Systems biology approaches towards predictive microbial ecology

Ectomycorrhizal fungi alter soil food webs and the functional potential of bacterial communities

Most of Earth's trees rely on critical soil nutrients that ectomycorrhizal fungi (EcMF) liberate and provide, and all of Earth's land plants associate with bacteria that help them survive in nature. Yet, our understanding of how the presence of EcMF modifies soil bacterial communities, soil food webs, and root chemistry requires direct experimental evidence to comprehend the effects that EcMF may generate in the belowground plant microbiome. To this end, we grew Pinus muricata plants in soils that were either inoculated with EcMF and native forest bacterial communities or only native bacterial communities. We then profiled the soil bacterial communities, applied metabolomics and lipidomics, and linked omics data sets to understand how the presence of EcMF modifies belowground biogeochemistry, bacterial community structure, and their functional potential. We found that the presence of EcMF (i) enriches soil bacteria linked to enhanced plant growth in nature, (ii) alters the quantity and composition of lipid and non-lipid soil metabolites, and (iii) modifies plant root chemistry toward pathogen suppression, enzymatic conservation, and reactive oxygen species scavenging. Using this multi-omic approach, we therefore show that this widespread fungal symbiosis may be a common factor for structuring soil food webs.IMPORTANCEUnderstanding how soil microbes interact with one another and their host plant will help us combat the negative effects that climate change has on terrestrial ecosystems. Unfortunately, we lack a clear understanding of how the presence of ectomycorrhizal fungi (EcMF)-one of the most dominant soil microbial groups on Earth-shapes belowground organic resources and the composition of bacterial communities. To address this knowledge gap, we profiled lipid and non-lipid metabolites in soils and plant roots, characterized soil bacterial communities, and compared soils amended either with or without EcMF. Our results show that the presence of EcMF changes soil organic resource availability, impacts the proliferation of different bacterial communities (in terms of both type and potential function), and primes plant root chemistry for pathogen suppression and energy conservation. Our findings therefore provide much-needed insight into how two of the most dominant soil microbial groups interact with one another and with their host plant.

G. de Lomana A, Gomes-Filho JV, Vêncio RZN, Moritz RL, Koide T, Baliga NS. A Genome-Scale Atlas Reveals Complex Interplay of Transcription and Translation in an Archaeon

The scale of post-transcriptional regulation and the implications of its interplay with other forms of regulation in environmental acclimation are underexplored for organisms of the domain Archaea. Here, we have investigated the scale of post-transcriptional regulation in the extremely halophilic archaeon Halobacterium salinarum NRC-1 by integrating the transcriptome-wide locations of transcript processing sites (TPSs) and SmAP1 binding, the genome-wide locations of antisense RNAs (asRNAs), and the consequences of RNase_2099C knockout on the differential expression of all genes. This integrated analysis has discovered that 54% of all protein-coding genes in the genome of this haloarchaeon are likely targeted by multiple mechanisms for putative post-transcriptional processing and regulation, with about 20% of genes likely being regulated by combinatorial schemes involving SmAP1, asRNAs, and RNase_2099C. Comparative analysis of mRNA levels (transcriptome sequencing [RNA-Seq]) and protein levels (sequential window acquisition of all theoretical fragment ion spectra mass spectrometry [SWATH-MS]) for 2,579 genes over four phases of batch culture growth in complex medium generated additional evidence for the conditional post-transcriptional regulation of 7% of all protein-coding genes. We demonstrate that post-transcriptional regulation may act to fine-tune specialized and rapid acclimation to stressful environments, e.g., as a switch to turn on gas vesicle biogenesis to promote vertical relocation under anoxic conditions and modulate the frequency of transposition by insertion sequence (IS) elements of the IS200/IS605, IS4, and ISH3 families. Findings from this study are provided as an atlas in a public Web resource (https://halodata.systemsbiology.net). IMPORTANCE While the transcriptional regulation landscape of archaea has been extensively investigated, we currently have limited knowledge about post-transcriptional regulation and its driving mechanisms in this domain of life. In this study, we collected and integrated omics data from multiple sources and technologies to infer post-transcriptionally regulated genes and the putative mechanisms modulating their expression at the protein level in Halobacterium salinarum NRC-1. The results suggest that post-transcriptional regulation may drive environmental acclimation by regulating hallmark biological processes. To foster discoveries by other research groups interested in the topic, we extended our integrated data to the public in the form of an interactive atlas (https://halodata.systemsbiology.net).

