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Background Glacier ice archives information, including microbiology, that helps reveal paleoclimate histories and predict future climate change. Though glacier-ice microbes are studied using culture or amplicon approaches, more challenging metagenomic approaches, which provide access to functional, genome-resolved information and viruses, are under-utilized, partly due to low biomass and potential contamination. Results We expand existing clean sampling procedures using controlled artificial ice-core experiments and adapted previously established low-biomass metagenomic approaches to study glacier-ice viruses. Controlled sampling experiments drastically reduced mock contaminants including bacteria, viruses, and free DNA to background levels. Amplicon sequencing from eight depths of two Tibetan Plateau ice cores revealed common glacier-ice lineages including Janthinobacterium , Polaromonas , Herminiimonas , Flavobacterium , Sphingomonas , and Methylobacterium as the dominant genera, while microbial communities were significantly different between two ice cores, associating with different climate conditions during deposition. Separately, ~355- and ~14,400-year-old ice were subject to viral enrichment and low-input quantitative sequencing, yielding genomic sequences for 33 vOTUs. These were virtually all unique to this study, representing 28 novel genera and not a single species shared with 225 environmentally diverse viromes. Further, 42.4% of the vOTUs were identifiable temperate, which is significantly higher than that in gut, soil, and marine viromes, and indicates that temperate phages are possibly favored in glacier-ice environments before being frozen. In silico host predictions linked 18 vOTUs to co-occurring abundant bacteria ( Methylobacterium , Sphingomonas , and Janthinobacterium ), indicating that these phages infected ice-abundant bacterial groups before being archived. Functional genome annotation revealed four virus-encoded auxiliary metabolic genes, particularly two motility genes suggest viruses potentially facilitate nutrient acquisition for their hosts. Finally, given their possible importance to methane cycling in ice, we focused on Methylobacterium viruses by contextualizing our ice-observed viruses against 123 viromes and prophages extracted from 131 Methylobacterium genomes, revealing that the archived viruses might originate from soil or plants. Conclusions Together, these efforts further microbial and viral sampling procedures for glacier ice and provide a first window into viral communities and functions in ancient glacier environments. Such methods and datasets can potentially enable researchers to contextualize new discoveries and begin to incorporate glacier-ice microbes and their viruses relative to past and present climate change in geographically diverse regions globally. 8eoz6b1Gq7e8M2dM_SBXdy Video Abstract

Dominant microorganisms of the Sargasso Sea are key drivers of the global carbon cycle. However, associated viruses that shape microbial community structure and function are not well characterised. Here, we combined short and long read sequencing to survey Sargasso Sea phage communities in virus- and cellular fractions at viral maximum (80 m) and mesopelagic (200 m) depths. We identified 2,301 Sargasso Sea phage populations from 186 genera. Over half of the phage populations identified here lacked representation in global ocean viral metagenomes, whilst 177 of the 186 identified genera lacked representation in genomic databases of phage isolates. Viral fraction and cell-associated viral communities were decoupled, indicating viral turnover occurred across periods longer than the sampling period of three days. Inclusion of long-read data was critical for capturing the breadth of viral diversity. Phage isolates that infect the dominant bacterial taxa Prochlorococcus and Pelagibacter , usually regarded as cosmopolitan and abundant, were poorly represented. The Sargasso Sea is a natural laboratory for understanding future conditions of warmer oceans and associated nutrient limitation. Here, the authors combined short- and long-read sequencing to survey Sargasso Sea viral communities.

Ocean microbes contribute to biogeochemical cycles and ecosystem function, but they do so under top-down pressure imposed by viruses. While viruses are increasingly understood spatially and beginning to be incorporated into predictive modeling, high-frequency ocean virus dynamics remain understudied due to methodological challenges. Here we sampled stratified Bermuda Atlantic Time Series (BATS) waters for 112 hours at sub-daily 4- (surface) or 12- (deep chlorophyll maximum) hour intervals, purified viral particles from these samples, sequenced their metagenomes, and used the resulting data to characterize high-frequency virus community dynamics. Aggregated community diversity metrics changed with depth, but were not statistically significant temporally at a fixed location. However, finer-scale population-level analyses revealed both depth and temporal change, including physicochemical depth-driven differences and, in surface waters, thousands of viral populations that exhibited statistically significant diel rhythms. Statistical analyses revealed three main archetypes of temporal dynamics that themselves differed in abundance patterns, host predictions, viral taxonomy, and gene functions. Among these, highlights include viruses resembling an archetype with a night peaking pattern in activity that include an over-representation of viruses that putatively infect Prochlorococcus , a phototrophic cyanobacteria. Together, these efforts provide baseline community- and population-scale short-time-frame observations relevant to future climate state modeling.

