Phytoplankton is fundamental to life on Earth. Their productivity is influenced by the microbial communities residing in the phycosphere surrounding algal cells. Expanding our knowledge on how algal-bacterial interactions affect algal growth to more hosts and bacteria can help elucidate general principles of algal-host interactions. Here, we isolated 368 bacterial strains from phycosphere communities, right after phycosphere recruitment from pond water and after a month of lab cultivation and examined their impacts on growth of five green algal species. We isolated both abundant and rare phycosphere members, representing 18.4% of the source communities. Positive and neutral effects predominated over negative effects on host growth. The proportion of each effect type and whether the day of isolation mattered varied by host species. Bacteria affected algal carrying capacity more than growth rate, suggesting that nutrient remineralization and toxic byproduct metabolism may be a dominant mechanism. Across-host algal fitness assays indicated host-specific growth effects of our isolates. We observed no phylogenetic conservation of the effect on host growth among bacterial isolates. Even isolates with the same ASV had divergent effects on host growth. Our results emphasize highly specific host-bacterial interactions in the phycosphere and raise questions as to which mechanisms mediate these interactions.

Bacteria associated with eukaryotic hosts can affect host fitness and trophic interactions between eukaryotes, but the extent to which bacteria influence the eukaryotic species interactions within trophic levels that modulate biodiversity and species coexistence is mostly unknown. Here, we used phytoplankton, which are a classic model for evaluating interactions between species, grown with and without associated bacteria to test whether the bacteria alter the strength and type of species interactions within a trophic level. We demonstrate that host-associated bacteria alter host growth rates and carrying capacity. This did not change the type but frequently changed the strength of host interspecific interactions by facilitating host growth in the presence of an established species. These findings indicate that microbiomes can regulate their host species' interspecific interactions. As between-species interaction strength impacts their ability to coexist, our findings show that microbiomes have the potential to modulate eukaryotic species diversity and community composition.IMPORTANCE Description of the Earth's microbiota has recently undergone a phenomenal expansion that has challenged basic assumptions in many areas of biology, including hominid evolution, human gastrointestinal and neurodevelopmental disorders, and plant adaptation to climate change. By using the classic model system of freshwater phytoplankton that has been drawn upon for numerous foundational theories in ecology, we show that microbiomes, by facilitating their host population, can also influence between-species interactions among their eukaryotic hosts. Between-species interactions, including competition for resources, has been a central tenet in the field of ecology because of its implications for the diversity and composition of communities and how this in turn shapes ecosystem functioning.

Community genomic data have revealed multiple levels of variation between and within microbial consortia. This variation includes large-scale differences in gene content between ecosystems as well as within-population sequence heterogeneity. In the present review, we focus specifically on how fine-scale variation within microbial and viral populations is apparent from community genomic data. A major unresolved question is how much of the observed variation is due to neutral vs. adaptive processes. Limited experimental data hint that some of this fine-scale variation may be in part functionally relevant, whereas sequence-based and modeling analyses suggest that much of it may be neutral. While methods for interpreting population genomic data are still in their infancy, we discuss current interpretations of existing datasets in the light of evolutionary processes and models. Finally, we highlight the importance of virus-host dynamics in generating and shaping within-population diversity.

Insights into symbiosis between eukaryotic hosts and their microbiomes have shifted paradigms on what determines host fitness, ecology, and behavior. Questions remain regarding the roles of host versus environment in shaping microbiomes, and how microbiome composition affects host fitness. Using a model system in ecology, phytoplankton, we tested whether microbiomes are host-specific, confer fitness benefits that are host-specific, and remain conserved in time in their composition and fitness effects. We used an experimental approach in which hosts were cleaned of bacteria and then exposed to bacterial communities from natural environments to permit recruitment of microbiomes. We found that phytoplankton microbiomes consisted of a subset of taxa recruited from these natural environments. Microbiome recruitment was host-specific, with host species explaining more variation in microbiome composition than environment. While microbiome composition shifted and then stabilized over time, host specificity remained for dozens of generations. Microbiomes increased host fitness, but these fitness effects were host-specific for only two of the five species. The shifts in microbiome composition over time amplified fitness benefits to the hosts. Overall, this work solidifies the importance of host factors in shaping microbiomes and elucidates the temporal dynamics of microbiome compositional and fitness effects.

