2-Hydroxyisovalerate Is Produced During Bacterial Vaginosis and Boosts HIV Infection in Resting T Cells.

Human immunodeficiency virus (HIV) infection and the ensuing acquired immunodeficiency syndrome (AIDS) disproportionally affect young women, yet understanding of the factors promoting heterosexual transmission in the female genital tract is limited. Colonization with highly diverse, Lactobacillus-deficient communities (HDCs) increases a woman's risk of acquiring HIV-1 compared with colonization with Lactobacillus-dominated low diversity communities (LDCs). The polymicrobial nature of these communities has made it challenging to elucidate the microbial mechanisms responsible for modulating HIV susceptibility. Here, we analyzed conserved changes in small-molecule metabolites present in the cervicovaginal lavage fluid collected from women colonized with HDCs and LDCs with the goal of identifying possible chemicals influencing HIV infection. As in previous studies, we found that the catabolite of the branched-chain amino acid valine, 2-hydroxyisovalerate (2-HV), was a consistent component of dysbiotic HDC microbiota. Effects of 2-HV on HIV infection were assessed. In experimental infections with HIV, treatment with 2-HV increased infections of resting CD4+ T cells. To understand bacterial production of 2-HV in more detail, we cultured purified HDC and LDC bacteria and used mass spectrometry to identify two HDC bacteria that synthesize high levels of 2-HV. In contrast, protective vaginal Lactobacilli did not produce high levels of 2-HV. A genomic analysis of genes encoding 2-HV synthetic pathways showed a correlation between high-level production of 2-HV and pathways for synthesis of the immediate precursor 2-ketoisovalerate. Thus, 2-HV is a candidate mediator linking vaginal microbiome structure and heterosexual HIV transmission in women.

Quantifying individual-level heterogeneity in infectiousness and susceptibility through household studies.

The spread of SARS-CoV-2, like that of many other pathogens, is governed by heterogeneity. "Superspreading," or "over-dispersion," is an important factor in transmission, yet it is hard to quantify. Estimates from contact tracing data are prone to potential biases due to the increased likelihood of detecting large clusters of cases, and may reflect variation in contact behavior more than biological heterogeneity. In contrast, the average number of secondary infections per contact is routinely estimated from household surveys, and these studies can minimize biases by testing all members of a household. However, the models used to analyze household transmission data typically assume that infectiousness and susceptibility are the same for all individuals or vary only with predetermined traits such as age. Here we develop and apply a combined forward simulation and inference method to quantify the degree of inter-individual variation in both infectiousness and susceptibility from observations of the distribution of infections in household surveys. First, analyzing simulated data, we show our method can reliably ascertain the presence, type, and amount of these heterogeneities given data from a sufficiently large sample of households. We then analyze a collection of household studies of COVID-19 from diverse settings around the world, and find strong evidence for large heterogeneity in both the infectiousness and susceptibility of individuals. Our results also provide a framework to improve the design of studies to evaluate household interventions in the presence of realistic heterogeneity between individuals.

Effects of Mask Reuse on the Oropharyngeal, Skin, and Mask Microbiome.

BACKGROUND: Face masks have been critical in the coronavirus disease 2019 (COVID-19) pandemic, but supplies were sometimes limited and disposable masks contribute greatly to environmental waste. Studies suggest that filtration capacity is retained with repeated use, and surveys indicate many people reuse surgical masks. However, the impact of mask reuse on the host is understudied. METHODS: We applied 16S rRNA gene sequencing to investigate the bacterial microbiome of the facial skin and oropharynx of individuals randomized to wearing fresh surgical masks daily versus masks reused for 1 week. RESULTS: Compared to daily fresh masks, reuse was associated with increased richness (number of taxa) of the skin microbiome and trend towards greater diversity, but no difference in the oropharyngeal microbiome. Used masks had either skin-dominant or oropharynx-dominant bacterial sequences, and reused masks had >100-fold higher bacterial content but no change in composition compared to those used for 1 day. CONCLUSIONS: One week of mask reuse increased the number of low-abundance taxa on the face but did not impact the upper respiratory microbiome. Thus, face mask reuse has little impact on the host microbiome, although whether minor changes to the skin microbiome might relate to reported skin sequelae of masking (maskne) remains to be determined.

