Efam: an expanded, metaproteome-supported HMM profile database of viral protein families

Motivation: Viruses infect, reprogram and kill microbes, leading to profound ecosystem consequences, from elemental cycling in oceans and soils to microbiome-modulated diseases in plants and animals. Although metagenomic datasets are increasingly available, identifying viruses in them is challenging due to poor representation and annotation of viral sequences in databases. Results: Here, we establish efam, an expanded collection of Hidden Markov Model (HMM) profiles that represent viral protein families conservatively identified from the Global Ocean Virome 2.0 dataset. This resulted in 240 311 HMM profiles, each with at least 2 protein sequences, making efam >7-fold larger than the next largest, pan-ecosystem viral HMM profile database. Adjusting the criteria for viral contig confidence from 'conservative' to 'eXtremely Conservative' resulted in 37 841 HMM profiles in our efam-XC database. To assess the value of this resource, we integrated efam-XC into VirSorter viral discovery software to discover viruses from less-studied, ecologically distinct oxygen minimum zone (OMZ) marine habitats. This expanded database led to an increase in viruses recovered from every tested OMZ virome by ∼24% on average (up to ∼42%) and especially improved the recovery of often-missed shorter contigs (<5 kb). Additionally, to help elucidate lesser-known viral protein functions, we annotated the profiles using multiple databases from the DRAM pipeline and virion-associated metaproteomic data, which doubled the number of annotations obtainable by standard, single-database annotation approaches. Together, these marine resources (efam and efam-XC) are provided as searchable, compressed HMM databases that will be updated bi-annually to help maximize viral sequence discovery and study from any ecosystem

Biosynthetic potential of the global ocean microbiome

8 pages, 4 figures, supplementary information https://doi.org/10.1038/s41586-022-04862-3.-- This Article is contribution number 130 of Tara OceansNatural microbial communities are phylogenetically and metabolically diverse. In addition to underexplored organismal groups1, this diversity encompasses a rich discovery potential for ecologically and biotechnologically relevant enzymes and biochemical compounds2,3. However, studying this diversity to identify genomic pathways for the synthesis of such compounds4 and assigning them to their respective hosts remains challenging. The biosynthetic potential of microorganisms in the open ocean remains largely uncharted owing to limitations in the analysis of genome-resolved data at the global scale. Here we investigated the diversity and novelty of biosynthetic gene clusters in the ocean by integrating around 10,000 microbial genomes from cultivated and single cells with more than 25,000 newly reconstructed draft genomes from more than 1,000 seawater samples. These efforts revealed approximately 40,000 putative mostly new biosynthetic gene clusters, several of which were found in previously unsuspected phylogenetic groups. Among these groups, we identified a lineage rich in biosynthetic gene clusters (‘Candidatus Eudoremicrobiaceae’) that belongs to an uncultivated bacterial phylum and includes some of the most biosynthetically diverse microorganisms in this environment. From these, we characterized the phospeptin and pythonamide pathways, revealing cases of unusual bioactive compound structure and enzymology, respectively. Together, this research demonstrates how microbiomics-driven strategies can enable the investigation of previously undescribed enzymes and natural products in underexplored microbial groups and environmentsThis work was supported by funding from the ETH and the Helmut Horten Foundation; the Swiss National Science Foundation (SNSF) through project grants 205321_184955 to S.S., 205320_185077 to J.P. and the NCCR Microbiomes (51NF40_180575) to S.S.; by the Gordon and Betty Moore Foundation (https://doi.org/10.37807/GBMF9204) and the European Union’s Horizon 2020 research and innovation programme under grant agreement no. 101000392 (MARBLES) to J.P.; by an ETH research grant ETH-21 18-2 to J.P.; and by the Peter and Traudl Engelhorn Foundation and by the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement no. 897571 to C.C.F. S.L.R. was supported by an ETH Zurich postdoctoral fellowship 20-1 FEL-07. M.L., L.M.C. and G.Z. were supported by EMBL Core Funding and the German Research Foundation (DFG, Deutsche Forschungsgemeinschaft, project no. 395357507, SFB 1371 to G.Z.). M.B.S. was supported by the NSF grant OCE#1829831. C.B. was supported by the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant agreement Diatomic, no. 835067). S.G.A. was supported by the Spanish Ministry of Economy and Competitiveness (PID2020-116489RB-I00). M.K. and H.M. were funded by the SNSF grant 407540_167331 as part of the Swiss National Research Programme 75 ‘Big Data’. M.K., H.M. and A.K. are also partially funded by ETH core funding (to G. Rätsch)With the institutional support of the ‘Severo Ochoa Centre of Excellence’ accreditation (CEX2019-000928-S)Peer reviewe

