Public good exploitation in natural bacterioplankton communities

A framework for understanding collective microbiome metabolism

Microbiome metabolism underlies numerous vital ecosystem functions. Individual microbiome members often perform partial catabolism of substrates or do not express all of the metabolic functions required for growth. Microbiome members can complement each other by exchanging metabolic intermediates and cellular building blocks to achieve a collective metabolism. We currently lack a mechanistic framework to explain why microbiome members adopt partial metabolism and how metabolic functions are distributed among them. Here we argue that natural selection for proteome efficiency-that is, performing essential metabolic fluxes at a minimal protein investment-explains partial metabolism of microbiome members, which underpins the collective metabolism of microbiomes. Using the carbon cycle as an example, we discuss motifs of collective metabolism, the conditions under which these motifs increase the proteome efficiency of individuals and the metabolic interactions they result in. In summary, we propose a mechanistic framework for how collective metabolic functions emerge from selection on individuals.

The predicted secreted proteome of activated sludge microorganisms indicates distinct nutrient niches

In wastewater treatment plants (WWTPs), complex microbial communities process diverse chemical compounds from sewage. Secreted proteins are critical because many are the first to interact with or degrade external (macro)molecules. To better understand microbial functions in WWTPs, we predicted secreted proteomes of WWTP microbiota from more than 1,000 high-quality metagenome-assembled genomes (MAGs) from 23 Danish WWTPs with biological nutrient removal. Focus was placed on examining secreted catabolic exoenzymes that target major classes of macromolecules. We demonstrate that Bacteroidota has a high potential to digest complex polysaccharides, but also proteins and nucleic acids. Poorly understood activated sludge members of Acidobacteriota and Gemmatimonadota also have high capacities for extracellular polysaccharide digestion. Secreted nucleases are encoded by 61% of MAGs indicating an importance for extracellular DNA and/or RNA digestion in WWTPs. Secreted lipases were the least common macromolecule-targeting enzymes predicted, encoded mainly by Gammaproteobacteria and Myxococcota. In contrast, diverse taxa encode extracellular peptidases, indicating that proteins are widely used nutrients. Diverse secreted multi-heme cytochromes suggest capabilities for extracellular electron transfer by various taxa, including some Bacteroidota that encode undescribed cytochromes with >100 heme-binding motifs. Myxococcota have exceptionally large secreted protein complements, probably related to predatory lifestyles and/or complex cell cycles. Many Gammaproteobacteria MAGs (mostly former Betaproteobacteria) encode few or no secreted hydrolases, but many periplasmic substrate-binding proteins and ABC- and TRAP-transporters, suggesting they are mostly sustained by small molecules. Together, this study provides a comprehensive overview of how WWTPs microorganisms interact with the environment, providing new insights into their functioning and niche partitioning.IMPORTANCEWastewater treatment plants (WWTPs) are critical biotechnological systems that clean wastewater, allowing the water to reenter the environment and limit eutrophication and pollution. They are also increasingly important for the recovery of resources. They function primarily by the activity of microorganisms, which act as a "living sponge," taking up and transforming nutrients, organic material, and pollutants. Despite much research, many microorganisms in WWTPs are uncultivated and poorly characterized, limiting our understanding of their functioning. Here, we analyzed a large collection of high-quality metagenome-assembled genomes from WWTPs for encoded secreted enzymes and proteins, with special emphasis on those used to degrade organic material. This analysis showed highly distinct secreted proteome profiles among different major phylogenetic groups of microorganisms, thereby providing new insights into how different groups function and co-exist in activated sludge. This knowledge will contribute to a better understanding of how to efficiently manage and exploit WWTP microbiomes.

