Challenge In Microbial Ecology Research Articles

Relating ecological diversity to genetic discontinuity across bacterial species

BackgroundGenetic discontinuity represents abrupt breaks in genomic identity among species. Advances in genome sequencing have enhanced our ability to track and characterize genetic discontinuity in bacterial populations. However, exploring the degree to which bacterial diversity exists as a continuum or sorted into discrete and readily defined species remains a challenge in microbial ecology. Here, we aim to quantify the genetic discontinuity (δ) and investigate how this metric is related to ecology.ResultsWe harness a dataset comprising 210,129 genomes to systematically explore genetic discontinuity patterns across several distantly related species, finding clear breakpoints which vary depending on the taxa in question. By delving into pangenome characteristics, we uncover a significant association between pangenome saturation and genetic discontinuity. Closed pangenomes are associated with more pronounced breaks, exemplified by Mycobacterium tuberculosis. Additionally, through a machine learning approach, we detect key features such as gene conservation patterns and functional annotations that significantly impact genetic discontinuity prediction.ConclusionsOur study clarifies bacterial genetic patterns and their ecological impacts, enhancing the delineation of species boundaries and deepening our understanding of microbial diversity.

OneNet-One network to rule them all: Consensus network inference from microbiome data.

Modeling microbial interactions as sparse and reproducible networks is a major challenge in microbial ecology. Direct interactions between the microbial species of a biome can help to understand the mechanisms through which microbial communities influence the system. Most state-of-the art methods reconstruct networks from abundance data using Gaussian Graphical Models, for which several statistically grounded and computationnally efficient inference approaches are available. However, the multiplicity of existing methods, when applied to the same dataset, generates very different networks. In this article, we present OneNet, a consensus network inference method that combines seven methods based on stability selection. This resampling procedure is used to tune a regularization parameter by computing how often edges are selected in the networks. We modified the stability selection framework to use edge selection frequencies directly and combine them in the inferred network to ensure that only reproducible edges are included in the consensus. We demonstrated on synthetic data that our method generally led to slightly sparser networks while achieving much higher precision than any single method. We further applied the method to gut microbiome data from liver-cirrothic patients and demonstrated that the resulting network exhibited a microbial guild that was meaningful in terms of human health.

Soils of two Antarctic Dry Valleys exhibit unique microbial community structures in response to similar environmental disturbances

BackgroundIsolating the effects of deterministic variables (e.g., physicochemical conditions) on soil microbial communities from those of neutral processes (e.g., dispersal) remains a major challenge in microbial ecology. In this study, we disturbed soil microbial communities of two McMurdo Dry Valleys of Antarctica exhibiting distinct microbial biogeographic patterns, both devoid of aboveground biota and different in macro- and micro-physicochemical conditions. We modified the availability of water, nitrogen, carbon, copper ions, and sodium chloride salts in a laboratory-based experiment and monitored the microbial communities for up to two months. Our aim was to mimic a likely scenario in the near future, in which similar selective pressures will be applied to both valleys. We hypothesized that, given their unique microbial communities, the two valleys would select for different microbial populations when subjected to the same disturbances.ResultsThe two soil microbial communities, subjected to the same disturbances, did not respond similarly as reflected in both 16S rRNA genes and transcripts. Turnover of the two microbial communities showed a contrasting response to the same environmental disturbances and revealed different potentials for adaptation to change. These results suggest that the heterogeneity between these microbial communities, reflected in their strong biogeographic patterns, was maintained even when subjected to the same selective pressure and that the ‘rare biosphere’, at least in these samples, were deeply divergent and did not act as a reservoir for microbiota that enabled convergent responses to change in environmental conditions.ConclusionsOur findings strongly support the occurrence of endemic microbial communities that show a structural resilience to environmental disturbances, spanning a wide range of physicochemical conditions. In the highly arid and nutrient-limited environment of the Dry Valleys, these results provide direct evidence of microbial biogeographic patterns that can shape the communities’ response in the face of future environmental changes.

