IMG/M v.5.0: an integrated data management and comparative analysis system for microbial genomes and microbiomes

HiOmics: A cloud-based one-stop platform for the comprehensive analysis of large-scale omics data

Analyzing the vast amount of omics data generated comprehensively by high-throughput sequencing technology is of utmost importance for scientists. In this context, we propose HiOmics, a cloud-based platform equipped with nearly 300 plugins designed for the comprehensive analysis and visualization of omics data. HiOmics utilizes the Element Plus framework to craft a user-friendly interface and harnesses Docker container technology to ensure the reliability and reproducibility of data analysis results. Furthermore, HiOmics employs the Workflow Description Language and Cromwell engine to construct workflows, ensuring the portability of data analysis and simplifying the examination of intricate data. Additionally, HiOmics has developed DataCheck, a tool based on Golang, which verifies and converts data formats. Finally, by leveraging the object storage technology and batch computing capabilities of public cloud platforms, HiOmics enables the storage and processing of large-scale data while maintaining resource independence among users.

Visualizing metagenomic and metatranscriptomic data: A comprehensive review

The fields of Metagenomics and Metatranscriptomics involve the examination of complete nucleotide sequences, gene identification, and analysis of potential biological functions within diverse organisms or environmental samples. Despite the vast opportunities for discovery in metagenomics, the sheer volume and complexity of sequence data often present challenges in processing analysis and visualization. This article highlights the critical role of advanced visualization tools in enabling effective exploration, querying, and analysis of these complex datasets. Emphasizing the importance of accessibility, the article categorizes various visualizers based on their intended applications and highlights their utility in empowering bioinformaticians and non-bioinformaticians to interpret and derive insights from meta-omics data effectively.

Seven genome sequences of airborne, bacterial isolates from Antarctica

Ice-covered and remote landscapes in the McMurdo Dry Valleys, Antarctica, are likely seeded by aeolian transport of biological material from ice-free local or distant environments. Here, we report the genome sequences of seven bacteria isolated from aerosols collected on top of two dry valley glaciers.

Identification of type VI secretion system effector-immunity pairs using structural bioinformatics

The type VI secretion system (T6SS) is an important mediator of microbe-microbe and microbe-host interactions. Gram-negative bacteria use the T6SS to inject T6SS effectors (T6Es), which are usually proteins with toxic activity, into neighboring cells. Antibacterial effectors have cognate immunity proteins that neutralize self-intoxication. Here, we applied novel structural bioinformatic tools to perform systematic discovery and functional annotation of T6Es and their cognate immunity proteins from a dataset of 17,920 T6SS-encoding bacterial genomes. Using structural clustering, we identified 517 putative T6E families, outperforming sequence-based clustering. We developed a logistic regression model to reliably quantify protein-protein interaction of new T6E-immunity pairs, yielding candidate immunity proteins for 231 out of the 517 T6E families. We used sensitive structure-based annotation which yielded functional annotations for 51% of the T6E families, again outperforming sequence-based annotation. Next, we validated four novel T6E-immunity pairs using basic experiments in E. coli. In particular, we showed that the Pfam domain DUF3289 is a homolog of Colicin M and that DUF943 acts as its cognate immunity protein. Furthermore, we discovered a novel T6E that is a structural homolog of SleB, a lytic transglycosylase, and identified a specific glutamate that acts as its putative catalytic residue. Overall, this study applies novel structural bioinformatic tools to T6E-immunity pair discovery, and provides an extensive database of annotated T6E-immunity pairs.

Protein family annotation for the Unified Human Gastrointestinal Proteome by DPCfam clustering

Technological advances in massively parallel sequencing have led to an exponential growth in the number of known protein sequences. Much of this growth originates from metagenomic projects producing new sequences from environmental and clinical samples. The Unified Human Gastrointestinal Proteome (UHGP) catalogue is one of the most relevant metagenomic datasets with applications ranging from medicine to biology. However, the low levels of sequence annotation may impair its usability. This work aims to produce a family classification of UHGP sequences to facilitate downstream structural and functional annotation. This is achieved through the release of the DPCfam-UHGP50 dataset containing 10,778 putative protein families generated using DPCfam clustering, an unsupervised pipeline grouping sequences into single or multi-domain architectures. DPCfam-UHGP50 considerably improves family coverage at protein and residue levels compared to the manually curated repository Pfam. In the hope that DPCfam-UHGP50 will foster future discoveries in the field of metagenomics of the human gut, we release a FAIR-compliant database of our results that is easily accessible via a searchable web server and Zenodo repository.

Engineering natural microbiomes toward enhanced bioremediation by microbiome modeling

Engineering natural microbiomes for biotechnological applications remains challenging, as metabolic interactions within microbiomes are largely unknown, and practical principles and tools for microbiome engineering are still lacking. Here, we present a combinatory top-down and bottom-up framework to engineer natural microbiomes for the construction of function-enhanced synthetic microbiomes. We show that application of herbicide and herbicide-degrader inoculation drives a convergent succession of different natural microbiomes toward functional microbiomes (e.g., enhanced bioremediation of herbicide-contaminated soils). We develop a metabolic modeling pipeline, SuperCC, that can be used to document metabolic interactions within microbiomes and to simulate the performances of different microbiomes. Using SuperCC, we construct bioremediation-enhanced synthetic microbiomes based on 18 keystone species identified from natural microbiomes. Our results highlight the importance of metabolic interactions in shaping microbiome functions and provide practical guidance for engineering natural microbiomes.

The macroecology of butyrate-producing bacteria via metagenomic assessment of butyrate production capacity

Butyrate-producing bacteria are found in many outdoor ecosystems and host organisms, including humans, and are vital to ecosystem functionality and human health. These bacteria ferment organic matter, producing the short-chain fatty acid butyrate. However, the macroecological influences on their biogeographical distribution remain poorly resolved. Here we aimed to characterise their global distribution together with key explanatory climatic, geographical and physicochemical variables. We developed new normalised butyrate production capacity (BPC) indices derived from global metagenomic (n = 13,078) and Australia-wide soil 16S rRNA (n = 1331) data, using Geographic Information System (GIS) and modelling techniques to detail their ecological and biogeographical associations. The highest median BPC scores were found in anoxic and fermentative environments, including the human (BPC = 2.99) and non-human animal gut (BPC = 2.91), and in some plant-soil systems (BPC = 2.33). Within plant-soil systems, roots (BPC = 2.50) and rhizospheres (BPC = 2.34) had the highest median BPC scores. Among soil samples, geographical and climatic variables had the strongest overall effects on BPC scores (variable importance score range = 0.30-0.03), with human population density also making a notable contribution (variable importance score = 0.20). Higher BPC scores were in soils from seasonally productive sandy rangelands, temperate rural residential areas and sites with moderate-to-high soil iron concentrations. Abundances of butyrate-producing bacteria in outdoor soils followed complex ecological patterns influenced by geography, climate, soil chemistry and hydrological fluctuations. These new macroecological insights further our understanding of the ecological patterns of outdoor butyrate-producing bacteria, with implications for emerging microbially focused ecological and human health policies.

MmcA is an electron conduit that facilitates both intracellular and extracellular electron transport in Methanosarcina acetivorans

Methanogens are a diverse group of Archaea that obligately couple energy conservation to the production of methane. Some methanogens encode alternate pathways for energy conservation, like anaerobic respiration, but the biochemical details of this process are unknown. We show that a multiheme c-type cytochrome called MmcA from Methanosarcina acetivorans is important for intracellular electron transport during methanogenesis and can also reduce extracellular electron acceptors like soluble Fe3+ and anthraquinone-2,6-disulfonate. Consistent with these observations, MmcA displays reversible redox features ranging from -100 to -450 mV versus SHE. Additionally, mutants lacking mmcA have significantly slower Fe3+ reduction rates. The mmcA locus is prevalent in members of the Order Methanosarcinales and is a part of a distinct clade of multiheme cytochromes that are closely related to octaheme tetrathionate reductases. Taken together, MmcA might act as an electron conduit that can potentially support a variety of energy conservation strategies that extend beyond methanogenesis.

