Discarded diversity: Novel megaphages, auxiliary metabolic genes, and virally encoded CRISPR-Cas systems in landfills.

Background: Viruses are the most abundant microbial entity on the planet, impacting microbial community structure and ecosystem services. Despite outnumbering Bacteria and Archaea by an order of magnitude, viruses have been comparatively underrepresented in reference databases. Metagenomic examinations have illustrated that viruses of Bacteria and Archaea have been specifically understudied in engineered environments. Here we employed metagenomic and computational biology methods to examine the diversity, host interactions, and genetic systems of viruses predicted from 27 samples taken from three municipal landfills across North America. Results: We identified numerous viruses that are not represented in reference databases, including the third largest bacteriophage genome identified to date (~678 kbp), and note a cosmopolitan diversity of viruses in landfills that are distinct from viromes in other systems. Host-virus interactions were examined via host CRISPR spacer to viral protospacer mapping which captured hyper-targeted viral populations and six viral populations predicted to infect across multiple phyla. Virally-encoded auxiliary metabolic genes (AMGs) were identified with the potential to augment hosts' methane, sulfur, and contaminant degradation metabolisms, including AMGs not previously reported in literature. CRISPR arrays and CRISPR-Cas systems were identified from predicted viral genomes, including the two largest bacteriophage genomes to contain these genetic features. Some virally encoded Cas effector proteins appear distinct relative to previously reported Cas systems and are interesting targets for potential genome editing tools. Conclusions: Our observations indicate landfills, as heterogeneous contaminated sites with unique selective pressures, are key locations for diverse viruses and atypical virus-host dynamics.

Legacy copper/nickel mine tailings potentially harbor novel iron/sulfur cycling microorganisms within highly variable communities.

The oxidation of sulfide-bearing mine tailings catalyzed by acidophilic iron and sulfur-oxidizing bacteria releases toxic metals and other contaminants into soil and groundwater as acid mine drainage. Understanding the environmental variables that control the community structure and metabolic activity of microbes indigenous to tailings (especially the abiotic stressors of low pH and high dissolved metal content) is crucial to developing sustainable bioremediation strategies. We determined the microbial community composition along two continuous vertical gradients of Cu/Ni mine tailings at each of two tailings impoundments near Sudbury, Ontario. 16S rRNA amplicon data showed high variability in community diversity and composition between locations, as well as at different depths within each location. A temporal comparison for one tailings location showed low fluctuation in microbial communities across 2 years. Differences in community composition correlated most strongly with pore-water pH, Eh, alkalinity, salinity, and the concentration of several dissolved metals (including iron, but not copper or nickel). The relative abundances of individual genera differed in their degrees of correlation with geochemical factors. Several abundant lineages present at these locations have not previously been associated with mine tailings environments, including novel species predicted to be involved in iron and sulfur cycling.IMPORTANCEMine tailings represent a significant threat to North American freshwater, with legacy tailings areas generating acid mine drainage (AMD) that contaminates rivers, lakes, and aquifers. Microbial activity accelerates AMD formation through oxidative metabolic processes but may also ameliorate acidic tailings by promoting secondary mineral precipitation and immobilizing dissolved metals. Tailings exhibit high geochemical variation within and between mine sites and may harbor many novel extremophiles adapted to high concentrations of toxic metals. Characterizing the unique microbiomes associated with tailing environments is key to identifying consortia that may be used as the foundation for innovative mine-waste bioremediation strategies. We provide an in-depth analysis of microbial diversity at four copper/nickel mine tailings impoundments, describe how communities (and individual lineages) differ based on geochemical gradients, predict organisms involved in AMD transformations, and identify taxonomically novel groups present that have not previously been observed in mine tailings.

Microbial methane cycling in a landfill on a decadal time scale.

