Taxonomy is an organizing principle of biology and is ideally based on evolutionary relationships among organisms. Development of a robust bacterial taxonomy has been hindered by an inability to obtain most bacteria in pure culture and, to a lesser extent, by the historical use of phenotypes to guide classification. Culture-independent sequencing technologies have matured sufficiently that a comprehensive genome-based taxonomy is now possible. We used a concatenated protein phylogeny as the basis for a bacterial taxonomy that conservatively removes polyphyletic groups and normalizes taxonomic ranks on the basis of relative evolutionary divergence. Under this approach, 58% of the 94,759 genomes comprising the Genome Taxonomy Database had changes to their existing taxonomy. This result includes the description of 99 phyla, including six major monophyletic units from the subdivision of the Proteobacteria, and amalgamation of the Candidate Phyla Radiation into a single phylum. Our taxonomy should enable improved classification of uncultured bacteria and provide a sound basis for ecological and evolutionary studies.

A standardized bacterial taxonomy based on genome phylogeny substantially revises the tree of life

Our growing awareness of the microbial world’s importance and diversity contrasts starkly with our limited understanding of its fundamental structure. Despite recent advances in DNA sequencing, a lack of standardized protocols and common analytical frameworks impedes comparisons among studies, hindering the development of global inferences about microbial life on Earth. Here we present a meta-analysis of microbial community samples collected by hundreds of researchers for the Earth Microbiome Project. Coordinated protocols and new analytical methods, particularly the use of exact sequences instead of clustered operational taxonomic units, enable bacterial and archaeal ribosomal RNA gene sequences to be followed across multiple studies and allow us to explore patterns of diversity at an unprecedented scale. The result is both a reference database giving global context to DNA sequence data and a framework for incorporating data from future studies, fostering increasingly complete characterization of Earth’s microbial diversity.

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A communal catalogue reveals Earth’s multiscale microbial diversity

Challenges in cultivating microorganisms have limited the phylogenetic diversity of currently available microbial genomes. This is being addressed by advances in sequencing throughput and computational techniques that allow for the cultivation-independent recovery of genomes from metagenomes. Here, we report the reconstruction of 7,903 bacterial and archaeal genomes from >1,500 public metagenomes. All genomes are estimated to be ≥50% complete and nearly half are ≥90% complete with ≤5% contamination. These genomes increase the phylogenetic diversity of bacterial and archaeal genome trees by >30% and provide the first representatives of 17 bacterial and three archaeal candidate phyla. We also recovered 245 genomes from the Patescibacteria superphylum (also known as the Candidate Phyla Radiation) and find that the relative diversity of this group varies substantially with different protein marker sets. The scale and quality of this data set demonstrate that recovering genomes from metagenomes provides an expedient path forward to exploring microbial dark matter.

Recovery of nearly 8,000 metagenome-assembled genomes substantially expands the tree of life

We present the Open Graph Benchmark (OGB), a diverse set of challenging and realistic benchmark datasets to facilitate scalable, robust, and reproducible graph machine learning (ML) research. OGB datasets are large-scale, encompass multiple important graph ML tasks, and cover a diverse range of domains, ranging from social and information networks to biological networks, molecular graphs, source code ASTs, and knowledge graphs. For each dataset, we provide a unified evaluation protocol using meaningful application-specific data splits and evaluation metrics. In addition to building the datasets, we also perform extensive benchmark experiments for each dataset. Our experiments suggest that OGB datasets present significant challenges of scalability to large-scale graphs and out-of-distribution generalization under realistic data splits, indicating fruitful opportunities for future research. Finally, OGB provides an automated end-to-end graph ML pipeline that simplifies and standardizes the process of graph data loading, experimental setup, and model evaluation. OGB will be regularly updated and welcomes inputs from the community. OGB datasets as well as data loaders, evaluation scripts, baseline code, and leaderboards are publicly available at this https URL .

Open Graph Benchmark: Datasets for Machine Learning on Graphs

Understanding the mechanisms controlling community diversity, functions, succession, and biogeography is a central, but poorly understood, topic in ecology, particularly in microbial ecology. Although stochastic processes are believed to play nonnegligible roles in shaping community structure, their importance relative to deterministic processes is hotly debated. The importance of ecological stochasticity in shaping microbial community structure is far less appreciated. Some of the main reasons for such heavy debates are the difficulty in defining stochasticity and the diverse methods used for delineating stochasticity. Here, we provide a critical review and synthesis of data from the most recent studies on stochastic community assembly in microbial ecology. We then describe both stochastic and deterministic components embedded in various ecological processes, including selection, dispersal, diversification, and drift. We also describe different approaches for inferring stochasticity from observational diversity patterns and highlight experimental approaches for delineating ecological stochasticity in microbial communities. In addition, we highlight research challenges, gaps, and future directions for microbial community assembly research.

https://escholarship.org/content/qt3884203g/qt3884203g.pdf?t=pxq64b

Stochastic Community Assembly: Does It Matter in Microbial Ecology?

