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The spatiotemporal structure of the human microbiome1,2, proteome3 and metabolome4,5 reflects and determines regional intestinal physiology and may have implications for disease6. Yet, little is known about the distribution of microorganisms, their environment and their biochemical activity in the gut because of reliance on stool samples and limited access to only some regions of the gut using endoscopy in fasting or sedated individuals7. To address these deficiencies, we developed an ingestible device that collects samples from multiple regions of the human intestinal tract during normal digestion. Collection of 240 intestinal samples from 15 healthy individuals using the device and subsequent multi-omics analyses identified significant differences between bacteria, phages, host proteins and metabolites in the intestines versus stool. Certain microbial taxa were differentially enriched and prophage induction was more prevalent in the intestines than in stool. The host proteome and bile acid profiles varied along the intestines and were highly distinct from those of stool. Correlations between gradients in bile acid concentrations and microbial abundance predicted species that altered the bile acid pool through deconjugation. Furthermore, microbially conjugated bile acid concentrations exhibited amino acid-dependent trends that were not apparent in stool. Overall, non-invasive, longitudinal profiling of microorganisms, proteins and bile acids along the intestinal tract under physiological conditions can help elucidate the roles of the gut microbiome and metabolome in human physiology and disease.

Policy reset and convergence on governance are needed

Objectives This study was conducted to determine whether bacteria, fungi, or archaea are detected in the amniotic fluid of patients who underwent midtrimester amniocentesis for clinical indications. Methods Amniotic fluid samples from 692 pregnancies were tested by using a combination of culture and end-point polymerase chain reaction (PCR) techniques. Intra-amniotic inflammation was defined as an interleukin-6 concentration >2,935 pg/mL. Results Microorganisms were detected in 0.3% (2/692) of cases based on cultivation, 1.73% (12/692) based on broad-range end-point PCR, and 2% (14/692) based on the combination of both methods. However, most (13/14) of these cases did not have evidence of intra-amniotic inflammation and delivered at term. Therefore, a positive culture or end-point PCR in most patients appears to have no apparent clinical significance. Conclusions Amniotic fluid in the midtrimester of pregnancy generally does not contain bacteria, fungi, or archaea. Interpretation of amniotic fluid culture and molecular microbiologic results is aided by the assessment of the inflammatory state of the amniotic cavity. The presence of microorganisms, as determined by culture or a microbial signal in the absence of intra-amniotic inflammation, appears to be a benign condition.

Most processing of the human diet occurs in the small intestine. Metabolites in the small intestine originate from host secretions, plus the ingested exposome1 and microbial transformations. Here we probe the spatiotemporal variation of upper intestinal luminal contents during routine daily digestion in 15 healthy male and female participants. For this, we use a non-invasive, ingestible sampling device to collect and analyse 274 intestinal samples and 60 corresponding stool homogenates by combining five mass spectrometry assays2,3 and 16S rRNA sequencing. We identify 1,909 metabolites, including sulfonolipids and fatty acid esters of hydroxy fatty acids (FAHFA) lipids. We observe that stool and intestinal metabolomes differ dramatically. Food metabolites display trends in dietary biomarkers, unexpected increases in dicarboxylic acids along the intestinal tract and a positive association between luminal keto acids and fruit intake. Diet-derived and microbially linked metabolites account for the largest inter-individual differences. Notably, two individuals who had taken antibiotics within 6 months before sampling show large variation in levels of bioactive FAHFAs and sulfonolipids and other microbially related metabolites. From inter-individual variation, we identify Blautia species as a candidate to be involved in FAHFA metabolism. In conclusion, non-invasive, in vivo sampling of the human small intestine and ascending colon under physiological conditions reveals links between diet, host and microbial metabolism.