Landfills generate outsized environmental footprints due to microbial degradation of organic matter in municipal solid waste, which produces the potent greenhouse gas methane. With global solid waste production predicted to increase substantially in the next few decades, there is a pressing need to better understand the temporal dynamics of biogeochemical processes that control methane cycling in landfills. Here, we use metagenomic approaches to characterize microbial methane cycling in waste that was landfilled over 39 years. Our analyses indicate that newer waste supports more diverse communities with similar composition compared to older waste, which contains lower diversity and more varied communities. Older waste contains primarily autotrophic organisms with versatile redox metabolisms, whereas newer waste is dominated by anaerobic fermenters. Methane-producing microbes are more abundant, diverse, and metabolically versatile in new waste compared to old waste. Our findings indicate that predictive models for methane emission in landfills overlook methane oxidation in the absence of oxygen, as well as certain microbial lineages that can potentially contribute to methane sinks in diverse habitats.

MT-MAG: Accurate and interpretable machine learning for complete or partial taxonomic assignments of metagenomeassembled genomes.

We propose MT-MAG, a novel machine learning-based software tool for the complete or partial hierarchically-structured taxonomic classification of metagenome-assembled genomes (MAGs). MT-MAG is alignment-free, with k-mer frequencies being the only feature used to distinguish a DNA sequence from another (herein k = 7). MT-MAG is capable of classifying large and diverse metagenomic datasets: a total of 245.68 Gbp in the training sets, and 9.6 Gbp in the test sets analyzed in this study. In addition to complete classifications, MT-MAG offers a "partial classification" option, whereby a classification at a higher taxonomic level is provided for MAGs that cannot be classified to the Species level. MT-MAG outputs complete or partial classification paths, and interpretable numerical classification confidences of its classifications, at all taxonomic ranks. To assess the performance of MT-MAG, we define a "weighted classification accuracy," with a weighting scheme reflecting the fact that partial classifications at different ranks are not equally informative. For the two benchmarking datasets analyzed (genomes from human gut microbiome species, and bacterial and archaeal genomes assembled from cow rumen metagenomic sequences), MT-MAG achieves an average of 87.32% in weighted classification accuracy. At the Species level, MT-MAG outperforms DeepMicrobes, the only other comparable software tool, by an average of 34.79% in weighted classification accuracy. In addition, MT-MAG is able to completely classify an average of 67.70% of the sequences at the Species level, compared with DeepMicrobes which only classifies 47.45%. Moreover, MT-MAG provides additional information for sequences that it could not classify at the Species level, resulting in the partial or complete classification of 95.13%, of the genomes in the datasets analyzed. Lastly, unlike other taxonomic assignment tools (e.g., GDTB-Tk), MT-MAG is an alignment-free and genetic marker-free tool, able to provide additional bioinformatics analysis to confirm existing or tentative taxonomic assignments.

CRISPR-resolved virus-host interactions in a municipal landfill include non-specific viruses, hyper-targeted viral populations, and interviral conflicts.

Viruses are the most abundant microbial guild on the planet, impacting microbial community structure and ecosystem services. Viruses are specifically understudied in engineered environments, including examinations of their host interactions. We examined host-virus interactions via host CRISPR spacer to viral protospacer mapping in a municipal landfill across two years. Viruses comprised ~ 4% of both the unassembled reads and assembled basepairs. A total of 458 unique virus-host connections captured hyper-targeted viral populations and host CRISPR array adaptation over time. Four viruses were predicted to infect across multiple phyla, suggesting that some viruses are far less host-specific than is currently understood. We detected 161 viral elements that encode CRISPR arrays, including one with 187 spacers, the longest virally-encoded CRISPR array described to date. Virally-encoded CRISPR arrays targeted other viral elements in interviral conflicts. CRISPR-encoding proviruses integrated into host chromosomes were latent examples of CRISPR-immunity-based superinfection exclusion. The bulk of the observed virus-host interactions fit the one-virus-one-host paradigm, but with limited geographic specificity. Our networks highlight rare and previously undescribed complex interactions influencing the ecology of this dynamic engineered system. Our observations indicate landfills, as heterogeneous contaminated sites with unique selective pressures, are key locations for atypical virus-host dynamics.