Prevotella are major contributors of sialidases in the human vaginal microbiome

Elevated bacterial sialidase activity in the female genital tract is strongly associated with poor health outcomes including preterm birth and bacterial vaginosis (BV). These negative effects may arise from sialidase-mediated degradation of the protective mucus layer in the cervicovaginal environment. Prior biochemical studies of vaginal bacterial sialidases have focused solely on the BV-associated organism Gardnerella vaginalis. Despite their implications for sexual and reproductive health, sialidases from other vaginal bacteria have not been characterized. Here, we show that vaginal Prevotella species produce sialidases that possess variable activity toward mucin substrates. The sequences of sialidase genes and their presence are largely conserved across clades of Prevotella from different geographies, hinting at their importance globally. Finally, we find that Prevotella sialidase genes and transcripts, including those encoding mucin-degrading sialidases from Prevotella timonensis, are highly prevalent and abundant in human vaginal genomes and transcriptomes. Together, our results identify Prevotella as a critical source of sialidases in the vaginal microbiome, improving our understanding of this detrimental bacterial activity.

Parallel ecological and evolutionary responses to selection in a natural bacterial community

Evolution can occur over ecological timescales, suggesting a potentially important role for rapid evolution in shaping community trait distributions. However, evidence of concordant eco-evolutionary dynamics often comes from in vitro studies of highly simplified communities, and measures of ecological and evolutionary dynamics are rarely directly comparable. Here, we quantified how ecological species sorting and rapid evolution simultaneously shape community trait distributions by tracking within- and between-species changes in a key trait in a complex bacterial community. We focused on the production of siderophores; bacteria use these costly secreted metabolites to scavenge poorly soluble iron and to detoxify environments polluted with toxic nonferrous metals. We found that responses to copper-imposed selection within and between species were ultimately the same-intermediate siderophore levels were favored-and occurred over similar timescales. Despite being a social trait, this level of siderophore production was selected regardless of whether species evolved in isolation or in a community context. Our study suggests that evolutionary selection can play a pivotal role in shaping community trait distributions within natural, highly complex, bacterial communities. Furthermore, trait evolution may not always be qualitatively affected by interactions with other community members.

Bacteria face trade-offs in the decomposition of complex biopolymers

Although depolymerization of complex carbohydrates is a growth-limiting bottleneck for microbial decomposers, we still lack understanding about how the production of different types of extracellular enzymes affect individual microbes and in turn the performance of whole decomposer communities. In this work we use a theoretical model to evaluate the potential trade-offs faced by microorganisms in biopolymer decomposition which arise due to the varied biochemistry of different depolymerizing enzyme classes. We specifically consider two broad classes of depolymerizing extracellular enzymes, which are widespread across microbial taxa: exo-enzymes that cleave small units from the ends of polymer chains and endo-enzymes that act at random positions generating degradation products of varied sizes. Our results demonstrate a fundamental trade-off in the production of these enzymes, which is independent of system's complexity and which appears solely from the intrinsically different temporal depolymerization dynamics. As a consequence, specialists that produce either exo- or only endo-enzymes limit their growth to high or low substrate conditions, respectively. Conversely, generalists that produce both enzymes in an optimal ratio expand their niche and benefit from the synergy between the two enzymes. Finally, our results show that, in spatially-explicit environments, consortia composed of endo- and exo-specialists can only exist under oligotrophic conditions. In summary, our analysis demonstrates that the (evolutionary or ecological) selection of a depolymerization pathway will affect microbial fitness under low or high substrate conditions, with impacts on the ecological dynamics of microbial communities. It provides a possible explanation why many polysaccharide degraders in nature show the genetic potential to produce both of these enzyme classes.