The association of obesity with cardiovascular events in patients with peripheral artery disease

Objectives: This systematic review aimed to summarise published evidence that has assessed the association of obesity with major cardiovascular events (CVEs) (non-fatal myocardial infarction, non-fatal stroke, cardiovascular death) in patients with peripheral artery disease (PAD). Methods: Studies investigating the association of markers of obesity with CVEs were identified by searching the PUBMED database. To be eligible for inclusion studies had to report an established measure of adiposity, i.e. body mass index (BMI), waist circumference (WC), waist-to-hip ratio (WHR) or an imaging technique to quantify adipose distribution. Results: A total of 9319 patients with PAD were followed for a mean of 1.0-5.7 years in the 7 studies identified. Four studies assessed BMI; one study assessed BMI and WC; one study assessed BMI, WC and WHR; one study assessed WHR. Both of the studies which assessed multiple adipose measures reported a more powerful positive association of WC with CVEs than BMI; one study reported less CVEs in obese subjects as defined by BMI; one study reported a negative association of overweight but not obesity, defined by BMI, with CVEs; one study reported an inverse association of BMI >20 with CVEs; one study did not find a significant association between WHR and cardiovascular death; one study did not find a significant association between BMI and CVEs. Meta-analysis of reported risk ratios found a mild positive association between combined measures of obesity and CVEs in patients with PAD (RR 1.09; 95%CI 1.03-1.16, P=0.006; random effects model). Conclusion: This meta-analysis suggests that obesity is an independent risk factor for CVEs in patients with PAD however larger and more homogeneous studies using equivalent anthropometric measures are needed for more definitive evidence

The association of genetic variants of matrix metalloproteinases with abdominal aortic aneurysm: a systematic review and meta-analysis

Context: Aberrant matrix turnover is believed to play a key role in the pathogenesis of abdominal aortic aneurysm (AAA). Matrix metalloproteinases (MMPs) and their inhibitors (tissue inhibitor of metalloproteinases; TIMPs) are important enzymes in the control of extracellular matrix remodelling.\ud \ud Objective: The aim of this study was to investigate if single nucleotide polymorphisms (SNPs) within MMP and TIMP gene families are associated with the presence of AAA.\ud \ud Data sources: We performed a search of MEDLINE and EMBASE databases on the 21st November 2012.\ud \ud Study selection: Case-control studies assessing the association of at least one SNP in a MMP or TIMP gene with AAA were included.\ud \ud Data extraction: Data were independently extracted by two reviewers. A random effects model was used to calculate combined odds ratios for commonly investigated SNPs according to dominant, recessive and additive inheritance.\ud \ud Results: Thirteen studies examining 58 SNPs within 10 different MMP and TIMP genes were identified. Eight SNPs were assessed in at least 3 studies (combined sample size ranging from 141- 2191 AAA cases and 340-2013 controls) and included in a meta-analysis. Results on 1258 cases and 1406 controls for MMP3 rs3025058 showed an association with AAA presence; best described by a dominant pattern of inheritance (OR=1.48 95%CI 1.23 – 1.78, p=3.95×10-5). No associations with AAA were identified for other SNPs assessed in this study including rs1799750 (MMP1), rs3918242 (MMP9), rs486055 (MMP10), rs2276109 (MMP12), rs2252070 (MMP13), rs4898 (TIMP1) or rs9619311 (TIMP3).\ud \ud Conclusion: A common SNP within the MMP3 promoter region, previously suggested to increase MMP3 expression, appears to be a moderate risk factor for AAA

Sustainable Aviation Fuel from Hydrothermal Liquefaction of Wet Wastes

Hydrothermal liquefaction (HTL) uses heat and pressure to liquefy the organic matter in biomass/waste feedstocks to produce biocrude. When hydrotreated the biocrude is converted into transportation fuels including sustainable aviation fuel (SAF). Further, by liquifying the organic matter in wet wastes such as sewage sludge, manure, and food waste, HTL can prevent landfilling or other disposal methods such as anerobic digestion, or incineration. A significant roadblock to the development of a new route for SAF is the strict approval process, and the large volumes required (>400 L) for testing. Tier α and β testing can predict some of the properties required for ASTM testing with <400 mL samples. The current study is the first to investigate the potential for utilizing wet-waste HTL biocrude (WWHTLB) as an SAF feedstock. Herein, several WWHTLB samples were produced from food waste, sewage sludge, and fats, oils, and grease, and subsequently hydrotreated and distilled to produce SAF samples. The fuels (both undistilled and distilled samples) were analyzed via elemental and 2D-GC-MS. Herein, we report the Tier α and β analysis of an SAF sample derived originally from a WWHTLB. The results of this work indicate that the upgraded WWHTLB material exhibits key fuel properties, including carbon number distribution, distillation profile, surface tension, density, viscosity, heat of combustion, and flash point, which all fall within the required range for aviation fuel. WWHTLB has therefore been shown to be a promising candidate feedstock for the production of SAF

