CheckM2: a rapid, scalable and accurate tool for assessing microbial genome quality using machine learning.

Advances in sequencing technologies and bioinformatics tools have dramatically increased the recovery rate of microbial genomes from metagenomic data. Assessing the quality of metagenome-assembled genomes (MAGs) is a critical step before downstream analysis. Here, we present CheckM2, an improved method of predicting genome quality of MAGs using machine learning. Using synthetic and experimental data, we demonstrate that CheckM2 outperforms existing tools in both accuracy and computational speed. In addition, CheckM2's database can be rapidly updated with new high-quality reference genomes, including taxa represented only by a single genome. We also show that CheckM2 accurately predicts genome quality for MAGs from novel lineages, even for those with reduced genome size (for example, Patescibacteria and the DPANN superphylum). CheckM2 provides accurate genome quality predictions across bacterial and archaeal lineages, giving increased confidence when inferring biological conclusions from MAGs.

Genome-centric view of carbon processing in thawing permafrost.

As global temperatures rise, large amounts of carbon sequestered in permafrost are becoming available for microbial degradation. Accurate prediction of carbon gas emissions from thawing permafrost is limited by our understanding of these microbial communities. Here we use metagenomic sequencing of 214 samples from a permafrost thaw gradient to recover 1,529 metagenome-assembled genomes, including many from phyla with poor genomic representation. These genomes reflect the diversity of this complex ecosystem, with genus-level representatives for more than sixty per cent of the community. Meta-omic analysis revealed key populations involved in the degradation of organic matter, including bacteria whose genomes encode a previously undescribed fungal pathway for xylose degradation. Microbial and geochemical data highlight lineages that correlate with the production of greenhouse gases and indicate novel syntrophic relationships. Our findings link changing biogeochemistry to specific microbial lineages involved in carbon processing, and provide key information for predicting the effects of climate change on permafrost systems.

Sequenceserver: A Modern Graphical User Interface for Custom BLAST Databases.

Comparing newly obtained and previously known nucleotide and amino-acid sequences underpins modern biological research. BLAST is a well-established tool for such comparisons but is challenging to use on new data sets. We combined a user-centric design philosophy with sustainable software development approaches to create Sequenceserver, a tool for running BLAST and visually inspecting BLAST results for biological interpretation. Sequenceserver uses simple algorithms to prevent potential analysis errors and provides flexible text-based and visual outputs to support researcher productivity. Our software can be rapidly installed for use by individuals or on shared servers.

Methane dynamics regulated by microbial community response to permafrost thaw.

Permafrost contains about 50% of the global soil carbon. It is thought that the thawing of permafrost can lead to a loss of soil carbon in the form of methane and carbon dioxide emissions. The magnitude of the resulting positive climate feedback of such greenhouse gas emissions is still unknown and may to a large extent depend on the poorly understood role of microbial community composition in regulating the metabolic processes that drive such ecosystem-scale greenhouse gas fluxes. Here we show that changes in vegetation and increasing methane emissions with permafrost thaw are associated with a switch from hydrogenotrophic to partly acetoclastic methanogenesis, resulting in a large shift in the δ(13)C signature (10-15‰) of emitted methane. We used a natural landscape gradient of permafrost thaw in northern Sweden as a model to investigate the role of microbial communities in regulating methane cycling, and to test whether a knowledge of community dynamics could improve predictions of carbon emissions under loss of permafrost. Abundance of the methanogen Candidatus 'Methanoflorens stordalenmirensis' is a key predictor of the shifts in methane isotopes, which in turn predicts the proportions of carbon emitted as methane and as carbon dioxide, an important factor for simulating the climate feedback associated with permafrost thaw in global models. By showing that the abundance of key microbial lineages can be used to predict atmospherically relevant patterns in methane isotopes and the proportion of carbon metabolized to methane during permafrost thaw, we establish a basis for scaling changing microbial communities to ecosystem isotope dynamics. Our findings indicate that microbial ecology may be important in ecosystem-scale responses to global change.

GraftM: a tool for scalable, phylogenetically informed classification of genes within metagenomes.

