A comparative whole-genome approach identifies bacterial traits for marine microbial interactions

Collaborative metabolic curation of an emerging model marine bacterium, Alteromonas macleodii ATCC 27126

Inferring the metabolic capabilities of an organism from its genome is a challenging process, relying on computationally-derived or manually curated metabolic networks. Manual curation can correct mistakes in the draft network and add missing reactions based on the literature, but requires significant expertise and is often the bottleneck for high-quality metabolic reconstructions. Here, we present a synopsis of a community curation workshop for the model marine bacterium Alteromonas macleodii ATCC 27126 and its genome database in BioCyc, focusing on pathways for utilizing organic carbon and nitrogen sources. Due to the scarcity of biochemical information or gene knock-outs, the curation process relied primarily on published growth phenotypes and bioinformatic analyses, including comparisons with related Alteromonas strains. We report full pathways for the utilization of the algal polysaccharides alginate and pectin in contrast to inconclusive evidence for one-carbon metabolism and mixed acid fermentation, in accordance with the lack of growth on methanol and formate. Pathways for amino acid degradation are ubiquitous across Alteromonas macleodii strains, yet enzymes in the pathways for the degradation of threonine, tryptophan and tyrosine were not identified. Nucleotide degradation pathways are also partial in ATCC 27126. We postulate that demonstrated growth on nitrate as sole nitrogen source proceeds via a nitrate reductase pathway that is a hybrid of known pathways. Our evidence highlights the value of joint and interactive curation efforts, but also shows major knowledge gaps regarding Alteromonas metabolism. The manually-curated metabolic reconstruction is available as a "Tier-2" database on BioCyc.

Identifying Opportunity Targets in Gram-Negative Pathogens for Infectious Disease Mitigation

Antimicrobial drug resistance (AMR) is a pressing global human health challenge. Humans face one of their grandest challenges as climate change expands the habitat of vectors that bear human pathogens, incidences of nosocomial infections rise, and new antibiotics discovery lags. AMR is a multifaceted problem that requires a multidisciplinary and an "all-hands-on-deck" approach. As chemical microbiologists, we are well positioned to understand the complexities of AMR while seeing opportunities for tackling the challenge. In this Outlook, we focus on vulnerabilities of human pathogens and posit that they represent "opportunity targets" for which few modulatory ligands exist. We center our attention on proteins in Gram-negative organisms, which are recalcitrant to many antibiotics because of their external membrane barrier. Our hope is to highlight such targets and explore their potential as "druggable" proteins for infectious disease mitigation. We posit that success in this endeavor will introduce new classes of antibiotics that might alleviate some of the current pressing AMR concerns.

Microbial functional diversity and redundancy: moving forward

Microbial functional ecology is expanding as we can now measure the traits of wild microbes that affect ecosystem functioning. Here, we review techniques and advances that could be the bedrock for a unified framework to study microbial functions. These include our newfound access to environmental microbial genomes, collections of microbial traits, but also our ability to study microbes' distribution and expression. We then explore the technical, ecological, and evolutionary processes that could explain environmental patterns of microbial functional diversity and redundancy. Next, we suggest reconciling microbiology with biodiversity-ecosystem functioning studies by experimentally testing the significance of microbial functional diversity and redundancy for the efficiency, resistance, and resilience of ecosystem processes. Such advances will aid in identifying state shifts and tipping points in microbiomes, enhancing our understanding of how and where will microbes guide Earth's biomes in the context of a changing planet.

Human activities-impacted lake dissolved organic matter (DOM) affects phycosphere microbial diversity and DOM diversification via carbon metabolism

