ABSTRACT The gastrointestinal (GI) tract is a site of replication of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and GI symptoms are often reported by patients. SARS-CoV-2 cell entry depends upon heparan sulfate (HS) proteoglycans, which commensal bacteria that bathe the human mucosa are known to modify. To explore human gut HS-modifying bacterial abundances and how their presence may impact SARS-CoV-2 infection, we developed a task-based analysis of proteoglycan degradation on large-scale shotgun metagenomic data. We observed that gut bacteria with high predicted catabolic capacity for HS differ by age and sex, factors associated with coronavirus disease 2019 (COVID-19) severity, and directly by disease severity during/after infection, but do not vary between subjects with COVID-19 comorbidities or by diet. Gut commensal bacterial HS-modifying enzymes reduce spike protein binding and infection of authentic SARS-CoV-2, suggesting that bacterial grooming of the GI mucosa may impact viral susceptibility.IMPORTANCESevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the virus responsible for coronavirus disease 2019, can infect the gastrointestinal (GI) tract, and individuals who exhibit GI symptoms often have more severe disease. The GI tract’s glycocalyx, a component of the mucosa covering the large intestine, plays a key role in viral entry by binding SARS-CoV-2’s spike protein via heparan sulfate (HS). Here, using metabolic task analysis of multiple large microbiome sequencing data sets of the human gut microbiome, we identify a key commensal human intestinal bacteria capable of grooming glycocalyx HS and modulating SARS-CoV-2 infectivity in vitro. Moreover, we engineered the common probiotic Escherichia coli Nissle 1917 (EcN) to effectively block SARS-CoV-2 binding and infection of human cell cultures. Understanding these microbial interactions could lead to better risk assessments and novel therapies targeting viral entry mechanisms.

In 2020, we identified cancer-specific microbial signals in The Cancer Genome Atlas (TCGA) [1]. Multiple peer-reviewed papers independently verified or extended our findings [2–12]. Given this impact, we carefully considered concerns by Gihawi et al. [13] that batch correction and database contamination with host sequences artificially created the appearance of cancer type-specific microbiomes. (1) We tested batch correction by comparing raw and Voom-SNM-corrected data per-batch, finding predictive equivalence and significantly similar features. We found consistent results with a modern microbiome-specific method (ConQuR [14]), and when restricting to taxa found in an independent, highly-decontaminated cohort. (2) Using Conterminator [15], we found low levels of human contamination in our original databases (~1% of genomes). We demonstrated that the increased detection of human reads in Gihawi et al. [13] was due to using a newer human genome reference. (3) We developed Exhaustive, a method twice as sensitive as Conterminator, to clean RefSeq. We comprehensively host-deplete TCGA with many human (pan)genome references. We repeated all analyses with this and the Gihawi et al. [13] pipeline, and found cancer type-specific microbiomes. These extensive re-analyses and updated methods validate our original conclusion that cancer type-specific microbial signatures exist in TCGA, and show they are robust to methodology.