Background Prokaryotic microbes have impacted marine biogeochemical cycles for billions of years. Viruses also impact these cycles, through lysis, horizontal gene transfer, and encoding and expressing genes that contribute to metabolic reprogramming of prokaryotic cells. While this impact is difficult to quantify in nature, we hypothesized that it can be examined by surveying virus-encoded auxiliary metabolic genes (AMGs) and assessing their ecological context. Results We systematically developed a global ocean AMG catalog by integrating previously described and newly identified AMGs and then placed this catalog into ecological and metabolic contexts relevant to ocean biogeochemistry. From 7.6 terabases of Tara Oceans paired prokaryote- and virus-enriched metagenomic sequence data, we increased known ocean virus populations to 579,904 (up 16%). From these virus populations, we then conservatively identified 86,913 AMGs that grouped into 22,779 sequence-based gene clusters, 7248 (~ 32%) of which were not previously reported. Using our catalog and modeled data from mock communities, we estimate that ~ 19% of ocean virus populations carry at least one AMG. To understand AMGs in their metabolic context, we identified 340 metabolic pathways encoded by ocean microbes and showed that AMGs map to 128 of them. Furthermore, we identified metabolic “hot spots” targeted by virus AMGs, including nine pathways where most steps (≥ 0.75) were AMG-targeted (involved in carbohydrate, amino acid, fatty acid, and nucleotide metabolism), as well as other pathways where virus-encoded AMGs outnumbered cellular homologs (involved in lipid A phosphates, phosphatidylethanolamine, creatine biosynthesis, phosphoribosylamine-glycine ligase, and carbamoyl-phosphate synthase pathways). Conclusions Together, this systematically curated, global ocean AMG catalog and analyses provide a valuable resource and foundational observations to understand the role of viruses in modulating global ocean metabolisms and their biogeochemical implications. 7DrB1a6JQbvrw3a2P4Hm3d Video Abstract

Viruses impact microbial diversity, gene flow and function through virus–host interactions. Although metagenomics surveys are rapidly cataloguing viral diversity, methods are needed to capture specific virus–host interactions in situ. Here, we leveraged metagenomics and repurposed emulsion paired isolation-concatenation PCR (epicPCR) to investigate viral diversity and virus–host interactions in situ over time in an estuarine environment. The method fuses a phage marker, the ribonucleotide reductase gene, with the host 16S rRNA gene of infected bacterial cells within emulsion droplets providing single-cell resolution for dozens of samples. EpicPCR captured in situ virus–host interactions for viral clades with no closely related database representatives. Abundant freshwater Actinobacteria lineages, in particular Rhodoluna sp., were the most common hosts for these poorly characterized viruses, with interactions correlated with environmental factors. Multiple methods used to identify virus–host interactions, including epicPCR, identified different and largely non-overlapping interactions within the vast virus–host interaction space. Tracking virus–host interaction dynamics also revealed that multi-host viruses had significantly longer periods with observed virus–host interactions, whereas single-host viruses were observed interacting with hosts at lower minimum abundances, suggesting more efficient interactions. Capturing in situ interactions with epicPCR revealed environmental and ecological factors shaping virus–host interactions, highlighting epicPCR as a valuable technique in viral ecology. Using epicPCR, a method that fuses a phage marker gene with the 16S rRNA gene of infected bacterial cells at single-cell resolution, the authors identify host–virus interactions and dynamics over time in an estuarine environment.