Genome-scale community modelling reveals conserved metabolic cross-feedings in epipelagic bacterioplankton communities

Marine microorganisms form complex communities of interacting organisms that influence central ecosystem functions in the ocean such as primary production and nutrient cycling. Identifying the mechanisms controlling their assembly and activities is a major challenge in microbial ecology. Here, we integrated Tara Oceans meta-omics data to predict genome-scale community interactions within prokaryotic assemblages in the euphotic ocean. A global genome-resolved co-activity network revealed a significant number of inter-lineage associations across diverse phylogenetic distances. Identified co-active communities include species displaying smaller genomes but encoding a higher potential for quorum sensing, biofilm formation, and secondary metabolism. Community metabolic modelling reveals a higher potential for interaction within co-active communities and points towards conserved metabolic cross-feedings, in particular of specific amino acids and group B vitamins. Our integrated ecological and metabolic modelling approach suggests that genome streamlining and metabolic auxotrophies may act as joint mechanisms shaping bacterioplankton community assembly in the global ocean surface.

Data-driven prediction of colonization outcomes for complex microbial communities

Microbial interactions can lead to different colonization outcomes of exogenous species, be they pathogenic or beneficial in nature. Predicting the colonization of exogenous species in complex communities remains a fundamental challenge in microbial ecology, mainly due to our limited knowledge of the diverse mechanisms governing microbial dynamics. Here, we propose a data-driven approach independent of any dynamics model to predict colonization outcomes of exogenous species from the baseline compositions of microbial communities. We systematically validate this approach using synthetic data, finding that machine learning models can predict not only the binary colonization outcome but also the post-invasion steady-state abundance of the invading species. Then we conduct colonization experiments for commensal gut bacteria species Enterococcus faecium and Akkermansia muciniphila in hundreds of human stool-derived in vitro microbial communities, confirming that the data-driven approaches can predict the colonization outcomes in experiments. Furthermore, we find that while most resident species are predicted to have a weak negative impact on the colonization of exogenous species, strongly interacting species could significantly alter the colonization outcomes, e.g., Enterococcus faecalis inhibits the invasion of E. faecium invasion. The presented results suggest that the data-driven approaches are powerful tools to inform the ecology and management of microbial communities.

Stochastic and deterministic assembly processes of microbial communities in relation to natural attenuation of black stains in Lascaux Cave.

Community assembly processes are complex and understanding them represents a challenge in microbial ecology. Here, we used Lascaux Cave as a stable, confined environment to quantify the importance of stochastic vs deterministic processes during microbial community dynamics across the three domains of life in relation to an anthropogenic disturbance that had resulted in the side-by-side occurrence of a resistant community (unstained limestone), an impacted community (present in black stains), and a resilient community (attenuated stains). Metabarcoding data showed that the microbial communities of attenuated stains, black stains, and unstained surfaces differed, with attenuated stains being in an intermediate position. We found four scenarios to explain community response to disturbance in stable conditions for the three domains of life. Specifically, we proposed the existence of a fourth, not-documented yet scenario that concerns the always-rare microbial taxa, where stochastic processes predominate even after disturbance but are replaced by deterministic processes during post-disturbance recovery. This suggests a major role of always-rare taxa in resilience, perhaps because they might provide key functions required for ecosystem recovery.IMPORTANCEThe importance of stochastic vs deterministic processes in cave microbial ecology has been a neglected topic so far, and this work provided an opportunity to do so in a context related to the dynamics of black-stain alterations in Lascaux, a UNESCO Paleolithic cave. Of particular significance was the discovery of a novel scenario for always-rare microbial taxa in relation to disturbance, in which stochastic processes are replaced later by deterministic processes during post-disturbance recovery, i.e., during attenuation of black stains.

Disturbance-diversity relationships of microbial communities change based on growth substrate.