Background: Early and accurate diagnosis of acute infection has important consequences for antibiotic stewardship, resource allocation, and clinical outcomes. However, limited sensitivity and specificity of current diagnostics lead to the erroneous prescription of antibiotics. Host-response-based diagnostics have the potential to address these challenges, but accuracy varies widely across heterogeneous global patient populations. Methods: We performed a multi-cohort analysis of 4,200 unique samples across 69 retrospective blood transcriptome datasets from 20 countries. These samples were collected from patients with acute bacterial or viral infections representing a broad spectrum of biological (age, sex, race, ethnicity, pathogen, host genetics), clinical (severity, day of presentation), and technical (Affymetrix, Agilent, Illumina) heterogeneity. We also enrolled patients with infectious diseases in two cohorts from Laos and Nepal. Findings: Current host-response-based gene signatures distinguished intracellular bacterial infection from viral infections with substantially lower accuracy. Using 69 datasets, divided into training and validation datasets, we identified an 8-gene signature that distinguished intracellular or extracellular bacterial infections from viral infections with an area under the receiver operating characteristic curve (AUROC) >0.91 (85.9% specificity, 90.2% sensitivity). In two prospective cohorts from Nepal and Laos, profiled using Fluidigm RT-PCR, the 8-gene classifier distinguished bacterial infections from viral infections with an AUROC of 0.94 (87.9% specificity, 91% sensitivity). Interpretation: The 8-gene signature met the target product profile (90% sensitivity, 80% specificity) proposed by the WHO and others for distinguishing bacterial and viral infections. The 8-gene signature should be considered for further validation and implementation. Funding Information: PK is funded in part by the Bill and Melinda Gates Foundation (OPP1113682); the National Institute of Allergy and Infectious Diseases (NIAID) grants 1U19AI109662, U19AI057229, and 5R01AI125197; Department of Defense contracts W81XWH-18-1-0253 and W81XWH1910235; and the Ralph & Marian Falk Medical Research Trust. DAR is supported by NIH/NIAID U19 AI109761 and the Thomas C. and Joan M. Merigan Endowment at Stanford University. LOMWRU is funded by the Wellcome Trust of Great Britain. AMR is funded by the National Science Foundation Graduate Research Fellowship and the Stanford Graduate Fellowship. This research was funded in whole, or in part, by the Wellcome Trust [Grant number 220211]. Declaration of Interests: AMR, SJP, TES, DAR, and PK are named as inventors on a patent application describing the 8-gene set, which has been licensed to Inflammatix. TES and SAT are employees of Inflammatix, and TES and PK are shareholders in Inflammatix. Inflammatix had no role in the design, funding, or reporting of this work. SD is currently employed by FIND. The other authors declare no conflicts of interest. Ethics Approval Statement: Ethical clearance was granted by the former Faculty of Medical Sciences Ethical Review Committee (now University of Health Sciences Ethics Committee), National University of Laos, the Oxford University Tropical Ethics Committee, and the Stanford University Institutional Review Board.

The vaginal microbiome has been linked to numerous negative health outcomes including preterm birth. Specific taxa, includingGardnerellaspp., have been identified as risk factors for these conditions. Historically, microbiome analysis methods have treated allGardnerellaspp. as one species, but the broad diversity ofGardnerellahas recently become more apparent. In the present study, we explore the diversity ofGardnerellaclades and genomic species in the vaginal microbiome of pregnant women and their impacts on microbiome composition and associations with preterm birth.Shotgun metagenomic sequencing data collected longitudinally from three distinct cohorts of pregnant women were assessed. Relative abundance ofGardnerellaclades and genomic species and other taxa was quantified, and associations betweenGardnerellaclades and signatures of the vaginal microbiome were measured. We also assessed the diversity and abundance ofGardnerellavariants in 16S rRNA gene amplicon sequencing data from seven previously conducted studies in differing populations on the vaginal microbiome and preterm birth.Individual microbiomes often contained multipleGardnerellavariants, and the number of clades was associated with increased microbial load. The genusGardnerellawas also associated with increased microbial load, or the ratio of non-human reads to human reads. Taxon co-occurrence patterns matched previously described community structures, and were largely consistent acrossGardnerellaclades and among cohorts. Some variants previously described as rare were prevalent in other cohorts, highlighting the importance of surveying a diverse set of populations to fully capture the diversity ofGardnerella.The diversity ofGardnerellaboth across populations and within individual vaginal microbiomes has long been unappreciated, as has been the intra-species diversity of many other members of the vaginal microbiome.1The broad genomic diversity ofGardnerellahas led to its reclassification as multiple species; here we demonstrate the diversity ofGardnerellafound within and between vaginal microbiomes. Further studies should investigate the phenotypes ofGardnerellavariants that may underlie the mechanisms by whichGardnerellaspecies may differentially shape the vaginal microbiome.