Widespread, human-associated redondoviruses infect the commensal protozoan Entamoeba gingivalis.

Redondoviruses are circular Rep-encoding single-stranded DNA (CRESS) viruses of high prevalence in healthy humans. Redondovirus abundance is increased in oro-respiratory samples from individuals with periodontitis, acute illness, and severe COVID-19. We investigated potential host cells supporting redondovirus replication in oro-respiratory samples and uncovered the oral amoeba Entamoeba gingivalis as a likely host. Redondoviruses are closely related to viruses of Entamoeba and contain reduced GC nucleotide content, consistent with Entamoeba hosts. Redondovirus and E. gingivalis co-occur in metagenomic data from oral disease and healthy human cohorts. When grown in xenic cultures with feeder bacteria, E. gingivalis was robustly positive for redondovirus RNA and DNA. A DNA proximity-ligation assay (Hi-C) on xenic culture cells showed enriched cross-linking of redondovirus and Entamoeba DNA, supporting E. gingivalis as the redondovirus host. While bacteria are established hosts for bacteriophages within the human virome, this work shows that eukaryotic commensals also contribute an abundant human-associated virus.

Quantifying individual-level heterogeneity in infectiousness and susceptibility through household studies.

The spread of SARS-CoV-2, like that of many other pathogens, is governed by heterogeneity. "Superspreading," or "over-dispersion," is an important factor in transmission, yet it is hard to quantify. Estimates from contact tracing data are prone to potential biases due to the increased likelihood of detecting large clusters of cases, and may reflect variation in contact behavior more than biological heterogeneity. In contrast, the average number of secondary infections per contact is routinely estimated from household surveys, and these studies can minimize biases by testing all members of a household. However, the models used to analyze household transmission data typically assume that infectiousness and susceptibility are the same for all individuals or vary only with predetermined traits such as age. Here we develop and apply a combined forward simulation and inference method to quantify the degree of inter-individual variation in both infectiousness and susceptibility from observations of the distribution of infections in household surveys. First, analyzing simulated data, we show our method can reliably ascertain the presence, type, and amount of these heterogeneities with data from a sufficiently large sample of households. We then analyze a collection of household studies of COVID-19 from diverse settings around the world, and find strong evidence for large heterogeneity in both the infectiousness and susceptibility of individuals. Our results also provide a framework to improve the design of studies to evaluate household interventions in the presence of realistic heterogeneity between individuals.

Alterations in the respiratory tract microbiome in COVID-19: current observations and potential significance.

SARS-CoV-2 infection causes COVID-19 disease, which can result in consequences ranging from undetectable to fatal, focusing attention on the modulators of outcomes. The respiratory tract microbiome is thought to modulate the outcomes of infections such as influenza as well as acute lung injury, raising the question to what degree does the airway microbiome influence COVID-19? Here, we review the results of 56 studies examining COVID-19 and the respiratory tract microbiome, summarize the main generalizations, and point to useful avenues for further research. Although the results vary among studies, a few consistent findings stand out. The diversity of bacterial communities in the oropharynx typically declined with increasing disease severity. The relative abundance of Haemophilus and Neisseria also declined with severity. Multiple microbiome measures tracked with measures of systemic immune responses and COVID outcomes. For many of the conclusions drawn in these studies, the direction of causality is unknown-did an alteration in the microbiome result in increased COVID severity, did COVID severity alter the microbiome, or was some third factor the primary driver, such as medication use. Follow-up mechanistic studies can help answer these questions. Video Abstract.

Elevated T cell repertoire diversity is associated with progression of lung squamous cell premalignant lesions.