Disturbance events can impact ecological community dynamics. Understanding how communities respond to disturbances and how those responses can vary is a challenge in microbial ecology. In this study, we grew a previously enriched specialized microbial community on either cellulose or glucose as a sole carbon source and subjected them to one of five different disturbance regimes of varying frequencies ranging from low to high. Using 16S rRNA gene amplicon sequencing, we show that the community structure is largely driven by substrate, but disturbance frequency affects community composition and successional dynamics. When grown on cellulose, bacteria in the genera Cellvibrio, Lacunisphaera, and Asticcacaulis are the most abundant microbes. However, Lacunisphaera is only abundant in the lower disturbance frequency treatments, while Asticcacaulis is more abundant in the highest disturbance frequency treatment. When grown on glucose, the most abundant microbes are two Pseudomonas sequence variants and a Cohnella sequence variant that is only abundant in the highest disturbance frequency treatment. Communities grown on cellulose exhibited a greater range of diversity (1.95-7.33 Hill 1 diversity) that peaks at the intermediate disturbance frequency treatment or one disturbance every 3 days. Communities grown on glucose, however, ranged from 1.63 to 5.19 Hill 1 diversity with peak diversity at the greatest disturbance frequency treatment. These results demonstrate that the dynamics of a microbial community can vary depending on substrate and the disturbance frequency and may potentially explain the variety of diversity-disturbance relationships observed in microbial systems.IMPORTANCEA generalizable diversity-disturbance relationship (DDR) of microbial communities remains a contentious topic. Various microbial systems have different DDRs. Rather than finding support or refuting specific DDRs, we investigated the underlying factors that lead to different DDRs. In this study, we measured a cellulose-enriched microbial community's response to a range of disturbance frequencies from high to low, across two different substrates: cellulose and glucose. We demonstrate that the community displays a unimodal DDR when grown on cellulose and a monotonically increasing DDR when grown on glucose. Our findings suggest that the same community can display different DDRs. These results suggest that the range of DDRs we observe across different microbial systems may be due to the nutritional resources microbial communities can access and the interactions between bacteria and their environment.

Dynamic social interactions and keystone species shape the diversity and stability of mixed-species biofilms – an example from dairy isolates

Identifying interspecies interactions in mixed-species biofilms is a key challenge in microbial ecology and is of paramount importance given that interactions govern community functionality and stability. We previously reported a bacterial four-species biofilm model comprising Stenotrophomonas rhizophila, Bacillus licheniformis, Microbacterium lacticum, and Calidifontibacter indicus that were isolated from the surface of a dairy pasteuriser after cleaning and disinfection. These bacteria produced 3.13-fold more biofilm mass compared to the sum of biofilm masses in monoculture. The present study confirms that the observed community synergy results from dynamic social interactions, encompassing commensalism, exploitation, and amensalism. M. lacticum appears to be the keystone species as it increased the growth of all other species that led to the synergy in biofilm mass. Interactions among the other three species (in the absence of M. lacticum) also contributed towards the synergy in biofilm mass. Biofilm inducing effects of bacterial cell-free-supernatants were observed for some combinations, revealing the nature of the observed synergy, and addition of additional species to dual-species combinations confirmed the presence of higher-order interactions within the biofilm community. Our findings provide understanding of bacterial interactions in biofilms which can be used as an interaction–mediated approach for cultivating, engineering, and designing synthetic bacterial communities.

Spatial scale impacts microbial community composition and distribution within and across stream ecosystems in North and Central America.

A mechanistic understanding of factors that structure spatiotemporal community composition is a major challenge in microbial ecology. Our study of microbial communities in the headwaters of three freshwater stream networks showed significant community changes at the small spatial scale of benthic habitats when compared to changes at mid- and large-spatial scales associated with stream order and catchment. Catchment (which included temperate and tropical catchments) had the strongest influence on community composition followed by habitat type (epipsammon or epilithon) and stream orders. Alpha diversity of benthic microbiomes resulted from interactions between catchment, habitat, and canopy. Epilithon contained relatively more Cyanobacteria and algae while Acidobacteria and Actinobacteria proportions were higher in epipsammic habitats. Turnover from replacement created ~60%-95% of beta diversity differences among habitats, stream orders, and catchments. Turnover within a habitat type generally decreased downstream indicating longitudinal linkages in stream networks while between habitat turnover also shaped benthic microbial community assembly. Our study suggests that factors influencing microbial community composition shift in dominance across spatial scales, with habitat dominating locally and catchment dominating globally.

