Deciphering microbial community robustness through synthetic ecology and molecular systems synecology

A systematic discussion and comparison of the construction methods of synthetic microbial community

Synthetic microbial community has widely concerned in the fields of agriculture, food and environment over the past few years. However, there is little consensus on the method to synthetic microbial community from construction to functional verification. Here, we review the concept, characteristics, history and applications of synthetic microbial community, summarizing several methods for synthetic microbial community construction, such as isolation culture, core microbiome mining, automated design, and gene editing. In addition, we also systematically summarized the design concepts, technological thresholds, and applicable scenarios of various construction methods, and highlighted their advantages and limitations. Ultimately, this review provides four efficient, detailed, easy-to-understand and -follow steps for synthetic microbial community construction, with major implications for agricultural practices, food production, and environmental governance.

Synthetic microbial communities: A gateway to understanding resistance, resilience, and functionality in spontaneously fermented food microbiomes

This review delves into the intricate traits of microbial communities encountered in spontaneously fermented foods (SFF), contributing to resistance, resilience, and functionality drivers. Traits of SFF microbiomes comprise of fluctuations in community composition, genetic stability, and condition-specific phenotypes. Synthetic microbial communities (SMCs) serve as a portal for mechanistic insights and strategic re-programming of microbial communities. Current literature underscores the pivotal role of microbiomes in SFF in shaping quality attributes and preserving the cultural heritage of their origin. In contrast to starter driven fermentations that tend to be more controlled but lacking the capacity to maintain or reproduce the complex flavors and intricacies found in SFF. SMCs, therefore, become indispensable tools, providing a nuanced understanding and control over fermented food microbiomes. They empower the prediction and engineering of microbial interactions and metabolic pathways with the aim of optimizing outcomes in food processing. Summarizing the current application of SMCs in fermented foods, there is still space for improvement. Challenges in achieving stability and reproducibility in SMCs are identified, stemming from non-standardized approaches. The future direction should involve embracing standardized protocols, advanced monitoring tools, and synthetic biology applications. A holistic, multi-disciplinary approach is paramount to unleashing the full potential of SMCs and fostering sustainable and innovative applications in fermented food systems.

Assessing long-term ecological impacts of PCE contamination in groundwater using a flow cytometric fingerprint approach

This study aims to develop and validate a comprehensive method for assessing ecological disturbances in groundwater ecosystems caused by tetrachloroethylene (PCE) contamination, utilizing flow cytometry (FCM) fingerprint approach. We hypothesized that the ecological disturbance resulting from PCE contamination would exhibit 'press disturbance', persisting over extended periods, and inducing notable phenotypic differences in the microbial community compared to undisturbed groundwater. We collected 40 groundwater samples from industrial district with a history of over twenty years of PCE contamination, along with 56 control groundwater from the national surveillance groundwater system. FCM revealed significant alterations in the phenotypic diversity of microbial communities in PCE-contaminated groundwater, particularly during the dry season. The presence of specific dechlorinating bacteria (Dehalococcoides, Dehalogenimonas, and Geobacter) and their syntrophic partners was identified as an indicator of contamination. Phenotypic diversity measures provided clearer and more direct reflections of contamination impact compared to taxonomic diversity measures. This study establishes FCM fingerprinting as a simple, robust, and accurate method for evaluating ecological disturbances, with potential applications in early warning systems and continuous monitoring of groundwater contamination. The findings not only underscore the sensitivity of FCM in detecting phenotypic variations induced by environmental stressors but also highlight its utility in understanding the complex dynamics of microbial communities in contaminated groundwater ecosystems.

Probiotics Pediococcus acidilactici GR-1 promotes the functional strains and remodels gut microbiota to reduce the Cr(VI) toxicity in a dual-chamber simulated intestinal system

Numerous animal studies have demonstrated the toxicity of hexavalent chromium [Cr(VI)] and the bioremediative effects of probiotics on the composition and functions of gut microbiota. Since the precise mechanisms of Cr(VI) detoxification and its interactions with human gut microbiota were unknown, a novel dual-chamber simulated intestinal (DCSI) system was developed to maintain both the stability of the simulated system and the composition of the gut microbiota. Probiotic GR-1 was found to regulate intestinal gut microbiota, thereby reducing the toxicity of Cr(VI) within the DCSI system. The results indicate that Cr(VI) levels were reduced from 2.260 ± 0.2438 μg/g to 1.7086 ± 0.1950 μg/g in the gut microbiota cell pellet, and Cr(VI) permeability decreased from 0.5521 ± 0.1132 μg/L to 0.3681 ± 0.0178 μg/L after 48 h in simulated gut fluid. Additionally, the removal rate of 1,1-Diphenyl-2-picrylhydrazyl (DPPH), reducibility (Vitamin C), and total antioxidant capacity (T-AOC) increased by 50.83%, 31.70%, and 27.56%, respectively, following probiotic treatment. The increase in antioxidant capacity correlated with total Cr removal (P < 0.05, r from -0.80 to 0.73). 16S rRNA sequencing analysis showed that gut microbiota composition was reshaped by the addition of probiotics, which regulated the recovery of the functional gut microbiota to normal levels, rather than restoring the entire gut microbiota composition for community function. Thus, this study not only demonstrates the feasibility and stability of culturing gut microbiota but also offers a new biotechnological approach to synthesizing functional communities with functional strains for environmental risk management.

Modeling Microbial Community Networks: Methods and Tools for Studying Microbial Interactions

Microbial interactions function as a fundamental unit in complex ecosystems. By characterizing the type of interaction (positive, negative, neutral) occurring in these dynamic systems, one can begin to unravel the role played by the microbial species. Towards this, various methods have been developed to decipher the function of the microbial communities. The current review focuses on the various qualitative and quantitative methods that currently exist to study microbial interactions. Qualitative methods such as co-culturing experiments are visualized using microscopy-based techniques and are combined with data obtained from multi-omics technologies (metagenomics, metabolomics, metatranscriptomics). Quantitative methods include the construction of networks and network inference, computational models, and development of synthetic microbial consortia. These methods provide a valuable clue on various roles played by interacting partners, as well as possible solutions to overcome pathogenic microbes that can cause life-threatening infections in susceptible hosts. Studying the microbial interactions will further our understanding of complex less-studied ecosystems and enable design of effective frameworks for treatment of infectious diseases.