Complete genome sequence of Methanosphaera sp. ISO3-F5, a rumen methylotrophic methanogen

Methanosphaera spp. are methylotrophic methanogenic archaea and members of the order Methanobacteriales with few cultured representatives. Methanosphaera sp. ISO3-F5 was isolated from sheep rumen contents in New Zealand. Here, we report its complete genome, consisting of a large chromosome and a megaplasmid (GenBank accession numbers CP118753 and CP118754, respectively).

Isolation of potentially novel species expands the genomic and functional diversity of Lachnospiraceae

The Lachnospiraceae family holds promise as a source of next-generation probiotics, yet a comprehensive delineation of its diversity is lacking, hampering the identification of suitable strains for future applications. To address this knowledge gap, we conducted an in-depth genomic and functional analysis of 1868 high-quality genomes, combining data from public databases with our new isolates. This data set represented 387 colonization-selective species-level clusters, of which eight genera represented multilineage clusters. Pan-genome analysis, single-nucleotide polymorphism (SNP) identification, and probiotic functional predictions revealed that species taxonomy, habitats, and geography together shape the functional diversity of Lachnospiraceae. Moreover, analyses of associations with atherosclerotic cardiovascular disease (ACVD) and inflammatory bowel disease (IBD) indicated that several strains of potentially novel Lachnospiraceae species possess the capacity to reduce the abundance of opportunistic pathogens, thereby imparting potential health benefits. Our findings shed light on the untapped potential of novel species enabling knowledge-based selection of strains for the development of next-generation probiotics holding promise for improving human health and disease management.

Methanooceanicella nereidis gen. nov., sp. nov., the first oceanic Methanocellaceae methanogen, isolated from potential methane hydrate bearing area offshore southwestern Taiwan

A novel mesophilic, hydrogenotrophic methanogen, strain CWC-04T, was obtained from a sediment sample extracted from a gravity core retrieved at station 22 within the KP-9 area off the southwestern coast of Taiwan during the ORIII-1368 cruise in 2009. Cells of strain CWC-04T were rod-shaped, 1.4-2.9 µm long by 0.5-0.6 µm wide, and occurred singly. Strain CWC-04Tutilized formate, H2/CO2, 2-propanol/CO2 or 2-butanol/CO2 as catabolic substrates. The optimal growth conditions were 42 °C, 0.17 M NaCl and pH 5.35. The genomic DNA G+C content calculated from the genome sequence of strain CWC-04T was 46.19 mol%. Phylogenetic analysis of 16S rRNA gene revealed that strain CWC-04T is affiliated with the genus Methanocella. The 16S rRNA gene sequences similarities within strains Methanocella arvoryzae MRE50T, Methanocella paludicola SANAET and Methanocella conradii HZ254T were 93.7, 93.0 and 91.3 %, respectively. In addition, the optical density of CWC-04T culture dropped abruptly upon entering the late-log growth phase, with virus-like particles (150 nm in diameter) being observed on and around the cells. This observation suggests that strain CWC-04T harbours a lytic virus. Based on these phenotypic, phylogenetic and genomic results, we propose that strain CWC-04T represents a novel species of a novel genus in the family Methanocellaceae, for which the name Methanooceanicella nereidis gen. nov., sp. nov. is proposed. The type strain is CWC-04T (=BCRC AR10050T=NBRC 113165T).

Pseudodesulfovibrio pelocollis sp. nov. a Sulfate-Reducing Bacterium Isolated from a Terrestrial Mud Volcano

Terrestrial mud volcanoes (TMVs), surface expressions of a deep-subterranean sedimentary volcanism, are widespread throughout the world. The methane and sulfur cycles are recognized as the most important biogeochemical cycles in these environments. Only few anaerobic bacterial strains were recovered from TMVs. We have isolated a novel sulfate-reducing bacterium (strain SB368T) from TMV located at Taman Peninsula, Russia. Optimum growth of strain SB368T was observed at 30 °C, pH 8.0 and 1% NaCl. Strain SB368T utilized lactate, pyruvate and fumarate in the presence of sulfate, sulfite or thiosulfate. Growth with molecular hydrogen was observed only in the presence of acetate. Fermentative growth occurred on pyruvate. Phylogenetic analysis revealed that strain SB368T belongs to the genus Pseudodesulfovibrio but is distinct from all described species. Based on its genomic and phenotypic properties, a new species, Pseudodesulfovibrio pelocollis sp. nov. is proposed with strain SB368T (= DSM 111087 T = VKM B-3585 T) as a type strain.

Comparative genomics reveals distinct diversification patterns among LysR-type transcriptional regulators in the ESKAPE pathogen Pseudomonas aeruginosa

Pseudomonas aeruginosa, a harmful nosocomial pathogen associated with cystic fibrosis and burn wounds, encodes for a large number of LysR-type transcriptional regulator proteins. To understand how and why LTTR proteins evolved with such frequency and to establish whether any relationships exist within the distribution we set out to identify the patterns underpinning LTTR distribution in P. aeruginosa and to uncover cluster-based relationships within the pangenome. Comparative genomic studies revealed that in the JGI IMG database alone ~86 000 LTTRs are present across the sequenced genomes (n=699). They are widely distributed across the species, with core LTTRs present in >93 % of the genomes and accessory LTTRs present in <7 %. Analysis showed that subsets of core LTTRs can be classified as either variable (typically specific to P. aeruginosa) or conserved (and found to be distributed in other Pseudomonas species). Extending the analysis to the more extensive Pseudomonas database, PA14 rooted analysis confirmed the diversification patterns and revealed PqsR, the receptor for the Pseudomonas quinolone signal (PQS) and 2-heptyl-4-quinolone (HHQ) quorum-sensing signals, to be amongst the most variable in the dataset. Successful complementation of the PAO1 pqsR - mutant using representative variant pqsR sequences suggests a degree of structural promiscuity within the most variable of LTTRs, several of which play a prominent role in signalling and communication. These findings provide a new insight into the diversification of LTTR proteins within the P. aeruginosa species and suggests a functional significance to the cluster, conservation and distribution patterns identified.

Beyond blast: enabling microbiologists to better extract literature, taxonomic distributions and gene neighbourhood information for protein families

Capturing the published corpus of information on all members of a given protein family should be an essential step in any study focusing on specific members of that family. Using a previously gathered dataset of more than 280 references mentioning a member of the DUF34 (NIF3/Ngg1-interacting Factor 3) family, we evaluated the efficiency of different databases and search tools, and devised a workflow that experimentalists can use to capture the most information published on members of a protein family in the least amount of time. To complement this workflow, web-based platforms allowing for the exploration of protein family members across sequenced genomes or for the analysis of gene neighbourhood information were reviewed for their versatility and ease of use. Recommendations that can be used for experimentalist users, as well as educators, are provided and integrated within a customized, publicly accessible Wiki.

Description of a new freshwater bacterium Aquirufa regiilacus sp. nov., classification of the genera Aquirufa, Arundinibacter, Sandaracinomonas, and Tellurirhabdus to the family Spirosomataceae, classification of the genus Chryseotalea to the family Fulvivirgaceae and Litoribacter to the family Cyclobacteriaceae, as well as classification of Litoribacter alkaliphilus as a later heterotypic synonym of Litoribacter ruber

Strains LEOWEIH-7CT and LEPPI-3A were isolated from the Leopoldskroner Weiher, a lake located in the city of Salzburg, Austria. 16S rRNA gene similarities and phylogenetic reconstructions with 16S rRNA gene sequences as well as based on genome sequences revealed that the new strains belong to the A. antheringensis branch of the genus Aquirufa. Calculated whole-genome average nucleotide identity (gANI) and digital DNA-DNA hybridization (dDDH) values with the closely related type strains showed that the two strains represent a single new species. The strains grew aerobically and chemoorganotrophically, and the cells were rod shaped, on average 0.8 µm long and 0.3 µm wide, red pigmented and motile by gliding. The genome size of both strains was 2.6 Mbp and the G+C value was 41.9%. The genomes comprised genes predicted for the complete light-harvesting rhodopsin system and various carotenoids. We proposed to establish the name Aquirufa regiilacus sp. nov. for strain LEOWEIH-7CT (=DSM 116390T = JCM 36347T) as the type strain. Strain LEPPI-3A (=DSM 116391 = JCM 36348) also belongs to this new species. The calculated genome-based phylogenetic tree revealed that Aquirufa and some other genera currently allocated in the family Cytophagaceae need a reclassification. Aquirufa, Arundinibacter, Sandaracinomonas, and Tellurirhabdus should be designated to the family Spirosomataceae, the genus Chryseotalea to the family Fulvivirgaceae, and the genus Litoribacter to the family Cyclobacteriaceae. Furthermore, based on calculated gANI and dDDH values, Litoribacter alkaliphilus should be reclassified as a later heterotypic synonym of Litoribacter ruber.