Simple Genomic Traits Predict Rates of Polysaccharide Biodegradation

Natural and chemically modified polysaccharides are extensively employed across a wide array of industries, leading to their prevalence in the waste streams of industrialized societies. With projected increasing demand, a pressing challenge is to swiftly assess and predict their biodegradability to inform the development of new sustainable materials. In this study, we developed a scalable method to evaluate polysaccharide breakdown by measuring microbial growth and analyzing microbial genomes. Our approach, applied to polysaccharides with various structures, correlates strongly with well-established regulatory methods based on oxygen demand. We show that modifications to the polysaccharide structure decreased degradability and favored the growth of microbes adapted to break down chemically modified sugars. More broadly, we discovered two main types of microbial communities associated with different polysaccharide structures─one dominated by fast-growing microbes and another by specialized degraders. Surprisingly, we were able to predict biodegradation rates based only on two genomic features that define these communities: the abundance of genes related to rRNA (indicating fast growth) and the abundance of glycoside hydrolases (enzymes that break down polysaccharides), which together predict nearly 70% of the variation in polysaccharide breakdown. This suggests a trade-off, whereby microbes are either adapted for fast growth or for degrading complex polysaccharide chains, but not both. Finally, we observe that viral elements (prophages) encoded in the genomes of degrading microbes are induced in easily degradable polysaccharides, leading to complex dynamics in biomass accumulation during degradation. In summary, our work provides a practical approach for efficiently assessing polymer degradability and offers genomic insights into how microbes break down polysaccharides.

Transcriptome analysis: a powerful tool to understand individual microbial behaviors and interactions in ecosystems

Transcriptome analysis is a powerful tool for studying microbial ecology, especially individual microbial functions in an ecosystem and their interactions. With the development of high-throughput sequencing technology, great progress has been made in analytical methods for microbial communities in natural environments. 16S rRNA gene amplicon sequencing (ie microbial community structure analysis) and shotgun metagenome analysis have been widely used to determine the composition and potential metabolic capability of microorganisms in target environments without requiring culture. However, even if the types of microorganisms present and their genes are known, it is difficult to determine what they are doing in an ecosystem. Gene expression analysis (transcriptome analysis; RNA-seq) is a powerful tool to address these issues. The history and basic information of gene expression analysis, as well as examples of studies using this method to analyze microbial ecosystems, are presented.

Searching for Principles of Microbial Ecology Across Levels of Biological Organization

Microbial communities play pivotal roles in ecosystems across different scales, from global elemental cycles to household food fermentations. These complex assemblies comprise hundreds or thousands of microbial species whose abundances vary over time and space. Unraveling the principles that guide their dynamics at different levels of biological organization, from individual species, their interactions, to complex microbial communities, is a major challenge. To what extent are these different levels of organization governed by separate principles, and how can we connect these levels to develop predictive models for the dynamics and function of microbial communities? Here, we will discuss recent advances that point towards principles of microbial communities, rooted in various disciplines from physics, biochemistry, and dynamical systems. By considering the marine carbon cycle as a concrete example, we demonstrate how the integration of levels of biological organization can offer deeper insights into the impact of increasing temperatures, such as those associated with climate change, on ecosystem-scale processes. We argue that by focusing on principles that transcend specific microbiomes, we can pave the way for a comprehensive understanding of microbial community dynamics and the development of predictive models for diverse ecosystems.

Ecological function and interaction of different bacterial groups during alginate processing in coastal seawater community

The degradation of high molecular weight organic matter (HMWOM) is a core process of oceanic carbon cycle, which is determined by the activity of microbial communities harboring hundreds of different species. Illustrating the active microbes and their interactions during HMWOM processing can provide key information for revealing the relationship between community composition and its ecological functions. In this study, the genomic and transcriptional responses of microbial communities to the availability of alginate, an abundant HMWOM in coastal ecosystem, were elucidated. The main degraders transcribing alginate lyase (Aly) genes came from genera Alteromonas, Psychrosphaera and Colwellia. Meanwhile, some strains, mainly from the Rhodobacteraceae family, did not transcribe Aly gene but could utilize monosaccharides to grow. The co-culture experiment showed that the activity of Aly-producing strain could promote the growth of Aly-non-producing strain when alginate was the sole carbon source. Interestingly, this interaction did not reduce the alginate degradation rate, possibly due to the easily degradable nature of alginate. This study can improve our understanding of the relationship between microbial community activity and alginate metabolism function as well as further manipulation of microbial community structure for alginate processing.