Loss of submerged macrophytes in shallow lakes alters bacterial and archaeal community structures, and reduces their co-occurrence networks connectivity and complexity

Introduction

Bacteria and archaea are important components in shallow lake ecosystems and are crucial for biogeochemical cycling. While the submerged macrophyte loss is widespread in shallow lakes, the effect on the bacteria and archaea in the sediment and water is not yet widely understood.

Methods

In this study, 16S rRNA gene sequencing was used to explore the bacteria and archaea in samples taken from the sediment and water in the submerged macrophyte abundant (MA) and submerged macrophyte loss (ML) areas of Caohai Lake, Guizhou, China.

Results

The results showed that the dominant bacterial phyla were Proteobacteria and Chloroflexi in the sediment; the dominant phyla were Proteobacteria, Actinobacteriota, and Bacteroidota in the water. The dominant archaea in sediment and water were the same, in the order of Crenarchaeota, Thermoplasmatota, and Halobacterota. Non-metric multidimensional scaling (NMDS) analyses showed that bacterial and archaeal community structures in the water were significantly affected by the loss of submerged macrophytes, but not by significant changes in the sediment. This suggests that the loss of submerged macrophytes has a stronger effect on the bacterial and archaeal community structures in water than in sediment. Furthermore, plant biomass (PB) was the key factor significantly influencing the bacterial community structure in water, while total nitrogen (TN) was the main factor significantly influencing the archaeal community structure in water. The loss of submerged macrophytes did not significantly affect the alpha diversity of the bacterial and archaeal communities in either the sediment or water. Based on network analyses, we found that the loss of submerged macrophytes reduced the connectivity and complexity of bacterial patterns in sediment and water. For archaea, network associations were stronger for MA network than for ML network in sediment, but network complexity for archaea in water was not significantly different between the two areas.

Discussion

This study assesses the impacts of submerged macrophyte loss on bacteria and archaea in lakes from microbial perspective, which can help to provide further theoretical basis for microbiological research and submerged macrophytes restoration in shallow lakes.

Microbial consortium assembly and functional analysis via isotope labelling and single-cell manipulation of polycyclic aromatic hydrocarbon degraders

Soil microbial flora constitutes a highly diverse and complex microbiome on Earth, often challenging to cultivation, with unclear metabolic mechanisms in situ. Here, we present a pioneering concept for the in situ construction of functional microbial consortia (FMCs) and introduce an innovative method for creating FMCs by utilizing phenanthrene as a model compound to elucidate their in situ biodegradation mechanisms. Our methodology involves single-cell identification, sorting, and culture of functional microorganisms, resulting in the formation of a precise in situ FMC. Through Raman-activated cell sorting-stable-isotope probing, we identified and isolated phenanthrene-degrading bacterial cells from Achromobacter sp. and Pseudomonas sp., achieving precise and controllable in situ consortia based on genome-guided cultivation. Our in situ FMC outperformed conventionally designed functional flora when tested in real soil, indicating its superior phenanthrene degradation capacity. We revealed that microorganisms with high degradation efficiency isolated through conventional methods may exhibit pollutant tolerance but lack actual degradation ability in natural environments. This finding highlights the potential to construct FMCs based on thorough elucidation of in situ functional degraders, thereby achieving sustained and efficient pollutant degradation. Single-cell sequencing linked degraders with their genes and metabolic pathways, providing insights regarding the construction of in situ FMCs. The consortium in situ comprising microorganisms with diverse phenanthrene metabolic pathways might offer distinct advantages for enhancing phenanthrene degradation efficiency, such as the division of labour and cooperation or communication among microbial species. Our approach underscores the importance of in situ, single-cell precision identification, isolation, and cultivation for comprehensive bacterial functional analysis and resource exploration, which can extend to investigate MFCs in archaea and fungi, clarifying FMC construction methods for element recycling and pollutant transformation in complex real-world ecosystems.

Heterogeneous bacterial communities affected by phytoplankton community turnover and microcystins in plateau lakes of Southwestern China

Both phytoplankton and bacteria are fundamental organisms with key ecological functions in lake ecosystems. However, the mechanistic interactions through which phytoplankton community change and bacterial communities interact remain poorly understood. Here, the responses of bacterial communities to the community structure, resource-use efficiency (RUE), and community turnover of phytoplankton and microcystins (MCs) were investigated in Lake Dianchi, Lake Xingyun, and Lake Erhai of Southwestern China across two seasons (May and October 2020). Among phytoplankton, Cyanobacteria was the dominant species in all three lakes and attained greater dominance in October than in May due to variation in the RUE of nitrogen and phosphorus and environmental changes. The production of MCs, including MC_LR, MC_RR and MC_YR, was the result of the massive Cyanobacteria. Decreases in diversity and increases in heterogeneity were observed in the bacterial community structure. Nutrient levels, environmental factors and MCs (especially MC_YR) jointly affected the bacterial community in lakes, namely its diversity and community assembly. The cascading effects in lakes mediated by environmental conditions, phytoplankton community composition, RUE, community turnover, and MCs on bacterial communities were revealed in this study. These findings underscore the importance of relating phytoplankton community change and MCs to the bacterial community, which is fundamental for better understanding the lake ecosystem functioning and potential risks of MCs.

Correlation Analysis of Microbial Community Changes and Physicochemical Characteristics in Aged Vinegar Brewing

This study aimed to explore key physicochemical characteristics and evolutionary patterns of microbial community structure during the fermentation of aged vinegar. The correlation between microorganisms and physicochemical characteristics during fermentation was examined. The results revealed significant differences in genera at different stages of fermentation. The dominant bacteria in R1 were Bacillus, Lactobacillus, Aspergillus, and Issatchenkia. During the R2 fermentation stage, Lactobacillus, Acetobacter, and Saccharomyces exhibited an upward trend and finally became the dominant bacteria. Aspergillus was the main bacterial genus at the end of overall fermentation. The correlation analysis showed that the bacterial genera significantly positively and negatively correlated with reducing sugars and amino acid nitrogen were the same in Cuqu. Similarly, the bacterial genera significantly positively and negatively correlated with pH and saccharification power were the same. pH, reducing sugar, and saccharification ability were mainly positively correlated with bacterial genera during fermentation. Further, studies found that the overall correlation between fungal communities and physicochemical characteristics was weaker than the correlation with bacteria during fermentation.