Photosynthetic carbon sequestration and microbial carbon metabolism are major processes of algae-bacteria interactions, affecting pollutant degradation as well as fundamental biogeochemical cycles in aquatic systems. Human-induced land-use changes greatly alter the molecular composition and input of terrestrial dissolved organic matter (DOM) in inland lakes. However, how the origin of DOM leads to varying effects on phycosphere microbial communities or molecular composition of DOM, e.g., via carbon metabolism, has been little studied in freshwater. Here, we incubated the cyanobacterium Microcystis aeruginosa and a bacterial community from natural lakes to establish an alga-bacteria model system. This allowed us to investigate how DOM from different sources affects phycosphere microbial diversity and DOM diversification. We showed that Suwannee River fulvic acid (SRFA), Suwannee River natural organic matter (SRNOM) and cropland lake DOM promote algal growth, whereas DOM from an urban lake inhibits algal growth. Algal metabolites and DOM together shaped the chemotaxis response of phycosphere communities. High-resolution mass spectrometry analysis demonstrated that DOM chemo-diversity tended to become uniform after interactions of diverse DOM sources with the algae-bacteria symbiosis system. Molecular thermodynamic analysis of DOM based on a substrate-explicit model further verified that microbial interactions render DOM less bioavailable and thus increase recalcitrant DOM formation. Metabolome analysis uncovered that DOM addition intensifies metabolic pathways related to labile and recalcitrant DOM utilization (mainly lignin/carboxyl-rich alicyclic molecule (CRAM)-like DOM, unsaturated hydrocarbon), whereby cofactor and vitamin metabolism represented an extremely strong activity in all metabolic pathways. Our results highlight covariation and interactions of DOM with microbial metabolism at the molecular level and expands our understanding of microbially mediated DOM shaping aquatic carbon cycling.

Understanding Nanoscale Interactions between Minerals and Microbes: Opportunities for Green Remediation of Contaminated Sites

In situ contaminant degradation and detoxification mediated by microbes and minerals is an important element of green remediation. Improved understanding of microbe-mineral interactions on the nanoscale offers promising opportunities to further minimize the environmental and energy footprints of site remediation. In this Perspective, we describe new methodologies that take advantage of an array of multidisciplinary tools─including multiomics-based analysis, bioinformatics, machine learning, gene editing, real-time spectroscopic and microscopic analysis, and computational simulations─to identify the key microbial drivers in the real environments, and to characterize in situ the dynamic interplay between minerals and microbes with high spatiotemporal resolutions. We then reflect on how the knowledge gained can be exploited to modulate the binding, electron transfer, and metabolic activities at the microbe-mineral interfaces, to develop new in situ contaminant degradation and detoxication technologies with combined merits of high efficacy, material longevity, and low environmental impacts. Two main strategies are proposed to maximize the synergy between minerals and microbes, including using mineral nanoparticles to enhance the versatility of microorganisms (e.g., tolerance to environmental stresses, growth and metabolism, directed migration, selectivity, and electron transfer), and using microbes to synthesize and regenerate highly dispersed nanostructures with desired structural/surface properties and reactivity.

Diversity in the utilization of different molecular classes of dissolved organic matter by heterotrophic marine bacteria

Heterotrophic marine bacteria utilize and recycle dissolved organic matter (DOM), impacting biogeochemical cycles. It is currently unclear to what extent distinct DOM components can be used by different heterotrophic clades. Here, we ask how a natural microbial community from the Eastern Mediterranean Sea (EMS) responds to different molecular classes of DOM (peptides, amino acids, amino sugars, disaccharides, monosaccharides, and organic acids) comprising much of the biomass of living organisms. Bulk bacterial activity increased after 24 h for all treatments relative to the control, while glucose and ATP uptake decreased or remained unchanged. Moreover, while the per-cell uptake rate of glucose and ATP decreased, that of Leucin significantly increased for amino acids, reflecting their importance as common metabolic currencies in the marine environment. Pseudoalteromonadaceae dominated the peptides treatment, while different Vibrionaceae strains became dominant in response to amino acids and amino sugars. Marinomonadaceae grew well on organic acids, and Alteromonadaseae on disaccharides. A comparison with a recent laboratory-based study reveals similar peptide preferences for Pseudoalteromonadaceae, while Alteromonadaceae, for example, grew well in the lab on many substrates but dominated in seawater samples only when disaccharides were added. We further demonstrate a potential correlation between the genetic capacity for degrading amino sugars and the dominance of specific clades in these treatments. These results highlight the diversity in DOM utilization among heterotrophic bacteria and complexities in the response of natural communities.