Plastics select for distinct early colonizing microbial populations with reproducible traits across environmental gradients

Little is known about early plastic biofilm assemblage dynamics and successional changes over time. By incubating virgin microplastics along oceanic transects and comparing adhered microbial communities with those of naturally occurring plastic litter at the same locations, we constructed gene catalogues to contrast the metabolic differences between early and mature biofilm communities. Early colonization incubations were reproducibly dominated by Alteromonadaceae and harboured significantly higher proportions of genes associated with adhesion, biofilm formation, chemotaxis, hydrocarbon degradation and motility. Comparative genomic analyses among the Alteromonadaceae metagenome assembled genomes (MAGs) highlighted the importance of the mannose-sensitive hemagglutinin (MSHA) operon, recognized as a key factor for intestinal colonization, for early colonization of hydrophobic plastic surfaces. Synteny alignments of MSHA also demonstrated positive selection for mshA alleles across all MAGs, suggesting that mshA provides a competitive advantage for surface colonization and nutrient acquisition. Large-scale genomic characteristics of early colonizers varied little, despite environmental variability. Mature plastic biofilms were composed of predominantly Rhodobacteraceae and displayed significantly higher proportions of carbohydrate hydrolysis enzymes and genes for photosynthesis and secondary metabolism. Our metagenomic analyses provide insight into early biofilm formation on plastics in the ocean and how early colonizers self-assemble, compared to mature, phylogenetically and metabolically diverse biofilms.

Genome content predicts the carbon catabolic preferences of heterotrophic bacteria

Heterotrophic bacteria-bacteria that utilize organic carbon sources-are taxonomically and functionally diverse across environments. It is challenging to map metabolic interactions and niches within microbial communities due to the large number of metabolites that could serve as potential carbon and energy sources for heterotrophs. Whether their metabolic niches can be understood using general principles, such as a small number of simplified metabolic categories, is unclear. Here we perform high-throughput metabolic profiling of 186 marine heterotrophic bacterial strains cultured in media containing one of 135 carbon substrates to determine growth rates, lag times and yields. We show that, despite high variability at all levels of taxonomy, the catabolic niches of heterotrophic bacteria can be understood in terms of their preference for either glycolytic (sugars) or gluconeogenic (amino and organic acids) carbon sources. This preference is encoded by the total number of genes found in pathways that feed into the two modes of carbon utilization and can be predicted using a simple linear model based on gene counts. This allows for coarse-grained descriptions of microbial communities in terms of prevalent modes of carbon catabolism. The sugar-acid preference is also associated with genomic GC content and thus with the carbon-nitrogen requirements of their encoded proteome. Our work reveals how the evolution of bacterial genomes is structured by fundamental constraints rooted in metabolism.

Changes in interactions over ecological time scales influence single-cell growth dynamics in a metabolically coupled marine microbial community

Microbial communities thrive in almost all habitats on earth. Within these communities, cells interact through the release and uptake of metabolites. These interactions can have synergistic or antagonistic effects on individual community members. The collective metabolic activity of microbial communities leads to changes in their local environment. As the environment changes over time, the nature of the interactions between cells can change. We currently lack understanding of how such dynamic feedbacks affect the growth dynamics of individual microbes and of the community as a whole. Here we study how interactions mediated by the exchange of metabolites through the environment change over time within a simple marine microbial community. We used a microfluidic-based approach that allows us to disentangle the effect cells have on their environment from how they respond to their environment. We found that the interactions between two species-a degrader of chitin and a cross-feeder that consumes metabolic by-products-changes dynamically over time as cells modify their environment. Cells initially interact positively and then start to compete at later stages of growth. Our results demonstrate that interactions between microorganisms are not static and depend on the state of the environment, emphasizing the importance of disentangling how modifications of the environment affects species interactions. This experimental approach can shed new light on how interspecies interactions scale up to community level processes in natural environments.