Stability of human gut microbiome: Comparison of ecological modelling and observational approaches

The gut microbiome plays a pivotal role in the human body, and perturbations in its composition have been linked to various disorders. Stability is an essential property of a healthy human gut microbiome, which allows it to maintain its functional richness under the external influences. This property has been explored through two distinct methodologies - mathematical modelling based on ecological principles and statistical analysis drawn from observations in interventional studies. Here we conducted a meta-analysis aimed to compare the two approaches utilising the data from 9 interventional and time series studies encompassing 3512 gut microbiome profiles obtained via 16S rRNA gene sequencing. By employing the previously published compositional Lotka-Volterra method, we modelled the dynamics of the microbial community and evaluated ecological stability measures. These measures were compared to those based on observed microbiome changes. There was a substantial correlation between the outcomes of the two approaches. Particularly, local stability assessed within the ecological paradigm was positively correlated with observational stability measures accounting for the compositional nature of microbiome data. Additionally, we were able to reproduce the previously reported inverse relationship between the community's robustness to microorganism loss and local stability, attributed to the distinct impacts of coefficient characterising the network decomposition on these two stability assessments. Our findings demonstrate harmonisation between the ecological and observational approaches to microbiome analysis, advancing the understanding of healthy gut microbiome concept. This paves the way to develop efficient microbiome-targeting interventions for disease prevention and treatment.

Spontaneously established syntrophic yeast communities improve bioproduction

Nutritional codependence (syntrophy) has underexplored potential to improve biotechnological processes by using cooperating cell types. So far, design of yeast syntrophic communities has required extensive genetic manipulation, as the co-inoculation of most eukaryotic microbial auxotrophs does not result in cooperative growth. Here we employ high-throughput phenotypic screening to systematically test pairwise combinations of auxotrophic Saccharomyces cerevisiae deletion mutants. Although most coculture pairs do not enter syntrophic growth, we identify 49 pairs that spontaneously form syntrophic, synergistic communities. We characterized the stability and growth dynamics of nine cocultures and demonstrated that a pair of tryptophan auxotrophs grow by exchanging a pathway intermediate rather than end products. We then introduced a malonic semialdehyde biosynthesis pathway split between different pairs of auxotrophs, which resulted in increased production. Our results report the spontaneous formation of stable syntrophy in S. cerevisiae auxotrophs and illustrate the biotechnological potential of dividing labor in a cooperating intraspecies community.

Microbiome engineering for bioremediation of emerging pollutants

Axenic microbial applications in the open environment are unrealistic and may not be always practically viable. Therefore, it is important to use mixed microbial cultures and their interactions with the microbiome in the targeted ecosystem to perform robust functions towards their sustainability in harsh environmental conditions. Emerging pollutants like phthalates and hydrocarbons that are toxic to several aquatic and terrestrial life forms in the water bodies and lands are an alarming situation. The present review explores the possibility of devising an inclusive eco-friendly strategy like microbiome engineering which proves to be a unique and crucial technology involving the power of microbial communication through quorum sensing. This review discusses the interspecies and intra-species communications between different microbial groups with their respective environments. Moreover, this review also envisages the efforts for designing the next level of microbiome-host engineering concept (MHEC). The focus of the review also extended toward using omics and metabolic network analysis-based tools for effective microbiome engineering. These approaches might be quite helpful in the future to understand such microbial interactions but it will be challenging to implement in the real environment to get the desired functions. Finally, the review also discusses multiple approaches for the bioremediation of toxic chemicals from the soil environment.

The Fashion Industry Needs Microbiology: Opportunities and Challenges

The fashion industry is the second most polluting industry in the world, representing a 2 trillion dollars and growing valuation. Fashion design practices have been perpetuating an industrial-focused approach, which relies mostly in the economic improvement through fast cycles of product development. Additionally, the fashion industry has also been closed to either multidisciplinary or transdisciplinary initiatives outside the scope of the artistic disciplines. Therefore, innovative approaches are needed to solve fashion industrial challenges. One of the most promising fields to tackle current environmental and technological problems in the fashion industry is microbiology. Through the emergent field of synthetic biology, the number of tools and approaches available is increasing and they can already be seen in niche applications. Despite the current advances and urgent need for change, there is still a long way until a more sustainable fashion industry is achieved.

Nutrient dynamics and microbial community response in macrophyte-dominated lakes: Implications for improved restoration strategies

Although lakes dominated by macrophytes are conducive to ecological balance, this balance is easily disrupted by excessive nutrients flowing into the lake. However, knowledge of whether excessive nutrients lead to different microbial environmental vulnerabilities in the lake sediment between macrophyte-dominated areas and macrophyte-free areas is a prerequisite for the implementation of targeted protection measures. In this study, we investigated bacterial communities in sediments using high-throughput sequencing of 16S rRNA genes. Our results showed that the sources of total nitrogen (TN) and organic matter (OM) were related to the macrophytes. The structure, drivers, and interspecific associations of bacterial community, which were more susceptible to increased changes in TN and OM, differed significantly between macrophyte-dominated areas and macrophyte-free areas. More precisely, the lake edge, where was occupied by macrophytes, had a higher proportion of deterministic phylogenetic turnover (88.89%) than other sites, as well as a wider ecological niche and a tighter network structure. Further, as the difference in TN increased, the main assembly processes in surface sediments changed from stochastic to deterministic. However, the majority of phyla from the lake edge showed a greater correlation with excessive nutrients, and the selection of the community by excessive nutrients was more obvious at the edge of the lake. In addition, our results demonstrated that the stability of the bacterial community in macrophyte-free areas is greater than in macrophyte-dominated areas, while an excessively high deterministic process ratio and nutrient (TN and OM) concentration significantly reduced bacterial community stability at macrophyte-dominated areas. Taken together, these results provide a better understanding of the effects of excessive nutrients derived from macrophytes on bacterial community patterns, and highlight the importance of avoiding the accumulation of TN and OM in macrophyte-dominated areas to enhance the sustainability of the ecosystem after restoration of lakes with macrophytes.

