The origins of SARS-CoV-2: A critical review.

Since the first reports of a novel severe acute respiratory syndrome (SARS)-like coronavirus in December 2019 in Wuhan, China, there has been intense interest in understanding how severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) emerged in the human population. Recent debate has coalesced around two competing ideas: a "laboratory escape" scenario and zoonotic emergence. Here, we critically review the current scientific evidence that may help clarify the origin of SARS-CoV-2.

Borgs are giant genetic elements with potential to expand metabolic capacity.

Anaerobic methane oxidation exerts a key control on greenhouse gas emissions1, yet factors that modulate the activity of microorganisms performing this function remain poorly understood. Here we discovered extraordinarily large, diverse DNA sequences that primarily encode hypothetical proteins through studying groundwater, sediments and wetland soil where methane production and oxidation occur. Four curated, complete genomes are linear, up to approximately 1 Mb in length and share genome organization, including replichore structure, long inverted terminal repeats and genome-wide unique perfect tandem direct repeats that are intergenic or generate amino acid repeats. We infer that these are highly divergent archaeal extrachromosomal elements with a distinct evolutionary origin. Gene sequence similarity, phylogeny and local divergence of sequence composition indicate that many of their genes were assimilated from methane-oxidizing Methanoperedens archaea. We refer to these elements as 'Borgs'. We identified at least 19 different Borg types coexisting with Methanoperedens spp. in four distinct ecosystems. Borgs provide methane-oxidizing Methanoperedens archaea access to genes encoding proteins involved in redox reactions and energy conservation (for example, clusters of multihaem cytochromes and methyl coenzyme M reductase). These data suggest that Borgs might have previously unrecognized roles in the metabolism of this group of archaea, which are known to modulate greenhouse gas emissions, but further studies are now needed to establish their functional relevance.

Transporter genes in biosynthetic gene clusters predict metabolite characteristics and siderophore activity.

Biosynthetic gene clusters (BGCs) are operonic sets of microbial genes that synthesize specialized metabolites with diverse functions, including siderophores and antibiotics, which often require export to the extracellular environment. For this reason, genes for transport across cellular membranes are essential for the production of specialized metabolites and are often genomically colocalized with BGCs. Here, we conducted a comprehensive computational analysis of transporters associated with characterized BGCs. In addition to known exporters, in BGCs we found many importer-specific transmembrane domains that co-occur with substrate binding proteins possibly for uptake of siderophores or metabolic precursors. Machine learning models using transporter gene frequencies were predictive of known siderophore activity, molecular weights, and a measure of lipophilicity (log P) for corresponding BGC-synthesized metabolites. Transporter genes associated with BGCs were often equally or more predictive of metabolite features than biosynthetic genes. Given the importance of siderophores as pathogenicity factors, we used transporters specific for siderophore BGCs to identify both known and uncharacterized siderophore-like BGCs in genomes from metagenomes from the infant and adult gut microbiome. We find that 23% of microbial genomes from premature infant guts have siderophore-like BGCs, but only 3% of those assembled from adult gut microbiomes do. Although siderophore-like BGCs from the infant gut are predominantly associated with Enterobacteriaceae and Staphylococcus, siderophore-like BGCs can be identified from taxa in the adult gut microbiome that have rarely been recognized for siderophore production. Taken together, these results show that consideration of BGC-associated transporter genes can inform predictions of specialized metabolite structure and function.

Novel soil bacteria possess diverse genes for secondary metabolite biosynthesis.

In soil ecosystems, microorganisms produce diverse secondary metabolites such as antibiotics, antifungals and siderophores that mediate communication, competition and interactions with other organisms and the environment1,2. Most known antibiotics are derived from a few culturable microbial taxa 3 , and the biosynthetic potential of the vast majority of bacteria in soil has rarely been investigated 4 . Here we reconstruct hundreds of near-complete genomes from grassland soil metagenomes and identify microorganisms from previously understudied phyla that encode diverse polyketide and nonribosomal peptide biosynthetic gene clusters that are divergent from well-studied clusters. These biosynthetic loci are encoded by newly identified members of the Acidobacteria, Verrucomicobia and Gemmatimonadetes, and the candidate phylum Rokubacteria. Bacteria from these groups are highly abundant in soils5-7, but have not previously been genomically linked to secondary metabolite production with confidence. In particular, large numbers of biosynthetic genes were characterized in newly identified members of the Acidobacteria, which is the most abundant bacterial phylum across soil biomes 5 . We identify two acidobacterial genomes from divergent lineages, each of which encodes an unusually large repertoire of biosynthetic genes with up to fifteen large polyketide and nonribosomal peptide biosynthetic loci per genome. To track gene expression of genes encoding polyketide synthases and nonribosomal peptide synthetases in the soil ecosystem that we studied, we sampled 120 time points in a microcosm manipulation experiment and, using metatranscriptomics, found that gene clusters were differentially co-expressed in response to environmental perturbations. Transcriptional co-expression networks for specific organisms associated biosynthetic genes with two-component systems, transcriptional activation, putative antimicrobial resistance and iron regulation, linking metabolite biosynthesis to processes of environmental sensing and ecological competition. We conclude that the biosynthetic potential of abundant and phylogenetically diverse soil microorganisms has previously been underestimated. These organisms may represent a source of natural products that can address needs for new antibiotics and other pharmaceutical compounds.