IMPORTANCE

A major goal of microbial ecology is to predict the dynamics of natural communities based on the identity of the organisms, their physiological traits, and their genomes. Our results show that several clades of heterotrophic bacteria each grow in response to one or more specific classes of organic matter. For some clades, but not others, growth in a complex community is similar to that of isolated strains in laboratory monoculture. Additionally, by measuring how the entire community responds to various classes of organic matter, we show that these results are ecologically relevant, and propose that some of these resources are utilized through common uptake pathways. Tracing the path between different resources to the specific microbes that utilize them, and identifying commonalities and differences between different natural communities and between them and lab cultures, is an important step toward understanding microbial community dynamics and predicting how communities will respond to perturbations.

Bacterioplankton taxa compete for iron along the early spring-summer transition in the Arctic Ocean

Microbial assemblages under the sea ice of the Dease Strait, Canadian Arctic, were sequenced for metagenomes of a small size fraction (0.2-3 μm). The community from early March was typical for this season, with Alpha- and Gammaproteobacteria as the dominant taxa, followed by Thaumarchaeota and Bacteroidetes. Toward summer, Bacteroidetes, and particularly the genus Polaribacter, became increasingly dominant, followed by the Gammaproteobacteria. Analysis of genes responsible for microbial acquisition of iron showed an abundance of ABC transporters for divalent cations and ferrous iron. The most abundant transporters, however, were the outer membrane TonB-dependent transporters of iron-siderophore complexes. The abundance of iron acquisition genes suggested this element was essential for the microbial assemblage. Interestingly, Gammaproteobacteria were responsible for most of the siderophore synthesis genes. On the contrary, Bacteroidetes did not synthesize siderophores but accounted for most of the transporters, suggesting a role as cheaters in the competition for siderophores as public goods. This cheating ability of the Bacteroidetes may have contributed to their dominance in the summer.

The recovery of soil eukaryotic alpha and beta diversity after wetland restoration

Soil eukaryotes play an important role in regulating the ecological processes and ecosystem functioning. However, the recovery potential of soil eukaryotic diversity during wetland restoration is largely unknown. We compared the alpha and beta diversity of soil eukaryotes of farmlands and natural and restored wetlands to explore the underlying abiotic and biotic driving forces in the Sanjiang Plain, China. We found that there was no significant difference of the alpha diversity of soil eukaryotes, while the beta diversity of soil eukaryotes differed significantly between the three land use types, with the mean values in the restored wetlands in between those in the natural wetlands and farmlands. The composition of soil eukaryotic communities were less diverse in farmlands compared to restored and natural wetlands. Network property of soil eukaryotes community (positive: negative edges) increased from farmlands to restored wetlands to natural wetlands, indicating enhanced species positive: negative interactions during restoration. The structural equation modeling indicated that species positive: negative interactions and soil nutrients directly affected soil eukaryotic beta diversity. Soil pH and soil water content indirectly affected soil eukaryotic beta diversity by directly affecting species interactions. Our findings suggest that wetland restoration could change soil environment, strengthen microbial cooperation, and increase eukaryotic beta diversity. However, it may take a very long time to reach the original level of soil eukaryotic structure and diversity.

A pan-genomic assessment: Delving into the genome of the marine epiphyte Bacillus altitudinis strain 19_A and other very close Bacillus strains from multiple environments

Marine macroalgae are the habitat of epiphytic bacteria and provide several conditions for a beneficial biological interaction to thrive. Although Bacillus is one of the most abundant epiphytic genera, genomic information on marine macroalgae-associated Bacillus species remains scarce. In this study, we further investigated our previously published genome of the epiphytic strain Bacillus altitudinis 19_A to find features that could be translated to potential metabolites produced by this microorganism, as well as genes that play a role in its interaction with its macroalgal host. To achieve this goal, we performed a pan-genome analysis of Bacillus sp. and a codon bias assessment, including the genome of the strain Bacillus altitudinis 19_A and 29 complete genome sequences of closely related Bacillus strains isolated from soil, marine environments, plants, extreme environments, air, and food. This genomic analysis revealed that Bacillus altitudinis 19_A possessed unique genes encoding proteins involved in horizontal gene transfer, DNA repair, transcriptional regulation, and bacteriocin biosynthesis. In this comparative analysis, codon bias was not associated with the habitat of the strains studied. Some accessory genes were identified in the Bacillus altitudinis 19_A genome that could be related to its epiphytic lifestyle, as well as gene clusters for the biosynthesis of a sporulation-killing factor and a bacteriocin, showing their potential as a source of antimicrobial peptides. Our results provide a comprehensive view of the Bacillus altitudinis 19_A genome to understand its adaptation to the marine environment and its potential as a producer of bioactive compounds.