The tree of life is one of the most important organizing principles in biology1. Gene surveys suggest the existence of an enormous number of branches2, but even an approximation of the full scale of the tree has remained elusive. Recent depictions of the tree of life have focused either on the nature of deep evolutionary relationships3–5 or on the known, well-classified diversity of life with an emphasis on eukaryotes6. These approaches overlook the dramatic change in our understanding of life's diversity resulting from genomic sampling of previously unexamined environments. New methods to generate genome sequences illuminate the identity of organisms and their metabolic capacities, placing them in community and ecosystem contexts7,8. Here, we use new genomic data from over 1,000 uncultivated and little known organisms, together with published sequences, to infer a dramatically expanded version of the tree of life, with Bacteria, Archaea and Eukarya included. The depiction is both a global overview and a snapshot of the diversity within each major lineage. The results reveal the dominance of bacterial diversification and underline the importance of organisms lacking isolated representatives, with substantial evolution concentrated in a major radiation of such organisms. This tree highlights major lineages currently underrepresented in biogeochemical models and identifies radiations that are probably important for future evolutionary analyses. An update to the ‘tree of life’ has revealed a dominance of bacterial diversity in many ecosystems and extensive evolution in some branches of the tree. It also highlights how few organisms we have been able to cultivate for further investigation.

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A new view of the tree of life

Geological sequestration in deep underground repositories is the prevailing proposed route for radioactive waste disposal. After the disposal of radioactive waste in the subsurface, H2 may be produced by corrosion of steel and, ultimately, radionuclides will be exposed to the surrounding environment. To evaluate the potential for microbial activities to impact disposal systems, we explored the microbial community structure and metabolic functions of a sediment-hosted ecosystem at the Horonobe Underground Research Laboratory, Hokkaido, Japan. Overall, we found that the ecosystem hosted organisms from diverse lineages, including many from the phyla that lack isolated representatives. The majority of organisms can metabolize H2, often via oxidative [NiFe] hydrogenases or electron-bifurcating [FeFe] hydrogenases that enable ferredoxin-based pathways, including the ion motive Rnf complex. Many organisms implicated in H2 metabolism are also predicted to catalyze carbon, nitrogen, iron and sulfur transformations. Notably, iron-based metabolism is predicted in a novel lineage of Actinobacteria and in a putative methane-oxidizing ANME-2d archaeon. We infer an ecological model that links microorganisms to sediment-derived resources and predict potential impacts of microbial activity on H2 consumption and retardation of radionuclide migration.

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Potential for microbial H2 and metal transformations associated with novel bacteria and archaea in deep terrestrial subsurface sediments.

Recent single-gene-based surveys of deep continental aquifers demonstrated the widespread occurrence of archaea related to Candidatus Methanoperedens nitroreducens (ANME-2d) known to mediate anaerobic oxidation of methane (AOM). However, it is unclear whether ANME-2d mediates AOM in the deep continental biosphere. In this study, we found the dominance of ANME-2d in groundwater enriched in sulfate and methane from a 300-m deep underground borehole in granitic rock. A near-complete genome of one representative species of the ANME-2d obtained from the underground borehole has most of functional genes required for AOM and assimilatory sulfate reduction. The genome of the subsurface ANME-2d is different from those of other members of ANME-2d by lacking functional genes encoding nitrate and nitrite reductases and multiheme cytochromes. In addition, the subsurface ANME-2d genome contains a membrane-bound NiFe hydrogenase gene putatively involved in respiratory H2 oxidation, which is different from those of other methanotrophic archaea. Short-term incubation of microbial cells collected from the granitic groundwater with 13C-labeled methane also demonstrates that AOM is linked to microbial sulfate reduction. Given the prominence of granitic continental crust and sulfate and methane in terrestrial subsurface fluids, we conclude that AOM may be widespread in the deep continental biosphere.

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Alex W Hernsdorf

Papers

A new view of the tree of life

Potential for microbial H2 and metal transformations associated with novel bacteria and archaea in deep terrestrial subsurface sediments.

Ecological and genomic profiling of anaerobic methane-oxidizing archaea in a deep granitic environment.