A bacterial sensor taxonomy across earth ecosystems for machine learning applications

Microbial communities have evolved to colonize all ecosystems of the planet, from the deep sea to the human gut. Microbes survive by sensing, responding, and adapting to immediate environmental cues. This process is driven by signal transduction proteins such as histidine kinases, which use their sensing domains to bind or otherwise detect environmental cues and "transduce" signals to adjust internal processes. We hypothesized that an ecosystem's unique stimuli leave a sensor "fingerprint," able to identify and shed insight on ecosystem conditions. To test this, we collected 20,712 publicly available metagenomes from Host-associated, Environmental, and Engineered ecosystems across the globe. We extracted and clustered the collection's nearly 18M unique sensory domains into 113,712 similar groupings with MMseqs2. We built gradient-boosted decision tree machine learning models and found we could classify the ecosystem type (accuracy: 87%) and predict the levels of different physical parameters (R2 score: 83%) using the sensor cluster abundance as features. Feature importance enables identification of the most predictive sensors to differentiate between ecosystems which can lead to mechanistic interpretations if the sensor domains are well annotated. To demonstrate this, a machine learning model was trained to predict patient's disease state and used to identify domains related to oxygen sensing present in a healthy gut but missing in patients with abnormal conditions. Moreover, since 98.7% of identified sensor domains are uncharacterized, importance ranking can be used to prioritize sensors to determine what ecosystem function they may be sensing. Furthermore, these new predictive sensors can function as targets for novel sensor engineering with applications in biotechnology, ecosystem maintenance, and medicine.IMPORTANCEMicrobes infect, colonize, and proliferate due to their ability to sense and respond quickly to their surroundings. In this research, we extract the sensory proteins from a diverse range of environmental, engineered, and host-associated metagenomes. We trained machine learning classifiers using sensors as features such that it is possible to predict the ecosystem for a metagenome from its sensor profile. We use the optimized model's feature importance to identify the most impactful and predictive sensors in different environments. We next use the sensor profile from human gut metagenomes to classify their disease states and explore which sensors can explain differences between diseases. The sensors most predictive of environmental labels here, most of which correspond to uncharacterized proteins, are a useful starting point for the discovery of important environment signals and the development of possible diagnostic interventions.

Multiple microbial guilds mediate soil methane cycling along a wetland salinity gradient

Estuarine wetlands harbor considerable carbon stocks, but rising sea levels could affect their ability to sequester soil carbon as well as their potential to emit methane (CH4). While sulfate loading from seawater intrusion may reduce CH4 production due to the higher energy yield of microbial sulfate reduction, existing studies suggest other factors are likely at play. Our study of 11 wetland complexes spanning a natural salinity and productivity gradient across the San Francisco Bay and Delta found that while CH4 fluxes generally declined with salinity, they were highest in oligohaline wetlands (ca. 3-ppt salinity). Methanogens and methanogenesis genes were weakly correlated with CH4 fluxes but alone did not explain the highest rates observed. Taxonomic and functional gene data suggested that other microbial guilds that influence carbon and nitrogen cycling need to be accounted for to better predict CH4 fluxes at landscape scales. Higher methane production occurring near the freshwater boundary with slight salinization (and sulfate incursion) might result from increased sulfate-reducing fermenter and syntrophic populations, which can produce substrates used by methanogens. Moreover, higher salinities can solubilize ionically bound ammonium abundant in the lower salinity wetland soils examined here, which could inhibit methanotrophs and potentially contribute to greater CH4 fluxes observed in oligohaline sediments.IMPORTANCELow-level salinity intrusion could increase CH4 flux in tidal freshwater wetlands, while higher levels of salinization might instead decrease CH4 fluxes. High CH4 emissions in oligohaline sites are concerning because seawater intrusion will cause tidal freshwater wetlands to become oligohaline. Methanogenesis genes alone did not account for landscape patterns of CH4 fluxes, suggesting mechanisms altering methanogenesis, methanotrophy, nitrogen cycling, and ammonium release, and increasing decomposition and syntrophic bacterial populations could contribute to increases in net CH4 flux at oligohaline salinities. Improved understanding of these influences on net CH4 emissions could improve restoration efforts and accounting of carbon sequestration in estuarine wetlands. More pristine reference sites may have older and more abundant organic matter with higher carbon:nitrogen compared to wetlands impacted by agricultural activity and may present different interactions between salinity and CH4. This distinction might be critical for modeling efforts to scale up biogeochemical process interactions in estuarine wetlands.

Seven genome sequences of bacterial, environmental isolates from Pony Lake, Antarctica

Dissolved organic matter (DOM) in Antarctic inland waters is unique in that its precursor molecules are microbially derived and lack the chemical signature of higher plants. Here, we report the genomic sequences of seven environmental, bacterial isolates from Pony Lake, Antarctica, to explore the genetic potential linked to DOM processing.

Toxinome-the bacterial protein toxin database

IMPORTANCE

Microbes use protein toxins as important tools to attack neighboring cells, microbial or eukaryotic, and for self-killing when attacked by viruses. These toxins work through different mechanisms to inhibit cell growth or kill cells. Microbes also use antitoxin proteins to neutralize the toxin activities. Here, we developed a comprehensive database called Toxinome of nearly two million toxins and antitoxins that are encoded in 59,475 bacterial genomes. We described the distribution of bacterial toxins and identified that they are depleted by bacteria that live in hot and cold temperatures. We found 5,161 cases in which toxins and antitoxins are densely clustered in bacterial genomes and termed these areas "Toxin Islands." The Toxinome database is a useful resource for anyone interested in toxin biology and evolution, and it can guide the discovery of new toxins.

Antibody reactive immunomes of Ehrlichia chaffeensis and E. canis are diverse and defined by conformational antigenic determinants

For decades, the defined antibody reactive proteins of Ehrlichia chaffeensis and E. canis were limited to a small group with linear antibody epitopes. Recently, our laboratory has utilized an immunomics-based approach to rapidly screen and identify undefined Ehrlichia chaffeensis and E. canis antigenic proteins and antibody epitopes. In this study, we analyzed the remaining portion (~50%) of the E. chaffeensis and E. canis proteomes (n = 444 and n = 405 proteins, respectively), that were not examined in previous studies, to define the complete immunomes of these important pathogens. Almost half of the E. chaffeensis proteins screened (196/444) reacted with antibodies in convalescent HME patient sera, while only 43 E. canis proteins reacted with CME dog sera. New major immunoreactive proteins were identified in E. chaffeensis (n = 7) and E. canis (n = 1), increasing the total number of E. chaffeensis (n = 14) and E. canis proteins (n = 18) that exhibited antibody reactivity comparable to well-defined major antigenic proteins (TRP120 and TRP19). All of the E. chaffeensis but only some E. canis major immunoreactive proteins contained major conformation-dependent antibody epitopes. The E. chaffeensis immunoreactive proteins were generally small (< 250 amino acids; ~27kDa) and the E. canis proteins were slightly larger (> 320 amino acids; ~35 kDa). The majority of these new Ehrlichia major immunoreactive proteins were predicted to be type I secreted effectors, some of which contained transmembrane domains. Characterization of the immunomes of E. chaffeensis and E. canis and understanding the host specific Ehrlichia immune responses will facilitate identification of protective antigens and define the biophysical epitope characteristics vital to effective vaccine development for the ehrlichioses.