Multi-Attribute Subset Selection enables prediction of representative phenotypes across microbial populations

The interpretation of complex biological datasets requires the identification of representative variables that describe the data without critical information loss. This is particularly important in the analysis of large phenotypic datasets (phenomics). Here we introduce Multi-Attribute Subset Selection (MASS), an algorithm which separates a matrix of phenotypes (e.g., yield across microbial species and environmental conditions) into predictor and response sets of conditions. Using mixed integer linear programming, MASS expresses the response conditions as a linear combination of the predictor conditions, while simultaneously searching for the optimally descriptive set of predictors. We apply the algorithm to three microbial datasets and identify environmental conditions that predict phenotypes under other conditions, providing biologically interpretable axes for strain discrimination. MASS could be used to reduce the number of experiments needed to identify species or to map their metabolic capabilities. The generality of the algorithm allows addressing subset selection problems in areas beyond biology.

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.

Succession of microbial community composition and secondary metabolism during marine biofilm development

In nature, secondary metabolites mediate interactions between microorganisms residing in complex microbial communities. However, the degree to which community dynamics can be linked to secondary metabolite potential remains largely unknown. In this study, we address the relationship between community succession and secondary metabolism variation. We used 16S and 18S rRNA gene and adenylation domain amplicon sequencing, genome-resolved metagenomics, and untargeted metabolomics to track the taxons, biosynthetic gene clusters, and metabolome dynamics in situ of microorganisms during marine biofilm succession over 113 days. Two phases were identified during the community succession, with a clear shift around Day 29, where the alkaloid secondary metabolites, pseudanes, were also detected. The microbial secondary metabolite potential changed between the phases, and only a few community members, including Myxococotta spp., were responsible for the majority of the biosynthetic gene cluster potential in the early succession phase. In the late phase, bryozoans and benthic copepods were detected, and the microbial nonribosomal peptide potential drastically decreased in association with a reduction in the relative abundance of the prolific secondary metabolite producers. Conclusively, this study provides evidence that the early succession of the marine biofilm community favors prokaryotes with high nonribosomal peptide synthetase potential. In contrast, the late succession is dominated by multicellular eukaryotes and a reduction in bacterial nonribosomal peptide synthetase potential.

Taxonomic distribution of metabolic functions in bacteria associated with Trichodesmium consortia

IMPORTANCE

Colonies of the cyanobacteria Trichodesmium act as a biological hotspot for the usage and recycling of key resources such as C, N, P, and Fe within an otherwise oligotrophic environment. While Trichodesmium colonies are known to interact and support a unique community of algae and particle-associated microbes, our understanding of the taxa that populate these colonies and the gene functions they encode is still limited. Characterizing the taxa and adaptive strategies that influence consortium physiology and its concomitant biogeochemistry is critical in a future ocean predicted to have increasingly resource-depleted regions.

Diatom-Bacteria Interactions in the Marine Environment: Complexity, Heterogeneity, and Potential for Biotechnological Applications

Diatom-bacteria interactions evolved during more than 200 million years of coexistence in the same environment. In this time frame, they established complex and heterogeneous cohorts and consortia, creating networks of multiple cell-to-cell mutualistic or antagonistic interactions for nutrient exchanges, communication, and defence. The most diffused type of interaction between diatoms and bacteria is based on a win-win relationship in which bacteria benefit from the organic matter and nutrients released by diatoms, while these last rely on bacteria for the supply of nutrients they are not able to produce, such as vitamins and nitrogen. Despite the importance of diatom-bacteria interactions in the evolutionary history of diatoms, especially in structuring the marine food web and controlling algal blooms, the molecular mechanisms underlying them remain poorly studied. This review aims to present a comprehensive report on diatom-bacteria interactions, illustrating the different interplays described until now and the chemical cues involved in the communication and exchange between the two groups of organisms. We also discuss the potential biotechnological applications of molecules and processes involved in those fascinating marine microbial networks and provide information on novel approaches to unveiling the molecular mechanisms underlying diatom-bacteria interactions.