The vaginal ecosystem is closely tied to human health and reproductive outcomes. However, its dynamics in the wake of childbirth remain poorly characterized. Here, we profiled the vaginal microbiota and cytokine milieu of subjects sampled throughout pregnancy (two cohorts;n= 196 pregnancies) and, in a subset, for one year postpartum (one cohort;n= 72 pregnancies). Delivery was associated with a vaginal pro-inflammatory cytokine response and the depletion of dominant taxa – typically,Lactobacillusspecies. By contrast, neither the progression of gestation nor the approach of labor strongly altered the vaginal ecosystem. At ~9.5 months postpartum (the latest timepoint at which cytokines were analyzed), elevated inflammation was associated with vaginal bacterial communities that had remained perturbed (i.e., highly diverse) from the time of delivery. Using time-to-event analysis, we found that the one-year postpartum probability of transitioning toLactobacillusdominance was 49.4% (95% confidence interval (CI) [33.6%, 61.5%];n= 58 at-risk cases, 86.2% of whom experienced this state prior to delivery). As diversity and inflammation declined postpartum, dominance byL. crispatus, the quintessential health-associated state, failed to recover: its prevalence before, immediately after, and one year after delivery was 41%, 4%, and 9%, respectively. Over the same period, states quasi-dominated by non-Lactobacillusspecies grew more common. Prompted by these findings, we revisited our pre-delivery data, discovering that a history of prior live birth was associated with a lower odds ofL. crispatusdominance in pregnant subjects (odds ratio (OR) 0.14; 95% CI [0.06, 0.32];P< 0.001) – an outcome modestly tempered by a longer (>18-month) interpregnancy interval. Our results suggest that reproductive history and childbirth in particular remodel the vaginal ecosystem and that the timing and degree of recovery from delivery may help determine the subsequent health of the woman and of future pregnancies.

Cell-free RNA from liquid biopsies can be analyzed to determine disease tissue of origin. We extend this concept to identify cell types of origin using the Tabula Sapiens transcriptomic cell atlas as well as individual tissue transcriptomic cell atlases in combination with the Human Protein Atlas RNA consensus dataset. We define cell type signature scores, which allow the inference of cell types that contribute to cell-free RNA for a variety of diseases.

Relationships between hosts and host-associated microbial communities are complex, intimate, and associated with a wide variety of health and disease states. For these reasons, these relationships have raised many difficult questions and claims about microbiome causation. While philosophers and scientists alike have pondered the challenges of causal inference and offered postulates and rules, there are no simple solutions, especially with poorly characterized, putative causal factors such as microbiomes, ill-defined host effects, and inadequate experimental models. Recommendations are provided here for conceptual and experimental approaches regarding microbiome causal inference, and for a research agenda.