Synthesizing Signaling Pathways from Temporal Phosphoproteomic Data

We present a method for automatically discovering signaling pathways from time-resolved phosphoproteomic data. The Temporal Pathway Synthesizer (TPS) algorithm uses constraint-solving techniques first developed in the context of formal verification to explore paths in an interaction network. It systematically eliminates all candidate structures for a signaling pathway where a protein is activated or inactivated before its upstream regulators. The algorithm can model more than one hundred thousand dynamic phosphosites and can discover pathway members that are not differentially phosphorylated. By analyzing temporal data, TPS defines signaling cascades without needing to experimentally perturb individual proteins. It recovers known pathways and proposes pathway connections when applied to the human epidermal growth factor and yeast osmotic stress responses. Independent kinase mutant studies validate predicted substrates in the TPS osmotic stress pathway. Köksal et al. present a computational technique, the temporal pathway synthesizer (TPS), that combines time series global phosphoproteomic data and protein-protein interaction networks to reconstruct the vast signaling pathways that control post-translational modifications.National Science Foundation (U.S.) ( grant DBI-1553206)National Institutes of Health (U.S.) (training grant T32-HL007312)National Institutes of Health (U.S.) (grant U01-CA184898)National Institutes of Health (U.S.) (grant U54-NS09104

Mapping substrate use across a permafrost thaw gradient

Permafrost thaw in northern peatlands is likely to create a positive feedback to climate change, as microbes transform soil carbon (C) into carbon dioxide (CO2) or methane (CH4). While the microbiome's encoded C-processing potential changes with thaw, the impact on substrate utilization and gas emissions is less well characterized. We therefore examined microbial C-cycling dynamics from a partially thawed Sphagnum-dominated bog to a fully thawed sedge-dominated fen in Stordalen Mire (68.35°N, 19.05°E), Sweden. We profiled C substrate utilization diversity and extent by Biolog Ecoplates™, then tested substrate-specific hypotheses by targeted additions (of glucose, the short chain fatty acids (SCFAs) acetate and butyrate, and the organic acids galacturonic acid and p-hydroxybenzoic acid, all at field-relevant concentrations) under anaerobic conditions at 15 °C. In parallel we characterized microbiomes (via 16S rRNA amplicon sequencing and quantitative polymerase chain reaction) and C gas emissions. The fen exhibited a higher substrate use diversity and faster rate of overall substrate utilization than in the bog, based on Biolog Ecoplate™ incubations. Simple glucose additions (akin to a positive control) to peat microcosms fueled fermentation as expected (reflected in enriched fermenter lineages, their inferred metabolisms, and CO2 production), but also showed potential priming of anaerobic phenol degradation in the bog. Addition of SCFAs to bog and fen produced the least change in lineages and in CO2, and modest suppression of CH4 primarily in the fen, attributed to inhibition. Addition of both organic acids greatly increased the CO2:CH4 ratio in the deep peats but had distinct individual gas dynamics and impacts on microbiota. Both organic acids appeared to act as both C source and as a microbial inhibitor, with galacturonic acid also likely playing a role in electron transfer or acceptance. Collectively, these results support the importance of aboveground-belowground linkages - and in particular the role of Sphagnum spp.- in supplying substrates and inhibitors that drive microbiome assembly and C processing in these dynamically changing systems. In addition, they highlight an important temporal dynamic: responses on the short time scale of incubations (which would reflect transition conditions in the field) differ from those evident at the longer scales of habitat transition, in ways consequential to C gas emissions. In the short term, substrate addition response reflected microbiome legacy (e.g., bog communities were slower to process C and better tolerated inhibitors than fen communities) but led to little overall increase in C gas production (and a high skew to CO2). At the longer time scale of bog and fen thaw stages (which are used to represent these systems in models) the concomitant shifts in plants, hydrology and microbiota attenuate microbiome legacy impacts on substrate processing and C gas emissions over time. As habitat transition areas expand under accelerating change, we hypothesize an increased role of microbiome legacy in the landscape overall, leading to a lag in the increase of CH4 emissions expected from fen expansion.Open access articleThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]

efam: an expanded, metaproteome-supported HMM profile database of viral protein families.