Carbohydrate complexity limits microbial growth and reduces the sensitivity of human gut communities to perturbations

Dietary fibre impacts the growth dynamics of human gut microbiota, yet we lack a detailed and quantitative understanding of how these nutrients shape microbial interaction networks and responses to perturbations. By building human gut communities coupled with computational modelling, we dissect the effects of fibres that vary in chemical complexity and each of their constituent sugars on community assembly and response to perturbations. We demonstrate that the degree of chemical complexity across different fibres limits microbial growth and the number of species that can utilize these nutrients. The prevalence of negative interspecies interactions is reduced in the presence of fibres compared with their constituent sugars. Carbohydrate chemical complexity enhances the reproducibility of community assembly and resistance of the community to invasion. We demonstrate that maximizing or minimizing carbohydrate competition between resident and invader species enhances resistance to invasion. In sum, the quantitative effects of carbohydrate chemical complexity on microbial interaction networks could be exploited to inform dietary and bacterial interventions to modulate community resistance to perturbations.

Core fungal species strengthen microbial cooperation in a food-waste composting process

In ecosystem engineering research, the contribution of microbial cooperation to ecosystem function has been emphasized. Fungi are one of the predominant decomposers in composting, but thus far, less attention has been given to fungal than to bacterial cooperation. Therefore, network and cohesion analyses were combined to reveal the correlation between fungal cooperation and organic matter (OM) degradation in ten composting piles. Positive cohesion, reflecting the cooperation degree, was positively linked to the degradation rate of OM. From the community perspective, core species (i.e., Candida tropicalis, Issatchenkia orientails, Kazachstania exigua, and Dipodascus australiensis) with high occurrence frequency and abundance were the key in regulating positive cohesion. These species were highly relevant to functional genera associated with OM degradation in both fungal and bacterial domains. Therefore, focusing on these core fungal species might be an appropriate strategy for targeted regulation of functional microbes and promotion of degradation rates.

Genome-Resolved Metaproteomics Decodes the Microbial and Viral Contributions to Coupled Carbon and Nitrogen Cycling in River Sediments

Rivers have a significant role in global carbon and nitrogen cycles, serving as a nexus for nutrient transport between terrestrial and marine ecosystems. Although rivers have a small global surface area, they contribute substantially to worldwide greenhouse gas emissions through microbially mediated processes within the river hyporheic zone. Despite this importance, research linking microbial and viral communities to specific biogeochemical reactions is still nascent in these sediment environments. To survey the metabolic potential and gene expression underpinning carbon and nitrogen biogeochemical cycling in river sediments, we collected an integrated data set of 33 metagenomes, metaproteomes, and paired metabolomes. We reconstructed over 500 microbial metagenome-assembled genomes (MAGs), which we dereplicated into 55 unique, nearly complete medium- and high-quality MAGs spanning 12 bacterial and archaeal phyla. We also reconstructed 2,482 viral genomic contigs, which were dereplicated into 111 viral MAGs (vMAGs) of >10 kb in size. As a result of integrating gene expression data with geochemical and metabolite data, we created a conceptual model that uncovered new roles for microorganisms in organic matter decomposition, carbon sequestration, nitrogen mineralization, nitrification, and denitrification. We show how these metabolic pathways, integrated through shared resource pools of ammonium, carbon dioxide, and inorganic nitrogen, could ultimately contribute to carbon dioxide and nitrous oxide fluxes from hyporheic sediments. Further, by linking viral MAGs to these active microbial hosts, we provide some of the first insights into viral modulation of river sediment carbon and nitrogen cycling. IMPORTANCE Here we created HUM-V (hyporheic uncultured microbial and viral), an annotated microbial and viral MAG catalog that captures strain and functional diversity encoded in these Columbia River sediment samples. Demonstrating its utility, this genomic inventory encompasses multiple representatives of dominant microbial and archaeal phyla reported in other river sediments and provides novel viral MAGs that can putatively infect these. Furthermore, we used HUM-V to recruit gene expression data to decipher the functional activities of these MAGs and reconstruct their active roles in Columbia River sediment biogeochemical cycling. Ultimately, we show the power of MAG-resolved multi-omics to uncover interactions and chemical handoffs in river sediments that shape an intertwined carbon and nitrogen metabolic network. The accessible microbial and viral MAGs in HUM-V will serve as a community resource to further advance more untargeted, activity-based measurements in these, and related, freshwater terrestrial-aquatic ecosystems.