Beyond Blast: Enabling Microbiologists to Better Extract Literature, Taxonomic Distributions and Gene Neighborhood Information for Protein Families

Capturing the published corpus of information on all members of a given protein family should be an essential step in any study focusing on specific members of that said family. Using a previously gathered dataset of more than 280 references mentioning a member of the DUF34 (NIF3/Ngg1-interacting Factor 3), we evaluated the efficiency of different databases and search tools, and devised a workflow that experimentalists can use to capture the most published information on members of a protein family in the least amount of time. To complement this workflow, web-based platforms allowing for the exploration of protein family members across sequenced genomes or for the analysis of gene neighborhood information were reviewed for their versatility and ease of use. Recommendations that can be used for experimentalist users, as well as educators, are provided and integrated within a customized, publicly accessible Wiki.

Positive Selection Screens for Programmable Endonuclease Activity Using I-SceI

Positive selection screens are high-throughput assays to characterize novel enzymes from environmental samples and enrich for more powerful variants from libraries in applications such as biodiversity mining and directed evolution. However, overly stringent selection can limit the power of these screens due to a high false-negative rate. To create a more flexible and less restrictive screen for novel programmable DNA endonucleases, we developed a novel I-SceI-based platform. In this system, mutant E. coli genomes are cleaved upon induction of I-SceI to inhibit cell growth. Growth is rescued in an activity-dependent manner by plasmid curing or cleavage of the I-SceI expression plasmid via endonuclease candidates. More active candidates more readily proliferate and overtake growth of less active variants leading to enrichment. While demonstrated here with Cas9, this protocol can be readily adapted to any programmable DNA endonuclease and used to characterize single candidates or to enrich more powerful variants from pooled candidates or libraries.

Microbial responses to long-term warming differ across soil microenvironments

Soil carbon loss is likely to increase due to climate warming, but microbiomes and microenvironments may dampen this effect. In a 30-year warming experiment, physical protection within soil aggregates affected the thermal responses of soil microbiomes and carbon dynamics. In this study, we combined metagenomic analysis with physical characterization of soil aggregates to explore mechanisms by which microbial communities respond to climate warming across different soil microenvironments. Long-term warming decreased the relative abundances of genes involved in degrading labile compounds (e.g. cellulose), but increased those genes involved in degrading recalcitrant compounds (e.g. lignin) across aggregate sizes. These changes were observed in most phyla of bacteria, especially for Acidobacteria, Actinobacteria, Bacteroidetes, Chloroflexi, and Planctomycetes. Microbial community composition was considerably altered by warming, leading to declined diversity for bacteria and fungi but not for archaea. Microbial functional genes, diversity, and community composition differed between macroaggregates and microaggregates, indicating the essential role of physical protection in controlling microbial community dynamics. Our findings suggest that microbes have the capacity to employ various strategies to acclimate or adapt to climate change (e.g. warming, heat stress) by shifting functional gene abundances and community structures in varying microenvironments, as regulated by soil physical protection.

Potential for functional divergence in ectomycorrhizal fungal communities across a precipitation gradient

Functional traits influence the assembly of microbial communities, but identifying these traits in the environment has remained challenging. We studied ectomycorrhizal fungal (EMF) communities inhabiting Populus trichocarpa roots distributed across a precipitation gradient in the Pacific Northwest, USA. We profiled these communities using taxonomic (meta-barcoding) and functional (metagenomic) approaches. We hypothesized that genes involved in fungal drought-stress tolerance and fungal mediated plant water uptake would be most abundant in drier soils. We were unable to detect support for this hypothesis; instead, the abundance of genes involved in melanin synthesis, hydrophobins, aquaporins, trehalose-synthases, and other gene families exhibited no significant shifts across the gradient. Finally, we studied variation in sequence homology for certain genes, finding that fungal communities in dry soils are composed of distinct aquaporin and hydrophobin gene sequences. Altogether, our results suggest that while EMF communities exhibit significant compositional shifts across this gradient, coupled functional turnover, at least as inferred using community metagenomics is limited. Accordingly, the consequences of these distinct EMF communities on plant water uptake remain critically unknown, and future studies targeting the expression of genes involved in drought stress tolerance are required.

Use of 16S rRNA gene sequences to identify cyanobacteria that can grow in far-red light

Although most cyanobacteria use visible light (VL; λ = 400-700 nm) for photosynthesis, some have evolved strategies to use far-red light (FRL; λ = 700-800 nm). These cyanobacteria are defined as far-red light-utilizing cyanobacteria (FRLCyano), including two groups: (1) chlorophyll d-producing Acaryochloris spp. and (2) polyphyletic cyanobacteria that produce chlorophylls d and f in response to FRL. Numerous ecological studies examine pigments, such as chlorophylls d and f, to investigate the presence of FRLCyano in the environment. This method is not ideal because it can only detect FRLCyano that have made chlorophylls d or f. Here we develop a new method, far-red cyanobacteria identification (FRCI), to identify FRLCyano based on 16S rRNA gene sequences. From public databases and published articles, 62 16S rRNA gene sequences of FRLCyano were extracted. Comparing with related lineages, we determined that 97% sequence identity is the optimal cut-off for distinguishing FRLCyano from other cyanobacteria. To test the method experimentally, we collected samples from 17 sites in Taipei, Taiwan, and conducted VL and FRL enrichments. Our results demonstrate that FRCI can detect FRLCyano during FRL enrichments more sensitively than pigment analysis. FRCI can also resolve the composition of FRLCyano at the genus level, which pigment analysis cannot do. In addition, we applied FRCI to published datasets and discovered putative FRLCyano in diverse environments, including soils, hot springs and deserts. Overall, our results indicate that FRCI is a sensitive and high-resolution method using 16S rRNA gene sequences to identify FRLCyano.

Widespread horizontal gene transfer between plants and bacteria

Plants host a large array of commensal bacteria that interact with the host. The growth of both bacteria and plants is often dependent on nutrients derived from the cognate partners, and the bacteria fine-tune host immunity against pathogens. This ancient interaction is common in all studied land plants and is critical for proper plant health and development. We hypothesized that the spatial vicinity and the long-term relationships between plants and their microbiota may promote cross-kingdom horizontal gene transfer (HGT), a phenomenon that is relatively rare in nature. To test this hypothesis, we analyzed the Arabidopsis thaliana genome and its extensively sequenced microbiome to detect events of horizontal transfer of full-length genes that transferred between plants and bacteria. Interestingly, we detected 75 unique genes that were horizontally transferred between plants and bacteria. Plants and bacteria exchange in both directions genes that are enriched in carbohydrate metabolism functions, and bacteria transferred to plants genes that are enriched in auxin biosynthesis genes. Next, we provided a proof of concept for the functional similarity between a horizontally transferred bacterial gene and its Arabidopsis homologue in planta. The Arabidopsis DET2 gene is essential for biosynthesis of the brassinosteroid phytohormones, and loss of function of the gene leads to dwarfism. We found that expression of the DET2 homologue from Leifsonia bacteria of the Actinobacteria phylum in the Arabidopsis det2 background complements the mutant and leads to normal plant growth. Together, these data suggest that cross-kingdom HGT events shape the metabolic capabilities and interactions between plants and bacteria.