Cloacimonadota metabolisms include adaptations in engineered environments that are reflected in the evolutionary history of the phylum.

Phylum Cloacimonadota (previously Cloacimonetes, WWE1) is an understudied bacterial lineage frequently associated with engineered and wastewater systems. Cloacimonadota members were abundant and diverse in metagenomic datasets from a municipal landfill, prompting an examination of phylogenetic relationships, metabolic diversity, and pangenomic dynamics across the phylum, based on the 30 publicly available genomes and 24 new metagenome-assembled genomes (MAGs) from landfill samples. We found that Cloacimonadota have distinct evolutionary histories associated with engineered versus natural environments and identified genomic features and metabolic strategies that correlate to habitat of origin. Metabolic reconstructions for MAGs predict an anaerobic, acetogenic, and mixed fermentative and flavin-bifurcation-based anaerobic respiratory lifestyle for the majority of Cloacimonadota surveyed. Genomes from engineered ecosystems encode a suite of genes not typically found in genomes from natural environments including acetate kinase, genes for cysteine degradation to pyruvate, increased diversity of carbon utilization enzymes, and different mechanisms for generating membrane potential and ATP synthesis. This phylum-level examination also clarifies the distribution of functions previously observed for members of the phylum, where propionate oxidation and reverse TCA cycles are not common components of Cloacimonadota metabolism.

Environmental Potential for Microbial 1,4-Dioxane Degradation Is Sparse despite Mobile Elements Playing a Role in Trait Distribution.

1,4-Dioxane (dioxane) is an emerging contaminant of concern for which bioremediation is seen as a promising solution. To date, eight distinct gene families have been implicated in dioxane degradation, though only dioxane monooxygenase (DXMO) from Pseudonocardia dioxanivorans is routinely used as a biomarker in environmental surveys. In order to assess the functional and taxonomic diversity of bacteria capable of dioxane degradation, we collated existing, poorly-organized information on known biodegraders to create a curated suite of biomarkers with confidence levels for assessing 1,4-dioxane degradation potential. The characterized enzyme systems for dioxane degradation are frequently found on mobile elements, and we identified that many of the curated biomarkers are associated with other hallmarks of genomic rearrangements, indicating lateral gene transfer plays a role in dissemination of this trait. This is contrasted by the extremely limited phylogenetic distribution of known dioxane degraders, where all representatives belong to four classes within three bacterial phyla. Based on the curated set of expanded biomarkers, a search of more than 11,000 publicly available metagenomes identified a sparse and taxonomically limited distribution of potential dioxane degradation proteins. Our work provides an important and necessary structure to the current knowledge base for dioxane degradation and clarifies the potential for natural attenuation of dioxane across different environments. It further highlights a disconnect between the apparent mobility of these gene families and their limited distributions, indicating dioxane degradation may be difficult to integrate into a microorganism's metabolism. IMPORTANCE New regulatory limits for 1,4-dioxane in groundwater have been proposed or adopted in many countries, including the United States and Canada, generating a direct need for remediation options as well as better tools for assessing the fate of dioxane in an environment. A comprehensive suite of biomarkers associated with dioxane degradation was identified and then leveraged to examine the global potential for dioxane degradation in natural and engineered environments. We identified consistent differences in the dioxane-degrading gene families associated with terrestrial, aquatic, and wetland environments, indicating reliance on a single biomarker for assessing natural attenuation of dioxane is likely to miss key players. Most environments do not currently host the capacity for dioxane degradation-the sparse distribution of dioxane degradation potential highlights the need for bioaugmentation approaches over biostimulation of naturally occurring microbial communities.

Substrate-restricted methanogenesis and limited volatile organic compound degradation in highly diverse and heterogeneous municipal landfill microbial communities.