Perturbation of Quorum Sensing after the Acquisition of Bacteriophage Resistance Could Contribute to Novel Traits in Vibrio alginolyticus

Bacteria employ a wide range of molecular mechanisms to confer resistance to bacteriophages, and these mechanisms are continuously being discovered and characterized. However, there are instances where certain bacterial species, despite lacking these known mechanisms, can still develop bacteriophage resistance through intricate metabolic adaptation strategies, potentially involving mutations in transcriptional regulators or phage receptors. Vibrio species have been particularly useful for studying the orchestrated metabolic responses of Gram-negative marine bacteria in various challenges. In a previous study, we demonstrated that Vibrio alginolyticus downregulates the expression of specific receptors and transporters in its membrane, which may enable the bacterium to evade infection by lytic bacteriophages. In our current study, our objective was to explore how the development of bacteriophage resistance in Vibrio species disrupts the quorum-sensing cascade, subsequently affecting bacterial physiology and metabolic capacity. Using a real-time quantitative PCR (rt-QPCR) platform, we examined the expression pattern of quorum-sensing genes, auto-inducer biosynthesis genes, and cell density regulatory proteins in phage-resistant strains. Our results revealed that bacteriophage-resistant bacteria downregulate the expression of quorum-sensing regulatory proteins, such as LuxM, LuxN, and LuxP. This downregulation attenuates the normal perception of quorum-sensing peptides and subsequently diminishes the expression of cell density regulatory proteins, including LuxU, aphA, and LuxR. These findings align with the diverse phenotypic traits observed in the phage-resistant strains, such as altered biofilm formation, reduced planktonic growth, and reduced virulence. Moreover, the transcriptional depletion of aphA, the master regulator associated with low cell density, was linked to the downregulation of genes related to virulence. This phenomenon appears to be phage-specific, suggesting a finely tuned metabolic adaptation driven by phage-host interaction. These findings contribute to our understanding of the role of Vibrio species in microbial marine ecology and highlight the complex interplay between phage resistance, quorum sensing, and bacterial physiology.

Temporal variability in the growth-enhancing effects of different bacteria within the microbiome of the diatom Actinocyclus sp

Reciprocal metabolite exchanges between diatoms and bacteria can enhance the growth of both partners and therefore fundamentally influence aquatic ecosystem productivity. Here, we examined the growth-promoting capabilities of 15 different bacterial isolates from the bacterial community associated with the marine diatom Actinocyclus sp. and investigated the magnitude and timing of their effect on the growth of this diatom. In the presence of its microbiome, Actinocyclus sp. growth was significantly enhanced relative to axenic cultures. Co-culture with each of the 15 bacterial isolates examined here (seven Rhodobacteraceae, four Vibrionaceae, two Pseudoalteromonadaceae, one Oceanospirillaceae and one Alteromonadaceae) increased the growth of the diatom host, with four isolates inducing rates of growth that were similar to those delivered by the diatom's full microbiome. However, the timing and duration of this effect differed between the different bacteria tested. Indeed, one Rhodobacteraceae and one Alteromonadaceae enhanced Actinocyclus sp. cell numbers between days 0-6 after co-incubation, five other Rhodobacteraceae promoted diatom cell numbers the most between days 8-12, whilst four Vibrionaceae, one Oceanospirillaceae and one Rhodobacteraceae enhanced Actinocyclus sp. cell abundance between days 14-16. These results are indicative of a succession of the growth-enhancing effects delivered by diverse bacteria throughout the Actinocyclus sp. life cycle, which will likely deliver sustained growth benefits to the diatom when its full microbiome is present.