Microcoleus (Cyanobacteria) form watershed-wide populations without strong gradients in population structure.

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 benthic Microcoleus-dominated cyanobacterial mats collected in the Eel and Russian River networks (California, USA). The 64 Microcoleus genomes 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 common Microcoleus species, 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.

Sewage, Salt, Silica, and SARS-CoV-2 (4S): An Economical Kit-Free Method for Direct Capture of SARS-CoV-2 RNA from Wastewater.

Wastewater-based epidemiology is an emerging tool to monitor COVID-19 infection levels by measuring the concentration of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA in wastewater. There remains a need to improve wastewater RNA extraction methods' sensitivity, speed, and reduce reliance on often expensive commercial reagents to make wastewater-based epidemiology more accessible. We present a kit-free wastewater RNA extraction method, titled "Sewage, Salt, Silica and SARS-CoV-2" (4S), that employs the abundant and affordable reagents sodium chloride (NaCl), ethanol, and silica RNA capture matrices to recover sixfold more SARS-CoV-2 RNA from wastewater than an existing ultrafiltration-based method. The 4S method concurrently recovered pepper mild mottle virus (PMMoV) and human 18S ribosomal subunit rRNA, which have been proposed as fecal concentration controls. The SARS-CoV-2 RNA concentrations measured in three sewersheds corresponded to the relative prevalence of COVID-19 infection determined via clinical testing. Lastly, controlled experiments indicate that the 4S method prevented RNA degradation during storage of wastewater samples, was compatible with heat pasteurization, and in our experience, 20 samples can be processed by one lab technician in approximately 2 h. Overall, the 4S method is promising for effective, economical, and accessible wastewater-based epidemiology for SARS-CoV-2, providing another tool to fight the global pandemic.

A benchmark for microRNA quantification algorithms using the OpenArray platform.

BACKGROUND: Several techniques have been tailored to the quantification of microRNA expression, including hybridization arrays, quantitative PCR (qPCR), and high-throughput sequencing. Each of these has certain strengths and limitations depending both on the technology itself and the algorithm used to convert raw data into expression estimates. Reliable quantification of microRNA expression is challenging in part due to the relatively low abundance and short length of the miRNAs. While substantial research has been devoted to the development of methods to quantify mRNA expression, relatively little effort has been spent on microRNA expression. RESULTS: In this work, we focus on the Life Technologies TaqMan OpenArray(Ⓡ) system, a qPCR-based platform to measure microRNA expression. Several algorithms currently exist to estimate expression from the raw amplification data produced by qPCR-based technologies. To assess and compare the performance of these methods, we performed a set of dilution/mixture experiments to create a benchmark data set. We also developed a suite of statistical assessments that evaluate many different aspects of performance: accuracy, precision, titration response, number of complete features, limit of detection, and data quality. The benchmark data and software are freely available via two R/Bioconductor packages, miRcomp and miRcompData. Finally, we demonstrate use of our software by comparing two widely used algorithms and providing assessments for four other algorithms. CONCLUSIONS: Benchmark data sets and software are crucial tools for the assessment and comparison of competing algorithms. We believe that the miRcomp and miRcompData packages will facilitate the development of new methodology for microRNA expression estimation.

Functional interactions of archaea, bacteria and viruses in a hypersaline endolithic community.