Metagenomic Analysis of Garden Soil-Derived Microbial Consortia and Unveiling Their Metabolic Potential in Mitigating Toxic Hexavalent Chromium

Soil microbial communities connect to the functional environment and play an important role in the biogeochemical cycle and waste degradation. The current study evaluated the distribution of the core microbial population of garden soil in the Varanasi region of Uttar Pradesh, India and their metabolic potential for mitigating toxic hexavalent chromium from wastewater. Metagenomes contain 0.2 million reads and 56.5% GC content. The metagenomic analysis provided insight into the relative abundance of soil microbial communities and revealed the domination of around 200 bacterial species belonging to different phyla and four archaeal phyla. The top 10 abundant genera in garden soil were Gemmata, Planctomyces, Steroidobacter, Pirellula, Pedomicrobium, Rhodoplanes, Nitrospira Mycobacterium, Pseudonocardia, and Acinetobacter. In this study, Gemmata was dominating bacterial genera. Euryarchaeota, Parvarchaeota, and Crenarchaeota archaeal species were present with low abundance in soil samples. X-ray photoelectric spectroscopy (XPS) analysis indicates the presence of carbon, nitrogen-oxygen, calcium, phosphorous, and silica in the soil. Soil-derived bacterial consortia showed high hexavalent chromium [Cr (VI)] removal efficiency (99.37%). The bacterial consortia isolated from garden soil had an important role in the hexavalent chromium bioremediation, and thus, this study could be beneficial for the design of a heavy-metal treatment system.

Cybergenetic control of microbial community composition

The use of bacterial communities in bioproduction instead of monocultures has potential advantages including increased productivity through division of labour, ability to utilise cheaper substrates, and robustness against perturbations. A key challenge in the application of engineered bacterial communities is the ability to reliably control the composition of the community in terms of its constituent species. This is crucial to prevent faster growing species from outcompeting others with a lower relative fitness, and to ensure that all species are present at an optimal ratio during different steps in a biotechnological process. In contrast to purely biological approaches such as synthetic quorum sensing circuits or paired auxotrophies, cybergenetic control techniques - those in which computers interface with living cells-are emerging as an alternative approach with many advantages. The community composition is measured through methods such as fluorescence intensity or flow cytometry, with measured data fed real-time into a computer. A control action is computed using a variety of possible control algorithms and then applied to the system, with actuation taking the form of chemical (e.g., inducers, nutrients) or physical (e.g., optogenetic, mechanical) inputs. Subsequent changes in composition are then measured and the cycle repeated, maintaining or driving the system to a desired state. This review discusses recent and future developments in methods for implementing cybergenetic control systems, contrasts their capabilities with those of traditional biological methods of population control, and discusses future directions and outstanding challenges for the field.

Multiscale engineering of microbial cell factories: A step forward towards sustainable natural products industry

Microbial cell factories (bacteria and fungi) are the leading producers of beneficial natural products such as lycopene, carotene, herbal medicine, and biodiesel etc. These microorganisms are considered efficient due to their effective bioprocessing strategy (monoculture- and consortial-based approach) under distinct processing conditions. Meanwhile, the advancement in genetic and process optimization techniques leads to enhanced biosynthesis of natural products that are known functional ingredients with numerous applications in the food, cosmetic and medical industries. Natural consortia and monoculture thrive in nature in a small proportion, such as wastewater, food products, and soils. In similitude to natural consortia, it is possible to engineer artificial microbial consortia and program their behaviours via synthetic biology tools. Therefore, this review summarizes the optimization of genetic and physicochemical parameters of the microbial system for improved production of natural products. Also, this review presents a brief history of natural consortium and describes the functional properties of monocultures. This review focuses on synthetic biology tools that enable new approaches to design synthetic consortia; and highlights the syntropic interactions that determine the performance and stability of synthetic consortia. In particular, the effect of processing conditions and advanced genetic techniques to improve the productibility of both monoculture and consortial based systems have been greatly emphasized. In this context, possible strategies are also discussed to give an insight into microbial engineering for improved production of natural products in the future. In summary, it is concluded that the coupling of genomic modifications with optimum physicochemical factors would be promising for producing a robust microbial cell factory that shall contribute to the increased production of natural products.

Effective orthophosphate removal from surface water using hydrogen-oxidizing bacteria: Moving towards applicability

Effective orthophosphate removal strategies are needed to counteract eutrophication and guarantee water quality. Previously, we established that hydrogen-oxidizing bacteria (HOB) have the ability to remove orthophosphate from artificial surface water. In the present study, we expand the application of the HOB orthophosphate removal strategy (1) to treat artificial surface water with low initial orthophosphate concentrations, (2) to treat real surface water and real wastewater effluent, and (3) to remove orthophosphate continuously. For synthetic surface water, irrespective of the initial concentration of 0.7, 0.5, 0.3, and 0.1 mg PO₄^3--P/L, ultra-low concentrations (0.0058 ± 0.0028 mg PO₄^3--P/L) were obtained. When artificial surface water was replaced by real surface water, without added nutrients or other chemicals, it was shown that over 90% orthophosphate could be removed within 30 min of operation in a batch configuration (0.031 ± 0.023 mg PO₄^3--P/L). In continuous operation, orthophosphate removal from surface water left an average concentration of 0.040 ± 0.036 for 60 days, and the lowest orthophosphate concentration measured was 0.013 mg PO₄^3-/L. Simultaneously, nitrate was continuously removed for 60 days below 0.1 mg/L. The ability to remove orthophosphate even under nitrogen limiting conditions might be related to the ability of HOB to fix nitrogen. This study brings valuable insights into the potential use of HOB biofilms for nutrient remediation and recovery.

Resolving the Rules of Robustness and Resilience in Biology Across Scales

Why do some biological systems and communities persist while others fail? Robustness, a system's stability, and resilience, the ability to return to a stable state, are key concepts that span multiple disciplines within and outside the biological sciences. Discovering and applying common rules that govern the robustness and resilience of biological systems is a critical step toward creating solutions for species survival in the face of climate change, as well as the for the ever-increasing need for food, health, and energy for human populations. We propose that network theory provides a framework for universal scalable mathematical models to describe robustness and resilience and the relationship between them, and hypothesize that resilience at lower organization levels contribute to robust systems. Insightful models of biological systems can be generated by quantifying the mechanisms of redundancy, diversity, and connectivity of networks, from biochemical processes to ecosystems. These models provide pathways towards understanding how evolvability can both contribute to and result from robustness and resilience under dynamic conditions. We now have an abundance of data from model and non-model systems and the technological and computational advances for studying complex systems. Several conceptual and policy advances will allow the research community to elucidate the rules of robustness and resilience. Conceptually, a common language and data structure that can be applied across levels of biological organization needs to be developed. Policy advances such as cross-disciplinary funding mechanisms, access to affordable computational capacity, and the integration of network theory and computer science within the standard biological science curriculum will provide the needed research environments. This new understanding of biological systems will allow us to derive ever more useful forecasts of biological behaviors and revolutionize the engineering of biological systems that can survive changing environments or disease, navigate the deepest oceans, or sustain life throughout the solar system.