Stable isotope-assisted metabolite profiling reveals new insights into L-tryptophan chemotrophic metabolism of Rubrivivax benzoatilyticus

Anoxygenic photosynthetic bacteria (APB) are metabolically versatile, capable of surviving with an extended range of carbon and nitrogen sources. This group of phototrophic bacteria have remarkable metabolic plasticity in utilizing an array of organic compounds as carbon source/electron donors and nitrogen sources with sophisticated growth modes. Rubrivivax benzoatilyticus JA2 is one such photosynthetic bacterium utilizes L-tryptophan as nitrogen source under phototrophic growth mode and produces an array of indolic compounds of biotechnological significance. However, chemotrophic L-tryptophan metabolism is largely unexplored and studying L-tryptophan metabolism under chemotrophic mode would provide new insights into metabolic potential of strain JA2. In the present study, we employed stable-isotopes assisted metabolite profiling to unravel the L-tryptophan catabolism in Rubrivivax benzoatilyticus strain JA2 under chemotrophic (dark aerobic) conditions. Utilization of L-tryptophan as a nitrogen source for growth and simultaneous production of indole derivatives was observed in strain JA2. Liquid chromatography mass spectrometry (LC-MS) analysis of exo-metabolite profiling of carbon labeled L-tryptophan (¹³C₁₁) fed cultures of strain JA2 revealed at least seventy labeled metabolites. Of these, only fourteen metabolites were confirmed using standards, while sixteen were putative and forty metabolites remained unidentified. L-tryptophan chemotrophic catabolism revealed multiple catabolic pathways and distinct differential catabolism of L-tryptophan under chemotropic state as compared to photo-catabolism of L-tryptophan in strain JA2.

Deciphering Microbial Metal Toxicity Responses via Random Bar Code Transposon Site Sequencing and Activity-Based Metabolomics

To uncover metal toxicity targets and defense mechanisms of the facultative anaerobe Pantoea sp. strain MT58 (MT58), we used a multiomic strategy combining two global techniques, random bar code transposon site sequencing (RB-TnSeq) and activity-based metabolomics. MT58 is a metal-tolerant Oak Ridge Reservation (ORR) environmental isolate that was enriched in the presence of metals at concentrations measured in contaminated groundwater at an ORR nuclear waste site. The effects of three chemically different metals found at elevated concentrations in the ORR contaminated environment were investigated: the cation Al³⁺, the oxyanion CrO₄^2-, and the oxycation UO₂²⁺. Both global techniques were applied using all three metals under both aerobic and anaerobic conditions to elucidate metal interactions mediated through the activity of metabolites and key genes/proteins. These revealed that Al³⁺ binds intracellular arginine, CrO₄^2- enters the cell through sulfate transporters and oxidizes intracellular reduced thiols, and membrane-bound lipopolysaccharides protect the cell from UO₂²⁺ toxicity. In addition, the Tol outer membrane system contributed to the protection of cellular integrity from the toxic effects of all three metals. Likewise, we found evidence of regulation of lipid content in membranes under metal stress. Individually, RB-TnSeq and metabolomics are powerful tools to explore the impact various stresses have on biological systems. Here, we show that together they can be used synergistically to identify the molecular actors and mechanisms of these pertubations to an organism, furthering our understanding of how living systems interact with their environment. IMPORTANCE Studying microbial interactions with their environment can lead to a deeper understanding of biological molecular mechanisms. In this study, two global techniques, RB-TnSeq and activity metabolomics, were successfully used to probe the interactions between a metal-resistant microorganism, Pantoea sp. strain MT58, and metals contaminating a site where the organism can be located. A number of novel metal-microbe interactions were uncovered, including Al³⁺ toxicity targeting arginine synthesis, which could lead to a deeper understanding of the impact Al³⁺ contamination has on microbial communities as well as its impact on higher-level organisms, including plants for whom Al³⁺ contamination is an issue. Using multiomic approaches like the one described here is a way to further our understanding of microbial interactions and their impacts on the environment overall.