Consuming fresh macroalgae induces specific catabolic pathways, stress reactions and Type IX secretion in marine flavobacterial pioneer degraders

Macroalgae represent huge amounts of biomass worldwide, largely recycled by marine heterotrophic bacteria. We investigated the strategies of bacteria within the flavobacterial genus Zobellia to initiate the degradation of whole algal tissues, which has received little attention compared to the degradation of isolated polysaccharides. Zobellia galactanivorans Dsij^T has the capacity to use fresh brown macroalgae as a sole carbon source and extensively degrades algal tissues via the secretion of extracellular enzymes, even in the absence of physical contact with the algae. Co-cultures experiments with the non-degrading strain Tenacibaculum aestuarii SMK-4^T showed that Z. galactanivorans can act as a pioneer that initiates algal breakdown and shares public goods with other bacteria. A comparison of eight Zobellia strains, and strong transcriptomic shifts in Z. galactanivorans cells using fresh macroalgae vs. isolated polysaccharides, revealed potential overlooked traits of pioneer bacteria. Besides brown algal polysaccharide degradation, they notably include oxidative stress resistance proteins, type IX secretion system proteins and novel uncharacterized polysaccharide utilization loci. Overall, this work highlights the relevance of studying fresh macroalga degradation to fully understand the metabolic and ecological strategies of pioneer microbial degraders, key players in macroalgal biomass remineralization.

Historical contingencies and phage induction diversify bacterioplankton communities at the microscale

In many natural environments, microorganisms decompose microscale resource patches made of complex organic matter. The growth and collapse of populations on these resource patches unfold within spatial ranges of a few hundred micrometers or less, making such microscale ecosystems hotspots of heterotrophic metabolism. Despite the potential importance of patch-level dynamics for the large-scale functioning of heterotrophic microbial communities, we have not yet been able to delineate the ecological processes that control natural populations at the microscale. Here, we address this challenge by characterizing the natural marine communities that assembled on over 1,000 individual microscale particles of chitin, the most abundant marine polysaccharide. Using low-template shotgun metagenomics and imaging, we find significant variation in microscale community composition despite the similarity in initial species pools across replicates. Chitin-degrading taxa that were rare in seawater established large populations on a subset of particles, resulting in a wide range of predicted chitinolytic abilities and biomass at the level of individual particles. We show, through a mathematical model, that this variability can be attributed to stochastic colonization and historical contingencies affecting the tempo of growth on particles. We find evidence that one biological process leading to such noisy growth across particles is differential predation by temperate bacteriophages of chitin-degrading strains, the keystone members of the community. Thus, initial stochasticity in assembly states on individual particles, amplified through ecological interactions, may have significant consequences for the diversity and functionality of systems of microscale patches.

Micron-scale biogeography reveals conservative intra anammox bacteria spatial co-associations

Micron-scale resolution can help to reliably identify true taxon-taxon interactions in complex microbial communities. Despite widespread recognition of the critical role of metabolic interactions in anaerobic ammonium oxidation (anammox) system performance, no studies have examined microbial interactions at the micron-scale in anammox consortia. To fill this gap, we extensively sampled (totally 242 samples) the consortia of a lab-scale anammox reactor at different length scales, including bulk-scale (∼cm), macro-scale (300-500 µm) and micron-scale (70-100 µm). We firstly observed evident micron-scale heterogeneity in anammox consortia, with the relative abundance of anammox bacteria fluctuated greatly across individual clusters (2.0%-79.3%), indicating that the biotic interactions play a significant role in the assembly of anammox communities under well-controlled and well-mixed condition. Importantly, by mapping the spatial associations in anammox consortia at micron-scale, we demonstrated that the conserved co-associations for anammox bacteria were restricted to three different Brocadia species over time, and their co-associations with heterotrophs were random, implying that there was no statistically significant symbiotic interaction between anammox bacteria and other heterotrophic populations. Further metagenomic binning revealed that the quorum sensing with secondary messenger c-di-GMP potentially holding on the conservative metabolic cooperation among Brocadia species. These results shed new light on the social behavior of the anammox community. Overall, delineating of biological structures at micron-scale opens a new way of monitoring the microbial spatial structure and interactions, paving the way for improved community engineering of biotreatment systems.