A Reduction of Transcriptional Regulation in Aquatic Oligotrophic Microorganisms Enhances Fitness in Nutrient-Poor Environments

In this review, we consider the regulatory strategies of aquatic oligotrophs, microbial cells that are adapted to thrive under low-nutrient concentrations in oceans, lakes, and other aquatic ecosystems. Many reports have concluded that oligotrophs use less transcriptional regulation than copiotrophic cells, which are adapted to high nutrient concentrations and are far more common subjects for laboratory investigations of regulation. It is theorized that oligotrophs have retained alternate mechanisms of regulation, such as riboswitches, that provide shorter response times and smaller amplitude responses and require fewer cellular resources. We examine the accumulated evidence for distinctive regulatory strategies in oligotrophs. We explore differences in the selective pressures copiotrophs and oligotrophs encounter and ask why, although evolutionary history gives copiotrophs and oligotrophs access to the same regulatory mechanisms, they might exhibit distinctly different patterns in how these mechanisms are used. We discuss the implications of these findings for understanding broad patterns in the evolution of microbial regulatory networks and their relationships to environmental niche and life history strategy. We ask whether these observations, which have emerged from a decade of increased investigation of the cell biology of oligotrophs, might be relevant to recent discoveries of many microbial cell lineages in nature that share with oligotrophs the property of reduced genome size.

Interactions between Culturable Bacteria Are Predicted by Individual Species' Growth

Predicting interspecies interactions is a key challenge in microbial ecology given that interactions shape the composition and functioning of microbial communities. However, predicting microbial interactions is challenging because they can vary considerably depending on species' metabolic capabilities and environmental conditions. Here, we employ machine learning models to predict pairwise interactions between culturable bacteria based on their phylogeny, monoculture growth capabilities, and interactions with other species. We trained our models on one of the largest available pairwise interactions data set containing over 7,500 interactions between 20 species from two taxonomic groups that were cocultured in 40 different carbon environments. Our models accurately predicted both the sign (accuracy of 88%) and the strength of effects (R² of 0.87) species had on each other's growth. Encouragingly, predictions with comparable accuracy could be made even when not relying on information about interactions with other species, which are often hard to measure. However, species' monoculture growth was essential to the model, as predictions based solely on species' phylogeny and inferred metabolic capabilities were significantly less accurate. These results bring us one step closer to a predictive understanding of microbial communities, which is essential for engineering beneficial microbial consortia. IMPORTANCE In order to understand the function and structure of microbial communities, one must know all pairwise interactions that occur between the different species within the community, as these interactions shape the community's structure and functioning. However, measuring all pairwise interactions can be an extremely difficult task especially when dealing with big complex communities. Because of that, predicting interspecies interactions is a key challenge in microbial ecology. Here, we use machine learning models in order to accurately predict the type and strength of interactions. We trained our models on one of the largest available pairwise interactions data set, containing over 7,500 interactions between 20 different species that were cocultured in 40 different environments. Our results show that, in general, accurate predictions can be made, and that the ability of each species to grow on its own in the given environment contributes the most to predictions. Being able to predict microbial interactions would put us one step closer to predicting the functionality of microbial communities and to rationally microbiome engineering.

Phototroph-heterotroph interactions during growth and long-term starvation across Prochlorococcus and Alteromonas diversity

Due to their potential impact on ecosystems and biogeochemistry, microbial interactions, such as those between phytoplankton and bacteria, have been studied intensively using specific model organisms. Yet, to what extent interactions differ between closely related organisms, or how these interactions change over time, or culture conditions, remains unclear. Here, we characterize the interactions between five strains each of two globally abundant marine microorganisms, Prochlorococcus (phototroph) and Alteromonas (heterotroph), from the first encounter between individual strains and over more than a year of repeated cycles of exponential growth and long-term nitrogen starvation. Prochlorococcus-Alteromonas interactions had little effect on traditional growth parameters such as Prochlorococcus growth rate, maximal fluorescence, or lag phase, affecting primarily the dynamics of culture decline, which we interpret as representing cell mortality and lysis. The shape of the Prochlorococcus decline curve and the carrying capacity of the co-cultures were determined by the phototroph and not the heterotroph strains involved. Comparing various mathematical models of culture mortality suggests that Prochlorococcus death rate increases over time in mono-cultures but decreases in co-cultures, with cells potentially becoming more resistant to stress. Our results demonstrate intra-species differences in ecologically relevant co-culture outcomes. These include the recycling efficiency of N and whether the interactions are mutually synergistic or competitive. They also highlight the information-rich growth and death curves as a useful readout of the interaction phenotype.