The microbiome of the ice-capped Cayambe Volcanic Complex in Ecuador.

A major challenge in microbial ecology is to understand the principles and processes by which microbes associate and interact in community assemblages. Microbial communities in mountain glaciers are unique as first colonizers and nutrient enrichment drivers for downstream ecosystems. However, mountain glaciers have been distinctively sensitive to climate perturbations and have suffered a severe retreat over the past 40 years, compelling us to understand glacier ecosystems before their disappearance. This is the first study in an Andean glacier in Ecuador offering insights into the relationship of physicochemical variables and altitude on the diversity and structure of bacterial communities. Our study covered extreme Andean altitudes at the Cayambe Volcanic Complex, from 4,783 to 5,583 masl. Glacier soil and ice samples were used as the source for 16S rRNA gene amplicon libraries. We found (1) effects of altitude on diversity and community structure, (2) the presence of few significantly correlated nutrients to community structure, (3) sharp differences between glacier soil and glacier ice in diversity and community structure, where, as quantified by the Shannon γ-diversity distribution, the meta-community in glacier soil showed more diversity than in glacier ice; this pattern was related to the higher variability of the physicochemical distribution of variables in the former substrate, and (4) significantly abundant genera associated with either high or low altitudes that could serve as biomarkers for studies on climate change. Our results provide the first assessment of these unexplored communities, before their potential disappearance due to glacier retreat and climate change.

Metabarcoding of the Three Domains of Life in Aquatic Saline Ecosystems.

High-throughput amplicon sequencing, known as metabarcoding, is a powerful technique to decipher exhaustive microbial diversity considering specific gene markers. While most of the studies investigating ecosystem functioning through microbial diversity targeted only one domain of life, either bacteria, or archaea or microeukaryotes, the remaining challenge in microbial ecology is to uncover the integrated view of microbial diversity occurring in ecosystems. Indeed, interactions occurring between the different microbial counterparts are now recognized having a great impact on stability and resilience of ecosystems. Here, we summarize protocols describing sampling, molecular, and simultaneous metabarcoding of bacteria, archaea, and microeukaryotes, as well asa bioinformatic pipeline allowing the study of exhaustive microbial diversity in natural aquatic saline samples.

TbasCO: trait-based comparative ‘omics identifies ecosystem-level and niche-differentiating adaptations of an engineered microbiome

A grand challenge in microbial ecology is disentangling the traits of individual populations within complex communities. Various cultivation-independent approaches have been used to infer traits based on the presence of marker genes. However, marker genes are not linked to traits with complete fidelity, nor do they capture important attributes, such as the timing of gene expression or coordination among traits. To address this, we present an approach for assessing the trait landscape of microbial communities by statistically defining a trait attribute as a shared transcriptional pattern across multiple organisms. Leveraging the KEGG pathway database as a trait library and the Enhanced Biological Phosphorus Removal (EBPR) model microbial ecosystem, we demonstrate that a majority (65%) of traits present in 10 or more genomes have niche-differentiating expression attributes. For example, while many genomes containing high-affinity phosphorus transporter pstABCS display a canonical attribute (e.g. up-regulation under phosphorus starvation), we identified another attribute shared by many genomes where transcription was highest under high phosphorus conditions. Taken together, we provide a novel framework for unravelling the functional dynamics of uncultivated microorganisms by assigning trait-attributes through genome-resolved time-series metatranscriptomics.

Similar assembly mechanisms but distinct co-occurrence patterns of free-living vs. particle-attached bacterial communities across different habitats and seasons in shallow, eutrophic Lake Taihu