Introduction: Links between cancer and microbes date back four millennia (Sepich-Poore et al. 2021. Science). Recently, we found that microbial DNA is detectable in tumor tissues and patient blood from many human cancer types (Poore et al. 2020. Nature). These intratumoral and bloodborne microbiomes were distinct between cancer types, between normal and malignant tissues, and present in cell-free plasma samples. However, the practical utility of cell-free microbial DNA (cf-mbDNA) as a bona fide liquid biopsy diagnostic, including its applicability in early-stage disease in treatment-naïve individuals, distinguishing histological subtypes, and discriminating against non-cancer-but-diseased patients remains unknown. Thus, we constructed an age and sex-matched cohort of >1000 individuals with lung cancer, lung disease, and no disease (healthy) to evaluate the utility of a cf-mbDNA-driven liquid biopsy diagnostic. Methods: Shallow shotgun metagenomic sequencing with gold-standard positive and negative controls was performed using 400 µL of patient plasma. Direct genome alignments separated human and microbial reads, and generated genome-wide binned and species-level abundances, respectively. Novel taxonomic diversity was captured by additionally performing de novo co-assemblies in tandem with tumor and blood samples from The Cancer Genome Atlas (TCGA). Multi-modal, stacked machine learning classifiers then evaluated the diagnostic performance of microbial-only and multi-species (microbial + human) information. Results: Cf-mbDNA provides strong diagnostic performance in treatment-naïve, cancer-bearing individuals versus age and sex-matched healthy controls, as early as stage I disease (AUROCs≥0.90). Furthermore, cf-mbDNA outperforms histological classification compared to human genomic information. Multi-species models paired with routinely-available clinicodemographic information provided robust discrimination of lung cancer versus lung diseases (AUROC≥0.80). Importantly, the addition of cell-free microbial information produced an integrated model surpassing the diagnostic performance of PET-CT and clinical risk models for lung nodule malignancy determination in a blinded validation cohort of Stage I lung cancer and non-cancer lung disease samples. Conclusion: Cf-mbDNA features comprise a novel class of biomarkers that are combinable with host analytes, and show promise for real-world, early-stage, lung cancer diagnosis. Citation Format: Serena Fraraccio, Stephen Wandro, Akanksha Singh-Taylor, Sandrine Miller-Montgomery, Eddie Adams, Rob Knight, Leopoldo N. Segal, Harvey I. Pass, Gregory D. Sepich-Poore. Assessing the real-world utility of cell-free microbial DNA in diagnosing early-stage lung cancer. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 5713.

Inter-individual differences in the gut microbiome are linked to alterations in inflammation and blood–brain barrier permeability, which may increase the risk of depression in people with HIV (PWH). The microbiome profile of blood, which is considered by many to be typically sterile, remains largely unexplored. We aimed to characterize the blood plasma microbiome composition and assess its association with major depressive disorder (MDD) in PWH and people without HIV (PWoH). In this cross-sectional, observational cohort, we used shallow-shotgun metagenomic sequencing to characterize the plasma microbiome of 151 participants (84 PWH and 67 PWoH), all of whom underwent a comprehensive neuropsychiatric assessment. The microbial composition did not differ between PWH and PWoH or between participants with MDD and those without it. Using the songbird model, we computed the log ratio of the highest and lowest 30% of the ranked classes associated with HIV and MDD. We found that HIV infection and lifetime MDD were enriched in a set of differentially abundant inflammatory classes, such as Flavobacteria and Nitrospira. Our results suggest that the circulating plasma microbiome may increase the risk of MDD related to dysbiosis-induced inflammation in PWH. If confirmed, these findings may indicate new biological mechanisms that could be targeted to improve treatment of MDD in PWH.

Links between cancer and microbes date back four millennia (Sepich-Poore et al. 2021. Science). Recently, we found that microbial DNA is detectable in tumor tissues and patient blood from many human cancer types (Poore et al. 2020. Nature; Narunsky-Haziza et al. 2022. Cell). These intratumoral and bloodborne microbiomes were distinct between cancer types, between normal and malignant tissues, and present in cell-free plasma samples. However, the practical utility of cell-free microbial DNA (cf-mbDNA) as a bona fide liquid biopsy remains untested, including its ability to diagnose early-stage disease in treatment-naïve individuals, to distinguish histological subtypes, and to discriminate against non-cancer-but-diseased patients.

