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Coexisting microbial cells of the same species often exhibit genetic variation that can affect phenotypes ranging from nutrient preference to pathogenicity. Here we present inStrain, a program that uses metagenomic paired reads to profile intra-population genetic diversity (microdiversity) across whole genomes and compares microbial populations in a microdiversity-aware man- ner, greatly increasing the accuracy of genomic comparisons when benchmarked against existing methods. We use inStrain to profile >1,000 fecal metagenomes from newborn premature infants and find that siblings share significantly more strains than unrelated infants, although identical twins share no more strains than fraternal siblings. Infants born by cesarean section har- bor Klebsiella with significantly higher nucleotide diversity than infants delivered vaginally, potentially reflecting acquisition from hospital rather than maternal microbiomes. Genomic loci that show diversity in individual infants include variants found between other infants, possibly reflecting inoculation from diverse hospital-associated sources. inStrain can be applied to any metagenomic dataset for microdiversity analysis and rigorous strain comparison. 

ABSTRACT Bacteria isolated from soils are major sources of specialized metabolites, including antibiotics and other compounds with clinical value that likely shape interactions among microbial community members and impact biogeochemical cycles. Yet, isolated lineages represent a small fraction of all soil bacterial diversity. It remains unclear how the production of specialized metabolites varies across the phylogenetic diversity of bacterial species in soils and whether the genetic potential for production of these metabolites differs with soil depth and vegetation type within a geographic region. We sampled soils and saprolite from three sites in a northern California Critical Zone Observatory with various vegetation and bedrock characteristics and reconstructed 1,334 metagenome-assembled genomes containing diverse biosynthetic gene clusters (BGCs) for secondary metabolite production. We obtained genomes for prolific producers of secondary metabolites, including novel groups within the Actinobacteria , Chloroflexi , and candidate phylum “ Candidatus Dormibacteraeota.” Surprisingly, one genome of a candidate phyla radiation (CPR) bacterium coded for a ribosomally synthesized linear azole/azoline-containing peptide, a capacity we found in other publicly available CPR bacterial genomes. Overall, bacteria with higher biosynthetic potential were enriched in shallow soils and grassland soils, with patterns of abundance of BGC type varying by taxonomy. IMPORTANCE Microbes produce specialized compounds to compete or communicate with one another and their environment. Some of these compounds, such as antibiotics, are also useful in medicine and biotechnology. Historically, most antibiotics have come from soil bacteria which can be isolated and grown in the lab. Though the vast majority of soil bacteria cannot be isolated, we can extract their genetic information and search it for genes which produce these specialized compounds. These understudied soil bacteria offer a wealth of potential for the discovery of new and important microbial products. Here, we identified the ability to produce these specialized compounds in diverse and novel bacteria in a range of soil environments. This information will be useful to other researchers who wish to isolate certain products. Beyond their use to humans, understanding the distribution and function of microbial products is key to understanding microbial communities and their effects on biogeochemical cycles. 

ABSTRACT Viral genome sequencing has guided our understanding of the spread and extent of genetic diversity of SARS-CoV-2 during the COVID-19 pandemic. SARS-CoV-2 viral genomes are usually sequenced from nasopharyngeal swabs of individual patients to track viral spread. Recently, RT-qPCR of municipal wastewater has been used to quantify the abundance of SARS-CoV-2 in several regions globally. However, metatranscriptomic sequencing of wastewater can be used to profile the viral genetic diversity across infected communities. Here, we sequenced RNA directly from sewage collected by municipal utility districts in the San Francisco Bay Area to generate complete and nearly complete SARS-CoV-2 genomes. The major consensus SARS-CoV-2 genotypes detected in the sewage were identical to clinical genomes from the region. Using a pipeline for single nucleotide variant calling in a metagenomic context, we characterized minor SARS-CoV-2 alleles in the wastewater and detected viral genotypes which were also found within clinical genomes throughout California. Observed wastewater variants were more similar to local California patient-derived genotypes than they were to those from other regions within the United States or globally. Additional variants detected in wastewater have only been identified in genomes from patients sampled outside California, indicating that wastewater sequencing can provide evidence for recent introductions of viral lineages before they are detected by local clinical sequencing. These results demonstrate that epidemiological surveillance through wastewater sequencing can aid in tracking exact viral strains in an epidemic context. 

A recent paper by Martiny argues that “high proportions” of bacteria in diverse Earth environments have been cultured. Here we reanalyze a portion of the data in that paper, and argue that the conclusion is based on several technical errors, most notably a calculation of sequence similarity that does not account for sequence gaps, and the reliance on 16S rRNA gene amplicons that are known to be biased towards cultured organisms. We further argue that the paper is also based on a conceptual error: namely, that sequence similarity cannot be used to infer “culturability” because one cannot infer physiology from 16S rRNA gene sequences. Combined with other recent, more reliable studies, the evidence supports the conclusion that most bacterial and archaeal taxa remain uncultured.

 

The relative importance of separation by distance and by environment to population genetic diversity can be conveniently tested in river networks, where these two drivers are often independently distributed over space. To evaluate the importance of dispersal and environmental conditions in shaping microbial population structures, we performed genome‐resolved metagenomic analyses of benthicMicrocoleus‐dominated cyanobacterial mats collected in the Eel and Russian River networks (California, USA). The 64 Microcoleusgenomes were clustered into three species that shared >96.5% average nucleotide identity (ANI). Most mats were dominated by one strain, but minor alleles within mats were often shared, even over large spatial distances (>300 km). Within the most commonMicrocoleusspecies, the ANI between the dominant strains within mats decreased with increasing spatial separation. However, over shorter spatial distances (tens of kilometres), mats from different subwatersheds had lower ANI than mats from the same subwatershed, suggesting that at shorter spatial distances environmental differences between subwatersheds in factors like canopy cover, conductivity, and mean annual temperature decreases ANI. Since mats in smaller creeks had similar levels of nucleotide diversity (π) as mats in larger downstream subwatersheds, within‐mat genetic diversity does not appear to depend on the downstream accumulation of upstream‐derived strains. The four‐gamete test and sequence length bias suggest recombination occurs between almost all strains within each species, even between populations separated by large distances or living in different habitats. Overall, our results show that, despite some isolation by distance and environmental conditions, sufficient gene‐flow occurs among cyanobacterial strains to prevent either driver from producing distinctive population structures across the watershed.