Eutrophication due to nitrogen and phosphorus input is an increasing problem in lake ecosystems. Free-living (FL) and particle-attached (PA) bacterial communities play a primary role in mediating biogeochemical processes in these lakes and in responding to eutrophication. However, knowledge of factors governing function, assembly mechanisms, and co-occurrence patterns of these communities remain poorly understood and are key challenges in microbial ecology. To address this knowledge gap, we collected 96 samples from Lake Taihu across four seasons and investigated the bacterial community using 16S rRNA gene sequencing. Our results demonstrate that the α-diversity, β-diversity, community composition, and functional composition of FL and PA bacterial communities exhibited differing spatiotemporal dynamics. FL and PA bacterial communities displayed similar distance-decay relationships across seasons. Deterministic processes (i.e., environmental filtering and species interaction) were the primary factors shaping community assembly in both FL and PA bacteria. Similar environmental factors shaped bacterial community structure while different environmental factors drove bacterial functional composition. Habitat filtering influenced enrichment of bacteria within specific functional groups. Among them, the FL bacterial community appeared to play a critical role in methane-utilization, whereas the PA bacteria contributed more to biogeochemical cycling of carbon. FL and PA bacterial communities exhibited distinct co-occurrence pattern across different seasons. In the FL network, Methylotenera and Methylophilaceae were identified as keystone taxa, while Burkholderiaceae and the hgcI clade were keystone taxa in the PA network. The PA bacterial community appeared to possess greater stability in the face of environmental change than did FL counterparts. These results broaden our knowledge of the driving factors, co-occurrence patterns, and assembly processes in FL and PA bacterial communities in eutrophic ecosystems and provide improved insight into the underlying mechanisms responsible for these results.

Contrasting resistance and resilience to light variation of the coupled oxic and anoxic components of an experimental microbial ecosystem.

Understanding how microbial communities of aquatic ecosystems respond to environmental change remains a critical challenge in microbial ecology. In this study, we used light‐dependent oxic–anoxic micro‐ecosystems to understand how the functioning and diversity of aerobic and anaerobic lake analog communities are affected by a pulse light deprivation. Continuous measurements of oxygen concentration were made and a time series of full‐length 16S rRNA sequencing was used to quantify changes in alpha‐ and beta diversity. In the upper oxic layer, oxygen concentration decreased significantly under light reduction, but showed resilience in daily mean, minimum, and maximum after light conditions were restored to control level. Only the amplitude of diurnal fluctuations in oxygen concentrations did not recover fully, and instead tended to remain lower in treated ecosystems. Alpha diversity of the upper oxic layer communities showed a delayed increase after light conditions were restored, and was not resilient in the longer term. In contrast, alpha diversity of the anoxic lower layer communities increased during the light reduction, but was resilient in the longer term. Community composition changed significantly during light reduction, and showed resilience in the oxic layer and lack of resilience in the anoxic layer. Alpha diversity and the amplitude of daily oxygen fluctuations within and among treatments were strongly correlated, suggesting that higher diversity could lead to less variable oxygen concentrations, or vice versa. Our experiment showed that light deprivation induces multifaceted responses of community function (oxygen respiration) and structure, hence focusing on a single stability component could potentially be misleading.

Different stochastic processes regulate bacterial and fungal community assembly in estuarine wetland soils

The long-standing challenge in microbial ecology is to quantify the relative importance of deterministic and stochastic processes in controlling the community structures through space and time. Deterministic processes are important when the environmental selection and species interactions are strong, whereas stochastic processes may dominate when there is large number of neutral births, death, speciation of microorganism. The existing studies are still lacking in understanding how these two processes structure microbial communities in an ecosystem whose environmental gradients change sharply at a very short geographic scale, such as in the fresh-saltwater transition zone. Here, we investigated the bacterial and fungal assembly processes in topsoil (0–10 cm) in a wetland transect with fresh-saltwater transition zone in the Yellow River Estuary, China, by calculating beta-mean-nearest taxon distance (βMNTD), beta nearest taxon index (βNTI) and Raup–Crick index. We found that stochastic processes primarily shaped the two communities. The bacterial assembly was controlled by homogenizing dispersal and dispersal limitation within and across the wetland transect, respectively. The fungal assembly, on the other hand, was mostly regulated by undominated processes, which are processes induced by weak selection/dispersal, diversification, and drift. Dispersal limitation had more pronounced effects on the bacterial diversity and cooccurrence in comparison with the effects of undominated processes on the fungal community. Nevertheless, environmental factors, such as pH, salinity and C/N, explained ∼30% (p < 0.01) of compositional variations with more explanatory power for bacteria than fungi. Our study highlights the different types of stochastic processes in regulating bacterial and fungal communities along the short natural environmental gradients. • Stochastic processes shaped microbial assembly in a natural estuarine wetland transect. • Bacteria showed high dispersal limitations across the transect. • Undominated processes controlled fungal assembly across the transect. • pH, salinity, and C/N explained ∼30% of variations of microbial compositional patterns.