Halite endoliths in the Atacama Desert represent one of the most extreme ecosystems on Earth. Cultivation-independent methods were used to examine the functional adaptations of the microbial consortia inhabiting halite nodules. The community was dominated by haloarchaea and functional analysis attributed most of the autotrophic CO2 fixation to one unique cyanobacterium. The assembled 1.1 Mbp genome of a novel nanohaloarchaeon, Candidatus Nanopetramus SG9, revealed a photoheterotrophic life style and a low median isoelectric point (pI) for all predicted proteins, suggesting a 'salt-in' strategy for osmotic balance. Predicted proteins of the algae identified in the community also had pI distributions similar to 'salt-in' strategists. The Nanopetramus genome contained a unique CRISPR/Cas system with a spacer that matched a partial viral genome from the metagenome. A combination of reference-independent methods identified over 30 complete or near complete viral or proviral genomes with diverse genome structure, genome size, gene content and hosts. Putative hosts included Halobacteriaceae, Nanohaloarchaea and Cyanobacteria. Despite the dependence of the halite community on deliquescence for liquid water availability, this study exposed an ecosystem spanning three phylogenetic domains, containing a large diversity of viruses and predominance of a 'salt-in' strategy to balance the high osmotic pressure of the environment.

Microbial diversity and the presence of algae in halite endolithic communities are correlated to atmospheric moisture in the hyper-arid zone of the Atacama Desert.

The Atacama Desert is one of the oldest and driest deserts in the world, and its hyper-arid core is described as 'the most barren region imaginable'. We used a combination of high-throughput sequencing and microscopy methods to characterize the endolithic microbial assemblages of halite pinnacles (salt rocks) collected in several hyper-arid areas of the desert. We found communities dominated by archaea that relied on a single phylotype of Halothece cyanobacteria for primary production. A few other phylotypes of salt-adapted bacteria and archaea, including Salinibacter, Halorhabdus, and Halococcus were major components of the halite communities, indicating specific adaptations to the unique halite environments. Multivariate statistical analyses of diversity metrics clearly separated the halite communities from that of the surrounding soil in the Yungay area. These analyses also revealed distribution patterns of halite communities correlated with atmospheric moisture. Microbial endolithic communities from halites exposed to coastal fogs and high relative humidity were more diverse; their archaeal and bacterial assemblages were accompanied by a novel algae related to oceanic picoplankton of the Mamiellales. In contrast, we did not find any algae in the Yungay pinnacles, suggesting that the environmental conditions in this habitat might be too extreme for eukaryotic photosynthetic life.

Genetic tracing of market wildlife and viruses at the epicenter of the COVID-19 pandemic.

Zoonotic spillovers of viruses have occurred through the animal trade worldwide. The start of the COVID-19 pandemic was traced epidemiologically to the Huanan Wholesale Seafood Market, the site with the most reported wildlife vendors in the city of Wuhan, China. Here, we analyze publicly available qPCR and sequencing data from environmental samples collected in the Huanan market in early 2020. We demonstrate that the SARS-CoV-2 genetic diversity linked to this market is consistent with market emergence, and find increased SARS-CoV-2 positivity near and within a particular wildlife stall. We identify wildlife DNA in all SARS-CoV-2 positive samples from this stall. This includes species such as civets, bamboo rats, porcupines, hedgehogs, and one species, raccoon dogs, known to be capable of SARS-CoV-2 transmission. We also detect other animal viruses that infect raccoon dogs, civets, and bamboo rats. Combining metagenomic and phylogenetic approaches, we recover genotypes of market animals and compare them to those from other markets. This analysis provides the genetic basis for a short list of potential intermediate hosts of SARS-CoV-2 to prioritize for retrospective serological testing and viral sampling.

Interactions of Non-Nutritive Artificial Sweeteners with the Microbiome in Metabolic Syndrome.

Replacing sugar with non-nutritive artificial sweeteners (NAS) is a popular dietary choice for the prevention and management of metabolic syndrome and its comorbidities. However, evidence in human trials is conflicted regarding the efficacy of this strategy and whether NAS may counterintuitively promote, rather than prevent, metabolic derangements. The heterogeneity in outcomes may stem in part from microbiome variation between human participants and across research animal vivaria, leading to differential interactions of NAS with gut bacteria. An increasing body of evidence indicates that NAS can alter the mammalian gut microbiome composition, function, and metabolome, which can, in turn, influence host metabolic health. While there is evidence for microbiome-mediated metabolic shifts in response to NAS, the mechanisms by which NAS affect the gut microbiome, and how the microbiome subsequently affects host metabolic processes, remain unclear. In this viewpoint, we discuss data from human and animal trials and provide an overview of the current evidence for NAS-mediated microbial and metabolomic changes. We also review potential mechanisms through which NAS may influence the microbiome and delineate the next steps required to inform public health policies.

