial ethanol fermentation

Sugarcane ethanol fermentation represents a simple microbial community dominated by S. cerevisiae and co-occurring bacteria with a clearly defined functionality. In this study, we dissect the microbial interactions in sugarcane ethanol fermentation by combinatorically reconstituting every possible combination of species, comprising approximately 80% of the biodiversity in terms of relative abundance. Functional landscape analysis shows that higher-order interactions counterbalance the negative effect of pairwise interactions on ethanol yield. In addition, we find that Lactobacillus amylovorus improves the yeast growth rate and ethanol yield by cross-feeding acetaldehyde, as shown by flux balance analysis and laboratory experiments. Our results suggest that Lactobacillus amylovorus could be considered a beneficial bacterium with the potential to improve sugarcane ethanol fermentation yields by almost 3%. These data highlight the biotechnological importance of comprehensively studying microbial communities and could be extended to other microbial systems with relevance to human health and the environment.

A peek in the micro-sized world: a review of design principles, engineering tools, and applications of engineered microbial community

Microbial communities drive diverse processes that impact nearly everything on this planet, from global biogeochemical cycles to human health. Harnessing the power of these microorganisms could provide solutions to many of the challenges that face society. However, naturally occurring microbial communities are not optimized for anthropogenic use. An emerging area of research is focusing on engineering synthetic microbial communities to carry out predefined functions. Microbial community engineers are applying design principles like top-down and bottom-up approaches to create synthetic microbial communities having a myriad of real-life applications in health care, disease prevention, and environmental remediation. Multiple genetic engineering tools and delivery approaches can be used to 'knock-in' new gene functions into microbial communities. A systematic study of the microbial interactions, community assembling principles, and engineering tools are necessary for us to understand the microbial community and to better utilize them. Continued analysis and effort are required to further the current and potential applications of synthetic microbial communities.

Enhanced production of methane in anaerobic water treatment as mediated by the immobilized fungi

Anaerobic digestion of organic waste and wastewater represents an attractive sustainable bio-technology to produce methane as an alternative to fossil energy. In response to improvement of methane production via enhancing methanogenesis, current strategies of the addition of external biological/non-biological materials have to confront either the loss of materials, high cost and/or possible destruction of the microbial community. Here, we report the first case of using immobilized fungi Aspergillus sydowii 8L-9-F02 to optimize the microbial community, achieving remarkable improvement of the methane production in both batch test (1.5 times) and continuous flow operation (1.13-1.31 times). The crucial role of fungi is associated with the stimulation of enrichment of Methanosaeta and Methanobacterium for methanogenesis from 28.2 to 67.4% as well as the improved activity of enzyme F420. Moreover, fungi also increase the content of extracellular polymeric substances, facilitating the formation of bio-aggregates. This work provides a new pathway to enhance methanogenesis during anaerobic digestion of wastewater by using fungi as bio-enhancer.

Metabolic Exchange and Energetic Coupling between Nutritionally Stressed Bacterial Species: Role of Quorum-Sensing Molecules

Formation of multispecies communities allows nearly every niche on earth to be colonized, and the exchange of molecular information among neighboring bacteria in such communities is key for bacterial success. To clarify the principles controlling interspecies interactions, we previously developed a coculture model with two anaerobic bacteria, Clostridium acetobutylicum (Gram positive) and Desulfovibrio vulgaris Hildenborough (Gram negative, sulfate reducing). Under conditions of nutritional stress for D. vulgaris, the existence of tight cell-cell interactions between the two bacteria induced emergent properties. Here, we show that the direct exchange of carbon metabolites produced by C. acetobutylicum allows D vulgaris to duplicate its DNA and to be energetically viable even without its substrates. We identify the molecular basis of the physical interactions and how autoinducer-2 (AI-2) molecules control the interactions and metabolite exchanges between C. acetobutylicum and D. vulgaris (or Escherichia coli and D. vulgaris). With nutrients, D. vulgaris produces a small molecule that inhibits in vitro the AI-2 activity and could act as an antagonist in vivo Sensing of AI-2 by D. vulgaris could induce formation of an intercellular structure that allows directly or indirectly metabolic exchange and energetic coupling between the two bacteria.IMPORTANCE Bacteria have usually been studied in single culture in rich media or under specific starvation conditions. However, in nature they coexist with other microorganisms and build an advanced society. The molecular bases of the interactions controlling this society are poorly understood. Use of a synthetic consortium and reducing complexity allow us to shed light on the bacterial communication at the molecular level. This study presents evidence that quorum-sensing molecule AI-2 allows physical and metabolic interactions in the synthetic consortium and provides new insights into the link between metabolism and bacterial communication.