MotivationViruses infect, reprogram, and kill microbes, leading to profound ecosystem consequences, from elemental cycling in oceans and soils to microbiome-modulated diseases in plants and animals. Although metagenomic datasets are increasingly available, identifying viruses in them is challenging due to poor representation and annotation of viral sequences in databases.ResultsHere we establish efam, an expanded collection of Hidden Markov Model (HMM) profiles that represent viral protein families conservatively identified from the Global Ocean Virome 2.0 dataset. This resulted in 240,311 HMM profiles, each with at least 2 protein sequences, making efam &gt;7-fold larger than the next largest, pan-ecosystem viral HMM profile database. Adjusting the criteria for viral contig confidence from "conservative" to "eXtremely Conservative" resulted in 37,841 HMM profiles in our efam-XC database. To assess the value of this resource, we integrated efam-XC into VirSorter viral discovery software to discover viruses from less-studied, ecologically distinct oxygen minimum zone (OMZ) marine habitats. This expanded database led to an increase in viruses recovered from every tested OMZ virome by ∼24% on average (up to ∼42%) and especially improved the recovery of often-missed shorter contigs (&lt;5 kb). Additionally, to help elucidate lesser-known viral protein functions, we annotated the profiles using multiple databases from the DRAM pipeline and virion-associated metaproteomic data, which doubled the number of annotations obtainable by standard, single-database annotation approaches. Together, these marine resources (efam and efam-XC) are provided as searchable, compressed HMM databases that will be updated bi-annually to help maximize viral sequence discovery and study from any ecosystem.AvailabilityThe resources are available on the iVirus platform at (doi.org/10.25739/9vze-4143).Supplementary informationSupplementary data are available at Bioinformatics online

Long-read powered viral metagenomics in the oligotrophic Sargasso Sea

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

Methylotrophy in the Mire: direct and indirect routes for methane production in thawing permafrost

ABSTRACTWhile wetlands are major sources of biogenic methane (CH4), our understanding of resident microbial metabolism is incomplete, which compromises the prediction of CH4 emissions under ongoing climate change. Here, we employed genome-resolved multi-omics to expand our understanding of methanogenesis in the thawing permafrost peatland of Stordalen Mire in Arctic Sweden. In quadrupling the genomic representation of the site’s methanogens and examining their encoded metabolism, we revealed that nearly 20% of the metagenome-assembled genomes (MAGs) encoded the potential for methylotrophic methanogenesis. Further, 27% of the transcriptionally active methanogens expressed methylotrophic genes; for Methanosarcinales and Methanobacteriales MAGs, these data indicated the use of methylated oxygen compounds (e.g., methanol), while for Methanomassiliicoccales, they primarily implicated methyl sulfides and methylamines. In addition to methanogenic methylotrophy, >1,700 bacterial MAGs across 19 phyla encoded anaerobic methylotrophic potential, with expression across 12 phyla. Metabolomic analyses revealed the presence of diverse methylated compounds in the Mire, including some known methylotrophic substrates. Active methylotrophy was observed across all stages of a permafrost thaw gradient in Stordalen, with the most frozen non-methanogenic palsa found to host bacterial methylotrophy and the partially thawed bog and fully thawed fen seen to house both methanogenic and bacterial methylotrophic activities. Methanogenesis across increasing permafrost thaw is thus revised from the sole dominance of hydrogenotrophic production and the appearance of acetoclastic at full thaw to consider the co-occurrence of methylotrophy throughout. Collectively, these findings indicate that methanogenic and bacterial methylotrophy may be an important and previously underappreciated component of carbon cycling and emissions in these rapidly changing wetland habitats.IMPORTANCEWetlands are the biggest natural source of atmospheric methane (CH4) emissions, yet we have an incomplete understanding of the suite of microbial metabolism that results in CH4 formation. Specifically, methanogenesis from methylated compounds is excluded from all ecosystem models used to predict wetland contributions to the global CH4 budget. Though recent studies have shown methylotrophic methanogenesis to be active across wetlands, the broad climatic importance of the metabolism remains critically understudied. Further, some methylotrophic bacteria are known to produce methanogenic by-products like acetate, increasing the complexity of the microbial methylotrophic metabolic network. Prior studies of Stordalen Mire have suggested that methylotrophic methanogenesis is irrelevant in situ and have not emphasized the bacterial capacity for metabolism, both of which we countered in this study. The importance of our findings lies in the significant advancement toward unraveling the broader impact of methylotrophs in wetland methanogenesis and, consequently, their contribution to the terrestrial global carbon cycle