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Deciphering the relationship between a gene and its genomic context is fundamental to understanding and engineering biological systems. Machine learning has shown promise in learning latent relationships underlying the sequence-structure-function paradigm from massive protein sequence datasets. However, to date, limited attempts have been made in extending this continuum to include higher order genomic context information. Evolutionary processes dictate the specificity of genomic contexts in which a gene is found across phylogenetic distances, and these emergent genomic patterns can be leveraged to uncover functional relationships between gene products. Here, we train a genomic language model (gLM) on millions of metagenomic scaffolds to learn the latent functional and regulatory relationships between genes. gLM learns contextualized protein embeddings that capture the genomic context as well as the protein sequence itself, and encode biologically meaningful and functionally relevant information (e.g. enzymatic function, taxonomy). Our analysis of the attention patterns demonstrates that gLM is learning co-regulated functional modules (i.e. operons). Our findings illustrate that gLM’s unsupervised deep learning of the metagenomic corpus is an effective and promising approach to encode functional semantics and regulatory syntax of genes in their genomic contexts and uncover complex relationships between genes in a genomic region.

 

Iron is one of the Earth's most abundant elements and is required for essentially all forms of life. Yet, iron's reactivity with oxygen and poor solubility in its oxidized form (Fe3+) mean that it is often a limiting nutrient in oxic, near-neutral pH environments like Earth's ocean. In addition to being a vital nutrient, there is a diversity of aerobic organisms that oxidize ferrous iron (Fe2+) to harness energy for growth and biosynthesis. Accordingly, these organisms rely on access to co-existing Fe2+ and O2 to survive. It is generally presumed that such aerobic iron-oxidizing bacteria (FeOB) are relegated to low-oxygen regimes where abiotic iron oxidation rates are slower, yet some FeOB live in higher oxygen environments where they cannot rely on lower oxygen concentrations to overcome abiotic competition. We hypothesized that FeOB chemically alter their environment to limit abiotic interactions between Fe2+ and O2. To test this, we incubated the secreted metabolites (collectively known as the exometabolome) of the deep-sea iron- and hydrogen-oxidizing bacterium Ghiorsea bivora TAG-1 with ferrous iron and oxygen. We found that this FeOB's iron-oxidizing exometabolome markedly impedes the abiotic oxidation of ferrous iron, increasing the half-life of Fe2+ 100-fold from ∼3 to ∼335 days in the presence of O2, while the exometabolome of TAG-1 grown on hydrogen had no effect. Moreover, the few precipitates that formed in the presence of TAG-1's iron-oxidizing exometabolome were poorly crystalline, compared with the abundant iron particles that mineralized in the absence of abiotic controls. We offer an initial exploration of TAG-1's iron-oxidizing exometabolome and discuss potential key contributors to this process. Overall, our findings demonstrate that the exometabolome as a whole leads to a sustained accumulation of ferrous iron in the presence of oxygen, consequently altering the redox equilibrium. This previously unknown adaptation likely enables these microorganisms to persist in an iron-oxidizing and iron-precipitating world and could have impacts on the bioavailability of iron to FeOB and other life in iron-limiting environments.

 

We assessed the relationship between rates of biological energy utilization and the biomass sustained by that energy utilization, at both the organism and biosphere level. We compiled a dataset comprising >10,000 basal, field, and maximum metabolic rate measurements made on >2,900 individual species, and, in parallel, we quantified rates of energy utilization, on a biomass-normalized basis, by the global biosphere and by its major marine and terrestrial components. The organism-level data, which are dominated by animal species, have a geometric mean among basal metabolic rates of 0.012 W (g C)⁻¹and an overall range of more than six orders of magnitude. The biosphere as a whole uses energy at an average rate of 0.005 W (g C)⁻¹but exhibits a five order of magnitude range among its components, from 0.00002 W (g C)⁻¹for global marine subsurface sediments to 2.3 W (g C)⁻¹for global marine primary producers. While the average is set primarily by plants and microorganisms, and by the impact of humanity upon those populations, the extremes reflect systems populated almost exclusively by microbes. Mass-normalized energy utilization rates correlate strongly with rates of biomass carbon turnover. Based on our estimates of energy utilization rates in the biosphere, this correlation predicts global mean biomass carbon turnover rates of ~2.3 y⁻¹for terrestrial soil biota, ~8.5 y⁻¹for marine water column biota, and ~1.0 y⁻¹and ~0.01 y⁻¹for marine sediment biota in the 0 to 0.1 m and >0.1 m depth intervals, respectively.

 

Many microbes in nature reside in dense, metabolically interdependent communities. We investigated the nature and extent of microbe-virus interactions in relation to microbial density and syntrophy by examining microbe-virus interactions in a biomass dense, deep-sea hydrothermal mat. Using metagenomic sequencing, we find numerous instances where phylogenetically distant (up to domain level) microbes encode CRISPR-based immunity against the same viruses in the mat. Evidence of viral interactions with hosts cross-cutting microbial domains is particularly striking between known syntrophic partners, for example those engaged in anaerobic methanotrophy. These patterns are corroborated by proximity-ligation-based (Hi-C) inference. Surveys of public datasets reveal additional viruses interacting with hosts across domains in diverse ecosystems known to harbour syntrophic biofilms. We propose that the entry of viral particles and/or DNA to non-primary host cells may be a common phenomenon in densely populated ecosystems, with eco-evolutionary implications for syntrophic microbes and CRISPR-mediated inter-population augmentation of resilience against viruses.