Microbial community structure is influenced by the environment and in turn exerts control on many environmental parameters. We applied this concept in a bioreactor study to test whether microbial community structure contains information sufficient to predict the concentration of H₂S as the product of sulfate reduction. Microbial sulfate reduction is a major source of H₂S in many industrial and environmental systems and is often influenced by the existing physicochemical conditions. Production of H₂S in industrial systems leads to occupational hazards and adversely affects the quality of products. A long-term (148 days) experiment was conducted in upflow bioreactors to mimic sulfidogenesis, followed by inhibition with nitrate salts and a resumption of H₂S generation when inhibition was released. We determined microbial community structure in 731 samples across 20 bioreactors using 16S rRNA gene sequencing and applied a random forest algorithm to successfully predict different phases of sulfidogenesis and mitigation (accuracy = 93.17%) and sessile and effluent microbial communities (accuracy = 100%). Similarly derived regression models that also included cell abundances were able to predict H₂S concentration with remarkably high fidelity (R² > 0.82). Metabolic profiles based on microbial community structure were also found to be reliable predictors for H₂S concentration (R² = 0.78). These results suggest that microbial community structure contains information sufficient to predict sulfidogenesis in a closed system, with anticipated applications to microbially driven processes in open environments. IMPORTANCE Microbial communities control many biogeochemical processes. Many of these processes are impractical or expensive to measure directly. Because the taxonomic structure of the microbial community is indicative of its function, it encodes information that can be used to predict biogeochemistry. Here, we demonstrate how a machine learning technique can be used to predict sulfidogenesis, a key biogeochemical process in a model system. A distinction of this research was the ability to predict H₂S production in a bioreactor from the effluent bacterial community structure without direct observations of the sessile community or other environmental conditions. This study establishes the ability to use machine learning approaches in predicting sulfide concentrations in a closed system, which can be further developed as a valuable tool for predicting biogeochemical processes in open environments. As machine learning algorithms continue to improve, we anticipate increased applications of microbial community structure to predict key environmental and industrial processes.

Abstract Background Metal sulfide mineral dissolution during bioleaching and acid mine drainage (AMD) formation creates an environment that is inhospitable to most life. Despite dominance by a small number of bacteria, AMD microbial biofilm communities contain a notable variety of coexisting and closely related Euryarchaea, most of which have defied cultivation efforts. For this reason, we used metagenomics to analyze variation in gene content that may contribute to niche differentiation among co-occurring AMD archaea. Our analyses targeted members of the Thermoplasmatales and related archaea. These results greatly expand genomic information available for this archaeal order. Results We reconstructed near-complete genomes for uncultivated, relatively low abundance organisms A-, E-, and Gplasma, members of Thermoplasmatales order, and for a novel organism, Iplasma. Genomic analyses of these organisms, as well as Ferroplasma type I and II, reveal that all are facultative aerobic heterotrophs with the ability to use many of the same carbon substrates, including methanol. Most of the genomes share genes for toxic metal resistance and surface-layer production. Only Aplasma and Eplasma have a full suite of flagellar genes whereas all but the Ferroplasma spp. have genes for pili production. Cryogenic-electron microscopy (cryo-EM) and tomography (cryo-ET) strengthen these metagenomics-based ultrastructural predictions. Notably, only Aplasma, Gplasma and the Ferroplasma spp. have predicted iron oxidation genes and Eplasma and Iplasma lack most genes for cobalamin, valine, (iso)leucine and histidine synthesis. Conclusion The Thermoplasmatales AMD archaea share a large number of metabolic capabilities. All of the uncultivated organisms studied here (A-, E-, G-, and Iplasma) are metabolically very similar to characterized Ferroplasma spp., differentiating themselves mainly in their genetic capabilities for biosynthesis, motility, and possibly iron oxidation. These results indicate that subtle, but important genomic differences, coupled with unknown differences in gene expression, distinguish these organisms enough to allow for co-existence. Overall this study reveals shared features of organisms from the Thermoplasmatales lineage and provides new insights into the functioning of AMD communities.