Futuristic avenues of metabolic engineering techniques in bioremediation

Bioremediation is a promising technology for the treatment of environmental contaminants and paving new avenues for the betterment of the environment. Over the last some years, several approaches have been employed to optimize the genetic machinery of microorganisms relevant to bioremediation. Metabolic engineering is one of them that provides a new insight for bioremediation. This review envisages the critical role of these techniques toward exploring the possibilities of the creation of a new pathway, leading to pathway expansion to new substrates by assembling of catabolic modules from different origins in the same microbial cell. The recombinant DNA technology and gene editing tools were also explored for the construction of metabolically engineered microbial strains for the degradation of complex pollutants. Moreover, the importance of CRISPR-Cas system for knock-in and knock-out of genes was described by using recent studies. Further, the idea of the cocultivation of more than one metabolic engineered microbial communities is also discussed, which can be crucial in the bioremediation of multiple and complex pollutants. Finally, this review also elucidates the effective application of metabolic engineering in bioremediation through these techniques and tools.

Coexisting mechanisms of bacterial community are changeable even under similar stable conditions in a chemostat culture

The coexisting mechanism of a synthetic bacterial community (SBC) was investigated to better understand how to manage microbial communities. The SBC was constructed with three kinds of phenol-utilizing bacteria, Pseudomonas sp. LAB-08, Comamonas testosteroni R2, and Cupriavidus sp. P-10, under chemostat conditions supplied with phenol as a sole carbon and energy source. Population densities of all strains were monitored by real-time quantitative PCR (qPCR) targeting the gene encoding the large subunit of phenol hydroxylase. Although the supply of phenol was stopped to allow perturbation in the SBC, all of the strains coexisted and the degradation of phenol was maintained for more than 800 days. The qPCR analyses showed that strains LAB-08 and R2 became dominant simultaneously, whereas strain P-10 was a minor population. This phenomenon was observed before and after the phenol-supply stoppage. The kinetic parameters for phenol of the SBC changed before and after the phenol-supply stoppage, which suggests a change in functional roles of strains in the SBC. Transcriptional levels of phenol hydroxylase and catechol dioxygenases of three strains were monitored by reverse-transcription qPCR (RT-qPCR). The RT-qPCR analyses revealed that all strains shared phenol and survived independently before the phenol-supply stoppage. After the stoppage, strain P-10 would incur the cost for degradation of phenol and catechol, whereas strains LAB-08 and R2 seemed to be cheaters using metabolites, indicating the development of the metabolic network. These results indicated that it is important for the management and redesign of microbial communities to understand the metabolism of bacterial communities.

The impact of the endophytic bacterial community on mulberry tree growth in the Three Gorges Reservoir ecosystem, China

Plant-associated microbes influence plant performance and may also impact biotic and abiotic stress tolerance. The microbiome of mulberry trees planted for ecological restoration in the hydro-fluctuation belt of the Three Gorges Reservoir Region, China, exhibited distinct patterns of localization. The endosphere exhibited lower α-diversity relative to the rhizosphere, but was more closely related to host growth status, especially in stem tissues. Pantoea was the predominant bacterial genus inhabiting the stems of two well-growing plants, while sequences identified as Pseudomonas and Pantoea were abundant in poorly growing plants. The complexity of the endophytic community was more connected to growth status in well-growing plants than it was in poorly growing plants. Among 151 endophytes cultured from collected samples of mulberry, 64 exhibited plant growth-promoting (PGP) potential in vitro and the majority of beneficial taxa were harvested from well-growing plants. Collectively, the present study indicates that the recruitment of beneficial endophytes may contribute to mulberry fitness under abiotic stress, and it provides a foundation for the development of a new strategy in vegetation restoration.

Circadian clock-controlled gene expression in co-cultured, mat-forming cyanobacteria

Natural coastal microbial mat communities are multi-species assemblages that experience fluctuating environmental conditions and are shaped by resource competition as well as by cooperation. Laboratory studies rarely address the natural complexity of microbial communities but are usually limited to homogeneous mono-cultures of key species grown in liquid media. The mat-forming filamentous cyanobacteria Lyngbya aestuarii and Coleofasciculus chthonoplastes were cultured under different conditions to investigate the expression of circadian clock genes and genes that are under their control. The cyanobacteria were grown in liquid medium or on a solid substrate (glass beads) as mono- or as co-cultures under a light-dark regime and subsequently transferred to continuous light. TaqMan-probe based qPCR assays were used to quantify the expression of the circadian clock genes kaiA, kaiB, and kaiC, and of four genes that are under control of the circadian clock: psbA, nifH, ftsZ, and prx. Expression of kaiABC was influenced by co-culturing the cyanobacteria and whether grown in liquid media or on a solid substrate. Free-running (i.e. under continuous light) expression cycle of the circadian clock genes was observed in L. aestuarii but not in C. chthonoplastes. In the former organism, maximum expression of psbA and nifH occurred temporally separated and independent of the light regime, although the peak shifted in time when the culture was transferred to continuous illumination. Although functionally similar, both species of cyanobacteria displayed different 24-h transcriptional patterns in response to the experimental treatments, suggesting that their circadian clocks have adapted to different life strategies adopted by these mat-forming cyanobacteria.