INTRODUCTION: Although the genome is often called the blueprint of an organism, it is perhaps more accurate to describe it as a parts list composed of the various genes that may or may not be used in the different cell types of a multicellular organism. Although nearly every cell in the body has essentially the same genome, each cell type makes different use of that genome and expresses a subset of all possible genes. This has motivated efforts to characterize the molecular composition of various cell types within humans and multiple model organisms, both by transcriptional and proteomic approaches. We created a human reference atlas comprising nearly 500,000 cells from 24 different tissues and organs, many from the same donor. This atlas enabled molecular characterization of more than 400 cell types, their distribution across tissues, and tissue-specific variation in gene expression. RATIONALE: One caveat to current approaches to make cell atlases is that individual organs are often collected at different locations, collected from different donors, and processed using different protocols. Controlled comparisons of cell types between different tissues and organs are especially difficult when donors differ in genetic background, age, environmental exposure, and epigenetic effects. To address this, we developed an approach to analyzing large numbers of organs from the same individual. RESULTS: We collected multiple tissues from individual human donors and performed coordinated single-cell transcriptome analyses on live cells. The donors come from a range of ethnicities, are balanced by gender, have a mean age of 51 years, and have a variety of medical backgrounds. Tissue experts used a defined cell ontology terminology to annotate cell types consistently across the different tissues, leading to a total of 475 distinct cell types with reference transcriptome profiles. The full dataset can be explored online with the cellxgene tool. Data were collected for the bladder, blood, bone marrow, eye, fat, heart, kidney, large intestine, liver, lung, lymph node, mammary, muscle, pancreas, prostate, salivary gland, skin, small intestine, spleen, thymus, tongue, trachea, uterus, and vasculature. Fifty-nine separate specimens in total were collected, processed, and analyzed, and 483,152 cells passed quality control filtering. On a per-compartment basis, the dataset includes 264,824 immune cells, 104,148 epithelial cells, 31,691 endothelial cells, and 82,478 stromal cells. Working with live cells, as opposed to isolated nuclei, ensured that the dataset includes all mRNA transcripts within the cell, including transcripts that have been processed by the cell’s splicing machinery, thereby enabling insight into variation in alternative splicing. The Tabula Sapiens also provided an opportunity to densely and directly sample the human microbiome throughout the gastrointestinal tract. The intestines from two donors were sectioned into five regions: the duodenum, jejunum, ileum, and ascending and sigmoid colon. Each section was transected, and three to nine samples were collected from each location, followed by amplification and sequencing of the 16S ribosomal RNA gene. CONCLUSION: The Tabula Sapiens has revealed discoveries relating to shared behavior and subtle, organ-specific differences across cell types. We found T cell clones shared between organs and characterized organ-dependent hypermutation rates among B cells. Endothelial cells and macrophages are shared across tissues, often showing subtle but clear differences in gene expression. We found an unexpectedly large and diverse amount of cell type–specific RNA splice variant usage and discovered and validated many previously undefined splices. The intestinal microbiome was revealed to have nonuniform species distributions down to the 3-inch (7.62-cm) length scale. These are but a few examples of how the Tabula Sapiens represents a broadly useful reference to deeply understand and explore human biology at cellular resolution.

Vaginal microbiota composition affects many facets of reproductive health. Lactobacillus iners-dominated microbial communities are associated with poorer outcomes, including higher risk of bacterial vaginosis (BV), compared with vaginal microbiota rich in L. crispatus. Unfortunately, standard-of-care metronidazole therapy for BV typically results in dominance of L. iners, probably contributing to post-treatment relapse. Here we generate an L. iners isolate collection comprising 34 previously unreported isolates from 14 South African women with and without BV and 4 previously unreported isolates from 3 US women. We also report an associated genome catalogue comprising 1,218 vaginal Lactobacillus isolate genomes and metagenome-assembled genomes from300 women across 4 continents. We show that, unlike L. crispatus, L. iners growth is dependent on L-cysteine in vitro and we trace this phenotype to the absence of canonical cysteine biosynthesis pathways and a restricted repertoire of cysteine-related transport mechanisms. We further show that cysteine concentrations in cervicovaginal lavage samples correlate with Lactobacillus abundance in vivo and that cystine uptake inhibitors selectively inhibit L. iners growth in vitro. Combining an inhibitor with metronidazole promotes L. crispatus dominance of defined BV-like communities in vitro by suppressing L. iners growth. Our findings enable a better understanding of L. iners biology and suggest candidate treatments to modulate the vaginal microbiota to improve reproductive health for women globally.