Cooperation within the microbial consortia of fermented grains and pit mud drives organic acid synthesis in strong-flavor Baijiu production

Mud cellars have long been used as anaerobic bioreactors for the fermentation of Chinese strong-flavor Baijiu, where starchy raw materials (mainly sorghum) are metabolized to ethanol and various flavor compounds by multi-species microorganisms. Jiupei (fermented grains) and pit mud are two spatially linked microbial habitats in the mud cellar, yet their metabolic division of labor remains unclear. Here, we investigated the changes in environmental variables (e.g., temperature, oxygen, pH), key metabolites (e.g., ethanol, organic acids) and microbial communities in jiupei and pit mud during fermentation. Jiupei (low pH, high ethanol) and pit mud (neutral pH) provided two habitats with distinctly different environmental conditions for microbial growth. Lactic acid accumulated in jiupei, while butyric and hexanoic acids were mainly produced by microbes inhabiting the pit mud. Biomass analysis using quantitative real-time PCR showed that bacteria dominated the microbial consortia during fermentation, moreover cluster and principal coordinate analysis (PCoA) analysis showed that the bacterial communities of jiupei and pit mud were significantly divergent. The bacterial community diversity of jiupei decreased significantly during the fermentation process, and was relatively stable in pit mud. Lactobacillus dominated the jiupei bacterial community, and its relative abundance reached 98.0% at the end of fermentation. Clostridia (relative abundance: 42.9-85.5%) was the most abundant bacteria in pit mud, mainly distributed in the genus Hydrogenispora (5.3-68.4%). Fungal communities of jiupei and pit mud showed a similar succession pattern, and Kazachstania, Aspergillus and Thermoascus were the predominant genera. PICRUSt analysis demonstrated that enzymes participating in the biosynthesis of acetic and lactic acid were mainly enriched in jiupei samples, while the bacterial community in the pit mud displayed greater potential for butyric and hexanoic acid synthesis. Assays from an in vitro simulated fermentation further validated the roles of jiupei microbiota in acetic and lactic acid production, and these acids were subsequently metabolized to butyric and hexanoic acid by the pit mud microbiota. This work has demonstrated the synergistic cooperation between the microbial communities of jiupei and pit mud for the representative flavor formation of strong-flavor Baijiu.

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.

Enhancement of microbiome management by machine learning for biological wastewater treatment

Here, we propose to develop microbiome-based machine learning models to predict the response of biological wastewater treatment systems to environmental or operational disturbances or to design specific microbiomes to achieve a desired system function. These machine learning models can be used to enhance the stability of microbiome-based biological systems and warn against the failure of these systems.

Interrelationships of Fiber-Associated Anaerobic Fungi and Bacterial Communities in the Rumen of Bloated Cattle Grazing Alfalfa

Frothy bloat is major digestive disorder of cattle grazing alfalfa pastures. Among the many factors identified to contribute to the development of frothy bloat, the disruption of rumen microbiota appears to be of central importance. Anaerobic rumen fungi (ARF) play an important role in sequential breakdown and fermentation of plant polysaccharides and promote the physical disruption of plant cell walls. In the present study, we investigated the dynamics of ARF during the development of alfalfa-induced frothy bloat and in response to bloat preventive treatments. By sequencing the internal transcribed spacer (ITS1) region of metagenomic DNA from the solid fraction of rumen contents, we were able to identify eight distinct genera of ARF, including Neocallimastix, Caecomyces, Orpinomyces, Piromyces, Cyllamyces, Anaeromyces, Buwchfawromyces, and unclassified Neocallimastigaceae. Overall, transition of steers from a baseline hay diet to alfalfa pastures was associated with drastic changes in the composition of the fungal community, but the overall composition of ARF did not differ (p > 0.05) among bloated and non-bloated steers. A correlation network analysis of the proportion of ARF and ruminal bacterial communities identified hub fungal species that were negatively correlated with several bacterial species, suggesting the presence of inter-kingdom competition among these rumen microorganisms. Interestingly, the number of negative correlations among ARF and bacteria decreased with frothy bloat, indicating a potential disruption of normal microbial profiles within a bloated rumen ecosystem. A better understanding of fungal-bacterial interactions that differ among bloated and non-bloated rumen ecosystem could advance our understanding of the etiology of frothy bloat.

Diversity Manipulation of Psychrophilic Bacterial Consortia for Improved Biological Treatment of Medium-Strength Wastewater at Low Temperature

Psychrophilic bacteria are valuable biocatalysts to develop robust bioaugmentation formulations for enhanced wastewater treatment at low temperatures or fluctuating temperature conditions. Here, using different biodiversity indices [based on species richness (SR), phylogenetic diversity (PD) and functional diversity (FD)], we studied the effects of microbial diversity of artificial bacterial consortia on the biomass gross yields (measured through OD₆₀₀) and removal efficiency of soluble chemical oxygen demand (mg sCOD removed/mg sCOD introduced) in synthetic, medium-strength wastewater. We built artificial consortia out of one to six bacterial strains isolated at 4°C through combinatorial biodiversity experiments. Increasing species richness resulted in improved sCOD removal efficiency (i.e., 0.266 ± 0.146, 0.542 ± 0.155, 0.742 ± 0.136, 0.822 ± 0.019 for mono-, tri-, penta-and hexacultures, respectively) and higher biomass gross yields (i.e., 0.065 ± 0.052, 0.132 ± 0.046, 0.173 ± 0.049, 0.216 ± 0.019 for mono-, tri-, penta,- and hexacultures, respectively). This positive relationship between biodiversity, sCOD removal and biomass gross yield was also observed when considering metabolic profiling (functional diversity) or evolutionary relationships (phylogenetic diversity). The positive effect of biodiversity on sCOD removal efficiency could be attributed to the selection of a particular, best-performing species (i.e., Pedobacter sp.) as well as complementary use of carbon resources among consortia members (i.e., complementarity effects). Among the biodiversity indices, PD diversity metrics explained higher variation in sCOD removal than SR and FD diversity metrics. For a more effective bioaugmentation, our results stress the importance of using phylogenetically diverse consortia, with an increased degradation ability, instead of single pure cultures. Moreover, PD could be used as an assembly rule to guide the composition of mixed cultures for wastewater bioaugmentation under psychrophilic conditions.

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.