Deeply sampled community genomic (metagenomic) datasets enable comprehensive analysis of heterogeneity in natural microbial populations. In this study, we used sequence data obtained from the dominant member of a low-diversity natural chemoautotrophic microbial community to determine how coexisting closely related individuals differ from each other in terms of gene sequence and gene content, and to uncover evidence of evolutionary processes that occur over short timescales. DNA sequence obtained from an acid mine drainage biofilm was reconstructed, taking into account the effects of strain variation, to generate a nearly complete genome tiling path for a Leptospirillum group II species closely related to L. ferriphilum (sampling depth ∼20×). The population is dominated by one sequence type, yet we detected evidence for relatively abundant variants (>99.5% sequence identity to the dominant type) at multiple loci, and a few rare variants. Blocks of other Leptospirillum group II types (∼94% sequence identity) have recombined into one or more variants. Variant blocks of both types are more numerous near the origin of replication. Heterogeneity in genetic potential within the population arises from localized variation in gene content, typically focused in integrated plasmid/phage-like regions. Some laterally transferred gene blocks encode physiologically important genes, including quorum-sensing genes of the LuxIR system. Overall, results suggest inter- and intrapopulation genetic exchange involving distinct parental genome types and implicate gain and loss of phage and plasmid genes in recent evolution of this Leptospirillum group II population. Population genetic analyses of single nucleotide polymorphisms indicate variation between closely related strains is not maintained by positive selection, suggesting that these regions do not represent adaptive differences between strains. Thus, the most likely explanation for the observed patterns of polymorphism is divergence of ancestral strains due to geographic isolation, followed by mixing and subsequent recombination.

Our current knowledge about nucleocytoplasmic large DNA viruses (NCLDVs) is largely derived from viral isolates that are co-cultivated with protists and algae. Here we reconstructed 2,074 NCLDV genomes from sampling sites across the globe by building on the rapidly increasing amount of publicly available metagenome data. This led to an 11-fold increase in phylogenetic diversity and a parallel 10-fold expansion in functional diversity. Analysis of 58,023 major capsid proteins from large and giant viruses using metagenomic data revealed the global distribution patterns and cosmopolitan nature of these viruses. The discovered viral genomes encoded a wide range of proteins with putative roles in photosynthesis and diverse substrate transport processes, indicating that host reprogramming is probably a common strategy in the NCLDVs. Furthermore, inferences of horizontal gene transfer connected viral lineages to diverse eukaryotic hosts. We anticipate that the global diversity of NCLDVs that we describe here will establish giant viruses-which are associated with most major eukaryotic lineages-as important players in ecosystems across Earth's biomes.

Well-studied innate immune systems exist throughout bacteria and archaea, but a more recently discovered genomic locus may offer prokaryotes surprising immunological adaptability. Mediated by a cassette-like genomic locus termed Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR), the microbial adaptive immune system differs from its eukaryotic immune analogues by incorporating new immunities unidirectionally. CRISPR thus stores genomically recoverable timelines of virus-host coevolution in natural organisms refractory to laboratory cultivation. Here we combined a population genetic mathematical model of CRISPR-virus coevolution with six years of metagenomic sequencing to link the recoverable genomic dynamics of CRISPR loci to the unknown population dynamics of virus and host in natural communities. Metagenomic reconstructions in an acid-mine drainage system document CRISPR loci conserving ancestral immune elements to the base-pair across thousands of microbial generations. This 'trailer-end conservation' occurs despite rapid viral mutation and despite rapid prokaryotic genomic deletion. The trailer-ends of many reconstructed CRISPR loci are also largely identical across a population. 'Trailer-end clonality' occurs despite predictions of host immunological diversity due to negative frequency dependent selection (kill the winner dynamics). Statistical clustering and model simulations explain this lack of diversity by capturing rapid selective sweeps by highly immune CRISPR lineages. Potentially explaining 'trailer-end conservation,' we record the first example of a viral bloom overwhelming a CRISPR system. The polyclonal viruses bloom even though they share sequences previously targeted by host CRISPR loci. Simulations show how increasing random genomic deletions in CRISPR loci purges immunological controls on long-lived viral sequences, allowing polyclonal viruses to bloom and depressing host fitness. Our results thus link documented patterns of genomic conservation in CRISPR loci to an evolutionary advantage against persistent viruses. By maintaining old immunities, selection may be tuning CRISPR-mediated immunity against viruses reemerging from lysogeny or migration.