Phages overcome bacterial immunity via diverse anti-defence proteins

It was recently shown that bacteria use, apart from CRISPR-Cas and restriction systems, a considerable diversity of phage resistance systems1-4, but it is largely unknown how phages cope with this multilayered bacterial immunity. Here we analysed groups of closely related Bacillus phages that showed differential sensitivity to bacterial defence systems, and discovered four distinct families of anti-defence proteins that inhibit the Gabija, Thoeris and Hachiman systems. We show that these proteins Gad1, Gad2, Tad2 and Had1 efficiently cancel the defensive activity when co-expressed with the respective defence system or introduced into phage genomes. Homologues of these anti-defence proteins are found in hundreds of phages that infect taxonomically diverse bacterial species. We show that the anti-Gabija protein Gad1 blocks the ability of the Gabija defence complex to cleave phage-derived DNA. Our data further reveal that the anti-Thoeris protein Tad2 is a 'sponge' that sequesters the immune signalling molecules produced by Thoeris TIR-domain proteins in response to phage infection. Our results demonstrate that phages encode an arsenal of anti-defence proteins that can disable a variety of bacterial defence mechanisms.

Phenotypic Characterization and Draft Genome Sequence Analyses of Two Novel Endospore-Forming Sporosarcina spp. Isolated from Canada Goose (Branta canadensis) Feces

In an attempt to isolate new probiotic bacteria, two Gram-variable, spore-forming, rod-shaped aerobic bacteria designated as strain A4 and A15 were isolated from the feces of Canada geese (Branta canadensis). Strain A4 was able to grow in high salt levels and exhibited lipase activity, while A15 did not propagate under these conditions. Both were positive for starch hydrolysis, and they inhibited the growth of Staphylococcus aureus. The strains of the 16S rRNA sequence shared only 94% similarity to previously identified Sporosarcina spp. The ANI (78.08%) and AAI (82.35%) between the two strains were less than the species threshold. Searches for the most similar genomes using the Mash/Minhash algorithm showed the nearest genome to strain A4 and A15 as Sporosarcina sp. P13 (distance of 21%) and S. newyorkensis (distance of 17%), respectively. Sporosarcina spp. strains A4 and A15 contain urease genes, and a fibronectin-binding protein gene indicates that these bacteria may bind to eukaryotic cells in host gastrointestinal tracts. Phenotypic and phylogenetic data, along with low dDDH, ANI, and AAI values for strains A4 and A15, indicate these bacteria are two novel isolates of the Sporosarcina genus: Sporosarcina sp. A4 sp. nov., type strain as Sporosarcina cascadiensis and Sporosarcina sp. A15 sp. nov., type strain Sporosarcina obsidiansis.

Targeted rRNA depletion enables efficient mRNA sequencing in diverse bacterial species and complex co-cultures

IMPORTANCE

Microbes present one of the most diverse sources of biochemistry in nature, and mRNA sequencing provides a comprehensive view of this biological activity by quantitatively measuring microbial transcriptomes. However, efficient mRNA capture for sequencing presents significant challenges in prokaryotes as mRNAs are not poly-adenylated and typically make up less than 5% of total RNA compared with rRNAs that exceed 80%. Recently developed methods for sequencing bacterial mRNA typically rely on depleting rRNA by tiling large probe sets against rRNAs; however, such approaches are expensive, time-consuming, and challenging to scale to varied bacterial species and complex microbial communities. Therefore, we developed EMBR-seq+, a method that requires fewer than 10 short oligonucleotides per rRNA to achieve up to 99% rRNA depletion in diverse bacterial species. Finally, EMBR-seq+ resulted in a deeper view of the transcriptome, enabling systematic quantification of how microbial interactions result in altering the transcriptional state of bacteria within co-cultures.

Genome sequence and characterisation of a freshwater photoarsenotroph, Cereibacter azotoformans strain ORIO, isolated from sediments capable of cyclic light-dark arsenic oxidation and reduction

A freshwater photosynthetic arsenite-oxidizing bacterium, Cereibacter azotoformans strain ORIO, was isolated from Owens River, CA, USA. The waters from Owens River are elevated in arsenic and serve as the headwaters to the Los Angeles Aqueduct. The complete genome sequence of strain ORIO is 4.8 Mb genome (68% G + C content) and comprises two chromosomes and six plasmids. Taxonomic analysis placed ORIO within the Cereibacter genus (formerly Rhodobacter). The ORIO genome contains arxB2 AB1 CD (encoding an arsenite oxidase), arxXSR (regulators) and several ars arsenic resistance genes all co-localised on a 136 kb plasmid, named pORIO3. Phylogenetic analysis of ArxA, the molybdenum-containing arsenite oxidase catalytic subunit, demonstrated photoarsenotrophy is likely to occur within members of the Alphaproteobacteria. ORIO is a mixotroph, oxidises arsenite to arsenate (As(V)) photoheterotrophically, and expresses arxA in cultures grown with arsenite. Further ecophysiology studies with Owens River sediment demonstrated the interconversion of arsenite and As(V) was dependent on light-dark cycling. arxA and arrA (As(V) respiratory reductase) genes were detected in the light-dark cycled sediment metagenomes suggesting syntrophic interactions among arsenotrophs. This work establishes C. azotoformans str. ORIO as a new model organism for studying photoarsenotrophy and light-dark arsenic biogeochemical cycling.

Integrating deep learning, threading alignments, and a multi-MSA strategy for high-quality protein monomer and complex structure prediction in CASP15

We report the results of the "UM-TBM" and "Zheng" groups in CASP15 for protein monomer and complex structure prediction. These prediction sets were obtained using the D-I-TASSER and DMFold-Multimer algorithms, respectively. For monomer structure prediction, D-I-TASSER introduced four new features during CASP15: (i) a multiple sequence alignment (MSA) generation protocol that combines multi-source MSA searching and a structural modeling-based MSA ranker; (ii) attention-network based spatial restraints; (iii) a multi-domain module containing domain partition and arrangement for domain-level templates and spatial restraints; (iv) an optimized I-TASSER-based folding simulation system for full-length model creation guided by a combination of deep learning restraints, threading alignments, and knowledge-based potentials. For 47 free modeling targets in CASP15, the final models predicted by D-I-TASSER showed average TM-score 19% higher than the standard AlphaFold2 program. We thus showed that traditional Monte Carlo-based folding simulations, when appropriately coupled with deep learning algorithms, can generate models with improved accuracy over end-to-end deep learning methods alone. For protein complex structure prediction, DMFold-Multimer generated models by integrating a new MSA generation algorithm (DeepMSA2) with the end-to-end modeling module from AlphaFold2-Multimer. For the 38 complex targets, DMFold-Multimer generated models with an average TM-score of 0.83 and Interface Contact Score of 0.60, both significantly higher than those of competing complex prediction tools. Our analyses on complexes highlighted the critical role played by MSA generating, ranking, and pairing in protein complex structure prediction. We also discuss future room for improvement in the areas of viral protein modeling and complex model ranking.

Candidatus Nemesobacterales is a sponge-specific clade of the candidate phylum Desulfobacterota adapted to a symbiotic lifestyle

Members of the candidate phylum Dadabacteria, recently reassigned to the phylum Candidatus Desulfobacterota, are cosmopolitan in the marine environment found both free-living and associated with hosts that are mainly marine sponges. Yet, these microorganisms are poorly characterized, with no cultured representatives and an ambiguous phylogenetic position in the tree of life. Here, we performed genome-centric metagenomics to elucidate their phylogenomic placement and predict the metabolism of the sponge-associated members of this lineage. Rank-based phylogenomics revealed several new species and a novel family (Candidatus Spongomicrobiaceae) within a sponge-specific order, named here Candidatus Nemesobacterales. Metabolic reconstruction suggests that Ca. Nemesobacterales are aerobic heterotrophs, capable of synthesizing most amino acids, vitamins and cofactors and degrading complex carbohydrates. We also report functional divergence between sponge- and seawater-associated metagenome-assembled genomes. Niche-specific adaptations to the sponge holobiont were evident from significantly enriched genes involved in defense mechanisms against foreign DNA and environmental stressors, host-symbiont interactions and secondary metabolite production. Fluorescence in situ hybridization gave a first glimpse of the morphology and lifestyle of a member of Ca. Desulfobacterota. Candidatus Nemesobacterales spp. were found both inside sponge cells centred around sponge nuclei and in the mesohyl of the sponge Geodia barretti. This study sheds light on the enigmatic group Ca. Nemesobacterales and their functional characteristics that reflect a symbiotic lifestyle.