OBJECTIVE: The immune response to invasive carcinoma has been the focus of published work, but little is known about the adaptive immune response to bronchial premalignant lesions (PMLs), precursors of lung squamous cell carcinoma. This study was designed to characterize the T cell receptor (TCR) repertoire in PMLs and its association with clinical, pathological, and molecular features. METHODS: Endobronchial biopsies (n=295) and brushings (n=137) from high-risk subjects (n=50), undergoing lung cancer screening at approximately 1-year intervals via autofluorescence bronchoscopy and CT, were profiled by RNA-seq. We applied the TCR Repertoire Utilities for Solid Tissue/Tumor tool to the RNA-seq data to identify TCR CDR3 sequences across all samples. In the biopsies, we measured the correlation of TCR diversity with previously derived immune-associated PML transcriptional signatures and PML outcome. We also quantified the spatial and temporal distribution of shared and clonally expanded TCRs. Using the biopsies and brushes, the ratio of private (ie, found in one patient only) and public (ie, found in two or more patients) TCRs was quantified, and the CDR3 sequences were compared with those found in curated databases with known antigen specificities. RESULTS: We detected 39,303 unique TCR sequences across all samples. In PML biopsies, TCR diversity was negatively associated with a transcriptional signature of T cell mediated immune activation (p=4e-4) associated with PML outcome. Additionally, in lesions of the proliferative molecular subtype, TCR diversity was decreased in regressive versus progressive/persistent PMLs (p=0.045). Within each patient, TCRs were more likely to be shared between biopsies sampled at the same timepoint than biopsies sampled at the same anatomic location at different times. Clonally expanded TCRs, within a biopsied lesion, were more likely to be expanded at future time points than non-expanded clones. The majority of TCR sequences were found in a single sample, with only 3396 (8.6%) found in more than one sample and 1057 (2.7%) found in two or more patients (ie, public); however, when compared with a public database of CDR3 sequences, 4543 (11.6%) of TCRs were identified as public. TCRs with known antigen specificities were enriched among public TCRs (p<0.001). CONCLUSIONS: Decreased TCR diversity may reflect nascent immune responses that contribute to PML elimination. Further studies are needed to explore the potential for immunoprevention of PMLs.

Signatures of COVID-19 Severity and Immune Response in the Respiratory Tract Microbiome.

Viral infection of the respiratory tract can be associated with propagating effects on the airway microbiome, and microbiome dysbiosis may influence viral disease. Here, we investigated the respiratory tract microbiome in coronavirus disease 2019 (COVID-19) and its relationship to disease severity, systemic immunologic features, and outcomes. We examined 507 oropharyngeal, nasopharyngeal, and endotracheal samples from 83 hospitalized COVID-19 patients as well as non-COVID patients and healthy controls. Bacterial communities were interrogated using 16S rRNA gene sequencing, and the commensal DNA viruses Anelloviridae and Redondoviridae were quantified by qPCR. We found that COVID-19 patients had upper respiratory microbiome dysbiosis and greater change over time than critically ill patients without COVID-19. Oropharyngeal microbiome diversity at the first time point correlated inversely with disease severity during hospitalization. Microbiome composition was also associated with systemic immune parameters in blood, as measured by lymphocyte/neutrophil ratios and immune profiling of peripheral blood mononuclear cells. Intubated patients showed patient-specific lung microbiome communities that were frequently highly dynamic, with prominence of Staphylococcus. Anelloviridae and Redondoviridae showed more frequent colonization and higher titers in severe disease. Machine learning analysis demonstrated that integrated features of the microbiome at early sampling points had high power to discriminate ultimate level of COVID-19 severity. Thus, the respiratory tract microbiome and commensal viruses are disturbed in COVID-19 and correlate with systemic immune parameters, and early microbiome features discriminate disease severity. Future studies should address clinical consequences of airway dysbiosis in COVID-19, its possible use as biomarkers, and the role of bacterial and viral taxa identified here in COVID-19 pathogenesis. IMPORTANCE COVID-19, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection of the respiratory tract, results in highly variable outcomes ranging from minimal illness to death, but the reasons for this are not well understood. We investigated the respiratory tract bacterial microbiome and small commensal DNA viruses in hospitalized COVID-19 patients and found that each was markedly abnormal compared to that in healthy people and differed from that in critically ill patients without COVID-19. Early airway samples tracked with the level of COVID-19 illness reached during hospitalization, and the airway microbiome also correlated with immune parameters in blood. These findings raise questions about the mechanisms linking SARS-CoV-2 infection and other microbial inhabitants of the airway, including whether the microbiome might regulate severity of COVID-19 disease and/or whether early microbiome features might serve as biomarkers to discriminate disease severity.