Good microbes, bad genes? The dissemination of antimicrobial resistance in the human microbiome.

A global rise in antimicrobial resistance among pathogenic bacteria has proved to be a major public health threat, with the rate of multidrug-resistant bacterial infections increasing over time. The gut microbiome has been studied as a reservoir of antibiotic resistance genes (ARGs) that can be transferred to bacterial pathogens via horizontal gene transfer (HGT) of conjugative plasmids and mobile genetic elements (the gut resistome). Advances in metagenomic sequencing have facilitated the identification of resistome modulators, including live microbial therapeutics such as probiotics and fecal microbiome transplantation that can either expand or reduce the abundances of ARG-carrying bacteria in the gut. While many different gut microbes encode for ARGs, they are not uniformly distributed across, or transmitted by, various members of the microbiome, and not all are of equal clinical relevance. Both experimental and theoretical approaches in microbial ecology have been applied to understand differing frequencies of ARG horizontal transfer between commensal microbes as well as between commensals and pathogens. In this commentary, we assess the evidence for the role of commensal gut microbes in encoding antimicrobial resistance genes, the degree to which they are shared both with other commensals and with pathogens, and the host and environmental factors that can impact resistome dynamics. We further discuss novel sequencing-based approaches for identifying ARGs and predicting future transfer events of clinically relevant ARGs from commensals to pathogens.

A widely distributed genus of soil Acidobacteria genomically enriched in biosynthetic gene clusters.

Bacteria of the phylum Acidobacteria are one of the most abundant groups across soil ecosystems, yet they are represented by comparatively few sequenced genomes, leaving gaps in our understanding of their metabolic diversity. Recently, genomes of Acidobacteria species with unusually large repertoires of biosynthetic gene clusters (BGCs) were reconstructed from grassland soil metagenomes, but the degree to which species with this trait are widespread is still unknown. To investigate this, we assembled 46 metagenome-assembled genomes recovered from permanently saturated organic-rich soils of a vernal (spring) pool ecosystem in Northern California. We obtained high and medium-quality draft genomes for three novel species from Candidatus Angelobacter (a proposed subdivision 1 Acidobacterial genus), a genus that is genomically enriched in genes for specialized metabolite biosynthesis. Acidobacteria were particularly abundant in the vernal pool sediments, and a Ca. Angelobacter species was the most abundant bacterial species detected in some samples. We identified numerous diverse biosynthetic gene clusters in these genomes, and also in five additional genomes from other publicly available soil metagenomes for other related Ca. Angelobacter species. Metabolic analysis indicates that Ca. Angelobacter likely are aerobes that ferment organic carbon, with potential to contribute to carbon compound turnover in soils. Using metatranscriptomics, we identified in situ metabolic activity and expression of specialized metabolic traits for two species from this genus. In conclusion, we expand genomic sampling of the uncultivated Ca. Angelobacter, and show that they represent common and sometimes highly abundant members of dry and saturated soil communities, with a high degree of capacity for synthesis of diverse specialized metabolites.

Priority effects in microbiome assembly.

Advances in next-generation sequencing have enabled the widespread measurement of microbiome composition across systems and over the course of microbiome assembly. Despite substantial progress in understanding the deterministic drivers of community composition, the role of historical contingency remains poorly understood. The establishment of new species in a community can depend on the order and/or timing of their arrival, a phenomenon known as a priority effect. Here, we review the mechanisms of priority effects and evidence for their importance in microbial communities inhabiting a range of environments, including the mammalian gut, the plant phyllosphere and rhizosphere, soil, freshwaters and oceans. We describe approaches for the direct testing and prediction of priority effects in complex microbial communities and illustrate these with re-analysis of publicly available plant and animal microbiome datasets. Finally, we discuss the shared principles that emerge across study systems, focusing on eco-evolutionary dynamics and the importance of scale. Overall, we argue that predicting when and how current community state impacts the success of newly arriving microbial taxa is crucial for the management of microbiomes to sustain ecological function and host health. We conclude by discussing outstanding conceptual and practical challenges that are faced when measuring priority effects in microbiomes.

Soils and sediments host Thermoplasmata archaea encoding novel copper membrane monooxygenases (CuMMOs).