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.

Quantification of the covariation of lake microbiomes and environmental variables using a machine learning-based framework

It is known that microorganisms are essential for the functioning of ecosystems, but the extent to which microorganisms respond to different environmental variables in their natural habitats is not clear. In the current study, we present a methodological framework to quantify the covariation of the microbial community of a habitat and environmental variables of this habitat. It is built on theoretical considerations of systems ecology, makes use of state-of-the-art machine learning techniques and can be used to identify bioindicators. We apply the framework to a data set containing operational taxonomic units (OTUs) as well as more than twenty physicochemical and geographic variables measured in a large-scale survey of European lakes. While a large part of variation (up to 61%) in many environmental variables can be explained by microbial community composition, some variables do not show significant covariation with the microbial lake community. Moreover, we have identified OTUs that act as "multitask" bioindicators, i.e., that are indicative for multiple environmental variables, and thus could be candidates for lake water monitoring schemes. Our results represent, for the first time, a quantification of the covariation of the lake microbiome and a wide array of environmental variables for lake ecosystems. Building on the results and methodology presented here, it will be possible to identify microbial taxa and processes that are essential for functioning and stability of lake ecosystems.

Mechanism Across Scales: A Holistic Modeling Framework Integrating Laboratory and Field Studies for Microbial Ecology

Over the last century, leaps in technology for imaging, sampling, detection, high-throughput sequencing, and -omics analyses have revolutionized microbial ecology to enable rapid acquisition of extensive datasets for microbial communities across the ever-increasing temporal and spatial scales. The present challenge is capitalizing on our enhanced abilities of observation and integrating diverse data types from different scales, resolutions, and disciplines to reach a causal and mechanistic understanding of how microbial communities transform and respond to perturbations in the environment. This type of causal and mechanistic understanding will make predictions of microbial community behavior more robust and actionable in addressing microbially mediated global problems. To discern drivers of microbial community assembly and function, we recognize the need for a conceptual, quantitative framework that connects measurements of genomic potential, the environment, and ecological and physical forces to rates of microbial growth at specific locations. We describe the Framework for Integrated, Conceptual, and Systematic Microbial Ecology (FICSME), an experimental design framework for conducting process-focused microbial ecology studies that incorporates biological, chemical, and physical drivers of a microbial system into a conceptual model. Through iterative cycles that advance our understanding of the coupling across scales and processes, we can reliably predict how perturbations to microbial systems impact ecosystem-scale processes or vice versa. We describe an approach and potential applications for using the FICSME to elucidate the mechanisms of globally important ecological and physical processes, toward attaining the goal of predicting the structure and function of microbial communities in chemically complex natural environments.

Biotechnological basis of microbial consortia for the removal of pesticides from the environment

The application of microbial strains as axenic cultures has frequently been employed in a diverse range of sectors. In the natural environment, microbes exist as multispecies and perform better than monocultures. Cell signaling and communication pathways play a key role in engineering microbial consortia, because in a consortium, the microorganisms communicate via diffusible signal molecules. Mixed microbial cultures have gained little attention due to the lack of proper knowledge about their interactions with each other. Some ideas have been proposed to deal with and study various microbes when they live together as a community, for biotechnological application purposes. In natural environments, microbes can possess unique metabolic features. Therefore, microbial consortia divide the metabolic burden among strains in the group and robustly perform pesticide degradation. Synthetic microbial consortia can perform the desired functions at naturally contaminated sites. Therefore, in this article, special attention is paid to the microbial consortia and their function in the natural environment. This review comprehensively discusses the recent applications of microbial consortia in pesticide degradation and environmental bioremediation. Moreover, the future directions of synthetic consortia have been explored. The review also explores the future perspectives and new platforms for these approaches, besides highlighting the practical understanding of the scientific information behind consortia.