Antimicrobial Resistance in Veterinary Medicine: An Overview

Antimicrobial resistance (AMR) represents one of the most important human- and animal health-threatening issues worldwide. Bacterial capability to face antimicrobial compounds is an ancient feature, enabling bacterial survival over time and the dynamic surrounding. Moreover, bacteria make use of their evolutionary machinery to adapt to the selective pressure exerted by antibiotic treatments, resulting in reduced efficacy of the therapeutic intervention against human and animal infections. The mechanisms responsible for both innate and acquired AMR are thoroughly investigated. Commonly, AMR traits are included in mobilizable genetic elements enabling the homogeneous diffusion of the AMR traits pool between the ecosystems of diverse sectors, such as human medicine, veterinary medicine, and the environment. Thus, a coordinated multisectoral approach, such as One-Health, provides a detailed comprehensive picture of the AMR onset and diffusion. Following a general revision of the molecular mechanisms responsible for both innate and acquired AMR, the present manuscript focuses on reviewing the contribution of veterinary medicine to the overall issue of AMR. The main sources of AMR amenable to veterinary medicine are described, driving the attention towards the indissoluble cross-talk existing between the diverse ecosystems and sectors and their cumulative cooperation to this warning phenomenon.

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.

Characterizing species interactions that contribute to biofilm formation in a multispecies model of a potable water bacterial community

Microbial biofilms are ubiquitous in drinking water systems, yet our understanding of drinking water biofilms lags behind our understanding of those in other environments. Here, a six-member model bacterial community was used to identify the interactions and individual contributions of each species to community biofilm formation. These bacteria were isolated from the International Space Station potable water system and include Cupriavidus metallidurans, Chryseobacterium gleum, Ralstonia insidiosa, Ralstonia pickettii, Methylorubrum (Methylobacterium) populi and Sphingomonas paucimobilis, but all six species are common members of terrestrial potable water systems. Using reconstituted assemblages, from pairs to all 6 members, community biofilm formation was observed to be robust to the absence of any single species and only removal of the C. gleum/S. paucimobilis pair, out of all 15 possible 2-species subtractions, led to loss of community biofilm formation. In conjunction with these findings, dual-species biofilm formation assays supported the view that the contribution of C. gleum to community biofilm formation was dependent on synergistic biofilm formation with either R. insidiosa or C. metallidurans. These data support a model of multiple, partially redundant species interactions to generate robustness in biofilm formation. A bacteriophage and multiple predatory bacteria were used to test the resilience of the community to the removal of individual members in situ, but the combination of precise and substantial depletion of a single target species was not achievable. We propose that this assemblage can be used as a tractable model to understand the molecular bases of the interactions described here and to decipher other functions of drinking water biofilms.

Nutrient Exchange of Carbon and Nitrogen Promotes the Formation of Stable Mutualisms Between Chlorella sorokiniana and Saccharomyces cerevisiae Under Engineered Synthetic Growth Conditions

Microbial biotechnological processes can be based on single species pure cultures or on multi-species assemblages. While these assemblages can be advantageous by offering more functionalities and more resilience to changing environmental conditions, they can be unpredictable and difficult to control under synthetically engineered growth conditions. To overcome the unpredictable nature of these microbial assemblages, the generation of stable mutualistic systems through synthetic ecology approaches may provide novel solutions for understanding microbial interactions in these environments. Here we establish a stable association between two evolutionarily unrelated, but biotechnologically complementary species isolated from winery wastewater; a strain of the yeast Saccharomyces cerevisiae and microalga, Chlorella sorokiniana. Yeast and microalgae were able to form obligate (interdependent) and non-obligate (facultative) mutualisms under engineered batch co-culture growth conditions. Obligate mutualism was maintained through the reciprocal exchange of carbon and nitrogen where the yeast ferments mannose to produce carbon dioxide for use by the microalga; and the microalga provides the yeast with nitrogen by metabolizing nitrite to ammonium. The effect of temperature and pH on the establishment of these mutualisms was evaluated and pH was found to be a key determinant for mutualism formation under obligatory conditions. Moreover, the combinations of the two species under non-obligatory growth conditions led to improvement in growth rate and biomass production when compared to single species cultures grown under the same conditions. Such engineered mutualisms are the first step in developing stable multi-species assemblages, while providing a system to generate novel insight into the evolution of mutualistic interactions between phylogenetically distant microorganisms.

Synthetic Biology Tools to Engineer Microbial Communities for Biotechnology

Microbial consortia have been used in biotechnology processes, including fermentation, waste treatment, and agriculture, for millennia. Today, synthetic biologists are increasingly engineering microbial consortia for diverse applications, including the bioproduction of medicines, biofuels, and biomaterials from inexpensive carbon sources. An improved understanding of natural microbial ecosystems, and the development of new tools to construct synthetic consortia and program their behaviors, will vastly expand the functions that can be performed by communities of interacting microorganisms. Here, we review recent advancements in synthetic biology tools and approaches to engineer synthetic microbial consortia, discuss ongoing and emerging efforts to apply consortia for various biotechnological applications, and suggest future applications.

Initial evenness determines diversity and cell density dynamics in synthetic microbial ecosystems

The effect of initial evenness on the temporal trajectory of synthetic communities in comprehensive, low-volume microcosm studies remains unknown. We used flow cytometric fingerprinting and 16S rRNA gene amplicon sequencing to assess the impact of time on community structure in one hundred synthetic ecosystems of fixed richness but varying initial evenness. Both methodologies uncovered a similar reduction in diversity within synthetic communities of medium and high initial evenness classes. However, the results of amplicon sequencing showed that there were no significant differences between and within the communities in all evenness groups at the end of the experiment. Nevertheless, initial evenness significantly impacted the cell density of the community after five medium transfers. Highly even communities retained the highest cell densities at the end of the experiment. The relative abundances of individual species could be associated to particular evenness groups, suggesting that their presence was dependent on the initial evenness of the synthetic community. Our results reveal that using synthetic communities for testing ecological hypotheses requires prior assessment of initial evenness, as it impacts temporal dynamics.

Microbial consortia: a critical look at microalgae co-cultures for enhanced biomanufacturing

Monocultures have been the preferred production route in the bio-industry, where contamination has been a major bottleneck. In nature, microorganisms usually exist as part of organized communities and consortia, gaining benefits from co-habitation, keeping invaders at bay. There is increasing interest in the use of co-cultures to tackle contamination issues, and simultaneously increase productivity and product diversity. The feasibility of extending the natural phenomenon of co-habitation to the biomanufacturing industry in the form of co-cultures requires careful and systematic consideration of several aspects. This article will critically examine and review current work on microbial co-cultures, with the intent of examining the concept and proposing a design pipeline that can be developed in a biomanufacturing context.