Microbes are engines of ocean biogeochemical processes. Viruses influence and shape microbial communities via lysis, horizontal gene transfer, and metabolic reprogramming. Viral lysis facilitates the export of carbon from the surface into the deep ocean via aggregates of sinking particles. In fact, they outperform prokaryotes and eukaryotes as the strong predictor for carbon fluxes in the oligotrophic ocean. Viruses also impact the gene flow of their hosts, and the genes transferred from virus-host interactions can be fixed in viral genomes. Viruses are known to carry and express host-derived auxiliary metabolic genes (AMGs) that directly reprogram metabolisms within virus-infected cells, termed virocells. However, viral communities are poorly characterized in the oligotrophic ocean, and their AMG-driven metabolic reprogramming lacks systematic descriptions from the global oceans.The Sargasso Sea is highly stratified and nutrient-depleted each year in the summer months. This seasonal pattern makes the Sargasso Sea one of the ideal model ecosystems to study oligotrophic oceans. In the Sargasso Sea, abundance of viral-like particles has seasonal and depth-associated structuring patterns. Here, to better survey the Sargasso Sea viruses, we apply sequencing approaches to characterize viral communities via metagenomics and uncover their biogeographical and ecological structures locally and globally in the ocean. As described in Chapter 2, comparison with global viral metagenomics revealed that Sargasso Sea viruses were similar across warm oligotrophic oceanic regions but not represented globally. They form discrete populations in the viral and cellular fractions at the viral maximum (80m) and mesopelagic (200m) depths. Inclusion of long-read data captured 1,257 viral genomes in addition to the 1,044 viral genomes derived from short-read assemblies, resulting in the identification of ecologically important and microdiverse viral genomes.Having established local viral community patterns at local geographical areas, we next leveraged on 7.6 terabases of sequencing to study viral AMG-driven metabolic reprogramming throughout global oceans. Although AMGs are now known to directly reprogram photosynthesis, carbon metabolism, and nutrient cycling in the oceans, approaches to identify bona fide AMGs (not just metabolic genes on cellular contigs) and best annotate AMGs lack standards and scalability. Here, leveraging global ocean sampling efforts enabled by Tara Oceans expedition and recent analytic improvements, we seek to systematically survey AMGs in viral genomes to establish a global ocean AMG catalog. Results from this analysis are described in Chapter 3 where we expanded known ocean viral populations to 579,904 (up 16%) and from these viral populations, we identified 22,779 AMGs with 32% of AMGs reported for the first time. Estimation from observed AMG frequencies and simulated mock community predicted that 19% of ocean viral populations could encode at least one AMG. Metabolically, these AMGs mapped to 128 out of 340 metabolic pathways present in ocean microbes. We focused on nine pathways where most steps (≥0.75) were AMG-targeted, identified as metabolic `hot spots? and at a high level associated with carbohydrate, amino acid, fatty acid and nucleotide metabolisms.With a global ocean AMG catalog now in-hand, we next sought to apply a statistical modeling framework to quantitatively estimate community-level metabolic properties and biogeochemical impacts of marine viruses in Chapter 4. With a supra-organism assumption that treated each collection of marine microbes within a single metagenome as a single entity, we established genome-scale metabolic models from the metagenomic and metatranscriptomic profiling of prokaryote- and virus-enriched samples. This revealed ~5K reactions across the global oceans with an average of ~4.7K reactions from any given water sample and 99% of the reactions being expressed. These reactions captured global ocean ecological patterns, with their importance within each network quantified via a synergetic score. The synergism versus autonomy of each marine ecosystem was subsequently identified. This revealed that synergetic metabolic activities were in concordance with taxonomic diversity and the Redfield ratios associated with carbon and nitrogen, but not phosphate, due to the lack of autotrophy in the models. Given that metabolic synergy ranks showed strong correlations with lyase activity, we evaluated the role of viruses within the metabolic networks and found significant associations of AMGs with important reactions involved in purine, pyrimidine, and one-carbon metabolisms.Together, these findings present an extensive expansion of our current understanding of marine viral communities in the oligotrophic ocean, their metabolic reprogramming potential through AMGs globally, and the contribution of viruses within a statistical modeling framework via AMGs, thus providing valuable insights into the role of viruses in biogeochemistry.

Funding was provided by the National Science Foundation (awards ABI#1759874, ABI#2149505, OCE#1536989, OCE#1829831, and OCE#2019589) and a Gordon and Betty Moore Foundation Investigator Award (#3790) to MBS and by the Natural Sciences and Engineering Research Council (NSERC) of Canada, the Canada Foundation for Innovation (CFI), and the G. Unger Vetlesen and Ambrose Monell Foundations to SJH. Bioinformatics analysis was supported by Ohio Supercomputer Center.