Dynamic proteome allocation regulates the profile of interaction of auxotrophic bacterial consortia

Microbial ecosystems are composed of multiple species in constant metabolic exchange. A pervasive interaction in microbial communities is metabolic cross-feeding and occurs when the metabolic burden of producing costly metabolites is distributed between community members, in some cases for the benefit of all interacting partners. In particular, amino acid auxotrophies generate obligate metabolic inter-dependencies in mixed populations and have been shown to produce a dynamic profile of interaction that depends upon nutrient availability. However, identifying the key components that determine the pair-wise interaction profile remains a challenging problem, partly because metabolic exchange has consequences on multiple levels, from allocating proteomic resources at a cellular level to modulating the structure, function and stability of microbial communities. To evaluate how ppGpp-mediated resource allocation drives the population-level profile of interaction, here we postulate a multi-scale mathematical model that incorporates dynamics of proteome partition into a population dynamics model. We compare our computational results with experimental data obtained from co-cultures of auxotrophic Escherichia coli K12 strains under a range of amino acid concentrations and population structures. We conclude by arguing that the stringent response promotes cooperation by inhibiting the growth of fast-growing strains and promoting the synthesis of metabolites essential for other community members.

Competition for fluctuating resources reproduces statistics of species abundance over time across wide-ranging microbiotas

Across diverse microbiotas, species abundances vary in time with distinctive statistical behaviors that appear to generalize across hosts, but the origins and implications of these patterns remain unclear. Here, we show that many of these macroecological patterns can be quantitatively recapitulated by a simple class of consumer-resource models, in which the metabolic capabilities of different species are randomly drawn from a common statistical distribution. Our model parametrizes the consumer-resource properties of a community using only a small number of global parameters, including the total number of resources, typical resource fluctuations over time, and the average overlap in resource-consumption profiles across species. We show that variation in these macroscopic parameters strongly affects the time series statistics generated by the model, and we identify specific sets of global parameters that can recapitulate macroecological patterns across wide-ranging microbiotas, including the human gut, saliva, and vagina, as well as mouse gut and rice, without needing to specify microscopic details of resource consumption. These findings suggest that resource competition may be a dominant driver of community dynamics. Our work unifies numerous time series patterns under a simple model, and provides an accessible framework to infer macroscopic parameters of effective resource competition from longitudinal studies of microbial communities.

Polysaccharide-Bacteria Interactions From the Lens of Evolutionary Ecology

Microbes have the unique ability to break down the complex polysaccharides that make up the bulk of organic matter, initiating a cascade of events that leads to their recycling. Traditionally, the rate of organic matter degradation is perceived to be limited by the chemical and physical structure of polymers. Recent advances in microbial ecology, however, suggest that polysaccharide persistence can result from non-linear growth dynamics created by the coexistence of alternate degradation strategies, metabolic roles as well as by ecological interactions between microbes. This complex "landscape" of degradation strategies and interspecific interactions present in natural microbial communities appears to be far from evolutionarily stable, as frequent gene gain and loss reshape enzymatic repertoires and metabolic roles. In this perspective, we discuss six challenges at the heart of this problem, ranging from the evolution of genetic repertoires, phenotypic heterogeneity in clonal populations, the development of a trait-based ecology, and the impact of metabolic interactions and microbial cooperation on degradation rates. We aim to reframe some of the key questions in the study of polysaccharide-bacteria interactions in the context of eco-evolutionary dynamics, highlighting possible research directions that, if pursued, would advance our understanding of polysaccharide degraders at the interface between biochemistry, ecology and evolution.