The cancer microbiome field tremendously accelerated following the release of our manuscript nearly three years ago 1 , including direct validation of our cancer type-specific conclusions in independent, international cohorts 2,3 and the tumor microbiome’s adoption into the hallmarks of cancer 4 . Disentangling contamination signals from biological signals is an important consideration for this research field. Therefore, despite numerous, high-impact, peer-reviewed research papers that either validated our conclusions or extended them using data we released 2,5–13 , we carefully considered criticism raised by Gihawi et al . about potential mishandling of contaminants, batch effects, and machine learning approaches—all of which were central topics in our manuscript. Nonetheless, a close examination of each concern alongside the original manuscript and re-analyses of our published data strongly demonstrates the robustness of the original findings. To remove all doubt, however, we have reproduced all key conclusions from the original manuscript using only overlapping bacterial genera identified in a highly decontaminated, multi-cancer, international cohort (Weizmann Institute of Science, WIS) 2 , with or without batch correction, and with multiclass machine learning analyses to mitigate class imbalances. Our published pan-cancer mycobiome manuscript 3 also affirms these findings using updated, state-of-the-art methods. We also note that every analysis shown here was possible using public data and code that we had already provided.

It is currently unknown whether endovascular filament (EF) models of acute subarachnoid hemorrhage (SAH) introduce any ‘side bias’ upon cerebrovascular reactivity by virtue of unilateral carotid manipulation, unilateral EF insertion, or potentially ipsilateral site of intracranial rupture. In this study, three experimental groups of adult male wistar rats were used: non-operated controls (n=20), sham operated controls (n=8), and SAH groups (n=26). All were anaesthetized with intraperitoneal 25% urethane (1 g/kg) except n=2 anaesthetized with intraperitoneal hypnorm/hypnovel. SAH was created by advancing an intraluminal thread through the intracranial internal carotid artery from an extracranial source in the neck. Using in vitro wire myography in all three groups, middle cerebral artery (MCA) responses ipsilateral and contralateral to EF insertion were compared using a range of vasoconstrictors and vasodilators within 3 h of SAH. No significant side differences in MCA reactivity were found with any agent in any group or sub-group analysed. In conclusion, EF-SAH models do not appear to introduce any significant ‘side bias’ upon ipsilateral MCA reactivity by virtue of the potentially confounding combination: (1) unilateral carotid manipulation, (2) unilateral EF insertion or (3) potentially ipsilateral intracranial rupture. They may thus be more confidentally used for post-SAH ex vivo cerebral vessel study—acute or delayed.

Introduction: Human tissues, including tumors, are extensively colonized by taxonomically diverse microbes. Intra-tumoral microbial activity and events of cellular turnover and trafficking contribute to shedding of microbial nucleic acids into the blood stream. Here we characterized microbial signatures (mbDNA) present in primary-tumor tissue and in the blood of patients affected with different cancer types, with particular focus on lung cancer, and we demonstrated the discriminatory power of such microbial signatures for the identification and classification of lung cancer versus other cancer types. We further validated our findings using plasma-derived cell-free microbial DNA (cf-mbDNA) to discriminate between lung cancer and cancer-free control samples. Methods: We examined The Cancer Genome Atlas (TCGA) compendium of treatment-naïve, whole genome and transcriptomic sequencing datasets to extrapolate genetic signatures of microbial origin associated with 33 different tumor types collected from 10,481 patients, which included non-neoplastic tumor-adjacent tissue and blood samples. 7.2% of TCGA sequencing reads were classified as non-human, of which 35.2% could be taxonomically classified using a reference database containing 59,974 total microbial genomes. These taxonomically assigned data sets were then used to train machine learning models (using a 70/30 train/test split for all cancers) to discriminate between and within types and stages of cancer. Results: We demonstrated that mbDNA signatures from whole blood can be used to accurately classify the tissue of origin of 20 unique cancer types, including lung adenocarcinoma and lung squamous cell carcinoma. For lung adenocarcinoma we reported high discrimination between paired tumor tissue and normal-adjacent tissue (Avg. {AUROC,AUPR}={0.85,0.95}) and between primary tumor tissue and all-other cancer types (Avg. {AUROC,AUPR}={0.96,0.69}, n=32 cancer-types). We also demonstrated the high performance of blood-derived mbDNA when discriminating among TCGA cancer types: Avg. {AUROC,AUPR}={0.97,0.80}. Subsequent liquid biopsy results using plasma-derived cf-mbDNA offer compelling evidence that cf-mbDNA signatures can robustly discriminate adenocarcinoma lung-cancer samples from non-cancer controls. Conclusion: mbDNA holds considerable promise as a truly orthogonal means of detecting and classifying lung cancer independently from host genomic alternations. Using only mbDNA signatures we have demonstrated robust discrimination between cancer-free controls and lung cancer samples and have provided early evidence of the applicability of this approach to liquid biopsy. Our present efforts analyzing plasma cf-mbDNA with an expanded sample cohort will serve to fully validate this new class of liquid biopsy biomarkers for lung cancer detection. Citation Format: Gregory D. Sepich-Poore, Serena Fraraccio, Stephen Wandro, Rob Knight, Sandrine Miller-Montgomery, Eddie Adams. Early-stage lung cancer detection via circulating microbial DNA biomarkers and machine learning classification [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 1184.