Life history strategies of soil bacterial communities across global terrestrial biomes

The life history strategies of soil microbes determine their metabolic potential and their response to environmental changes. Yet these strategies remain poorly understood. Here we use shotgun metagenomes from terrestrial biomes to characterize overarching covariations of the genomic traits that capture dominant life history strategies in bacterial communities. The emerging patterns show a triangle of life history strategies shaped by two trait dimensions, supporting previous theoretical and isolate-based studies. The first dimension ranges from streamlined genomes with simple metabolisms to larger genomes and expanded metabolic capacities. As metabolic capacities expand, bacterial communities increasingly differentiate along a second dimension that reflects a trade-off between increasing capacities for environmental responsiveness or for nutrient recycling. Random forest analyses show that soil pH, C:N ratio and precipitation patterns together drive the dominant life history strategy of soil bacterial communities and their biogeographic distribution. Our findings provide a trait-based framework to compare life history strategies of soil bacteria.

Data-driven identification of major axes of functional variation in bacteria

The discovery of major axes of correlated functional variation among species and habitats has revealed the fundamental trade-offs structuring both functional and taxonomic diversity in eukaryotes such as plants. Whether such functional axes exist in the bacterial realm and whether they could explain bacterial taxonomic turnover among ecosystems remains unknown. Here, we use a data-driven approach to leverage global genomic and metagenomic datasets to reveal the existence of major axes of functional variation explaining both evolutionary differentiation within Bacteria and their ecological sorting across diverse habitats. We show that metagenomic variation among bacterial communities from various ecosystems is structured along a few axes of correlated functional pathways. Similar clusters of traits explained phylogenetic trait variation among >16,000 bacterial genomes, suggesting that functional turnover among bacterial communities from distinct habitats does not only result from the differential filtering of similar functions among communities, but also from phylogenetic correlations among these functions. Concordantly, functional pathways associated with trait clusters that were most important for defining functional turnover among bacterial communities were also those that had the highest phylogenetic signal in the bacterial genomic phylogeny. This study overall underlines the important role of evolutionary history in shaping contemporary distributions of bacteria across ecosystems.

Virus diversity and activity is driven by snowmelt and host dynamics in a high-altitude watershed soil ecosystem

BACKGROUND

Viruses impact nearly all organisms on Earth, including microbial communities and their associated biogeochemical processes. In soils, highly diverse viral communities have been identified, with a global distribution seemingly driven by multiple biotic and abiotic factors, especially soil temperature and moisture. However, our current understanding of the stability of soil viral communities across time and their response to strong seasonal changes in environmental parameters remains limited. Here, we investigated the diversity and activity of environmental soil DNA and RNA viruses, focusing especially on bacteriophages, across dynamics' seasonal changes in a snow-dominated mountainous watershed by examining paired metagenomes and metatranscriptomes.

RESULTS

We identified a large number of DNA and RNA viruses taxonomically divergent from existing environmental viruses, including a significant proportion of fungal RNA viruses, and a large and unsuspected diversity of positive single-stranded RNA phages (Leviviricetes), highlighting the under-characterization of the global soil virosphere. Among these, we were able to distinguish subsets of active DNA and RNA phages that changed across seasons, consistent with a "seed-bank" viral community structure in which new phage activity, for example, replication and host lysis, is sequentially triggered by changes in environmental conditions. At the population level, we further identified virus-host dynamics matching two existing ecological models: "Kill-The-Winner" which proposes that lytic phages are actively infecting abundant bacteria, and "Piggyback-The-Persistent" which argues that when the host is growing slowly, it is more beneficial to remain in a dormant state. The former was associated with summer months of high and rapid microbial activity, and the latter with winter months of limited and slow host growth.

CONCLUSION

Taken together, these results suggest that the high diversity of viruses in soils is likely associated with a broad range of host interaction types each adapted to specific host ecological strategies and environmental conditions. As our understanding of how environmental and host factors drive viral activity in soil ecosystems progresses, integrating these viral impacts in complex natural microbiome models will be key to accurately predict ecosystem biogeochemistry. Video Abstract.

Common loss of far-red light photoacclimation in cyanobacteria from hot and cold deserts: a case study in the Chroococcidiopsidales

Deserts represent an extreme challenge for photosynthetic life. Despite their aridity, they are often inhabited by diverse microscopic communities of cyanobacteria. These organisms are commonly found in lithic habitats, where they are partially sheltered from extremes of temperature and UV radiation. However, living under the rock surface imposes additional constraints, such as limited light availability, and enrichment of longer wavelengths than are typically usable for oxygenic photosynthesis. Some cyanobacteria from the genus Chroococcidiopsis can use this light to photosynthesize, in a process known as far-red light photoacclimation, or FaRLiP. This genus has commonly been reported from both hot and cold deserts. However, not all Chroococcidiopsis strains carry FaRLiP genes, thus motivating our study into the interplay between FaRLiP and extreme lithic environments. The abundance of sequence data and strains provided the necessary material for an in-depth phylogenetic study, involving spectroscopy, microscopy, and determination of pigment composition, as well as gene and genome analyses. Pigment analyses revealed the presence of red-shifted chlorophylls d and f in all FaRLiP strains tested. In addition, eight genus-level taxa were defined within the encompassing Chroococcidiopsidales, clarifying the phylogeny of this long-standing polyphyletic order. FaRLiP is near universally present in a generalist genus identified in a wide variety of environments, Chroococcidiopsis sensu stricto, while it is rare or absent in closely related, extremophile taxa, including those preferentially inhabiting deserts. This likely reflects the evolutionary process of gene loss in specialist lineages.

Taxonomic and functional restoration of tallgrass prairie soil microbial communities in comparison to remnant and agricultural soils

Restoring ecosystems requires the re-establishment of diverse soil microbial communities that drive critical ecosystem functions. In grasslands, restoration and management require the application of disturbances like fire and grazing. Disturbances can shape microbial taxonomic composition and potentially functional composition as well. We characterized taxonomic and functional gene composition of soil communities using whole genome shotgun metagenomic sequencing to determine how restored soil communities differed from pre-restoration agricultural soils and original remnant soils, how management affects soil microbes, and whether restoration and management affect the number of microbial genes associated with carbohydrate degradation. We found distinct differences in both taxonomic and functional diversity and composition among restored, remnant, and agricultural soils. Remnant soils had low taxonomic and functional richness and diversity, as well as distinct composition, indicating that restoration of agricultural soils does not re-create soil microbial communities that match remnants. Prescribed fire management increased functional diversity, which also was higher in more recently planted restorations. Finally, restored and post-fire soils included high abundances of genes encoding cellulose-degrading enzymes, so restorations and their ongoing management can potentially support functions important in carbon cycling.

Chakrabartyella piscis gen. nov., sp. nov., a member of the family Lachnospiraceae, isolated from the hindgut of the marine herbivorous fish Kyphosus sydneyanus

A Gram-stain-negative, non-spore-forming, rod-shaped, obligately anaerobic bacterium, designated strain BP5GT, was isolated from the hindgut of a silver drummer (Kyphosus sydneyanus) fish collected from the Hauraki Gulf, New Zealand. Phylogenetic analysis based on the 16S rRNA gene sequence indicated that the isolate belonged to the family Lachnospiraceae in the phylum Bacillota and was most closely related to Anaerotignum propionicum with 94.06 % sequence identity. Isolate BP5GT grew on agar medium containing mannitol and fish gut fluid as carbon sources. Clear colonies of approximately 1 mm diameter of the isolate grew within a week at 20-28 °C (optimum, 28 °C) and pH 7.6-8.5 (optimum, pH 8.5). Strain BP5GT was very sensitive to NaCl and the optimal concentration for growth was 0.045 % (w/v). Acetate and propionate were the major fermentation products. The major cellular fatty acids were C12 : 0, C14 : 0, C15 : 0 and C16 : 0. The genome sequence of the isolate was determined. Its G+C content was 38.41 mol% and the 71.41 % average nucleotide identity of the BP5GT genome to its closest neighbour with a sequenced genome (A. propionicum DSM 1682T) indicated low genomic relatedness. Based on the phenotypic and taxonomic characteristics observed in this study, a novel genus and species named Chakrabartyella piscis gen. nov., sp. nov. is proposed for isolate BP5GT (=ICMP 24687T=JCM 35769T).