 

ABSTRACT Some marine microbes are seemingly “ubiquitous,” thriving across a wide range of environmental conditions. While the increased depth in metagenomic sequencing has led to a growing body of research on within-population heterogeneity in environmental microbial populations, there have been fewer systematic comparisons and characterizations of population-level genetic diversity over broader expanses of time and space. Here, we investigated the factors that govern the diversification of ubiquitous microbial taxa found within and between ocean basins. Specifically, we use mapped metagenomic paired reads to examine the genetic diversity of ammonia-oxidizing archaeal (“ Candidatus Nitrosopelagicus brevis”) populations in the Pacific (Hawaii Ocean Time-series [HOT]) and Atlantic (Bermuda Atlantic Time Series [BATS]) Oceans sampled over 2 years. We observed higher nucleotide diversity in “ Ca. N. brevis” at HOT, driven by a higher rate of homologous recombination. In contrast, “ Ca. N. brevis” at BATS featured a more open pangenome with a larger set of genes that were specific to BATS, suggesting a history of dynamic gene gain and loss events. Furthermore, we identified highly differentiated genes that were regulatory in function, some of which exhibited evidence of recent selective sweeps. These findings indicate that different modes of genetic diversification likely incur specific adaptive advantages depending on the selective pressures that they are under. Within-population diversity generated by the environment-specific strategies of genetic diversification is likely key to the ecological success of “ Ca. N. brevis.” IMPORTANCE Ammonia-oxidizing archaea (AOA) are one of the most abundant chemolithoautotrophic microbes in the marine water column and are major contributors to global carbon and nitrogen cycling. Despite their ecological importance and geographical pervasiveness, there have been limited systematic comparisons and characterizations of their population-level genetic diversity over time and space. Here, we use metagenomic time series from two ocean observatories to address the fundamental questions of how abiotic and biotic factors shape the population-level genetic diversity and how natural microbial populations adapt across diverse habitats. We show that the marine AOA “ Candidatus Nitrosopelagicus brevis” in different ocean basins exhibits distinct modes of genetic diversification in response to their selective regimes shaped by nutrient availability and patterns of environmental fluctuations. Our findings specific to “ Ca. N. brevis” have broader implications, particularly in understanding the population-level responses to the changing climate and predicting its impact on biogeochemical cycles. 

Seafloor hydrothermalism plays a critical role in fundamental interactions between geochemical and biological processes in the deep ocean. A significant number of hydrothermal vents are hypothesized to exist, but many of these remain undiscovered due in part to the difficulty of detecting hydrothermalism using standard sensors on rosettes towed in the water column or robotic platforms performing surveys. Here, we use in situ methane sensors to complement standard sensing technology for hydrothermalism discovery and compare sensors on a towed rosette and an autonomous underwater vehicle (AUV) during a 17 km long transect in the Northern Guaymas Basin in the Gulf of California. This transect spatially intersected with a known hydrothermally active venting site. These data show that methane signalled possible hydrothermal-activity 1.5–3 km laterally (100–150 m vertically) from a known vent. Methane as a signal for hydrothermalism performed similarly to standard turbidity sensors (plume detection 2.2–3.3 km from reference source), and more sensitively and clearly than temperature, salinity, and oxygen instruments which readily respond to physical mixing in background seawater. We additionally introduce change-point detection algorithms—streaming cross-correlation and regime identification—as a means of real-time hydrothermalism discovery and discuss related data supervision technologies that could be used in planning, executing, and monitoring explorative surveys for hydrothermalism. 

ABSTRACT Genome and proteome data predict the presence of both the reductive citric acid cycle (rCAC; also called the reductive tricarboxylic acid cycle) and the Calvin-Benson-Bassham cycle (CBB) in “ Candidatus Endoriftia persephonae,” the autotrophic sulfur-oxidizing bacterial endosymbiont from the giant hydrothermal vent tubeworm Riftia pachyptila . We tested whether these cycles were differentially induced by sulfide supply, since the synthesis of biosynthetic intermediates by the rCAC is less energetically expensive than that by the CBB. R. pachyptila was incubated under in situ conditions in high-pressure aquaria under low (28 to 40 μmol · h −1 ) or high (180 to 276 μmol · h −1 ) rates of sulfide supply. Symbiont-bearing trophosome samples excised from R. pachyptila maintained under the two conditions were capable of similar rates of CO 2 fixation. Activities of the rCAC enzyme ATP-dependent citrate lyase (ACL) and the CBB enzyme 1,3-bisphosphate carboxylase/oxygenase (RubisCO) did not differ between the two conditions, although transcript abundances for ATP-dependent citrate lyase were 4- to 5-fold higher under low-sulfide conditions. δ 13 C values of internal dissolved inorganic carbon (DIC) pools were varied and did not correlate with sulfide supply rate. In samples taken from freshly collected R. pachyptila , δ 13 C values of lipids fell between those collected for organisms using either the rCAC or the CBB exclusively. These observations are consistent with cooccurring activities of the rCAC and the CBB in this symbiosis. IMPORTANCE Previous to this study, the activities of the rCAC and CBB in R. pachyptila had largely been inferred from “omics” studies of R. pachyptila without direct assessment of in situ conditions prior to collection. In this study, R. pachyptila was maintained and monitored in high-pressure aquaria prior to measuring its CO 2 fixation parameters. Results suggest that ranges in sulfide concentrations similar to those experienced in situ do not exert a strong influence on the relative activities of the rCAC and the CBB. This observation highlights the importance of further study of this symbiosis and other organisms with multiple CO 2 -fixing pathways, which recent genomics and biochemical studies suggest are likely to be more prevalent than anticipated.