Microbial communities in landfills transform waste and generate methane in an environment unique from other built and natural environments. Landfill microbial diversity has predominantly been observed at the phylum level, without examining the extent of shared organismal diversity across space or time. We used 16S rRNA gene amplicon and shotgun metagenomic sequencing to examine the taxonomic and functional diversity of the microbial communities inhabiting a Southern Ontario landfill. The microbial capacity for volatile organic compound degradation in leachate and groundwater samples was correlated with geochemical conditions. Across the landfill, 25 bacterial and archaeal phyla were present at >1% relative abundance within at least one landfill sample, with Patescibacteria, Bacteroidota, Firmicutes, and Proteobacteria dominating. Methanogens were neither numerous nor particularly abundant, and were predominantly constrained to either acetoclastic or methylotrophic methanogenesis. The landfill microbial community was highly heterogeneous, with 90.7% of organisms present at only one or two sites within this interconnected system. Based on diversity measures, the landfill is a microbial system undergoing a constant state of disturbance and change, driving the extreme heterogeneity observed. Significant differences in geochemistry occurred across the leachate and groundwater wells sampled, with calcium, iron, magnesium, boron, meta and para xylenes, ortho xylenes, and ethylbenzene concentrations contributing most strongly to observed site differences. Predicted microbial degradation capacities indicated a heterogeneous community response to contaminants, including identification of novel proteins implicated in anaerobic degradation of key volatile organic compounds.

Adapting Macroecology to Microbiology: Using Occupancy Modeling To Assess Functional Profiles across Metagenomes.

Metagenomic sequencing provides information on the metabolic capacities and taxonomic affiliations for members of a microbial community. When assessing metabolic functions in a community, missing genes in pathways can occur in two ways; the genes may legitimately be missing from the community whose DNA was sequenced, or the genes were missed during shotgun sequencing or failed to assemble, and thus the metabolic capacity of interest is wrongly absent from the sequence data. Here, we borrow and adapt occupancy modeling from macroecology to provide mathematical context to metabolic predictions from metagenomes. We review the five assumptions underlying occupancy modeling through the lens of microbial community sequence data. Using the methane cycle, we apply occupancy modeling to examine the presence and absence of methanogenesis and methanotrophy genes from nearly 10,000 metagenomes spanning global environments. We determine that methanogenesis and methanotrophy are positively correlated across environments, providing a predictive framework for assessing gene absences for these functions. We present this adaptation of macroecology's occupancy modeling to metagenomics as a tool to quantify the uncertainty in predictions of the presence/absence of traits in environmental microbiological surveys. We further initiate a call for stronger metadata standards to accompany metagenome deposition, to enable robust statistical approaches in the future. IMPORTANCE Metagenomics is maturing rapidly as a field but is hampered by a lack of available statistical tools. A primary area of uncertainty is around missing genes or functions from a metagenomic data set. Here, we borrow an established modeling approach from macroecology and adapt it to metagenomic data sets. Rather than multiple sampling trips to a specific area to detect a species of interest (e.g., identifying a cardinal in a forest), we leverage the enormous amount of information within a metagenome and use multiple gene markers for a function of interest (e.g., subunits of an enzyme complex). We applied our adapted occupancy modeling to a case study examining methane cycling capacity. Our models show methanogens and methanotrophs are both more likely to cooccur than be present in the absence of the other guild. The lack of consistent and complete metadata is a significant hurdle for increasing the statistical rigor of metagenomic analyses.

Prediction, enrichment and isolation identify a responsive, competitive community of cellulolytic microorganisms from a municipal landfill.