Signatures of COVID-19 severity and immune response in the respiratory tract microbiome.

Rationale: Viral infection of the respiratory tract can be associated with propagating effects on the airway microbiome, and microbiome dysbiosis may influence viral disease. Objective: To define the respiratory tract microbiome in COVID-19 and relationship disease severity, systemic immunologic features, and outcomes. Methods and Measurements: We examined 507 oropharyngeal, nasopharyngeal and endotracheal samples from 83 hospitalized COVID-19 patients, along with non-COVID patients and healthy controls. Bacterial communities were interrogated using 16S rRNA gene sequencing, commensal DNA viruses Anelloviridae and Redondoviridae were quantified by qPCR, and immune features were characterized by lymphocyte/neutrophil (L/N) ratios and deep immune profiling of peripheral blood mononuclear cells (PBMC). Main Results: COVID-19 patients had upper respiratory microbiome dysbiosis, and greater change over time than critically ill patients without COVID-19. Diversity at the first time point correlated inversely with disease severity during hospitalization, and microbiome composition was associated with L/N ratios and PBMC profiles in blood. Intubated patients showed patient-specific and dynamic lung microbiome communities, with prominence of Staphylococcus. Anelloviridae and Redondoviridae showed more frequent colonization and higher titers in severe disease. Machine learning analysis demonstrated that integrated features of the microbiome at early sampling points had high power to discriminate ultimate level of COVID-19 severity. Conclusions: The respiratory tract microbiome and commensal virome are disturbed in COVID-19, correlate with systemic immune parameters, and early microbiome features discriminate disease severity. Future studies should address clinical consequences of airway dysbiosis in COVID-19, possible use as biomarkers, and role of bacterial and viral taxa identified here in COVID-19 pathogenesis.

Diplorickettsia Bacteria in an Ixodes scapularis Tick, Vermont, USA.

An unexpected Diplorickettsia species closely related to the tickborne pathogen D. massieliensis was found in the microbiome of an Ixodes scapularis tick in Vermont, USA. This evidence of Diplorickettsia in North American ticks suggests a need for disease surveillance using molecular screening of ticks and serologic studies of humans.

Effect of Intermittent Versus Continuous Low-Dose Aspirin on Nasal Epithelium Gene Expression in Current Smokers: A Randomized, Double-Blinded Trial.

A chemopreventive effect of aspirin (ASA) on lung cancer risk is supported by epidemiologic and preclinical studies. We conducted a randomized, double-blinded study in current heavy smokers to compare modulating effects of intermittent versus continuous low-dose ASA on nasal epithelium gene expression and arachidonic acid (ARA) metabolism. Fifty-four participants were randomized to intermittent (ASA 81 mg daily for one week/placebo for one week) or continuous (ASA 81 mg daily) for 12 weeks. Low-dose ASA suppressed urinary prostaglandin E2 metabolite (PGEM; change of -4.55 ± 11.52 from baseline 15.44 ± 13.79 ng/mg creatinine for arms combined, P = 0.02), a surrogate of COX-mediated ARA metabolism, but had minimal effects on nasal gene expression of nasal or bronchial gene-expression signatures associated with smoking, lung cancer, and chronic obstructive pulmonary disease. Suppression of urinary PGEM correlated with favorable changes in a smoking-associated gene signature (P < 0.01). Gene set enrichment analysis (GSEA) showed that ASA intervention led to 1,079 enriched gene sets from the Canonical Pathways within the Molecular Signatures Database. In conclusion, low-dose ASA had minimal effects on known carcinogenesis gene signatures in nasal epithelium of current smokers but results in wide-ranging genomic changes in the nasal epithelium, demonstrating utility of nasal brushings as a surrogate to measure gene-expression responses to chemoprevention. PGEM may serve as a marker for smoking-associated gene-expression changes and systemic inflammation. Future studies should focus on NSAIDs or agent combinations with broader inhibition of pro-inflammatory ARA metabolism to shift gene signatures in an anti-carcinogenic direction.