SummaryThe response of the human gut microbiome to disruptions is often difficult to discern without model systems that remove the complexity of the host environment. Fluctuations in iron availability provide a case in point: the responses of pathogenic bacteria to iron in vitro are much better understood than those of the indigenous human gut commensal microbiota. In a clinical study of iron supplementation in healthy humans, we identified gradual, participant-specific microbiota shifts correlated with bacterial iron internalization. To identify direct effects due to taxon-specific iron sensitivity, we used stool samples from these participants as inocula to derive in vitro communities. Iron supplementation of these communities caused small shifts in structure, similar to in vivo, whereas iron deprivation dramatically inhibited growth with irreversible and cumulative reduction in diversity and replacement of some dominant species. Sensitivity of individual species to iron deprivation during growth in axenic culture generally predicted iron dependency in a community context. Finally, exogenous heme acted as a source of inorganic iron to prevent depletion of some community members. Our results highlight the complementarity of in vivo and in vitro studies in deconstructing how environmental factors affect gut microbiome structure.

The spatiotemporal structure of the human microbiome and metabolome reflects and determines regional intestinal physiology and may have implications for disease. Yet, we know little about the distribution of microbes and their products in the gut because of reliance on stool samples and limited access only to some regions of the gut using endoscopy in fasting or sedated individuals. To address these deficiencies, we developed and evaluated a safe, ingestible device that collects samples from multiple regions of the human intestinal tract during normal digestion. The collection of 240 intestinal samples from 15 healthy individuals using the device revealed significant differences between microbes and metabolites present in the intestines versus stool. Certain microbial taxa were differentially enriched, and bile acid profiles varied along the intestines and were highly distinct from those of stool. Correlations between gradients in bile acid concentrations and microbial abundance predicted species that altered the bile acid pool through deconjugation. Overall, we identified heterogeneous intestinal profiles of bacterial taxa and metabolites indicating that non-invasive multi-regional sampling of the intestinal tract under physiological conditions can help elucidate the roles of the gut microbiome and metabolome in human physiology and disease.

BackgroundThe oral microbiota is emerging as an influential factor of host physiology and disease state. Factors influencing oral microbiota composition have not been well characterised. In particular, there is a lack of population-based studies. We undertook a large hypothesis-free study of the saliva microbiota, considering potential influential factors of host health (frailty; diet; periodontal disease), demographics (age; sex; BMI) and sample processing (storage time), in a sample (n=679) of the TwinsUK cohort of adult twins.ResultsAlpha and beta diversity of the saliva microbiota was associated most strongly with frailty (alpha diversity: Q = 0.003, Observed; Q=0.002, Shannon; Q=0.003, Simpson; Beta diversity: Q = 0.002, Bray Curtis dissimilarity) and age (alpha diversity: Q=0.006, Shannon; Q=0.003, Simpson; beta diversity: Q=0.002, Bray Curtis dissimilarity; Q= 0.032, Weighted UniFrac) in multivariate models including age, frailty, sex, BMI, frailty and diet, and adjustment for multiple testing. Those with a more advanced age were more likely to be dissimilar in the saliva microbiota composition than younger participants (P = 5.125e-06, ANOVA). In subsample analyses, including consideration of periodontal disease (total n=138, periodontal disease n=66), the association with frailty remained for alpha diversity (Q=0.002, Observed ASVs; Q= 0.04 Shannon Index), but not beta diversity, whilst age was not demonstrated to associate with alpha or beta diversity in this subsample, potentially due to insufficient statistical power. Length of time that samples were stored prior to sequencing was associated with beta diversity (Q = 0.002, Bray Curtis dissimilarity). Six bacterial taxa were associated with age after adjustment for frailty and diet.ConclusionsFrailty and age emerged as the most influential factors of saliva microbiota composition. Whilst frailty and age are correlates, the associations were independent of each other, suggesting that both biological and chronological ageing are key drivers of saliva microbiota composition.