Composition and Metabolic Functions of the Microbiome in Fermented Grain during Light-Flavor Baijiu Fermentation

The metabolism and accumulation of flavor compounds in Chinese Baijiu are driven by microbiota succession and their inter-related metabolic processes. Changes in the microbiome composition during Baijiu production have been examined previously; however, the respective metabolic functions remain unclear. Using shotgun metagenomic sequencing and metabolomics, we examined the microbial and metabolic characteristics during light-flavor Baijiu fermentation to assess the correlations between microorganisms and their potential functions. During fermentation, the bacterial abundance increased from 58.2% to 97.65%, and fermentation resulted in the accumulation of various metabolites, among which alcohols and esters were the most abundant. Correlation analyses revealed that the levels of major metabolites were positively correlated with bacterial abundance but negatively with that of fungi. Gene annotation showed that the Lactobacillus species contained key enzyme genes for carbohydrate metabolism and contributed to the entire fermentation process. Lichtheimia ramosa, Saccharomycopsis fibuligera, Bacillus licheniformis, Saccharomyces cerevisiae, and Pichia kudriavzevii play major roles in starch degradation and ethanol production. A link was established between the composition and metabolic functions of the microbiota involved in Baijiu fermentation, which helps elucidate microbial and metabolic patterns of fermentation and provides insights into the potential optimization of Baijiu production.

Escherichia coli O157 survival in liquid culture and artificial soil microcosms with variable pH, humic acid and clay content

AIMS

This research was performed to investigate the influence of clay and humic acid on Escherichia coli O157 survival in model soils. Additionally, the influence of pH and humic acid on E. coli O157 in liquid culture was investigated.

METHODS AND RESULTS

Artificial soil microcosms were prepared with sand, kaolinite, bentonite and humic acid. Artificial soil microcosms pH was adjusted (6·0-7·0) with aluminium sulphate before E. coli O157 inoculation. After 56 days of incubation at 30°C, significant differences in E. coli O157 log CFU per gram were observed between 0 and 1000 ppm (P < 0·0001) and 0 and 5000 ppm (P < 0·0001) humic acid in 1·5% clay soils, but not in 7·5 or 15% clay soils. Significant differences (P < 0·05) in E. coli O157 log CFU per ml were observed in liquid culture influenced by humic acid concentrations after 8 h at 37°C.

CONCLUSIONS

The developed model soils support E. coli O157 populations over 28 days, and higher clay soils may aid in E. coli O157 survival.

SIGNIFICANCE AND IMPACT OF THE STUDY

These results provide insights into physicochemical properties of soil that may influence E. coli O157 in the environment and help explain E. coli O157 survival in various soils and geographical regions.

Majority sensing in synthetic microbial consortia

As synthetic biocircuits become more complex, distributing computations within multi-strain microbial consortia becomes increasingly beneficial. However, designing distributed circuits that respond predictably to variation in consortium composition remains a challenge. Here we develop a two-strain gene circuit that senses and responds to which strain is in the majority. This involves a co-repressive system in which each strain produces a signaling molecule that signals the other strain to down-regulate production of its own, orthogonal signaling molecule. This co-repressive consortium links gene expression to ratio of the strains rather than population size. Further, we control the cross-over point for majority via external induction. We elucidate the mechanisms driving these dynamics by developing a mathematical model that captures consortia response as strain fractions and external induction are varied. These results show that simple gene circuits can be used within multicellular synthetic systems to sense and respond to the state of the population.

Investigation of microbial community interactions between Lake Washington methanotrophs using -------genome-scale metabolic modeling

Background

The role of methane in global warming has become paramount to the environment and the human society, especially in the past few decades. Methane cycling microbial communities play an important role in the global methane cycle, which is why the characterization of these communities is critical to understand and manipulate their behavior. Methanotrophs are a major player in these communities and are able to oxidize methane as their primary carbon source.

Results

Lake Washington is a freshwater lake characterized by a methane-oxygen countergradient that contains a methane cycling microbial community. Methanotrophs are a major part of this community involved in assimilating methane from lake water. Two significant methanotrophic species in this community are Methylobacter and Methylomonas. In this work, these methanotrophs are computationally studied via developing highly curated genome-scale metabolic models. Each model was then integrated to form a community model with a multi-level optimization framework. The competitive and mutualistic metabolic interactions among Methylobacter and Methylomonas were also characterized. The community model was next tested under carbon, oxygen, and nitrogen limited conditions in addition to a nutrient-rich condition to observe the systematic shifts in the internal metabolic pathways and extracellular metabolite exchanges. Each condition showed variations in the methane oxidation pathway, pyruvate metabolism, and the TCA cycle as well as the excretion of formaldehyde and carbon di-oxide in the community. Finally, the community model was simulated under fixed ratios of these two members to reflect the opposing behavior in the two-member synthetic community and in sediment-incubated communities. The community simulations predicted a noticeable switch in intracellular carbon metabolism and formaldehyde transfer between community members in sediment-incubated vs. synthetic condition.