Cancer-microbe associations have been explored for centuries, but cancer-associated fungi have rarely been examined. Here, we comprehensively characterize the cancer mycobiome within 17,401 patient tissue, blood, and plasma samples across 35 cancer types in four independent cohorts. We report fungal DNA and cells at low abundances across many major human cancers, with differences in community compositions that differ among cancer types, even when accounting for technical background. Fungal histological staining of tissue microarrays supported intratumoral presence and frequent spatial association with cancer cells and macrophages. Comparing intratumoral fungal communities with matched bacteriomes and immunomes re-vealed co-occurring bi-domain ecologies, often with permissive, rather than competitive, microenvironments and distinct immune responses. Clinically focused assessments suggested prognostic and diagnostic ca-pacities of the tissue and plasma mycobiomes, even in stage I cancers, and synergistic predictive perfor-mance with bacteriomes.

Assigning taxonomy remains a challenging topic in microbiome studies, due largely to ambiguity of reads which overlap multiple reference genomes. With the Web of Life (WoL) reference database hosting 10,575 reference genomes and growing, the percentage of ambiguous reads will only increase. The resulting artifacts create both the illusion of co-occurrence and a long tail end of extraneous reference hits that confound interpretation. We introduce genome cover, the fraction of reference genome overlapped by reads, to distinguish these artifacts. We show how to dynamically predict genome cover by read count and examine our model in Staphylococcus aureus monoculture. Our modeling cleanly separates both S. aureus and true contaminants from the false artifacts of reference overlap. We next introduce saturated genome cover, the true fraction of a reference genome overlapped by sample contents. Genome cover may not saturate for low abundance or low prevalence bacteria. We assuage this worry with examination of a large human fecal data set. By compositing the metric across like samples, genome cover saturates even for rare species. We note that it is a threshold on saturated genome cover, not genome cover itself, which indicates a spurious reference hit or distant relative. We present Zebra, a method to compute and threshold the genome cover metric across like samples, a recurrence to estimate genome cover and confirm saturation, and provide guidance for choosing cover thresholds in real world scenarios. Standalone genome cover and integration into Woltka are available: https://github.com/biocore/zebra_filter, https://github.com/qiyunzhu/woltka. IMPORTANCE Taxonomic assignment, assigning sequences to specific taxonomic units, is a crucial processing step in microbiome analyses. Issues in taxonomic assignment affect interpretation of what microbes are present in each sample and may be associated with specific environmental or clinical conditions. Assigning importance to a particular taxon relies strongly on independence of assigned counts. The false inclusion of thousands of correlated taxa makes interpretation ambiguous, leading to underconstrained results which cannot be reproduced. The importance sometimes attached to implausible artifacts such as anthrax or bubonic plague is especially problematic. We show that the Zebra filter retrieves only the nearest relatives of sample contents enabling more reproducible and biologically plausible interpretation of metagenomic data.