Diverse and non-Lactobacillus-dominated vaginal microbial communities are associated with adverse health outcomes such as preterm birth and acquisition of sexually transmitted infections. Despite the importance of recognizing and understanding the key risk-associated features of these communities, their heterogeneous structure and properties remain ill-defined. Clustering approaches have been commonly used to characterize vaginal communities, but they lack sensitivity and robustness in resolving community substructures and revealing transitions between potential sub-communities. We used a highly resolved approach based on mixed membership topic models with multi-domain longitudinal data from cohorts of pregnant and non-pregnant study participants to identify several non-Lactobacillus-dominated sub-communities common to both cohorts regardless of reproductive status. These sub-communities correlated with clusters in metabolite concentrations. In non-pregnant individuals, we identified non-Lactobacillus-dominated sub-communities that were more common during menses but did not predict an increased likelihood of other non-Lactobacillus-dominated communities during the rest of the menstrual cycle. The menstrual cycle was a strong driver of transitions between sub-communities and was correlated with changes in levels of cytokines and metabolites, such as elevated TNF-α concentrations at the time of ovulation, and elevated kynurenine concentrations during menses, respectively. In pregnant individuals, some metabolite clusters were predictive of temporal instability in vaginal microbiota structure. Overall, our analyses based on mixed membership models revealed new substructures of the vaginal ecosystems which may have potentially important clinical or biological associations.

Responses of the indigenous human gut commensal microbiota to iron are poorly understood because of an emphasis on in vitro studies of pathogen iron sensitivity. In a study of iron supplementation in healthy humans, we identified gradual microbiota shifts in some participants correlated with bacterial iron internalization. To identify direct effects due to taxon-specific iron sensitivity, we used participant stool samples to derive diverse in vitro communities. Iron supplementation of these communities caused small compositional shifts, mimicking those in vivo, whereas iron deprivation dramatically inhibited growth with irreversible, cumulative reduction in diversity and replacement of dominant species. Sensitivity of individual species to iron deprivation in axenic culture generally predicted iron dependency in a community. Finally, exogenous heme acted as a source of inorganic iron to prevent depletion of some species. Our results highlight the complementarity of in vivo and in vitro studies in understanding how environmental factors affect gut microbiotas.

Much remains to be explored regarding the diversity of host-associated microbes. Here, we report the discovery of microbial structures in the mouths of bottlenose dolphins that we refer to as rectangular cell-like units (RCUs). DNA staining revealed multiple paired bands that suggested cells in the act of dividing along the longitudinal axis. Deep sequencing of samples enriched in RCUs through micromanipulation indicated that the RCUs are bacterial and distinct from Simonsiella, a genus with somewhat similar morphology and division patterning found in oral cavities of animals. Cryogenic transmission electron microscopy and tomography showed that RCUs are composed of parallel membrane-bound segments, likely individual cells, encapsulated by an S-layer-like periodic surface covering. RCUs displayed pilus-like appendages protruding as bundles of multiple threads that extend parallel to each other, and splay out at the tips and/or intertwine, in stark contrast to all known types of bacterial pili that consist of single, hair-like structures. These observations highlight the diversity of novel microbial forms and lifestyles that await discovery and characterization using tools complementary to genomics such as microscopy.