Large-scale metagenomic datasets enable the recovery of hundreds of population genomes from environmental samples. However, these genomes do not typically represent the full diversity of complex microbial communities. Gene-centric approaches can be used to gain a comprehensive view of diversity by examining each read independently, but traditional pairwise comparison approaches typically over-classify taxonomy and scale poorly with increasing metagenome and database sizes. Here we introduce GraftM, a tool that uses gene specific packages to rapidly identify gene families in metagenomic data using hidden Markov models (HMMs) or DIAMOND databases, and classifies these sequences using placement into pre-constructed gene trees. The speed and accuracy of GraftM was benchmarked with in silico and in vitro mock communities using taxonomic markers, and was found to have higher accuracy at the family level with a processing time 2.0-3.7× faster than currently available software. Exploration of a wetland metagenome using 16S rRNA- and methyl-coenzyme M reductase (McrA)-specific gpkgs revealed taxonomic and functional shifts across a depth gradient. Analysis of the NCBI nr database using the McrA gpkg allowed the detection of novel sequences belonging to phylum-level lineages. A growing collection of gpkgs is available online (https://github.com/geronimp/graftM_gpkgs), where curated packages can be uploaded and exchanged.

OrfM: a fast open reading frame predictor for metagenomic data.

UNLABELLED: Finding and translating stretches of DNA lacking stop codons is a task common in the analysis of sequence data. However, the computational tools for finding open reading frames are sufficiently slow that they are becoming a bottleneck as the volume of sequence data grows. This computational bottleneck is especially problematic in metagenomics when searching unassembled reads, or screening assembled contigs for genes of interest. Here, we present OrfM, a tool to rapidly identify open reading frames (ORFs) in sequence data by applying the Aho-Corasick algorithm to find regions uninterrupted by stop codons. Benchmarking revealed that OrfM finds identical ORFs to similar tools ('GetOrf' and 'Translate') but is four-five times faster. While OrfM is sequencing platform-agnostic, it is best suited to large, high quality datasets such as those produced by Illumina sequencers. AVAILABILITY AND IMPLEMENTATION: Source code and binaries are freely available for download at http://github.com/wwood/OrfM or through GNU Guix under the LGPL 3+ license. OrfM is implemented in C and supported on GNU/Linux and OSX. CONTACTS: b.woodcroft@uq.edu.au SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

The Amphimedon queenslandica genome and the evolution of animal complexity.

Sponges are an ancient group of animals that diverged from other metazoans over 600 million years ago. Here we present the draft genome sequence of Amphimedon queenslandica, a demosponge from the Great Barrier Reef, and show that it is remarkably similar to other animal genomes in content, structure and organization. Comparative analysis enabled by the sequencing of the sponge genome reveals genomic events linked to the origin and early evolution of animals, including the appearance, expansion and diversification of pan-metazoan transcription factor, signalling pathway and structural genes. This diverse 'toolkit' of genes correlates with critical aspects of all metazoan body plans, and comprises cell cycle control and growth, development, somatic- and germ-cell specification, cell adhesion, innate immunity and allorecognition. Notably, many of the genes associated with the emergence of animals are also implicated in cancer, which arises from defects in basic processes associated with metazoan multicellularity.

Early origins and evolution of microRNAs and Piwi-interacting RNAs in animals.

In bilaterian animals, such as humans, flies and worms, hundreds of microRNAs (miRNAs), some conserved throughout bilaterian evolution, collectively regulate a substantial fraction of the transcriptome. In addition to miRNAs, other bilaterian small RNAs, known as Piwi-interacting RNAs (piRNAs), protect the genome from transposons. Here we identify small RNAs from animal phyla that diverged before the emergence of the Bilateria. The cnidarian Nematostella vectensis (starlet sea anemone), a close relative to the Bilateria, possesses an extensive repertoire of miRNA genes, two classes of piRNAs and a complement of proteins specific to small-RNA biology comparable to that of humans. The poriferan Amphimedon queenslandica (sponge), one of the simplest animals and a distant relative of the Bilateria, also possesses miRNAs, both classes of piRNAs and a full complement of the small-RNA machinery. Animal miRNA evolution seems to have been relatively dynamic, with precursor sizes and mature miRNA sequences differing greatly between poriferans, cnidarians and bilaterians. Nonetheless, miRNAs and piRNAs have been available as classes of riboregulators to shape gene expression throughout the evolution and radiation of animal phyla.

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

While 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.

Borg extrachromosomal elements of methane-oxidizing archaea have conserved and expressed genetic repertoires.