Temperature Stress Induces Shift From Co-Existence to Competition for Organic Carbon in Microalgae-Bacterial Photobioreactor Community - Enabling Continuous Production of Microalgal Biomass

To better predict the consequences of environmental change on aquatic microbial ecosystems it is important to understand what enables community resilience. The mechanisms by which a microbial community maintain its overall function, for example, the cycling of carbon, when exposed to a stressor, can be explored by considering three concepts: biotic interactions, functional adaptations, and community structure. Interactions between species are traditionally considered as, e.g., mutualistic, parasitic, or neutral but are here broadly defined as either coexistence or competition, while functions relate to their metabolism (e.g., autotrophy or heterotrophy) and roles in ecosystem functioning (e.g., oxygen production, organic matter degradation). The term structure here align with species richness and diversity, where a more diverse community is though to exhibit a broader functional capacity than a less diverse community. These concepts have here been combined with ecological theories commonly used in resilience studies, i.e., adaptive cycles, panarchy, and cross-scale resilience, that describe how the status and behavior at one trophic level impact that of surrounding levels. This allows us to explore the resilience of a marine microbial community, cultivated in an outdoor photobioreactor, when exposed to a naturally occurring seasonal stress. The culture was monitored for 6weeks during which it was exposed to two different temperature regimes (21 ± 2 and 11 ± 1°C). Samples were taken for metatranscriptomic analysis, in order to assess the regulation of carbon uptake and utilization, and for amplicon (18S and 16S rRNA gene) sequencing, to characterize the community structure of both autotrophs (dominated by the green microalgae Mychonastes) and heterotrophs (associated bacterioplankton). Differential gene expression analyses suggested that community function at warm temperatures was based on concomitant utilization of inorganic and organic carbon assigned to autotrophs and heterotrophs, while at colder temperatures, the uptake of organic carbon was performed primarily by autotrophs. Upon the shift from high to low temperature, community interactions shifted from coexistence to competition for organic carbon. Network analysis indicated that the community structure showed opposite trends for autotrophs and heterotrophs in having either high or low diversity. Despite an abrupt change of temperature, the microbial community as a whole responded in a way that maintained the overall level of diversity and function within and across autotrophic and heterotrophic levels. This is in line with cross-scale resilience theory describing how ecosystems may balance functional overlaps within and functional redundancy between levels in order to be resilient to environmental change (such as temperature).

A continuously changing selective context on microbial communities associated with fish, from egg to fork

Fast increase of fish aquaculture production to meet consumer demands is accompanied by important ecological concerns such as disease outbreaks. Meanwhile, food waste is an important concern with fish products since they are highly perishable. Recent aquaculture and fish product microbiology, and more recently, microbiota research, paved the way to a highly integrated approach to understand complex relationships between host fish, product and their associated microbial communities at health/disease and preservation/spoilage frontiers. Microbial manipulation strategies are increasingly validated as promising tools either to replace or to complement traditional veterinary and preservation methods. In this review, we consider evolutionary forces driving fish microbiota assembly, in particular the changes in the selective context along the production chain. We summarize the current knowledge concerning factors governing assembly and dynamics of fish hosts and food microbial communities. Then, we discuss the current microbial community manipulation strategies from an evolutionary standpoint to provide a perspective on the potential for risks, conflict and opportunities. Finally, we conclude that to harness evolutionary forces in the development of sustainable microbiota manipulation applications in the fish industry, an integrated knowledge of the controlling abiotic and especially biotic factors is required.

Combining Molecular Observations and Microbial Ecosystem Modeling: A Practical Guide

Advances in technologies for molecular observation are leading to novel types of data, including gene, transcript, protein, and metabolite levels, which are fundamentally different from the types traditionally compared with microbial ecosystem models, such as biomass (e.g., chlorophyll a) and nutrient concentrations. A grand challenge is to use these data to improve predictive models and use models to explain observed patterns. This article presents a framework that aligns observations and models along the dimension of abstraction or biological organization-from raw sequences to ecosystem patterns for observations, and from sequence simulators to ecological theory for models. It then reviews 16 studies that compared model results with molecular observations. Molecular data can and are being combined with microbial ecosystem models, but to keep up with and take advantage of the full scope of observations, models need to become more mechanistically detailed and complex, which is a technical and cultural challenge for the ecological modeling community.