While the study of the tumor microbiome and its effects on cancer biology has expanded considerably over the last few years, most of this research focused on bacteria and viruses, leaving behind the fungal kingdom. Recently, a few studies have demonstrated that specific fungi may promote tumor progression, stressing the importance of comprehensively studying the tumor mycobiome and its effects. To address this, we have characterized the mycobiome in 1,183 human tumors and their adjacent tissues, originating from eight major solid tumor types. Staining and imaging demonstrated the presence of fungi in both cancer and immune cells, with tumor-type specific distribution patterns. Quantitative PCR of the fungal 5.8s rDNA revealed the presence of fungal DNA in all tumor types. To characterize the tumor mycobiome and address potential contamination during tissue handling and processing, we subjected all samples, as well as 295 negative controls of different types, to sequencing of the ITS2 region that is situated between fungal rRNA genes. We found cancer-type specific mycobial signatures with relatively high similarity between tumors and their adjacent tissues. While the fungal mycobiome had a lower species richness as compared to the bacterial microbiome of the same tumors, fungi showed significant co-occurrences with specific bacteria, suggesting the existence of ecological niches within the tumors. We also found significant correlations with clinical parameters such as patient’s age, tumor stage, progression-free survival, overall survival, and response to immune checkpoint blockade therapy. Characterization of the tumor mycobiome may add a biologically relevant, previously overlooked, component to be considered in the study of cancer, including its effects on tumor initiation, progression, diagnosis, and response to therapy. Citation Format: Lian Narunsky Haziza, Gregory D. Sepich-Poore, Ilana Livyatan, Omer Asraf, Cameron Martino, Deborah Nejman, Nancy Gavert, Jason E. Stajich, Guy Amit, Antonio González, Stephen Wandro, Gili Perry, Ruthie Ariel, Arnon Meltser, Justin P. Shaffer, Qiyun Zhu, Nora Balint-Lahat, Iris Barshack, Maya Dadian, Einav N. Gal-Yam, Sandip P. Pate, Amir Bashan, Austin D. Swafford, Yitzhak Pilpel, Rob Knight, Ravid Straussman. Pan-cancer characterization of the tumor mycobiome and its clinical effects [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 3054.

Phages that infect pathogenic bacteria present a valuable resource for treating antibiotic-resistant infections. We isolated and developed a collection of 19 Enterococcus phages, including myoviruses, siphoviruses, and a podovirus, that can infect both Enterococcus faecalis and Enterococcus faecium. Several of the Myoviridae phages that we found in southern California wastewater were from the Brockvirinae subfamily (formerly Spounavirinae) and had a broad host range across both E faecium and E. faecalis. By searching the NCBI Sequence Read Archive, we showed that these phages are prevalent globally in human and animal microbiomes. Enterococcus is a regular member of healthy human gut microbial communities; however, it is also an opportunistic pathogen responsible for an increasing number of antibiotic-resistant infections. We tested the ability of each phage to clear Enterococcus host cultures and delay the emergence of phage-resistant Enterococcus. We found that some phages were ineffective at clearing Enterococcus cultures individually but were effective when combined into cocktails. Quantitative PCR was used to track phage abundance in cocultures and revealed dynamics ranging from one dominant phage to an even distribution of phage growth. Genomic characterization showed that mutations in Enterococcus exopolysaccharide synthesis genes were consistently found in the presence of phage infection. This work will help to inform cocktail design for Enterococcus, which is an important target for phage therapy applications. IMPORTANCE Due to the rise in antibiotic resistance, Enterococcus infections are a major health crisis that requires the development of alternative therapies. Phage therapy offers an alternative to antibiotics and has shown promise in both in vitro and early clinical studies. Here, we established a collection of 19 Enterococcus phages and tested whether combining phages into cocktails could delay growth and the emergence of resistant mutants in comparison with individual phages. We showed that cocktails of two or three phages often prevented the growth of phage-resistant mutants, and we identified which phages were replicating the most in each cocktail. When resistant mutants emerged to single phages, they showed consistent accumulation of mutations in exopolysaccharide synthesis genes. These data serve to demonstrate that a cocktail approach can inform efforts to improve efficacy against Enterococcus isolates and reduce the emergence of resistance.