Borgs are huge extrachromosomal elements (ECE) of anaerobic methane-consuming "Candidatus Methanoperedens" archaea. Here, we used nanopore sequencing to validate published complete genomes curated from short reads and to reconstruct new genomes. 13 complete and four near-complete linear genomes share 40 genes that define a largely syntenous genome backbone. We use these conserved genes to identify new Borgs from peatland soil and to delineate Borg phylogeny, revealing two major clades. Remarkably, Borg genes encoding nanowire-like electron-transferring cytochromes and cell surface proteins are more highly expressed than those of host Methanoperedens, indicating that Borgs augment the Methanoperedens activity in situ. We reconstructed the first complete 4.00 Mbp genome for a Methanoperedens that is inferred to be a Borg host and predicted its methylation motifs, which differ from pervasive TC and CC methylation motifs of the Borgs. Thus, methylation may enable Methanoperedens to distinguish their genomes from those of Borgs. Very high Borg to Methanoperedens ratios and structural predictions suggest that Borgs may be capable of encapsulation. The findings clearly define Borgs as a distinct class of ECE with shared genomic signatures, establish their diversification from a common ancestor with genetic inheritance, and raise the possibility of periodic existence outside of host cells.

Microbial polyphenol metabolism is part of the thawing permafrost carbon cycle.

With rising global temperatures, permafrost carbon stores are vulnerable to microbial degradation. The enzyme latch theory states that polyphenols should accumulate in saturated peatlands due to diminished phenol oxidase activity, inhibiting resident microbes and promoting carbon stabilization. Pairing microbiome and geochemical measurements along a permafrost thaw-induced saturation gradient in Stordalen Mire, a model Arctic peatland, we confirmed a negative relationship between phenol oxidase expression and saturation but failed to support other trends predicted by the enzyme latch. To inventory alternative polyphenol removal strategies, we built CAMPER, a gene annotation tool leveraging polyphenol enzyme knowledge gleaned across microbial ecosystems. Applying CAMPER to genome-resolved metatranscriptomes, we identified genes for diverse polyphenol-active enzymes expressed by various microbial lineages under a range of redox conditions. This shifts the paradigm that polyphenols stabilize carbon in saturated soils and highlights the need to consider both oxic and anoxic polyphenol metabolisms to understand carbon cycling in changing ecosystems.

Biogem: an effective tool-based approach for scaling up open source software development in bioinformatics.

SUMMARY: Biogem provides a software development environment for the Ruby programming language, which encourages community-based software development for bioinformatics while lowering the barrier to entry and encouraging best practices. Biogem, with its targeted modular and decentralized approach, software generator, tools and tight web integration, is an improved general model for scaling up collaborative open source software development in bioinformatics. AVAILABILITY: Biogem and modules are free and are OSS. Biogem runs on all systems that support recent versions of Ruby, including Linux, Mac OS X and Windows. Further information at http://www.biogems.info. A tutorial is available at http://www.biogems.info/howto.html CONTACT: bonnal@ingm.org.

Taxonomic and carbon metabolic diversification of Bathyarchaeia during its coevolution history with early Earth surface environment.

Bathyarchaeia, as one of the most abundant microorganisms on Earth, play vital roles in the global carbon cycle. However, our understanding of their origin, evolution, and ecological functions remains poorly constrained. Here, we present the largest dataset of Bathyarchaeia metagenome assembled genome to date and reclassify Bathyarchaeia into eight order-level units corresponding to the former subgroup system. Highly diversified and versatile carbon metabolisms were found among different orders, particularly atypical C1 metabolic pathways, indicating that Bathyarchaeia represent overlooked important methylotrophs. Molecular dating results indicate that Bathyarchaeia diverged at ~3.3 billion years, followed by three major diversifications at ~3.0, ~2.5, and ~1.8 to 1.7 billion years, likely driven by continental emergence, growth, and intensive submarine volcanism, respectively. The lignin-degrading Bathyarchaeia clade emerged at ~300 million years perhaps contributed to the sharply decreased carbon sequestration rate during the Late Carboniferous period. The evolutionary history of Bathyarchaeia potentially has been shaped by geological forces, which, in turn, affected Earth's surface environment.

Anaerobic methanotroph 'Candidatus Methanoperedens nitroreducens' has a pleomorphic life cycle.