Copper membrane monooxygenases (CuMMOs) play critical roles in the global carbon and nitrogen cycles. Organisms harboring these enzymes perform the first, and rate limiting, step in aerobic oxidation of ammonia, methane, or other simple hydrocarbons. Within archaea, only organisms in the order Nitrososphaerales (Thaumarchaeota) encode CuMMOs, which function exclusively as ammonia monooxygenases. From grassland and hillslope soils and aquifer sediments, we identified 20 genomes from distinct archaeal species encoding divergent CuMMO sequences. These archaea are phylogenetically clustered in a previously unnamed Thermoplasmatota order, herein named the Ca. Angelarchaeales. The CuMMO proteins in Ca. Angelarchaeales are more similar in structure to those in Nitrososphaerales than those of bacteria, and contain all functional residues required for general monooxygenase activity. Ca. Angelarchaeales genomes are significantly enriched in blue copper proteins (BCPs) relative to sibling lineages, including plastocyanin-like electron carriers and divergent nitrite reductase-like (nirK) 2-domain cupredoxin proteins co-located with electron transport machinery. Ca. Angelarchaeales also encode significant capacity for peptide/amino acid uptake and degradation and share numerous electron transport mechanisms with the Nitrososphaerales. Ca. Angelarchaeales are detected at high relative abundance in some of the environments where their genomes originated from. While the exact substrate specificities of the novel CuMMOs identified here have yet to be determined, activity on ammonia is possible given their metabolic and ecological context. The identification of an archaeal CuMMO outside of the Nitrososphaerales significantly expands the known diversity of CuMMO enzymes in archaea and suggests previously unaccounted organisms contribute to critical global nitrogen and/or carbon cycling functions.

The Huanan Seafood Wholesale Market in Wuhan was the early epicenter of the COVID-19 pandemic.

Understanding how severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) emerged in 2019 is critical to preventing future zoonotic outbreaks before they become the next pandemic. The Huanan Seafood Wholesale Market in Wuhan, China, was identified as a likely source of cases in early reports, but later this conclusion became controversial. We show here that the earliest known COVID-19 cases from December 2019, including those without reported direct links, were geographically centered on this market. We report that live SARS-CoV-2-susceptible mammals were sold at the market in late 2019 and that within the market, SARS-CoV-2-positive environmental samples were spatially associated with vendors selling live mammals. Although there is insufficient evidence to define upstream events, and exact circumstances remain obscure, our analyses indicate that the emergence of SARS-CoV-2 occurred through the live wildlife trade in China and show that the Huanan market was the epicenter of the COVID-19 pandemic.

Species- and site-specific genome editing in complex bacterial communities.

Understanding microbial gene functions relies on the application of experimental genetics in cultured microorganisms. However, the vast majority of bacteria and archaea remain uncultured, precluding the application of traditional genetic methods to these organisms and their interactions. Here, we characterize and validate a generalizable strategy for editing the genomes of specific organisms in microbial communities. We apply environmental transformation sequencing (ET-seq), in which nontargeted transposon insertions are mapped and quantified following delivery to a microbial community, to identify genetically tractable constituents. Next, DNA-editing all-in-one RNA-guided CRISPR-Cas transposase (DART) systems for targeted DNA insertion into organisms identified as tractable by ET-seq are used to enable organism- and locus-specific genetic manipulation in a community context. Using a combination of ET-seq and DART in soil and infant gut microbiota, we conduct species- and site-specific edits in several bacteria, measure gene fitness in a nonmodel bacterium and enrich targeted species. These tools enable editing of microbial communities for understanding and control.

The molecular epidemiology of multiple zoonotic origins of SARS-CoV-2.

Understanding the circumstances that lead to pandemics is important for their prevention. We analyzed the genomic diversity of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) early in the coronavirus disease 2019 (COVID-19) pandemic. We show that SARS-CoV-2 genomic diversity before February 2020 likely comprised only two distinct viral lineages, denoted "A" and "B." Phylodynamic rooting methods, coupled with epidemic simulations, reveal that these lineages were the result of at least two separate cross-species transmission events into humans. The first zoonotic transmission likely involved lineage B viruses around 18 November 2019 (23 October to 8 December), and the separate introduction of lineage A likely occurred within weeks of this event. These findings indicate that it is unlikely that SARS-CoV-2 circulated widely in humans before November 2019 and define the narrow window between when SARS-CoV-2 first jumped into humans and when the first cases of COVID-19 were reported. As with other coronaviruses, SARS-CoV-2 emergence likely resulted from multiple zoonotic events.

inStrain profiles population microdiversity from metagenomic data and sensitively detects shared microbial strains.

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 manner, 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 harbor 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.