The first week after birth is a critical time for the establishment of microbial communities for infants. Preterm infants face unique environmental impacts on their newly acquired microbiomes, including increased incidence of cesarean section delivery and exposure to antibiotics as well as delayed enteral feeding and reduced human interaction during their intensive care unit stay. Using contextualized paired metabolomics and 16S sequencing data, the development of the gut, skin, and oral microbiomes of infants is profiled daily for the first week after birth, and it is found that the skin microbiome appears robust to early life perturbation, while direct exposure of infants to antibiotics, rather than presumed maternal transmission, delays microbiome development and prevents the early differentiation based on body site regardless of delivery mode. Metabolomic analyses identify the development of all gut metabolomes of preterm infants toward full-term infant profiles, but a significant increase of primary bile acid metabolism only in the non-antibiotic treated vaginally birthed late preterm infants. This study provides a framework for future multi-omic, multibody site analyses on these high-risk preterm infant populations and suggests opportunities for monitoring and intervention, with infant antibiotic exposure as the primary driver of delays in microbiome development.

Human tissues, including tumors, are extensively colonized by taxonomically diverse microbes. Intra-tumoral microbial activity and events of cellular turnover and trafficking contribute to shedding microbial nucleic acids into the blood stream. Here we characterized microbial signatures present in primary-tumor tissue and in the blood of patients affected with different cancer types, with particular focus on lung cancer, and we demonstrated the discriminatory power of such microbial signatures for the identification and classification of lung cancer versus other cancer types.

Antibiotic resistant Enterococcus infections are a major health crisis that requires the development of alternative therapies. Phage therapy could be an alternative to antibiotics and has shown promise in in vitro and in early clinical studies. Phage therapy is often deployed as a cocktail of phages, but there is little understanding of how to most effectively combine phages. Here we utilized a collection of 20 Enterococcus phages to test principles of phage cocktail design and determine the phenotypic effects of evolving phage resistance in Enterococcus isolates that were susceptible or resistant to antibiotics (e.g., Vancomycin Resistant Enterococcus (VRE)). We tested the ability of each phage to clear Enterococcus host cultures and prevent the emergence of phage resistant Enterococcus. We found that some phages which were ineffective individually were effective at clearing the bacterial culture when used in cocktails. To understand the dynamics within phage cocktails, we used qPCR to track which phages increased in abundance in each cocktail, and saw dynamics ranging from one dominant phage to even phage growth. Further, we isolated several phage-resistant mutants to test for altered Vancomycin sensitivity. We found that mutants tended to have no change or slightly increased resistance to Vancomycin. By demonstrating the efficacy of phage cocktails in suppressing growth of antibiotic susceptible and VRE clinical isolates when exposed to phages, this work will help to inform cocktail design for future phage therapy applications. IMPORTANCE Antibiotic resistant Enterococcus infections are a major health crisis that requires the development of alternative therapies. Phage therapy could be an alternative to antibiotics and has shown promise in in vitro and in early clinical studies. Phage therapy in the form of cocktails is often suggested, with similar goals as the combination therapy that has been successful in the treatment of HIV infection, but there is little understanding about how to combine phages most effectively. Here we utilized a collection of 20 Enterococcus phages to test whether several phage cocktails could prevent the host from evolving resistance to therapy and to determine whether evolving resistance to phages affected host susceptibility to antibiotics. We showed that cocktails of two or three unrelated phages often prevented the growth of phage-resistant mutants, when the same phages applied individually were not able to.