Shared and contrasting associations in the dynamic nano- and picoplankton communities of two close but contrasting sites from the Bay of Biscay

Pico- and nanoplankton are key players in the marine ecosystems due to their implication in the biogeochemical cycles, nutrient recycling and the pelagic food webs. However, the specific dynamics and niches of most bacterial, archaeal and eukaryotic plankton remain unknown, as well as the interactions between them. Better characterization of these is critical for understanding and predicting ecosystem functioning under anthropogenic pressures. We used environmental DNA metabarcoding across a 6-year time series to explore the structure and seasonality of pico- and nanoplankton communities in two sites of the Bay of Biscay, one coastal and one offshore, and construct association networks to reveal potential keystone and connector taxa. Temporal trends in alpha diversity were similar between the two sites, and concurrent communities more similar than within the same site at different times. However, we found differences between the network topologies of the two sites, with both shared and site-specific keystones and connectors. For example, Micromonas, with lower abundance in the offshore site is a keystone here, indicating a stronger effect of associations such as resource competition. This study provides an example of how time series and association network analysis can reveal how similar communities may function differently despite being geographically close.

Metabolic Phenotyping of Marine Heterotrophs on Refactored Media Reveals Diverse Metabolic Adaptations and Lifestyle Strategies

Microbial communities, through their metabolism, drive carbon cycling in marine environments. These complex communities are composed of many different microorganisms including heterotrophic bacteria, each with its own nutritional needs and metabolic capabilities. Yet, models of ecosystem processes typically treat heterotrophic bacteria as a “black box,” which does not resolve metabolic heterogeneity nor address ecologically important processes such as the successive modification of different types of organic matter. Here we directly address the heterogeneity of metabolism by characterizing the carbon source utilization preferences of 63 heterotrophic bacteria representative of several major marine clades. By systematically growing these bacteria on 10 media containing specific subsets of carbon sources found in marine biomass, we obtained a phenotypic fingerprint that we used to explore the relationship between metabolic preferences and phylogenetic or genomic features. At the class level, these bacteria display broadly conserved patterns of preference for different carbon sources. Despite these broad taxonomic trends, growth profiles correlate poorly with phylogenetic distance or genome-wide gene content. However, metabolic preferences are strongly predicted by a handful of key enzymes that preferentially belong to a few enriched metabolic pathways, such as those involved in glyoxylate metabolism and biofilm formation. We find that enriched pathways point to enzymes directly involved in the metabolism of the corresponding carbon source and suggest potential associations between metabolic preferences and other ecologically relevant traits. The availability of systematic phenotypes across multiple synthetic media constitutes a valuable resource for future quantitative modeling efforts and systematic studies of interspecies interactions.

IMPORTANCE Half of the Earth’s annual primary production is carried out by phytoplankton in the surface ocean. However, this metabolic activity is heavily impacted by heterotrophic bacteria, which dominate the transformation of organic matter released from phytoplankton. Here, we characterize the diversity of metabolic preferences across many representative heterotrophs by systematically growing them on different fractions of dissolved organic carbon. Our analysis suggests that different clades of bacteria have substantially distinct preferences for specific carbon sources, in a way that cannot be simply mapped onto phylogeny. These preferences are associated with the presence of specific genes and pathways, reflecting an association between metabolic capabilities and ecological lifestyles. In addition to helping understand the importance of heterotrophs under different conditions, the phenotypic fingerprint we obtained can help build higher resolution quantitative models of global microbial activity and biogeochemical cycles in the oceans.

The role of organic nutrients in structuring freshwater phytoplankton communities in a rapidly changing world

Carbon, nitrogen, and phosphorus are critical macroelements in freshwater systems. Historically, researchers and managers have focused on inorganic forms, based on the premise that the organic pool was not available for direct uptake by phytoplankton. We now know that phytoplankton can tap the organic nutrient pool through a number of mechanisms including direct uptake, enzymatic hydrolysis, mixotrophy, and through symbiotic relationships with microbial communities. In this review, we explore these mechanisms considering current and projected future anthropogenically-driven changes to freshwater systems. In particular, we focus on how naturally- and anthropogenically- derived organic nutrients can influence phytoplankton community structure. We also synthesize knowledge gaps regarding phytoplankton physiology and the potential challenges of nutrient management in an organically dynamic and anthropogenically modified world. Our review provides a basis for exploring these topics and suggests several avenues for future work on the relation between organic nutrients and eutrophication and their ecological implications in freshwater systems.