The lung is a unique immunological niche with diverse immune cell types. The effects of stimulation through innate and adaptive immune receptors on human lung immune cells has largely been extrapolated from studies of blood immune cells. While multiple immune cell types and many genes have been implicated as contributing to asthma, the dynamics of these in human lung immune cells following activation will yield insights into asthma pathogenesis and lung immunity more broadly. Human lung immune cells from 6 donors were isolated. Mixed leukocytes were treated separately with lipopolysaccharide (LPS), F(ab)2-anti-human-IgM/IgG + IL4 and anti-CD3/CD28 for 4 and 18 hours and underwent single cell RNA sequencing (scRNAseq). Lung immune cell types were annotated, and gene expression compared across conditions. Genes at prior asthma-associated genetic loci were characterized across cell types, treatments and timepoints. Expression of non-classical class II genes associated with asthma, HLA-DQA2 and HLA-DQB2, and their protein products was characterized with immunohistochemistry. We characterized gene expression in 116,697 lung immune cells. Cell-, treatment-, and timepoint-specific effects on gene expression were detected in all lung immune cell populations. Correlation of gene expression between lung and blood lymphocyte populations decreased following stimulation. Among the genes that were differentially expressed, 97 receptor:ligand pairs had changes with treatments. 96.0% of genes at asthma risk loci demonstrated differential expression in at least one cell type and at least one treatment. B cells were the cell type with the highest expression of HLA-DQA2 and HLA-DQB2 which increased with anti-IgM/IgG treatment and the HLA-DQB2 protein was identified in lung B cells from a donor with asthma. Human lung immune activation elicits a broad range of cellular responses that deviate from those of blood immune cells and are relevant to asthma. Lung B cells expressing HLA-DQA2 and HLA-DQB2 appear to be involved in a novel antigen presentation pathway that contributes to asthma risk.

Ocean microbes contribute to biogeochemical cycles and ecosystem function, but they do so under top-down pressure imposed by viruses. While viruses are increasingly understood spatially and beginning to be incorporated into predictive modeling, high-frequency ocean virus dynamics remain understudied due to methodological challenges. Here we sampled stratified Bermuda Atlantic Time Series (BATS) waters for 112 hours at sub-daily 4-(surface) or 12-(deep chlorophyll maximum) hour intervals, purified viral particles from these samples, sequenced their metagenomes, and used the resulting data to characterize high-frequency virus community dynamics. Aggregated community diversity metrics changed with depth, but were not statistically significant temporally at a fixed location. However, finer-scale population-level analyses revealed both depth and temporal change, including physicochemical depth-driven differences and, in surface waters, thousands of viral populations that exhibited statistically significant diel rhythms. Statistical analyses revealed three main archetypes of temporal dynamics that themselves differed in abundance patterns, host predictions, viral taxonomy, and gene functions. Among these, highlights include viruses resembling an archetype with a night peaking pattern in activity that include an over-representation of viruses that putatively infect Prochlorococcus, a phototrophic cyanobacteria. Together, these efforts provide baseline community-and population-scale short-time-frame observations relevant to future climate state modeling.

The oceans buffer against climate change via biogeochemical cycles underpinned by microbial metabolic networks. While planetary-scale surveys provide baseline microbiome data, inferring metabolic and biogeochemical impacts remains challenging. Here, we constructed a metabolic model for each TARA Ocean metagenome or metatranscriptome, quantified the importance of each metabolic reaction, and used this to assess planetary-scale heterotrophic prokaryotic metabolic phenotypes as a proxy for marine biogeochemistry. This revealed metabolism-inferred ecological zones that matched taxonomy- and function-inferred ones, connections between microbial metabolism and diversity, and predictions about long-sought virus ecological roles, including that virus-encoded metabolic genes target important reactions and identify viral shuntor shuttle-enriched ocean regions. Together, this framework is agile and resolves planetary-scale community metabolic features to better incorporate microbes and viruses into future predictive ecosystem and climate models.Competing Interest StatementSJH has a conflict of interest; he is a co-founder of Koonkie Inc., a bioinformatics consulting company that designs and provides scalable algorithmic and data analytics solutions in the cloud.