Lymphocytes within the intestinal epithelial layer (IEL) in mammals have unique composition compared with their counterparts in the lamina propria. Little is known about the role of some of the key colonic IEL subsets, such as TCRαβ+CD8+ T cells, in inflammation. We have recently described liver-enriched innate-like TCRαβ+CD8αα regulatory T cells, partly controlled by the non-classical MHC molecule, Qa-1b, that upon adoptive transfer protect from T cell-induced colitis. In this study, we found that TCRαβ+CD8αα T cells are reduced among the colonic IEL during inflammation, and that their activation with an agonistic peptide leads to significant Qa-1b-dependent protection in an acute model of colitis. Cellular expression of Qa-1b during inflammation and corresponding dependency in peptide-mediated protection suggest that Batf3-dependent CD103+CD11b- type 1 conventional dendritic cells control the protective function of TCRαβ+CD8αα T cells in the colonic epithelium. In the colitis model, expression of the potential barrier-protective gene, Muc2, is enhanced upon administration of a Qa-1b agonistic peptide. Notably, in steady state, the mucin metabolizing Akkermansia muciniphila was found in significantly lower abundance amid a dramatic change in overall microbiome and metabolome, increased IL-6 in explant culture, and enhanced sensitivity to dextran sulfate sodium in Qa-1b deficiency. Finally, in patients with inflammatory bowel disease, we found upregulation of HLA-E, a Qa-1b analog with inflammation and biologic non-response, in silico, suggesting the importance of this regulatory mechanism across species.

As the number of human microbiome studies expand, it is increasingly important to identify cost-effective, practical preservatives that allow for room temperature sample storage. Here, we reanalyzed 16S rRNA gene amplicon sequencing data from a large sample storage study published in 2016 and performed shotgun metagenomic sequencing on remnant DNA from this experiment. Both results support the initial findings that 95% ethanol, a nontoxic, cost-effective preservative, is effective at preserving samples at room temperature for weeks. We expanded on this analysis by collecting a new set of fecal, saliva, and skin samples to determine the optimal ratio of 95% ethanol to sample. We identified optimal collection protocols for fecal samples (storing a fecal swab in 95% ethanol) and saliva samples (storing unstimulated saliva in 95% ethanol at a ratio of 1:2). Storing skin swabs in 95% ethanol reduced microbial biomass and disrupted community composition, highlighting the difficulties of low biomass sample preservation. The results from this study identify practical solutions for large-scale analyses of fecal and oral microbial communities.IMPORTANCE Expanding our knowledge of microbial communities across diverse environments includes collecting samples in places far from the laboratory. Identifying cost-effective preservatives that will enable room temperature storage of microbial communities for sequencing analysis is crucial to enabling microbiome analyses across diverse populations. Here, we validate findings that 95% ethanol efficiently preserves microbial composition at room temperature for weeks. We also identified the optimal ratio of 95% ethanol to sample for stool and saliva to preserve both microbial load and composition. These results provide rationale for an accessible, nontoxic, cost-effective solution that will enable crowdsourcing microbiome studies, such as The Microsetta Initiative, and lower the barrier for collecting diverse samples.

Systematic characterization of the cancer microbiome provides the opportunity to develop techniques that exploit non-human, microorganism-derived molecules in the diagnosis of a major human disease. Following recent demonstrations that some types of cancer show substantial microbial contributions1–10, we re-examined whole-genome and whole-transcriptome sequencing studies in The Cancer Genome Atlas11 (TCGA) of 33 types of cancer from treatment-naive patients (a total of 18,116 samples) for microbial reads, and found unique microbial signatures in tissue and blood within and between most major types of cancer. These TCGA blood signatures remained predictive when applied to patients with stage Ia–IIc cancer and cancers lacking any genomic alterations currently measured on two commercial-grade cell-free tumour DNA platforms, despite the use of very stringent decontamination analyses that discarded up to 92.3% of total sequence data. In addition, we could discriminate among samples from healthy, cancer-free individuals (n = 69) and those from patients with multiple types of cancer (prostate, lung, and melanoma; 100 samples in total) solely using plasma-derived, cell-free microbial nucleic acids. This potential microbiome-based oncology diagnostic tool warrants further exploration. Microbial nucleic acids are detected in samples of tissues and blood from more than 10,000 patients with cancer, and machine learning is used to show that these can be used to discriminate between and among different types of cancer, suggesting a new microbiome-based diagnostic approach.