Landfills are engineered, heterogeneously contaminated sites containing large reservoirs of paper waste. Cellulose degradation is an important process within landfill microbial ecology, and these anoxic, saturated environments are prime locations for discovery of cellulases that may offer improvements on industrial cellulose degradation efforts. We sampled leachate from three locations within a municipal landfill, a leachate collection cistern, and groundwater from an adjacent aquifer to identify cellulolytic populations and their associated cellulases. Metagenomic sequencing identified wide-spread and taxonomically diverse cellulolytic potential, with a notable scarcity of predicted exocellulases. 16S rRNA amplicon sequencing detected nine landfill microorganisms enriched in a customized leachate medium amended with microcrystalline cellulose or common paper stocks. Paper-enrichment cultures showed competition dynamics in response to the specific composition (lignin: hemi-cellulose: cellulose) of the different paper stocks. From leachate biomass, four novel cellulolytic bacteria were isolated, including two with the capacity for cellulolysis at industrially relevant temperatures. None of the isolates demonstrated exocellulase activity, consistent with the metagenome-based predictions. However, there was very little overlap between metagenome-derived predicted cellulolytic organisms, organisms enriched on paper sources, or the isolates, suggesting the landfill cellulolytic community is at low abundance but able to rapidly respond to introduced substrates.

Composition of the North American Wood Frog (Rana sylvatica) Bacterial Skin Microbiome and Seasonal Variation in Community Structure.

While a number of amphibian skin microbiomes have been characterized, it is unclear how these communities might vary in response to seasonal changes in the environment and the corresponding behaviors that many amphibians exhibit. Given recent studies demonstrating the importance of the skin microbiome in frog innate immune defense against pathogens, investigating how changes in the environment impact the microbial species present will provide a better understanding of conditions that may alter host susceptibility to pathogens in their environment. We sampled the bacterial skin microbiome of North American wood frogs (Rana sylvatica) from two breeding ponds in the spring, along with the bacterial community present in their vernal breeding pools, and frogs from the nearby forest floor in the summer and fall to determine whether community composition differs by sex, vernal pond site, or temporally across season (spring, summer, fall). Taxon relative abundance data reveals a profile of bacterial phyla similar to those previously described on anuran skin, with Proteobacteria, Bacteroidetes, and Actinobacteria dominating the wood frog skin microbiome. Our results indicate that sex had no significant effect on skin microbiota diversity; however, this may be due to our limited female frog sample size. Vernal pool site had a small but significant effect on skin microbiota, but skin-associated communities were more similar to each other than to the communities observed in the frogs' respective pond water. Across seasons, diversity analyses suggest that there are significant differences between the bacterial skin microbiome of frogs from spring and summer/fall groups while the average α-diversity per frog remained consistent. These results illustrate seasonal variation in wood frog skin microbiome structure and highlight the importance of considering temporal trends in an amphibian microbiome, particularly for species whose life history requires recurrent shifts in habitat and behavior.

A Need for Improved Cellulase Identification from Metagenomic Sequence Data.

Improved sequencing technologies and the maturation of metagenomic approaches allow the identification of gene variants with potential industrial applications, including cellulases. Cellulase identification from metagenomic environmental surveys is complicated by inconsistent nomenclature and multiple categorization systems. Here, we summarize the current classification and nomenclature systems, with recommendations for improvements to these systems. Addressing the issues described will strengthen the annotation of cellulose-active enzymes from environmental sequence data sets-a rapidly growing resource in environmental and applied microbiology.

Groundwater Elusimicrobia are metabolically diverse compared to gut microbiome Elusimicrobia and some have a novel nitrogenase paralog.