Parallelized, Aerobic, Single Carbon-Source Enrichments from Different Natural Environments Contain Divergent Microbial Communities

Microbial communities that inhabit environments such as soil can contain thousands of distinct taxa, yet little is known about how this diversity is maintained in response to environmental perturbations such as changes in the availability of carbon. By utilizing aerobic substrate arrays to examine the effect of carbon amendment on microbial communities taken from six distinct environments (soil from a temperate prairie and forest, tropical forest soil, subalpine forest soil, and surface water and soil from a palustrine emergent wetland), we examined how carbon amendment and inoculum source shape the composition of the community in each enrichment. Dilute subsamples from each environment were used to inoculate 96-well microtiter plates containing triplicate wells amended with one of 31 carbon sources from six different classes of organic compounds (phenols, polymers, carbohydrates, carboxylic acids, amines, amino acids). After incubating each well aerobically in the dark for 72 h, we analyzed the composition of the microbial communities on the substrate arrays as well as the initial inocula by sequencing 16S rRNA gene amplicons using the Illumina MiSeq platform. Comparisons of alpha and beta diversity in these systems showed that, while the composition of the communities that grow to inhabit the wells in each substrate array diverges sharply from that of the original community in the inoculum, these enrichment communities are still strongly affected by the inoculum source. We found most enrichments were dominated by one or several OTUs most closely related to aerobes or facultative anaerobes from the Proteobacteria (e.g., Pseudomonas, Burkholderia, and Ralstonia) or Bacteroidetes (e.g., Chryseobacterium). Comparisons within each substrate array based on the class of carbon source further show that the communities inhabiting wells amended with a carbohydrate differ significantly from those enriched with a phenolic compound. Selection therefore seems to play a role in shaping the communities in the substrate arrays, although some stochasticity is also seen whereby several replicate wells within a single substrate array display strongly divergent community compositions. Overall, the use of highly parallel substrate arrays offers a promising path forward to study the response of microbial communities to perturbations in a changing environment.

Analysis of Microbial Functions in the Rhizosphere Using a Metabolic-Network Based Framework for Metagenomics Interpretation

Advances in metagenomics enable high resolution description of complex bacterial communities in their natural environments. Consequently, conceptual approaches for community level functional analysis are in high need. Here, we introduce a framework for a metagenomics-based analysis of community functions. Environment-specific gene catalogs, derived from metagenomes, are processed into metabolic-network representation. By applying established ecological conventions, network-edges (metabolic functions) are assigned with taxonomic annotations according to the dominance level of specific groups. Once a function-taxonomy link is established, prediction of the impact of dominant taxa on the overall community performances is assessed by simulating removal or addition of edges (taxa associated functions). This approach is demonstrated on metagenomic data describing the microbial communities from the root environment of two crop plants – wheat and cucumber. Predictions for environment-dependent effects revealed differences between treatments (root vs. soil), corresponding to documented observations. Metabolism of specific plant exudates (e.g., organic acids, flavonoids) was linked with distinct taxonomic groups in simulated root, but not soil, environments. These dependencies point to the impact of these metabolite families as determinants of community structure. Simulations of the activity of pairwise combinations of taxonomic groups (order level) predicted the possible production of complementary metabolites. Complementation profiles allow formulating a possible metabolic role for observed co-occurrence patterns. For example, production of tryptophan-associated metabolites through complementary interactions is unique to the tryptophan-deficient cucumber root environment. Our approach enables formulation of testable predictions for species contribution to community activity and exploration of the functional outcome of structural shifts in complex bacterial communities. Understanding community-level metabolism is an essential step toward the manipulation and optimization of microbial function. Here, we introduce an analysis framework addressing three key challenges of such data: producing quantified links between taxonomy and function; contextualizing discrete functions into communal networks; and simulating environmental impact on community performances. New technologies will soon provide a high-coverage description of biotic and a-biotic aspects of complex microbial communities such as these found in gut and soil. This framework was designed to allow the integration of high-throughput metabolomic and metagenomic data toward tackling the intricate associations between community structure, community function, and metabolic inputs.

Probiotic Diversity Enhances Rhizosphere Microbiome Function and Plant Disease Suppression

Bacterial communities associated with plant roots play an important role in the suppression of soil-borne pathogens, and multispecies probiotic consortia may enhance disease suppression efficacy. Here we introduced defined Pseudomonas species consortia into naturally complex microbial communities and measured the importance of Pseudomonas community diversity for their survival and the suppression of the bacterial plant pathogen Ralstonia solanacearum in the tomato rhizosphere microbiome. The survival of introduced Pseudomonas consortia increased with increasing diversity. Further, high Pseudomonas diversity reduced pathogen density in the rhizosphere and decreased the disease incidence due to both intensified resource competition and interference with the pathogen. These results provide novel mechanistic insights into elevated pathogen suppression by diverse probiotic consortia in naturally diverse plant rhizospheres. Ecologically based community assembly rules could thus play a key role in engineering functionally reliable microbiome applications.

The increasing demand for food supply requires more-efficient control of plant diseases. The use of probiotics, i.e., naturally occurring bacterial antagonists and competitors that suppress pathogens, has recently reemerged as a promising alternative to agrochemical use. It is, however, still unclear how many and which strains we should choose for constructing effective probiotic consortia. Here we present a general ecological framework for assembling effective probiotic communities based on in vitro characterization of community functioning. Specifically, we show that increasing the diversity of probiotic consortia enhances community survival in the naturally diverse rhizosphere microbiome, leading to increased pathogen suppression via intensified resource competition and interference with the pathogen. We propose that these ecological guidelines can be put to the test in microbiome engineering more widely in the future.