Physiological and evolutionary contexts of a new symbiotic species from the nitrogen-recycling gut community of turtle ants

While genome sequencing has expanded our knowledge of symbiosis, role assignment within multi-species microbiomes remains challenging due to genomic redundancy and the uncertainties of in vivo impacts. We address such questions, here, for a specialized nitrogen (N) recycling microbiome of turtle ants, describing a new genus and species of gut symbiont-Ischyrobacter davidsoniae (Betaproteobacteria: Burkholderiales: Alcaligenaceae)-and its in vivo physiological context. A re-analysis of amplicon sequencing data, with precisely assigned Ischyrobacter reads, revealed a seemingly ubiquitous distribution across the turtle ant genus Cephalotes, suggesting ≥50 million years since domestication. Through new genome sequencing, we also show that divergent I. davidsoniae lineages are conserved in their uricolytic and urea-generating capacities. With phylogenetically refined definitions of Ischyrobacter and separately domesticated Burkholderiales symbionts, our FISH microscopy revealed a distinct niche for I. davidsoniae, with dense populations at the anterior ileum. Being positioned at the site of host N-waste delivery, in vivo metatranscriptomics and metabolomics further implicate I. davidsoniae within a symbiont-autonomous N-recycling pathway. While encoding much of this pathway, I. davidsoniae expressed only a subset of the requisite steps in mature adult workers, including the penultimate step deriving urea from allantoate. The remaining steps were expressed by other specialized gut symbionts. Collectively, this assemblage converts inosine, made from midgut symbionts, into urea and ammonia in the hindgut. With urea supporting host amino acid budgets and cuticle synthesis, and with the ancient nature of other active N-recyclers discovered here, I. davidsoniae emerges as a central player in a conserved and impactful, multipartite symbiosis.

Revisiting evolutionary trajectories and the organization of the Pleolipoviridae family

Archaeal pleomorphic viruses belonging to the Pleolipoviridae family represent an enigmatic group as they exhibit unique genomic features and are thought to have evolved through recombination with different archaeal plasmids. However, most of our understanding of the diversity and evolutionary trajectories of this clade comes from a handful of isolated representatives. Here we present 164 new genomes of pleolipoviruses obtained from metagenomic data of Australian hypersaline lakes and publicly available metagenomic data. We perform a comprehensive analysis on the diversity and evolutionary relationships of the newly discovered viruses and previously described pleolipoviruses. We propose to classify the viruses into five genera within the Pleolipoviridae family, with one new genus represented only by virus genomes retrieved in this study. Our data support the current hypothesis that pleolipoviruses reshaped their genomes through recombining with multiple different groups of plasmids, which is reflected in the diversity of their predicted replication strategies. We show that the proposed genus Epsilonpleolipovirus has evolutionary ties to pRN1-like plasmids from Sulfolobus, suggesting that this group could be infecting other archaeal phyla. Interestingly, we observed that the genome size of pleolipoviruses is correlated to the presence or absence of an integrase. Analyses of the host range revealed that all but one virus exhibit an extremely narrow range, and we show that the predicted tertiary structure of the spike protein is strongly associated with the host family, suggesting a specific adaptation to the host S-layer glycoprotein organization.

A critical review of machine-learning for "multi-omics" marine metabolite datasets

During the last decade, genomic, transcriptomic, proteomic, metabolomic, and other omics datasets have been generated for a wide range of marine organisms, and even more are still on the way. Marine organisms possess unique and diverse biosynthetic pathways contributing to the synthesis of novel secondary metabolites with significant bioactivities. As marine organisms have a greater tendency to adapt to stressed environmental conditions, the chance to identify novel bioactive metabolites with potential biotechnological application is very high. This review presents a comprehensive overview of the available "-omics" and "multi-omics" approaches employed for characterizing marine metabolites along with novel data integration tools. The need for the development of machine-learning algorithms for "multi-omics" approaches is briefly discussed. In addition, the challenges involved in the analysis of "multi-omics" data and recommendations for conducting "multi-omics" study were discussed.

The oxidoreductase activity of Rnf balances redox cofactors during fermentation of glucose to propionate in Prevotella

Propionate is a microbial metabolite formed in the gastrointestinal tract, and it affects host physiology as a source of energy and signaling molecule. Despite the importance of propionate, the biochemical pathways responsible for its formation are not clear in all microbes. For the succinate pathway used during fermentation, a key enzyme appears to be missing-one that oxidizes ferredoxin and reduces NAD. Here we show that Rnf [ferredoxin-NAD+ oxidoreductase (Na+-transporting)] is this key enzyme in two abundant bacteria of the rumen (Prevotella brevis and Prevotella ruminicola). We found these bacteria form propionate, succinate, and acetate with the classic succinate pathway. Without ferredoxin:NAD+ oxidoreductase, redox cofactors would be unbalanced; it would produce almost equal excess amounts of reduced ferredoxin and oxidized NAD. By combining growth experiments, genomics, proteomics, and enzyme assays, we point to the possibility that these bacteria solve this problem by oxidizing ferredoxin and reducing NAD with Rnf [ferredoxin-NAD+ oxidoreductase (Na+-transporting)]. Genomic and phenotypic data suggest many bacteria may use Rnf similarly. This work shows the ferredoxin:NAD+ oxidoreductase activity of Rnf is important to propionate formation in Prevotella species and other bacteria from the environment, and it provides fundamental knowledge for manipulating fermentative propionate production.

A Proteorhodopsin-Related Photosensor Expands the Repertoire of Structural Motifs Employed by Sensory Rhodopsins

Microbial rhodopsins are light-activated retinal-binding membrane proteins that perform a variety of ion transport and photosensory functions. They display several cases of convergent evolution where the same function is present in unrelated or very distant protein groups. Here we report another possible case of such convergent evolution, describing the biophysical properties of a new group of sensory rhodopsins. The first representative of this group was identified in 2004 but none of the members had been expressed and characterized. The well-studied haloarchaeal sensory rhodopsins interacting with methyl-accepting Htr transducers are close relatives of the halobacterial proton pump bacteriorhodopsin. In contrast, the sensory rhodopsins we describe here are relatives of proteobacterial proton pumps, proteorhodopsins, but appear to interact with Htr-like transducers likewise, even though they do not conserve the residues important for the interaction of haloarchaeal sensory rhodopsins with their transducers. The new sensory rhodopsins display many unusual amino acid residues, including those around the retinal chromophore; most strikingly, a tyrosine in place of a carboxyl counterion of the retinal Schiff base on helix C. To characterize their unique sequence motifs, we augment the spectroscopy and biochemistry data by structural modeling of the wild-type and three mutants. Taken together, the experimental data, bioinformatics sequence analyses, and structural modeling suggest that the tyrosine/aspartate complex counterion contributes to a complex water-mediated hydrogen-bonding network that couples the protonated retinal Schiff base to an extracellular carboxylic dyad.

Single-cell isotope tracing reveals functional guilds of bacteria associated with the diatom Phaeodactylum tricornutum

Bacterial remineralization of algal organic matter fuels algal growth but is rarely quantified. Consequently, we cannot currently predict whether some bacterial taxa may provide more remineralized nutrients to algae than others. Here, we quantified bacterial incorporation of algal-derived complex dissolved organic carbon and nitrogen and algal incorporation of remineralized carbon and nitrogen in fifteen bacterial co-cultures growing with the diatom Phaeodactylum tricornutum at the single-cell level using isotope tracing and nanoSIMS. We found unexpected strain-to-strain and cell-to-cell variability in net carbon and nitrogen incorporation, including non-ubiquitous complex organic nitrogen utilization and remineralization. We used these data to identify three distinct functional guilds of metabolic interactions, which we termed macromolecule remineralizers, macromolecule users, and small-molecule users, the latter exhibiting efficient growth under low carbon availability. The functional guilds were not linked to phylogeny and could not be elucidated strictly from metabolic capacity as predicted by comparative genomics, highlighting the need for direct activity-based measurements in ecological studies of microbial metabolic interactions.