Currently described members of Elusimicrobia, a relatively recently defined phylum, are animal-associated and rely on fermentation. However, free-living Elusimicrobia have been detected in sediments, soils and groundwater, raising questions regarding their metabolic capacities and evolutionary relationship to animal-associated species. Here, we analyzed 94 draft-quality, non-redundant genomes, including 30 newly reconstructed genomes, from diverse animal-associated and natural environments. Genomes group into 12 clades, 10 of which previously lacked reference genomes. Groundwater-associated Elusimicrobia are predicted to be capable of heterotrophic or autotrophic lifestyles, reliant on oxygen or nitrate/nitrite-dependent respiration, or a variety of organic compounds and Rhodobacter nitrogen fixation (Rnf) complex-dependent acetogenesis with hydrogen and carbon dioxide as the substrates. Genomes from two clades of groundwater-associated Elusimicrobia often encode a new group of nitrogenase paralogs that co-occur with an extensive suite of radical S-Adenosylmethionine (SAM) proteins. We identified similar genomic loci in genomes of bacteria from the Gracilibacteria phylum and the Myxococcales order and predict that the gene clusters reduce a tetrapyrrole, possibly to form a novel cofactor. The animal-associated Elusimicrobia clades nest phylogenetically within two free-living-associated clades. Thus, we propose an evolutionary trajectory in which some Elusimicrobia adapted to animal-associated lifestyles from free-living species via genome reduction.

Roadmap for naming uncultivated Archaea and Bacteria.

The assembly of single-amplified genomes (SAGs) and metagenome-assembled genomes (MAGs) has led to a surge in genome-based discoveries of members affiliated with Archaea and Bacteria, bringing with it a need to develop guidelines for nomenclature of uncultivated microorganisms. The International Code of Nomenclature of Prokaryotes (ICNP) only recognizes cultures as 'type material', thereby preventing the naming of uncultivated organisms. In this Consensus Statement, we propose two potential paths to solve this nomenclatural conundrum. One option is the adoption of previously proposed modifications to the ICNP to recognize DNA sequences as acceptable type material; the other option creates a nomenclatural code for uncultivated Archaea and Bacteria that could eventually be merged with the ICNP in the future. Regardless of the path taken, we believe that action is needed now within the scientific community to develop consistent rules for nomenclature of uncultivated taxa in order to provide clarity and stability, and to effectively communicate microbial diversity.

High functional diversity among Nitrospira populations that dominate rotating biological contactor microbial communities in a municipal wastewater treatment plant.

Nitrification, the oxidation of ammonia to nitrate via nitrite, is an important process in municipal wastewater treatment plants (WWTPs). Members of the Nitrospira genus that contribute to complete ammonia oxidation (comammox) have only recently been discovered and their relevance to engineered water treatment systems is poorly understood. This study investigated distributions of Nitrospira, ammonia-oxidizing archaea (AOA), and ammonia-oxidizing bacteria (AOB) in biofilm samples collected from tertiary rotating biological contactors (RBCs) of a municipal WWTP in Guelph, Ontario, Canada. Using quantitative PCR (qPCR), 16S rRNA gene sequencing, and metagenomics, our results demonstrate that Nitrospira species strongly dominate RBC biofilm samples and that comammox Nitrospira outnumber all other nitrifiers. Genome bins recovered from assembled metagenomes reveal multiple populations of comammox Nitrospira with distinct spatial and temporal distributions, including several taxa that are distinct from previously characterized Nitrospira members. Diverse functional profiles imply a high level of niche heterogeneity among comammox Nitrospira, in contrast to the sole detected AOA representative that was previously cultivated and characterized from the same RBC biofilm. Our metagenome bins also reveal two cyanase-encoding populations of comammox Nitrospira, suggesting an ability to degrade cyanate, which has only been shown previously for several Nitrospira representatives that are strict nitrite oxidizers. This study demonstrates the importance of RBCs as model systems for continued investigation of environmental factors that control the distributions and activities of AOB, AOA, comammox Nitrospira, and other nitrite oxidizers.

AnnoTree: visualization and exploration of a functionally annotated microbial tree of life.