Conclusion

In this work, we attempted to predict the response of a simplified methane cycling microbial community from Lake Washington to varying environments and also provide an insight into the difference of dynamics in sediment-incubated microcosm community and synthetic co-cultures. Overall, this study lays the ground for in silico systems-level studies of freshwater lake ecosystems, which can drive future efforts of understanding, engineering, and modifying these communities for dealing with global warming issues.

It takes three to tango: the importance of microbes, host plant, and soil management to elucidate manipulation strategies for the plant microbiome

The world’s population is expected to grow to almost 10 billion by 2050, placing unprecedented demands on agriculture and natural resources. The risk in food security is also aggravated by climate change and land degradation, which compromise agricultural productivity. In recent years, our understanding of the role of microbial communities on ecosystem functioning, including plant-associated microbes, has advanced considerably. Yet, translating this knowledge into practical agricultural technologies is challenged by the intrinsic complexity of agroecosystems. Here, we review current strategies for plant microbiome manipulation, classifying them into three main pillars: (i) introducing and engineering microbiomes, (ii) breeding and engineering the host plant, and (iii) selecting agricultural practices that enhance resident soil and plant-associated microbial communities. In each of these areas, we analyze current trends in research, as well as research priorities and future perspectives.

Scoring Species for Synthetic Community Design: Network Analyses of Functional Core Microbiomes

Constructing biological communities is a major challenge in both basic and applied sciences. Although model synthetic communities with a few species have been constructed, designing systems consisting of tens or hundreds of species remains one of the most difficult goals in ecology and microbiology. By utilizing high-throughput sequencing data of interspecific association networks, we here propose a framework for exploring “functional core” species that have great impacts on whole community processes and functions. The framework allows us to score each species within a large community based on three criteria: namely, topological positions, functional portfolios, and functional balance within a target network. The criteria are measures of each species’ roles in maximizing functional benefits at the community or ecosystem level. When species with potentially large contributions to ecosystem-level functions are screened, the framework also helps us design “functional core microbiomes” by focusing on properties of species groups (modules) within a network. When embedded into agroecosystems or human gut, such functional core microbiomes are expected to organize whole microbiome processes and functions. An application to a plant-associated microbiome dataset actually highlighted potential functional core microbes that were known to control rhizosphere microbiomes by suppressing pathogens. Meanwhile, an example of application in mouse gut microbiomes called attention to poorly investigated bacterial species, whose potential roles within gut microbiomes deserve future experimental studies. The framework for gaining “bird’s-eye” views of functional cores within networks is applicable not only to agricultural and medical data but also to datasets produced in food processing, brewing, waste water purification, and biofuel production.

A Bottom-Up Approach To Develop a Synthetic Microbial Community Model: Application for Efficient Reduced-Salt Broad Bean Paste Fermentation

Humans have used high salinity for the production of bean-based fermented foods over thousands of years. Although high salinity can inhibit the growth of harmful microbes and select functional microbiota in an open environment, it also affects fermentation efficiency of bean-based fermented foods and has a negative impact on people's health. Therefore, it is imperative to develop novel defined starter cultures for reduced-salt fermentation in a sterile environment. Here, we explored the microbial assembly and function in the fermentation of traditional Chinese broad bean paste with 12% salinity. The results revealed that the salinity and microbial interactions together drove the dynamic of community and pointed out that five dominant genera (Staphylococcus, Bacillus, Weissella, Aspergillus, and Zygosaccharomyces) may play different key roles in different fermentation stages. Then, core species were isolated from broad bean paste, and their salinity tolerance, interactions, and metabolic characteristics were evaluated. The results provided an opportunity to validate in situ predictions through in vitro dissection of microbial assembly and function. Last, we reconstructed the synthetic microbial community with five strains (Aspergillus oryzae, Bacillus subtilis, Staphylococcus gallinarum, Weissella confusa, and Zygosaccharomyces rouxii) under different salinities and realized efficient fermentation of broad bean paste for 6 weeks in a sterile environment with 6% salinity. In general, this work provided a bottom-up approach for the development of a simplified microbial community model with desired functions to improve the fermentation efficiency of bean-based fermented foods by deconstructing and reconstructing the microbial structure and function.IMPORTANCE Humans have mastered high-salinity fermentation techniques for bean-based fermented product preparation over thousands of years. High salinity was used to select the functional microbiota and conducted food fermentation production with unique flavor. Although a high-salinity environment is beneficial for suppressing harmful microbes in the open fermentation environment, the fermentation efficiency of functional microbes is partially inhibited. Therefore, application of defined starter cultures for reduced-salt fermentation in a sterile environment is an alternative approach to improve the fermentation efficiency of bean-based fermented foods and guide the transformation of traditional industry. However, the assembly and function of self-organized microbiota in an open fermentation environment are still unclear. This study provides a comprehensive understanding of microbial function and the mechanism of community succession in a high-salinity environment during the fermentation of broad bean paste so as to reconstruct the microbial community and realize efficient fermentation of broad bean paste in a sterile environment.