Genome-resolved correlation mapping links microbial community structure to metabolic interactions driving methane production from wastewater

Anaerobic digestion of municipal mixed sludge produces methane that can be converted into renewable natural gas. To improve economics of this microbial mediated process, metabolic interactions catalyzing biomass conversion to energy need to be identified. Here, we present a two-year time series associating microbial metabolism and physicochemistry in a full-scale wastewater treatment plant. By creating a co-occurrence network with thousands of time-resolved microbial populations from over 100 samples spanning four operating configurations, known and novel microbial consortia with potential to drive methane production were identified. Interactions between these populations were further resolved in relation to specific process configurations by mapping metagenome assembled genomes and cognate gene expression data onto the network. Prominent interactions included transcriptionally active Methanolinea methanogens and syntrophic benzoate oxidizing Syntrophorhabdus, as well as a Methanoregulaceae population and putative syntrophic acetate oxidizing bacteria affiliated with Bateroidetes (Tenuifilaceae) expressing the glycine cleavage bypass of the Wood-Ljungdahl pathway.

A predicted CRISPR-mediated symbiosis between uncultivated archaea

CRISPR-Cas systems defend prokaryotic cells from invasive DNA of viruses, plasmids and other mobile genetic elements. Here, we show using metagenomics, metatranscriptomics and single-cell genomics that CRISPR systems of widespread, uncultivated archaea can also target chromosomal DNA of archaeal episymbionts of the DPANN superphylum. Using meta-omics datasets from Crystal Geyser and Horonobe Underground Research Laboratory, we find that CRISPR spacers of the hosts Candidatus Altiarchaeum crystalense and Ca. A. horonobense, respectively, match putative essential genes in their episymbionts' genomes of the genus Ca. Huberiarchaeum and that some of these spacers are expressed in situ. Metabolic interaction modelling also reveals complementation between host-episymbiont systems, on the basis of which we propose that episymbionts are either parasitic or mutualistic depending on the genotype of the host. By expanding our analysis to 7,012 archaeal genomes, we suggest that CRISPR-Cas targeting of genomes associated with symbiotic archaea evolved independently in various archaeal lineages.

Sedimenticola hydrogenitrophicus sp. nov. a chemolithoautotrophic bacterium isolated from a terrestrial mud volcano, and proposal of Sedimenticolaceae fam. nov. in the order Chromatiales

Chemolithoautotrophic microorganisms can play a significant role in the biogeochemical cycling of elements in deep-subsurface-associated environments. A novel facultatively anaerobic lithoautotrophic bacteria (strains SB48T and SN1189) were isolated from terrestrial mud volcanoes (Krasnodar Krai, Russia). Cells of the strains were straight motile rods. Growth was observed at temperatures up to 35 °C (optimum at 30 °C), pH 6.0-8.5 (optimum at pH 7.5) and NaCl concentrations of 0.5-4.0% (w/v) (optimum at 1.5-2.0% (w/v)). The isolates grew chemolithoautotrophically with molecular hydrogen or thiosulfate as an electron donor, nitrate as an electron acceptor and CO2/HCO3- as a carbon source. They also grew with organic acids, ethanol, yeast extract and peptone. The isolates were capable of either anaerobic respiration with nitrate or nitrous oxide as the electron acceptors or aerobic respiration under microaerobic condition. The total size of the genome of strains SB48T and SN1189 was 4.71 and 5.13 Mbp, respectively. Based on phenotypic and phylogenetic characteristics, strains SB48T and SN1189 represent a novel species of the genus Sedimenticola, S. hydrogenitrophicus (the type strain is SB48T = KCTC 25568 T = VKM B-3680 T). The new isolates are the first representatives of the genus Sedimenticola isolated from a terrestrial ecosystem. Based on phylogenomic reconstruction we propose to include the genus Sedimenticola and the related genera into a new family Sedimenticolaceae fam. nov. within the order Chromatiales.

Genome-scale metabolic reconstruction of 7,302 human microorganisms for personalized medicine

The human microbiome influences the efficacy and safety of a wide variety of commonly prescribed drugs. Designing precision medicine approaches that incorporate microbial metabolism would require strain- and molecule-resolved, scalable computational modeling. Here, we extend our previous resource of genome-scale metabolic reconstructions of human gut microorganisms with a greatly expanded version. AGORA2 (assembly of gut organisms through reconstruction and analysis, version 2) accounts for 7,302 strains, includes strain-resolved drug degradation and biotransformation capabilities for 98 drugs, and was extensively curated based on comparative genomics and literature searches. The microbial reconstructions performed very well against three independently assembled experimental datasets with an accuracy of 0.72 to 0.84, surpassing other reconstruction resources and predicted known microbial drug transformations with an accuracy of 0.81. We demonstrate that AGORA2 enables personalized, strain-resolved modeling by predicting the drug conversion potential of the gut microbiomes from 616 patients with colorectal cancer and controls, which greatly varied between individuals and correlated with age, sex, body mass index and disease stages. AGORA2 serves as a knowledge base for the human microbiome and paves the way to personalized, predictive analysis of host-microbiome metabolic interactions.

SAMBA: Structure-Learning of Aquaculture Microbiomes Using a Bayesian Approach

Gut microbiomes of fish species consist of thousands of bacterial taxa that interact among each other, their environment, and the host. These complex networks of interactions are regulated by a diverse range of factors, yet little is known about the hierarchy of these interactions. Here, we introduce SAMBA (Structure-Learning of Aquaculture Microbiomes using a Bayesian Approach), a computational tool that uses a unified Bayesian network approach to model the network structure of fish gut microbiomes and their interactions with biotic and abiotic variables associated with typical aquaculture systems. SAMBA accepts input data on microbial abundance from 16S rRNA amplicons as well as continuous and categorical information from distinct farming conditions. From this, SAMBA can create and train a network model scenario that can be used to (i) infer information of how specific farming conditions influence the diversity of the gut microbiome or pan-microbiome, and (ii) predict how the diversity and functional profile of that microbiome would change under other variable conditions. SAMBA also allows the user to visualize, manage, edit, and export the acyclic graph of the modelled network. Our study presents examples and test results of Bayesian network scenarios created by SAMBA using data from a microbial synthetic community, and the pan-microbiome of gilthead sea bream (Sparus aurata) in different feeding trials. It is worth noting that the usage of SAMBA is not limited to aquaculture systems as it can be used for modelling microbiome-host network relationships of any vertebrate organism, including humans, in any system and/or ecosystem.

A conserved family of immune effectors cleaves cellular ATP upon viral infection

During viral infection, cells can deploy immune strategies that deprive viruses of molecules essential for their replication. Here, we report a family of immune effectors in bacteria that, upon phage infection, degrade cellular adenosine triphosphate (ATP) and deoxyadenosine triphosphate (dATP) by cleaving the N-glycosidic bond between the adenine and sugar moieties. These ATP nucleosidase effectors are widely distributed within multiple bacterial defense systems, including cyclic oligonucleotide-based antiviral signaling systems (CBASS), prokaryotic argonautes, and nucleotide-binding leucine-rich repeat (NLR)-like proteins, and we show that ATP and dATP degradation during infection halts phage propagation. By analyzing homologs of the immune ATP nucleosidase domain, we discover and characterize Detocs, a family of bacterial defense systems with a two-component phosphotransfer-signaling architecture. The immune ATP nucleosidase domain is also encoded within diverse eukaryotic proteins with immune-like architectures, and we show biochemically that eukaryotic homologs preserve the ATP nucleosidase activity. Our findings suggest that ATP and dATP degradation is a cell-autonomous innate immune strategy conserved across the tree of life.