Bacterial genomics has revolutionized our understanding of the microbial tree of life; however, mapping and visualizing the distribution of functional traits across bacteria remains a challenge. Here, we introduce AnnoTree-an interactive, functionally annotated bacterial tree of life that integrates taxonomic, phylogenetic and functional annotation data from over 27 000 bacterial and 1500 archaeal genomes. AnnoTree enables visualization of millions of precomputed genome annotations across the bacterial and archaeal phylogenies, thereby allowing users to explore gene distributions as well as patterns of gene gain and loss in prokaryotes. Using AnnoTree, we examined the phylogenomic distributions of 28 311 gene/protein families, and measured their phylogenetic conservation, patchiness, and lineage-specificity within bacteria. Our analyses revealed widespread phylogenetic patchiness among bacterial gene families, reflecting the dynamic evolution of prokaryotic genomes. Genes involved in phage infection/defense, mobile elements, and antibiotic resistance dominated the list of most patchy traits, as well as numerous intriguing metabolic enzymes that appear to have undergone frequent horizontal transfer. We anticipate that AnnoTree will be a valuable resource for exploring prokaryotic gene histories, and will act as a catalyst for biological and evolutionary hypothesis generation. AnnoTree is freely available at http://annotree.uwaterloo.ca.

Distribution of reactive oxygen species defense mechanisms across domain bacteria.

Bacteria are the most diverse and numerous organisms on the planet, inhabiting environments from the deep subsurface to particles in clouds. Across this range of conditions, bacteria have evolved a diverse suite of enzymes to mitigate cellular damage from reactive oxygen species (ROS). Here, we review the diversity and distribution of ROS enzymatic defense mechanisms across the domain Bacteria, using both peer-reviewed literature and publicly available genome databases. We describe the specific strategies used by well-characterized organisms in order to highlight differences in oxidative stress responses between aerobic, facultatively anaerobic, and anaerobic lifestyles. We present evidence from genome minimization experiments to suggest that ROS defenses are obligately required for life. This review clarifies the variability in ROS defenses across Bacteria, including the novel diversity found in currently uncharacterized Candidate Phyla.

Subsampled Assemblies and Hybrid Nucleotide Composition/Differential Coverage Binning for Genome-Resolved Metagenomics.

Metagenomic analyses for reconstruction of genomes from mixed microbial community datasets now routinely allow rapid, accurate genome recovery for tens to hundreds of organisms from environmental samples. This chapter provides a step-by-step protocol for reconstructing genomes from metagenomic datasets, with a focus on the most abundant community members. Subsampling assembly approaches are implemented to improve assembly of abundant genome sequences, an iterative process that targets progressively less abundant populations and improves total community representation in the final merged assembly. A hybrid approach to genome binning is described, combining differential coverage information from a series of metagenomic samples with nucleotide composition information. This approach strengthens binning through application of multiple independent variables for contig clustering. Genome curation through error correction and gap closure leads to high-quality draft genomes, and, for some community members, closed and complete genome sequences reconstructed directly from environmental samples.

Sizing Up the Uncultured Microbial Majority.

Predicting the total number of microbial cells on Earth and exploring the full diversity of life are fundamental research concepts that have undergone paradigm shifts in the genomic era. In this issue, Lloyd and colleagues (K. G. Lloyd, A. D. Steen, J. L. Ladau, J. Yin, and L. Crosby, mSystems 3:e00055-18, https://doi.org/10.1128/mSystems.00055-18, 2018) present results that combine these two concepts by estimating the total diversity of all cells from Earth's environments. Leveraging publicly available amplicon, metagenomic, and metatranscriptomic datasets, they determined that nearly all environments are dominated by uncultured lineages, with the exception of humans and human-associated habitats. They define a new concept: phylogenetically diverse noncultured cells (PDNC). Unlike viable but nonculturable cells (VBNC), PDNC are microorganisms for which traditional isolation techniques may never succeed. Lloyd et al. estimate that the majority of microorganisms in Earth's ecosystems may be PDNC and conclude that culture-independent methods combined with innovative culturing techniques may be required to understand the ecology and physiology of these abundant and divergent microorganisms.