Increasing sulfate levels show a differential impact on synthetic communities comprising different methanogens and a sulfate reducer

Methane-producing microbial communities are of ecological and biotechnological interest. Syntrophic interactions among sulfate reducers and aceto/hydrogenotrophic and obligate hydrogenotrophic methanogens form a key component of these communities, yet, the impact of these different syntrophic routes on methane production and their stability against sulfate availability are not well understood. Here, we construct model synthetic communities using a sulfate reducer and two types of methanogens representing different methanogenesis routes. We find that tri-cultures with both routes increase methane production by almost twofold compared to co-cultures and are stable in the absence of sulfate. With increasing sulfate, system stability and productivity decreases and does so faster in communities with aceto/hydrogenotrophic methanogens despite the continued presence of acetate. We show that this is due to a shift in the metabolism of these methanogens towards co-utilization of hydrogen with acetate. These findings indicate the important role of hydrogen dynamics in the stability and productivity of syntrophic communities.

Evolution of mutualistic behaviour between Chlorella sorokiniana and Saccharomyces cerevisiae within a synthetic environment

Yeast and microalgae are microorganisms with widely diverging physiological and biotechnological properties. Accordingly, their fields of applications diverge: yeasts are primarily applied in processes related to fermentation, while microalgae are used for the production of high-value metabolites and green technologies such as carbon capture. Heterotrophic-autotrophic systems and synthetic ecology approaches have been proposed as tools to achieve stable combinations of such evolutionarily unrelated species. We describe an entirely novel synthetic ecology-based approach to evolve co-operative behaviour between winery wastewater isolates of the yeast Saccharomyces cerevisiae and microalga Chlorella sorokiniana. The data show that biomass production and mutualistic growth improved when co-evolved yeast and microalgae strains were paired together. Combinations of co-evolved strains displayed a range of phenotypes, including differences in amino acid profiles. Taken together, the results demonstrate that biotic selection pressures can lead to improved mutualistic growth phenotypes over relatively short time periods.

Woody Plant Declines. What's Wrong with the Microbiome?

Woody plant (WP) declines have multifactorial determinants as well as a biological and economic reality. The vascular system of WPs involved in the transport of carbon, nitrogen, and water from sources to sinks has a seasonal activity, which places it at a central position for mediating plant-environment interactions from nutrient cycling to community assembly and for regulating a variety of processes. To limit effects and to fight against declines, we propose: (i) to consider the WP and its associated microbiota as an holobiont and as a set of functions; (ii) to consider simultaneously, without looking at what comes first, the physiological or pathogenic disorders; and (iii) to define pragmatic strategies, including preventive and curative agronomical practices based on microbiota engineering.

Mechanistic insights into bacterial metabolic reprogramming from omics-integrated genome-scale models

Understanding the adaptive responses of individual bacterial strains is crucial for microbiome engineering approaches that introduce new functionalities into complex microbiomes, such as xenobiotic compound metabolism for soil bioremediation. Adaptation requires metabolic reprogramming of the cell, which can be captured by multi-omics, but this data remains formidably challenging to interpret and predict. Here we present a new approach that combines genome-scale metabolic modeling with transcriptomics and exometabolomics, both of which are common tools for studying dynamic population behavior. As a realistic demonstration, we developed a genome-scale model of Pseudomonas veronii 1YdBTEX2, a candidate bioaugmentation agent for accelerated metabolism of mono-aromatic compounds in soil microbiomes, while simultaneously collecting experimental data of P. veronii metabolism during growth phase transitions. Predictions of the P. veronii growth rates and specific metabolic processes from the integrated model closely matched experimental observations. We conclude that integrative and network-based analysis can help build predictive models that accurately capture bacterial adaptation responses. Further development and testing of such models may considerably improve the successful establishment of bacterial inoculants in more complex systems.

Guiding Mineralization Co-Culture Discovery Using Bayesian Optimization

Many disciplines rely on testing combinations of compounds, materials, proteins, or bacterial species to drive scientific discovery. It is time-consuming and expensive to determine experimentally, via trial-and-error or random selection approaches, which of the many possible combinations will lead to desirable outcomes. Hence, there is a pressing need for more rational and efficient experimental design approaches to reduce experimental effort. In this work, we demonstrate the potential of machine learning methods for the in silico selection of promising co-culture combinations in the application of bioaugmentation. We use the example of pollutant removal in drinking water treatment plants, which can be achieved using co-cultures of a specialized pollutant degrader with combinations of bacterial isolates. To reduce the experimental effort needed to discover high-performing combinations, we propose a data-driven experimental design. Based on a dataset of mineralization performance for all pairs of 13 bacterial species co-cultured with MSH1, we built a Gaussian process regression model to predict the Gompertz mineralization parameters of the co-cultures of two and three species, based on the single-strain parameters. We subsequently used this model in a Bayesian optimization scheme to suggest potentially high-performing combinations of bacteria. We achieved good performance with this approach, both for predicting mineralization parameters and for selecting effective co-cultures, despite the limited dataset. As a novel application of Bayesian optimization in bioremediation, this experimental design approach has promising applications for highlighting co-culture combinations for in vitro testing in various settings, to lessen the experimental burden and perform more targeted screenings.