Exploring rhizo-microbiome transplants as a tool for protective plant-microbiome manipulation

The development of strategies for effectively manipulating and engineering beneficial plant-associated microbiomes is a major challenge in microbial ecology. In this sense, the efficacy and potential implications of rhizosphere microbiome transplant (RMT) in plant disease management have only scarcely been explored in the literature. Here, we initially investigated potential differences in rhizosphere microbiomes of 12 Solanaceae eggplant varieties and accessed their level of resistance promoted against bacterial wilt disease caused by the pathogen Ralstonia solanacearum, in a 3-year field trial. We elected 6 resistant microbiomes and further tested the broad feasibility of using RMT from these donor varieties to a susceptible model Solanaceae tomato variety MicroTom. Overall, we found the rhizosphere microbiome of resistant varieties to enrich for distinct and specific bacterial taxa, of which some displayed significant associations with the disease suppression. Quantification of the RMT efficacy using source tracking analysis revealed more than 60% of the donor microbial communities to successfully colonize and establish in the rhizosphere of recipient plants. RTM from distinct resistant donors resulted in different levels of wilt disease suppression, reaching up to 47% of reduction in disease incidence. Last, we provide a culture-dependent validation of potential bacterial taxa associated with antagonistic interactions with the pathogen, thus contributing to a better understanding of the potential mechanism associated with the disease suppression. Our study shows RMT from appropriate resistant donors to be a promising tool to effectively modulate protective microbiomes and promote plant health. Together we advocate for future studies aiming at understanding the ecological processes and mechanisms mediating rates of coalescence between donor and recipient microbiomes in the plant rhizosphere.

Contrasting the assembly of phytoplankton and zooplankton communities in a polluted semi-closed sea: Effects of marine compartments and environmental selection

Understanding the underlying mechanisms of community assembly is a major challenge in microbial ecology, particularly in communities composed of diverse organisms with different ecological characteristics. However, very little is known about the effects of marine compartments in shaping marine planktonic communities; primarily, how they are related to organism types and environmental variables. In this study, we used multiple statistical methods to explore the mechanisms driving phytoplankton and zooplankton metacommunity dynamics at the regional scale in the Bohai Sea, China. Clear geographic patterns were observed in both phytoplankton and zooplankton communities. Zooplankton showed a stronger distance-decay of similarity than phytoplankton, which had greater community differences between locations with further distances. Our analyses indicated that the zooplankton communities were primarily governed by species sorting versus dispersal limitation than the phytoplankton communities. Furthermore, we detected that zooplankton exhibited wider habitat niche breadths and dispersal abilities than phytoplankton. Our findings also showed that environmental pollution affected high trophic organisms via food webs; the presence of heavy metals in the Bohai Sea altered the abundance of some phytoplankton, and thus modified the zooplankton that feed on them.

A Landscape of Opportunities for Microbial Ecology Research.

Microbes encompass tremendous biodiversity, provide support to all living forms, including humans, and play an important role in many ecosystem services. The rules that govern microorganism community assembly are increasingly revealed due to key advances in molecular and analytical methods but their understanding remain a key challenge in microbial ecology. The existence of biogeographic patterns within microbial communities has been established and explained in relation to landscape-scale processes, including selection, drift, dispersal and mutation. The effect of habitat patchiness on microorganisms’ assembly rules remains though incompletely understood. Here, we review how landscape ecology principles can be adapted to explore new perspectives on the mechanisms that determine microbial community structure. To provide a general overview, we characterize microbial landscapes, the spatial and temporal scales of the mechanisms that drive microbial assembly and the feedback between microorganisms and landscape structure. We provide evidence for the effects of landscape heterogeneity, landscape fragmentation and landscape dynamics on microbial community structure, and show that predictions made for macro-organisms at least partly also apply to microorganisms. We explain why emerging metacommunity approaches in microbial ecology should include explicit characterization of landscape structure in their development and interpretation. We also explain how biotic interactions, such as competition, prey-predator or mutualist relations may influence the microbial landscape and may be involved in the above-mentioned feedback process. However, we argue that the application of landscape ecology to the microbial world cannot simply involve transposing existing theoretical frameworks. This is due to the particularity of these organisms, in terms of size, generation time, and for some of them, tight interaction with hosts. These characteristics imply dealing with unusual and dependent space and time scales of effect. Evolutionary processes have also a strong importance in microorganisms’ response to their landscapes. Lastly, microorganisms’ activity and distribution induce feedback effects on the landscape that have to be taken into account. The transposition of the landscape ecology framework to microorganisms provides many challenging research directions for microbial ecology.