Metagenomics: Probing pollutant fate in natural and engineered ecosystems

Polluted environments are a reservoir of microbial species able to degrade or to convert pollutants to harmless compounds. The proper management of microbial resources requires a comprehensive characterization of their genetic pool to assess the fate of contaminants and increase the efficiency of bioremediation processes. Metagenomics offers appropriate tools to describe microbial communities in their whole complexity without lab-based cultivation of individual strains. After a decade of use of metagenomics to study microbiomes, the scientific community has made significant progress in this field. In this review, we survey the main steps of metagenomics applied to environments contaminated with organic compounds or heavy metals. We emphasize technical solutions proposed to overcome encountered obstacles. We then compare two metagenomic approaches, i.e. library-based targeted metagenomics and direct sequencing of metagenomes. In the former, environmental DNA is cloned inside a host, and then clones of interest are selected based on (i) their expression of biodegradative functions or (ii) sequence homology with probes and primers designed from relevant, already known sequences. The highest score for the discovery of novel genes and degradation pathways has been achieved so far by functional screening of large clone libraries. On the other hand, direct sequencing of metagenomes without a cloning step has been more often applied to polluted environments for characterization of the taxonomic and functional composition of microbial communities and their dynamics. In this case, the analysis has focused on 16S rRNA genes and marker genes of biodegradation. Advances in next generation sequencing and in bioinformatic analysis of sequencing data have opened up new opportunities for assessing the potential of biodegradation by microbes, but annotation of collected genes is still hampered by a limited number of available reference sequences in databases. Although metagenomics is still facing technical and computational challenges, our review of the recent literature highlights its value as an aid to efficiently monitor the clean-up of contaminated environments and develop successful strategies to mitigate the impact of pollutants on ecosystems.

Spatial and Temporal Dynamics of Pacific Oyster Hemolymph Microbiota across Multiple Scales

Unveiling the factors and processes that shape the dynamics of host associated microbial communities (microbiota) under natural conditions is an important part of understanding and predicting an organism's response to a changing environment. The microbiota is shaped by host (i.e., genetic) factors as well as by the biotic and abiotic environment. Studying natural variation of microbial community composition in multiple host genetic backgrounds across spatial as well as temporal scales represents a means to untangle this complex interplay. Here, we combined a spatially-stratified with a longitudinal sampling scheme within differentiated host genetic backgrounds by reciprocally transplanting Pacific oysters between two sites in the Wadden Sea (Sylt and Texel). To further differentiate contingent site from host genetic effects, we repeatedly sampled the same individuals over a summer season to examine structure, diversity and dynamics of individual hemolymph microbiota following experimental removal of resident microbiota by antibiotic treatment. While a large proportion of microbiome variation could be attributed to immediate environmental conditions, we observed persistent effects of antibiotic treatment and translocation suggesting that hemolymph microbial community dynamics is subject to within-microbiome interactions and host population specific factors. In addition, the analysis of spatial variation revealed that the within-site microenvironmental heterogeneity resulted in high small-scale variability, as opposed to large-scale (between-site) stability. Similarly, considerable within-individual temporal variability was in contrast with the overall temporal stability at the site level. Overall, our longitudinal, spatially-stratified sampling design revealed that variation in hemolymph microbiota is strongly influenced by site and immediate environmental conditions, whereas internal microbiome dynamics and oyster-related factors add to their long-term stability. The combination of small and large scale resolution of spatial and temporal observations therefore represents a crucial but underused tool to study host-associated microbiome dynamics.

Biotic Interactions in Microbial Communities as Modulators of Biogeochemical Processes: Methanotrophy as a Model System

Microbial interaction is an integral component of microbial ecology studies, yet the role, extent, and relevance of microbial interaction in community functioning remains unclear, particularly in the context of global biogeochemical cycles. While many studies have shed light on the physico-chemical cues affecting specific processes, (micro)biotic controls and interactions potentially steering microbial communities leading to altered functioning are less known. Yet, recent accumulating evidence suggests that the concerted actions of a community can be significantly different from the combined effects of individual microorganisms, giving rise to emergent properties. Here, we exemplify the importance of microbial interaction for ecosystem processes by analysis of a reasonably well-understood microbial guild, namely, aerobic methane-oxidizing bacteria (MOB). We reviewed the literature which provided compelling evidence for the relevance of microbial interaction in modulating methane oxidation. Support for microbial associations within methane-fed communities is sought by a re-analysis of literature data derived from stable isotope probing studies of various complex environmental settings. Putative positive interactions between active MOB and other microbes were assessed by a correlation network-based analysis with datasets covering diverse environments where closely interacting members of a consortium can potentially alter the methane oxidation activity. Although, methanotrophy is used as a model system, the fundamentals of our postulations may be applicable to other microbial guilds mediating other biogeochemical processes.

Multi-omic data integration and analysis using systems genomics approaches: methods and applications in animal production, health and welfare

In the past years, there has been a remarkable development of high-throughput omics (HTO) technologies such as genomics, epigenomics, transcriptomics, proteomics and metabolomics across all facets of biology. This has spearheaded the progress of the systems biology era, including applications on animal production and health traits. However, notwithstanding these new HTO technologies, there remains an emerging challenge in data analysis. On the one hand, different HTO technologies judged on their own merit are appropriate for the identification of disease-causing genes, biomarkers for prevention and drug targets for the treatment of diseases and for individualized genomic predictions of performance or disease risks. On the other hand, integration of multi-omic data and joint modelling and analyses are very powerful and accurate to understand the systems biology of healthy and sustainable production of animals. We present an overview of current and emerging HTO technologies each with a focus on their applications in animal and veterinary sciences before introducing an integrative systems genomics framework for analysing and integrating multi-omic data towards improved animal production, health and welfare. We conclude that there are big challenges in multi-omic data integration, modelling and systems-level analyses, particularly with the fast emerging HTO technologies. We highlight existing and emerging systems genomics approaches and discuss how they contribute to our understanding of the biology of complex traits or diseases and holistic improvement of production performance, disease resistance and welfare.

Time-series metagenomic analysis reveals robustness of soil microbiome against chemical disturbance

Soil microbial communities have great potential for bioremediation of recalcitrant aromatic compounds. However, it is unclear which taxa and genes in the communities, and how they contribute to the bioremediation in the polluted soils. To get clues about this fundamental question here, time-course (up to 24 weeks) metagenomic analysis of microbial community in a closed soil microcosm artificially polluted with four aromatic compounds, including phenanthrene, was conducted to investigate the changes in the community structures and gene pools. The pollution led to drastic changes in the community structures and the gene sets for pollutant degradation. Complete degradation of phenanthrene was strongly suggested to occur by the syntrophic metabolism by Mycobacterium and the most proliferating genus, Burkholderia. The community structure at Week 24 (∼12 weeks after disappearance of the pollutants) returned to the structure similar to that before pollution. Our time-course metagenomic analysis of phage genes strongly suggested the involvement of the ‘kill-the-winner’ phenomenon (i.e. phage predation of Burkholderia cells) for the returning of the microbial community structure. The pollution resulted in a decrease in taxonomic diversity and a drastic increase in diversity of gene pools in the communities, showing the functional redundancy and robustness of the communities against chemical disturbance.