Omics approaches for microalgal applications: Prospects and challenges

In recent impetus of phycological research, microalgae have emerged as a potential candidate for various arena of application-driven research. Omics-based tactics are used for disentangling the regulation and network integration for biosynthesis/degradation of metabolic precursors, intermediates, end products, and identifying the networks that regulate the metabolic flux. Multi-omics coupled with data analytics have facilitated understanding of biological processes and allow ample access to diverse metabolic pathways utilized for genetic manipulations making microalgal factories more efficient. The present review discusses state-of-art "Algomics" and the prospect of microalgae and their role in symbiotic association by using omics approaches including genomics, transcriptomics, proteomics and metabolomics. Microalgal based uni- and multi-omics approaches are critically analyzed in wastewater treatment, metal toxicity and remediation, biofuel production, and therapeutics to provide an imminent outlook for an array of environmentally sustainable and economically viable microalgal applications.

Simultaneous and sequential based co-fermentations of Trichoderma asperellum GDFS1009 and Bacillus amyloliquefaciens 1841: a strategy to enhance the gene expression and metabolites to improve the bio-control and plant growth promoting activity

BACKGROUND

The consequence of simultaneous and sequential inoculation of T. asperellum and B. amyloliquefaciens cultures with respect to growth rate, differential expression of vital genes and metabolites were examined.

RESULTS

The competition was observed between T. asperellum and B. amyloliquefaciens under co-cultivation. The proliferation of Trichoderma was reduced in the simultaneous inoculation (TB1) method, possibly due to the fastest growth of Bacillus. Both T. asperellum and B. amyloliquefaciens were proliferated in sequential inoculation method (TB2). The sequential inoculation method (TB2) upregulated the expression of metabolites and vital genes (sporulation, secondary metabolites, mycoparasitism enzymes and antioxidants) in Trichoderma and downregulated in Bacillus and vice versa in co-inoculation method (TB1). The metabolic changes in the co-culture promoted the maize plant growth and defense potential under normal and biotic stress conditions.

CONCLUSION

The metabolites produced by the co-culture of T. asperellum and B. amyloliquefaciens improved the maize plant growth and defense potential under normal and biotic stress conditions.

Contrasting Strategies: Human Eukaryotic Versus Bacterial Microbiome Research

Most discussions of human microbiome research have focused on bacterial investigations and findings. Our target is to understand how human eukaryotic microbiome research is developing, its potential distinctiveness, and how problems can be addressed. We start with an overview of the entire eukaryotic microbiome literature (578 papers), show tendencies in the human‐based microbiome literature, and then compare the eukaryotic field to more developed human bacterial microbiome research. We are particularly concerned with problems of interpretation that are already apparent in human bacterial microbiome research (e.g. disease causality, probiotic interventions, evolutionary claims). We show where each field converges and diverges, and what this might mean for progress in human eukaryotic microbiome research. Our analysis then makes constructive suggestions for the future of the field.

Assessing interactions, predicting function, and increasing degradation potential of a PAH-degrading bacterial consortium by effect of an inoculant strain

A natural phenanthrene-degrading consortium CON was inoculated with an exogenous strain Sphingobium sp. (ex Sp. paucimobilis) 20006FA yielding the consortium called I-CON, in order to study ecological interactions into the bacterial community. DGGE and proteomic profiles and analyses by HTS (High-Throughput Sequencing) technologies demonstrated inoculant establishment and changes on CON composition. Inoculation increased degradation efficiency in I-CON and prevented intermediate HNA accumulation. This could be explained not only by the inoculation, but also by enrichment in Achromobacter genus at expense of a decrease in Klebsiella genus. After inoculation, cooperation between Sphingobium and Achromobacter genera were improved, thereby, some competition could have been generated, and as a consequence, species in minor proportion (cheaters), as Inquilinus sp. and Luteibacter sp., were not detected. Sequences of Sphingobium (corresponding to the inoculated strain) did not vary. PICRUSt predicted a network with bacterial phylotypes connected with enzymes, showing functional redundancy in the phenanthrene pathway, with exception of the first enzymes biphenyl-2,3-diol 1,2-dioxygenase and protocatechuate 4,5-dioxygenase that were only encoded in Sphingobium sp. This is the first report where a natural consortium that has been characterized by HTS technologies is inoculated with an exogenous strain in order to study competitiveness and interactions.

Toxicity drives facilitation between 4 bacterial species

Competition between microbes is extremely common, with many investing in mechanisms to harm other strains and species. Yet positive interactions between species have also been documented. What makes species help or harm each other is currently unclear. Here, we studied the interactions between 4 bacterial species capable of degrading metal working fluids (MWF), an industrial coolant and lubricant, which contains growth substrates as well as toxic biocides. We were surprised to find only positive or neutral interactions between the 4 species. Using mathematical modeling and further experiments, we show that positive interactions in this community were likely due to the toxicity of MWF, whereby each species' detoxification benefited the others by facilitating their survival, such that they could grow and degrade MWF better when together. The addition of nutrients, the reduction of toxicity, or the addition of more species instead resulted in competitive behavior. Our work provides support to the stress gradient hypothesis by showing how harsh, toxic environments can strongly favor facilitation between microbial species and mask underlying competitive interactions.