Microbes and their metabolic products influence early-life immune and microbiome development, yet remain understudied during pregnancy. Vaginal microbial communities are typically dominated by one or a few well-adapted microbes which are able to survive in a narrow pH range and are adapted to live on host-derived carbon sources, likely sourced from glycogen and mucin present in the vaginal environment. We characterized the cervicovaginal microbiomes of 16 healthy women throughout the three trimesters of pregnancy. Additionally, we analyzed saliva and urine metabolomes using gas chromatography-time of flight mass spectrometry (GC-TOF MS) and liquid chromatography-tandem mass spectrometry (LC-MS/MS) lipidomics approaches for samples from mothers and their infants through the first year of life. Amplicon sequencing revealed most women had either a simple community with one highly abundant species of Lactobacillus or a more diverse community characterized by a high abundance of Gardnerella, as has also been previously described in several independent cohorts. Integrating GC-TOF MS and lipidomics data with amplicon sequencing, we found metabolites that distinctly associate with particular communities. For example, cervicovaginal microbial communities dominated by Lactobacillus crispatus have high mannitol levels, which is unexpected given the characterization of L. crispatus as a homofermentative Lactobacillus species. It may be that fluctuations in which Lactobacillus dominate a particular vaginal microbiome are dictated by the availability of host sugars, such as fructose, which is the most likely substrate being converted to mannitol. Overall, using a multi-"omic" approach, we begin to address the genetic and molecular means by which a particular vaginal microbiome becomes vulnerable to large changes in composition.IMPORTANCE Humans have a unique vaginal microbiome compared to other mammals, characterized by low diversity and often dominated by Lactobacillus spp. Dramatic shifts in vaginal microbial communities sometimes contribute to the presence of a polymicrobial overgrowth condition called bacterial vaginosis (BV). However, many healthy women lacking BV symptoms have vaginal microbiomes dominated by microbes associated with BV, resulting in debate about the definition of a healthy vaginal microbiome. Despite substantial evidence that the reproductive health of a woman depends on the vaginal microbiota, future therapies that may improve reproductive health outcomes are stalled due to limited understanding surrounding the ecology of the vaginal microbiome. Here, we use sequencing and metabolomic techniques to show novel associations between vaginal microbes and metabolites during healthy pregnancy. We speculate these associations underlie microbiome dynamics and may contribute to a better understanding of transitions between alternative vaginal microbiome compositions.

The human microbiota has a close relationship with human disease and it remodels components of the glycocalyx including heparan sulfate (HS). Studies of the severe acute respiratory syndrome coronavirus (SARS-CoV-2) spike protein receptor binding domain suggest that infection requires binding to HS and angiotensin converting enzyme 2 (ACE2) in a codependent manner. Here, we show that commensal host bacterial communities can modify HS and thereby modulate SARS-CoV-2 spike protein binding and that these communities change with host age and sex. Common human-associated commensal bacteria whose genomes encode HS-modifying enzymes were identified. The prevalence of these bacteria and the expression of key microbial glycosidases in bronchoalveolar lavage fluid (BALF) was lower in adult COVID-19 patients than in healthy controls. The presence of HS-modifying bacteria decreased with age in two large survey datasets, FINRISK 2002 and American Gut, revealing one possible mechanism for the observed increase in COVID-19 susceptibility with age. In vitro , bacterial glycosidases from unpurified culture media supernatants fully blocked SARS-CoV-2 spike binding to human H1299 protein lung adenocarcinoma cells. HS-modifying bacteria in human microbial communities may regulate viral adhesion, and loss of these commensals could predispose individuals to infection. Understanding the impact of shifts in microbial community composition and bacterial lyases on SARS-CoV-2 infection may lead to new therapeutics and diagnosis of susceptibility.