One of the outstanding questions regarding the human gut microbiota is how interventions designed to manipulate the microbiota may influence host phenotypic traits. Here, we employed a dietary intervention to probe this question in the context of lactose intolerance. To assess the effects of dairy elimination and reintroduction on the microbiota and host phenotype, we paired fecal 16S rRNA amplicon sequencing with a clinical assay for lactose intolerance, the hydrogen breath test. We studied 12 self-reported mildly lactose intolerant adults, each with tri-weekly collection of fecal samples over a 12-week study period (2 weeks baseline, 4 weeks of dairy elimination, 6 weeks of gradual milk reintroduction) and a hydrogen breath test before and after each phase. We found that although none of the subjects experienced a change in clinically defined status of lactose intolerant or tolerant, most subjects were qualitatively better able to tolerate dairy products with minimal symptoms at the end of the study compared to their baseline. Like clinical status, gut microbiota also resisted modification. Although the mean fraction of the genus Bifidobacterium, a group known to metabolize lactose, increased slightly with dairy reintroduction (from 0.0125 to 0.0206; Wilcoxon P = 0.068), the overall structure of each subject’s gut microbiota remained highly individualized and largely stable. Our study is small, but it suggests the possibility of qualitatively improved tolerance in the absence of change in clinically defined tolerance nor major change in the gut microbiota.

Low salivary flow, or hyposalivation, is associated with an increased incidence of dental caries and a shift in their location from biting surfaces towards coronal and root surfaces. However, the relationship between salivary flow and periodontal disease is less clear. To identify clinical indicators of low salivary flow -- including the spatial pattern of dental and periodontal disease, features of the supra- and subgingival microbiota, and symptoms of dry mouth -- we enrolled individuals into two cohorts. The low flow cohort (N = 32) consisted of individuals with a presumptive diagnosis of the autoimmune disorder Sjögren’s Syndrome (SS) while the control cohort (N = 119) consisted of healthy controls. We constructed a series of tooth-specific linear models to quantify the extent to which patient cohort, age, and unstimulated whole salivary flow rate (UWS-FR), independent of each other, are associated with dental and periodontal disease at each tooth. While age and a diagnosis of SS correlated with the site-specific increment of disease so too did UWS-FR. Not only were lower UWS-FRs associated with a greater number of decayed, missing, or filled surfaces at 21 teeth, but they were also associated with increased recession, as measured by clinical attachment loss (CAL), at 10 teeth (adjusted p < 0.05). In addition, we examined microbiota community structure at different tooth sites using data from 427 subgingival and supragingival samples of 6 individuals and found that microbial dispersal is reduced in patients with low salivary flow, but only at supragingival and not at subgingival sites. Finally, we found that complaints by subjects of a negative impact on overall quality of life were associated with a UWS-FR less than 0.1 mL/min. Overall, our results suggest that novel predictors of hyposalivation can be identified by integrating clinical, microbial, and patient history data.

We find ourselves ten months into one of the most catastrophic global health events of our lifetime and, disturbingly, we still do not know how it began. What’s even more troubling is that despite the critical importance of this question, efforts to investigate the origins of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus and of the associated disease, coronavirus disease 2019 (COVID-19), have become mired in politics, poorly supported assumptions and assertions, and incomplete information. To avoid or mitigate the dire consequences of this and future pandemics (here, people in PPE bury a victim in Delhi, India in June), unraveling the origins of SARS-CoV-2 and COVID-19 will be essential—even though a definitive answer may be elusive, and an objective analysis means broaching some uncomfortable possibilities. Image credit: Shutterstock/PradeepGaurs. SARS-CoV-2 is a betacoronavirus whose apparent closest relatives, RaTG13 and RmYN02, are reported to have been collected from bats in 2013 and 2019, respectively, in Yunnan Province, China (1). COVID-19 was first reported in December 2019 more than 1,000 miles away in Wuhan City, Hubei Province, China. Beyond these facts, the “origin story” is missing many key details, including a plausible and suitably detailed recent evolutionary history of the virus, the identity and provenance of its most recent ancestors, and surprisingly, the place, time, and mechanism of transmission of the first human infection. Even though a definitive answer may not be forthcoming, and even though an objective analysis requires addressing some uncomfortable possibilities, it is crucial that we pursue this question. Preventing the next pandemic depends on understanding the origins of this one. There are several potential origin scenarios. First, SARS-CoV-2 may … [↵][1]1Email: relman{at}stanford.edu. [1]: #xref-corresp-1-1