Synthetic Methane-Consuming Communities from a Natural Lake Sediment

The metabolism of methane is an important part of the global carbon cycle. While deciphering the community function and the potential role of the different functional guilds is very difficult when considering native complex communities, synthetic communities, built of species originating from a study site in question, present a simplified model and allow specific questions to be addressed as to carbon, nitrogen, and other nutrient transfer among species in a controlled system. This study applies an ecophysiological approach, as a proof of principle, to an already well-studied model system, contributing to a better understanding of microbial community function and microbial ecosystem processes.

The factors and processes that influence the behavior and functionality of ecosystems inhabited by complex microbiomes are still far from being clearly understood. Synthetic microbial communities provide reduced-complexity models that allow an examination of ecological theories under defined and controlled conditions. In this study, we applied a multiphasic approach to study synthetic methane-oxidizing communities and species interactions as proxies to the natural communities. Our results confirm that, under selective pressures, natural-sediment communities of high complexity simplify rapidly, selecting for several major functional guilds, the major partners in methane oxidation being the Methylococcaceae methanotrophs and the Methylophilaceae methylotrophs, along with minor but persistent partners, members of Burkholderiales and Flavobacteriales. As a proof of concept, we established minimalist synthetic communities that were representative of the four functional guilds to demonstrate the dependency of the non-methane-utilizing species on the methanotrophs as the primary carbon-providing species. We observed that in communities consisting of multiple representatives of the key guilds, members of the same guild appeared to compete for resources. For example, when two methanotrophs of the same family were present, the two expressed similar key methanotrophy pathways and responded similarly to changing environmental conditions, suggesting that they perform a similar keystone function in situ. Similar observations were made for the Methylophilaceae. However, differences were noted in the expression of auxiliary and unique genes among strains of the same functional guild, reflecting differential adaptation and suggesting mechanisms for competition. At the same time, differences were also noted in the performances of partners with specific metabolic schemes. For example, a mutant of Methylotenera mobilis impaired in nitrate utilization behaved as a more efficient cooperator in methane consumption, suggesting that the loss of function may lead to changes in communal behavior. Overall, we demonstrate the robust nature of synthetic communities built of native lake sediment strains and their utility in addressing important ecological questions while using a simplified model.

Synthetic microbial consortia for biosynthesis and biodegradation: promises and challenges

Functional differentiation and metabolite exchange enable microbial consortia to perform complex metabolic tasks and efficiently cycle the nutrients. Inspired by the cooperative relationships in environmental microbial consortia, synthetic microbial consortia have great promise for studying the microbial interactions in nature and more importantly for various engineering applications. However, challenges coexist with promises, and the potential of consortium-based technologies is far from being fully harnessed. Thorough understanding of the underlying molecular mechanisms of microbial interactions is greatly needed for the rational design and optimization of defined consortia. These knowledge gaps could be potentially filled with the assistance of the ongoing revolution in systems biology and synthetic biology tools. As current fundamental and technical obstacles down the road being removed, we would expect new avenues with synthetic microbial consortia playing important roles in biological and environmental engineering processes such as bioproduction of desired chemicals and fuels, as well as biodegradation of persistent contaminants.

Learning Single-Cell Distances from Cytometry Data

Recent years have seen an increased interest in employing data analysis techniques for the automated identification of cell populations in the field of cytometry. These techniques highly depend on the use of a distance metric, a function that quantifies the distances between single-cell measurements. In most cases, researchers simply use the Euclidean distance metric. In this article, we exploit the availability of single-cell labels to find an optimal Mahalanobis distance metric derived from the data. We show that such a Mahalanobis distance metric results in an improved identification of cell populations compared with the Euclidean distance metric. Once determined, it can be used for the analysis of multiple samples that were measured under the same experimental setup. We illustrate this approach for cytometry data from two different origins, that is, flow cytometry applied to microbial cells and mass cytometry for the analysis of human blood cells. We also illustrate that such a distance metric results in an improved identification of cell populations when clustering methods are employed. Generally, these results imply that the performance of data analysis techniques can be improved by using a more advanced distance metric. © 2019 International Society for Advancement of Cytometry.

Advances in the technologies for studying consortia of bacteria and cyanobacteria/microalgae in wastewaters

The excessive generation and discharge of wastewaters have been serious concerns worldwide in the recent past. From an environmental friendly perspective, bacteria, cyanobacteria and microalgae, and the consortia have been largely considered for biological treatment of wastewaters. For efficient use of bacteria‒cyanobacteria/microalgae consortia in wastewater treatment, detailed knowledge on their structure, behavior and interaction is essential. In this direction, specific analytical tools and techniques play a significant role in studying these consortia. This review presents a critical perspective on physical, biochemical and molecular techniques such as microscopy, flow cytometry with cell sorting, nanoSIMS and omics approaches used for systematic investigations of the structure and function, particularly nutrient removal potential of bacteria‒cyanobacteria/microalgae consortia. In particular, the use of specific molecular techniques of genomics, transcriptomics, proteomics metabolomics and genetic engineering to develop more stable consortia of bacteria and cyanobacteria/microalgae with their improved biotechnological capabilities in wastewater treatment has been highlighted.