Spatial abundance distribution of prokaryotes is associated with dissolved organic matter composition and ecosystem function

AbstractDiverse prokaryotic communities consume and transform a broad suite of molecules in the dissolved organic matter (DOM) pool, which controls major biogeochemical cycles. Despite methodological advancements that provide increasingly more detailed information on the diversity of both prokaryotic communities and DOM components, understanding how these two component parts are structured to influence ecosystem functioning remains a major challenge in microbial ecology. Using empirical data collected along a gradient of productivity in the Labrador Sea, we characterized relationships among DOM compounds, metabolic processing, and prokaryotic diversity by structuring prokaryotic communities using spatial abundance distribution (SpAD) modeling. We identified strong associations of different SpAD taxonomic groups with specific organic substrates as well as with metabolic rates. Amplicon sequence variants (ASVs) with more cosmopolitan distributions (i.e. normal‐like) such as Bacteroidia were related to fresher DOM substrates such as free and combined amino acids whereas rare ASVs (i.e. logistic) like δ‐proteobacteria were associated with complex forms of organic matter. In terms of ecosystem function, rates of respiration and production were most strongly predicted by the abundance of certain SpAD taxonomic groups. Given the importance and complexity of linking environmental conditions, prokaryotic community structure, and ecosystem function, we propose a framework to bridge the gap between prokaryotic diversity, microbial ecology, and biogeochemistry among methods and across scales. Our work suggests that SpAD modeling can be used as an intermediate step to link prokaryotic community structure to both finer DOM details and larger ecosystem scale processes.

Synergic Effects of Temperature and Irradiance on the Physiology of the Marine Synechococcus Strain WH7803.

Understanding how microorganisms adjust their metabolism to maintain their ability to cope with short-term environmental variations constitutes one of the major current challenges in microbial ecology. Here, the best physiologically characterized marine Synechococcus strain, WH7803, was exposed to modulated light/dark cycles or acclimated to continuous high-light (HL) or low-light (LL), then shifted to various stress conditions, including low (LT) or high temperature (HT), HL and ultraviolet (UV) radiations. Physiological responses were analyzed by measuring time courses of photosystem (PS) II quantum yield, PSII repair rate, pigment ratios and global changes in gene expression. Previously published membrane lipid composition were also used for correlation analyses. These data revealed that cells previously acclimated to HL are better prepared than LL-acclimated cells to sustain an additional light or UV stress, but not a LT stress. Indeed, LT seems to induce a synergic effect with the HL treatment, as previously observed with oxidative stress. While all tested shift conditions induced the downregulation of many photosynthetic genes, notably those encoding PSI, cytochrome b6/f and phycobilisomes, UV stress proved to be more deleterious for PSII than the other treatments, and full recovery of damaged PSII from UV stress seemed to involve the neo-synthesis of a fairly large number of PSII subunits and not just the reassembly of pre-existing subunits after D1 replacement. In contrast, genes involved in glycogen degradation and carotenoid biosynthesis pathways were more particularly upregulated in response to LT. Altogether, these experiments allowed us to identify responses common to all stresses and those more specific to a given stress, thus highlighting genes potentially involved in niche acclimation of a key member of marine ecosystems. Our data also revealed important specific features of the stress responses compared to model freshwater cyanobacteria.