'Candidatus Methanoperedens' are anaerobic methanotrophic (ANME) archaea with global importance to methane cycling. Here meta-omics and fluorescence in situ hybridization (FISH) were applied to characterize a bioreactor dominated by 'Candidatus Methanoperedens nitroreducens' performing anaerobic methane oxidation coupled to nitrate reduction. Unexpectedly, FISH revealed the stable co-existence of two 'Ca. M. nitroreducens' morphotypes: the archetypal coccobacilli microcolonies and previously unreported planktonic rods. Metagenomic analysis showed that the 'Ca. M. nitroreducens' morphotypes were genomically identical but had distinct gene expression profiles for proteins associated with carbon metabolism, motility and cell division. In addition, a third distinct phenotype was observed, with some coccobacilli 'Ca. M. nitroreducens' storing carbon as polyhydroxyalkanoates. The phenotypic variation of 'Ca. M. nitroreducens' probably aids their survival and dispersal in the face of sub-optimal environmental conditions. These findings further demonstrate the remarkable ability of members of the 'Ca. Methanoperedens' to adapt to their environment.

A functional microbiome catalog crowdsourced from North American rivers.

Predicting elemental cycles and maintaining water quality under increasing anthropogenic influence requires understanding the spatial drivers of river microbiomes. However, the unifying microbial processes governing river biogeochemistry are hindered by a lack of genome-resolved functional insights and sampling across multiple rivers. Here we employed a community science effort to accelerate the sampling, sequencing, and genome-resolved analyses of river microbiomes to create the Genome Resolved Open Watersheds database (GROWdb). This resource profiled the identity, distribution, function, and expression of thousands of microbial genomes across rivers covering 90% of United States watersheds. Specifically, GROWdb encompasses 1,469 microbial species from 27 phyla, including novel lineages from 10 families and 128 genera, and defines the core river microbiome for the first time at genome level. GROWdb analyses coupled to extensive geospatial information revealed local and regional drivers of microbial community structuring, while also presenting a myriad of foundational hypotheses about ecosystem function. Building upon the previously conceived River Continuum Concept 1 , we layer on microbial functional trait expression, which suggests the structure and function of river microbiomes is predictable. We make GROWdb available through various collaborative cyberinfrastructures 2, 3 so that it can be widely accessed across disciplines for watershed predictive modeling and microbiome-based management practices.

Marked changes in neuropeptide expression accompany broadcast spawnings in the gastropod Haliotis asinina.

INTRODUCTION: A huge diversity of marine species reproduce by synchronously spawning their gametes into the water column. Although this species-specific event typically occurs in a particular season, the precise time and day of spawning often can not be predicted. There is little understanding of how the environment (e.g. water temperature, day length, tidal and lunar cycle) regulates a population's reproductive physiology to synchronise a spawning event. The Indo-Pacific tropical abalone, Haliotis asinina, has a highly predictable spawning cycle, where individuals release gametes on the evenings of spring high tides on new and full moons during the warmer half of the year. These calculable spawning events uniquely allow for the analysis of the molecular and cellular processes underlying reproduction. Here we characterise neuropeptides produced in H. asinina ganglia that are known in egg-laying molluscs to control vital aspects of reproduction. RESULTS: We demonstrate that genes encoding APGWamide, myomodulin, the putative proctolin homologue whitnin, FMRFamide, a schistosomin-like peptide (SLP), a molluscan insulin-related peptide (MIP) and a haliotid growth-associated peptide (HGAP) all are differentially expressed in the anterior ganglia during the two week spawning cycle in both male and female abalone. Each gene has a unique and sex-specific expression profile. Despite these differences, expression levels in most of the genes peak at or within 12 h of the spawning event. In contrast, lowest levels of transcript abundance typically occurs 36 h before and 24 h after spawning, with differences in peak and low expression levels being most pronounced in genes orthologous to known molluscan reproduction neuromodulators. CONCLUSIONS: Exploiting the predictable semi-lunar spawning cycle of the gastropod H. asinina, we have identified a suite of evolutionarily-conserved, mollusc-specific and rapidly-evolving neuropeptides that appear to contribute to the regulation of spawning. Dramatic increases and decreases in ganglionic neuropeptide expression levels from 36 h before to 24 h after the broadcast spawning event are consistent with these peptides having a regulatory role in translating environmental signals experienced by a population into a synchronous physiological output, in this case, the release of gametes.

Recoding of stop codons expands the metabolic potential of two novel Asgardarchaeota lineages.