Reconstructing functional networks in the human intestinal tract using synthetic microbiomes

The human intestinal tract harbors one of the most densely populated and open microbial ecosystems. The application of multi-omics approaches has provided insight into a wide array of complex interactions between the various groups of mainly anaerobic colonic microbes as well as the host-microbe dialogue. Integration of multi-omics techniques in cultivation based experiments that vary in complexity from monocultures to synthetic microbial communities identified key metabolic players in the trophic interactions as well as their ecological dynamics. A synergy between these approaches will be of utmost importance to reconstruct the functional interaction networks at the ecosystem level within the human intestinal microbiome. The improved understanding of microbiome functioning at ecosystem level will further aid in developing better predictive models and design of effective microbiome modulation strategies for health benefits.

Coculturing Bacteria Leads to Reduced Phenotypic Heterogeneities

Isogenic bacterial populations are known to exhibit phenotypic heterogeneity at the single-cell level. Because of difficulties in assessing the phenotypic heterogeneity of a single taxon in a mixed community, the importance of this deeper level of organization remains relatively unknown for natural communities. In this study, we have used membrane-based microcosms that allow the probing of the phenotypic heterogeneity of a single taxon while interacting with a synthetic or natural community. Individual taxa were studied under axenic conditions, as members of a coculture with physical separation, and as a mixed culture. Phenotypic heterogeneity was assessed through both flow cytometry and Raman spectroscopy. Using this setup, we investigated the effect of microbial interactions on the individual phenotypic heterogeneities of two interacting drinking water isolates. Through flow cytometry we have demonstrated that interactions between these bacteria lead to a reduction of their individual phenotypic diversities and that this adjustment is conditional on the bacterial taxon. Single-cell Raman spectroscopy confirmed a taxon-dependent phenotypic shift due to the interaction. In conclusion, our data suggest that bacterial interactions may be a general driver of phenotypic heterogeneity in mixed microbial populations.IMPORTANCE Laboratory studies have shown the impact of phenotypic heterogeneity on the survival and functionality of isogenic populations. Because phenotypic heterogeneity plays an important role in pathogenicity and virulence, antibiotic resistance, biotechnological applications, and ecosystem properties, it is crucial to understand its influencing factors. An unanswered question is whether bacteria in mixed communities influence the phenotypic heterogeneity of their community partners. We found that coculturing bacteria leads to a reduction in their individual phenotypic heterogeneities, which led us to the hypothesis that the individual phenotypic diversity of a taxon is dependent on the community composition.

Coexistence and Pattern Formation in Bacterial Mixtures with Contact-Dependent Killing

Multistrain microbial communities often exhibit complex spatial organization that emerges because of the interplay of various cooperative and competitive interaction mechanisms. One strong competitive mechanism is contact-dependent neighbor killing enabled by the type VI secretion system. It has been previously shown that contact-dependent killing can result in bistability of bacterial mixtures so that only one strain survives and displaces the other. However, it remains unclear whether stable coexistence is possible in such mixtures. Using a population dynamics model for two interacting bacterial strains, we found that coexistence can be made possible by the interplay of contact-dependent killing and long-range growth inhibition, leading to the formation of various cellular patterns. These patterns emerge in a much broader parameter range than that required for the linear Turing-like instability, suggesting this may be a robust mechanism for pattern formation.

Isolation of novel quorum-sensing active bacteria from microbial mats in Shark Bay Australia

Quorum sensing is a potent system of genetic control allowing phenotypes to be coordinated across localized communities. In this study, quorum sensing systems in Shark Bay microbial mats were delineated using a targeted approach analyzing whole mat extractions as well as the creation of an isolate library. A library of 165 isolates from different mat types were screened using the AHL biosensor E. coli MT102. Based on sequence identity 30 unique isolates belonging to Proteobacteria, Actinobacteria and Firmicutes were found to activate the AHL biosensor, suggesting AHLs or analogous compounds were potentially present. Several of the isolates have not been shown previously to produce signal molecules, particularly the members of the Actinobacteria and Firmicutes phyla including Virgibacillus, Halobacillius, Microbacterium and Brevibacterium. These active isolates were further screened using thin-layer chromatography (TLC) providing putative identities of AHL molecules present within the mat communities. Nine isolates were capable of producing several spots of varying sizes after TLC separation, suggesting the presence of multiple signalling molecules. This study is the first to delineate AHL-based signalling in the microbial mats of Shark Bay, and suggests quorum sensing may play a role in the ecosphysiological coordination of complex phenotypes across microbial mat communities.