Asgardarchaeota have been proposed as the closest living relatives to eukaryotes, and a total of 72 metagenome-assembled genomes (MAGs) representing six primary lineages in this archaeal phylum have thus far been described. These organisms are predicted to be fermentative heterotrophs contributing to carbon cycling in sediment ecosystems. Here, we double the genomic catalogue of Asgardarchaeota by obtaining 71 MAGs from a range of habitats around the globe, including the deep subsurface, brackish shallow lakes, and geothermal spring sediments. Phylogenomic inferences followed by taxonomic rank normalisation confirmed previously established Asgardarchaeota classes and revealed four additional lineages, two of which were consistently recovered as monophyletic classes. We therefore propose the names Candidatus Sifarchaeia class nov. and Ca. Jordarchaeia class nov., derived from the gods Sif and Jord in Norse mythology. Metabolic inference suggests that both classes represent hetero-organotrophic acetogens, which also have the ability to utilise methyl groups such as methylated amines, with acetate as the probable end product in remnants of a methanogen-derived core metabolism. This inferred mode of energy conservation is predicted to be enhanced by genetic code expansions, i.e., stop codon recoding, allowing the incorporation of the rare 21st and 22nd amino acids selenocysteine (Sec) and pyrrolysine (Pyl). We found Sec recoding in Jordarchaeia and all other Asgardarchaeota classes, which likely benefit from increased catalytic activities of Sec-containing enzymes. Pyl recoding, on the other hand, is restricted to Sifarchaeia in the Asgardarchaeota, making it the first reported non-methanogenic archaeal lineage with an inferred complete Pyl machinery, likely providing members of this class with an efficient mechanism for methylamine utilisation. Furthermore, we identified enzymes for the biosynthesis of ester-type lipids, characteristic of bacteria and eukaryotes, in both newly described classes, supporting the hypothesis that mixed ether-ester lipids are a shared feature among Asgardarchaeota.

Successional dynamics and alternative stable states in a saline activated sludge microbial community over 9 years.

BACKGROUND: Microbial communities in both natural and applied settings reliably carry out myriads of functions, yet how stable these taxonomically diverse assemblages can be and what causes them to transition between states remains poorly understood. We studied monthly activated sludge (AS) samples collected over 9 years from a full-scale wastewater treatment plant to answer how complex AS communities evolve in the long term and how the community functions change when there is a disturbance in operational parameters. RESULTS: Here, we show that a microbial community in activated sludge (AS) system fluctuated around a stable average for 3 years but was then abruptly pushed into an alternative stable state by a simple transient disturbance (bleaching). While the taxonomic composition rapidly turned into a new state following the disturbance, the metabolic profile of the community and system performance remained remarkably stable. A total of 920 metagenome-assembled genomes (MAGs), representing approximately 70% of the community in the studied AS ecosystem, were recovered from the 97 monthly AS metagenomes. Comparative genomic analysis revealed an increased ability to aggregate in the cohorts of MAGs with correlated dynamics that are dominant after the bleaching event. Fine-scale analysis of dynamics also revealed cohorts that dominated during different periods and showed successional dynamics on seasonal and longer time scales due to temperature fluctuation and gradual changes in mean residence time in the reactor, respectively. CONCLUSIONS: Our work highlights that communities can assume different stable states under highly similar environmental conditions and that a specific disturbance threshold may lead to a rapid shift in community composition. Video Abstract.

Diverse sediment microbiota shape methane emission temperature sensitivity in Arctic lakes.

Northern post-glacial lakes are significant, increasing sources of atmospheric carbon through ebullition (bubbling) of microbially-produced methane (CH4) from sediments. Ebullitive CH4 flux correlates strongly with temperature, reflecting that solar radiation drives emissions. However, here we show that the slope of the temperature-CH4 flux relationship differs spatially across two post-glacial lakes in Sweden. We compared these CH4 emission patterns with sediment microbial (metagenomic and amplicon), isotopic, and geochemical data. The temperature-associated increase in CH4 emissions was greater in lake middles-where methanogens were more abundant-than edges, and sediment communities were distinct between edges and middles. Microbial abundances, including those of CH4-cycling microorganisms and syntrophs, were predictive of porewater CH4 concentrations. Results suggest that deeper lake regions, which currently emit less CH4 than shallower edges, could add substantially to CH4 emissions in a warmer Arctic and that CH4 emission predictions may be improved by accounting for spatial variations in sediment microbiota.