Repurposed Drugs That Activate Autophagy in Filarial Worms Act as Effective Macrofilaricides

Onchocerciasis and lymphatic filariasis are two neglected tropical diseases caused by filarial nematodes that utilize insect vectors for transmission to their human hosts. Current control strategies are based on annual or biannual mass drug administration (MDA) of the drugs Ivermectin or Ivermectin plus Albendazole, respectively. These drug regimens kill the first-stage larvae of filarial worms (i.e., microfilariae) and interrupt the transmission of infections. MDA programs for these microfilaricidal drugs must be given over the lifetime of the filarial adult worms, which can reach 15 years in the case of Onchocerca volvulus. This is problematic because of suboptimal responses to ivermectin in various endemic regions and inefficient reduction of transmission even after decades of MDA. There is an urgent need for the development of novel alternative treatments to support the 2030 elimination goals of onchocerciasis and lymphatic filariasis. One successful approach has been to target Wolbachia, obligatory endosymbiotic bacteria on which filarial worms are dependent for their survival and reproduction within the human host. A 4-6-week antibiotic therapy with doxycycline, for example, resulted in the loss of Wolbachia that subsequently led to extensive apoptosis of somatic cells, germline, embryos, and microfilariae, as well as inhibition of fourth-stage larval development. However, this long-course regimen has limited use in MDA programs. As an alternative approach to the use of bacteriostatic antibiotics, in this study, we focused on autophagy-inducing compounds, which we hypothesized could disturb various pathways involved in the interdependency between Wolbachia and filarial worms. We demonstrated that several such compounds, including Niclosamide, an FDA-approved drug, Niclosamide ethanolamine (NEN), and Rottlerin, a natural product derived from Kamala trees, significantly reduced the levels of Wolbachia in vitro. Moreover, when these compounds were used in vivo to treat Brugia pahangi-infected gerbils, Niclosamide and NEN significantly decreased adult worm survival, reduced the release of microfilariae, and decreased embryonic development depending on the regimen and dose used. All three drugs given orally significantly reduced Wolbachia loads and induced an increase in levels of lysosome-associated membrane protein in worms from treated animals, suggesting that Niclosamide, NEN, and Rottlerin were effective in causing drug-induced autophagy in these filarial worms. These repurposed drugs provide a new avenue for the clearance of adult worms in filarial infections.

CD4+ and CD8+ T cells are required to prevent SARS-CoV-2 persistence in the nasal compartment

SARS-CoV-2 is the causative agent of COVID-19 and continues to pose a significant public health threat throughout the world. Following SARS-CoV-2 infection, virus-specific CD4+ and CD8+ T cells are rapidly generated to form effector and memory cells and persist in the blood for several months. However, the contribution of T cells in controlling SARS-CoV-2 infection within the respiratory tract are not well understood. Using C57BL/6 mice infected with a naturally occurring SARS-CoV-2 variant (B.1.351), we evaluated the role of T cells in the upper and lower respiratory tract. Following infection, SARS-CoV-2-specific CD4+ and CD8+ T cells are recruited to the respiratory tract and a vast proportion secrete the cytotoxic molecule Granzyme B. Using antibodies to deplete T cells prior to infection, we found that CD4+ and CD8+ T cells play distinct roles in the upper and lower respiratory tract. In the lungs, T cells play a minimal role in viral control with viral clearance occurring in the absence of both CD4+ and CD8+ T cells through 28 days post-infection. In the nasal compartment, depletion of both CD4+ and CD8+ T cells, but not individually, results in persistent and culturable virus replicating in the nasal compartment through 28 days post-infection. Using in situ hybridization, we found that SARS-CoV-2 infection persisted in the nasal epithelial layer of tandem CD4+ and CD8+ T cell-depleted mice. Sequence analysis of virus isolates from persistently infected mice revealed mutations spanning across the genome, including a deletion in ORF6. Overall, our findings highlight the importance of T cells in controlling virus replication within the respiratory tract during SARS-CoV-2 infection.

Patient Subtyping Analysis of Baseline Multi-omic Data Reveals Distinct Pre-immune States Predictive of Vaccination Responses

Understanding the molecular mechanisms that underpin diverse vaccination responses is a critical step toward developing efficient vaccines. Molecular subtyping approaches can offer valuable insights into the heterogeneous nature of responses and aid in the design of more effective vaccines. In order to explore the molecular signatures associated with the vaccine response, we analyzed baseline transcriptomics data from paired samples of whole blood, proteomics and glycomics data from serum, and metabolomics data from urine, obtained from influenza vaccine recipients (2019-2020 season) prior to vaccination. After integrating the data using a network-based model, we performed a subtyping analysis. The integration of multiple data modalities from 62 samples resulted in five baseline molecular subtypes with distinct molecular signatures. These baseline subtypes differed in the expression of pre-existing adaptive or innate immunity signatures, which were linked to significant variation across subtypes in baseline immunoglobulin A (IgA) and hemagglutination inhibition (HAI) titer levels. It is worth noting that these significant differences persisted through day 28 post-vaccination, indicating the effect of initial immune state on vaccination response. These findings highlight the significance of interpersonal variation in baseline immune status as a crucial factor in determining vaccine response and efficacy. Ultimately, incorporating molecular profiling could enable personalized vaccine optimization.

Wolbachia interferes with Zika virus replication by hijacking cholesterol metabolism in mosquito cells

IMPORTANCE

Arthropod-borne viruses are emerging pathogens that are spread widely by mosquitos. Zika virus is an arbovirus that can infect humans and be transmitted from an infected mother to the fetus, potentially leading to microcephaly in infants. One promising strategy to prevent disease caused by arboviruses is to target the insect vector population. Recent field studies have shown that mosquito populations infected with Wolbachia bacteria suppress arbovirus replication and transmission. Here, we describe how intracellular bacteria redirect resources within their host cells and suppress Zika virus replication at the cellular level. Understanding the mechanism behind Wolbachia-induced interference of arbovirus replication could help advance strategies to control arbovirus pathogens in insect vectors and human populations.

Lower Airway Dysbiosis Augments Lung Inflammatory Injury in Mild-to-Moderate Chronic Obstructive Pulmonary Disease

Rationale: Chronic obstructive pulmonary disease (COPD) is associated with high morbidity, mortality, and healthcare costs. Cigarette smoke is a causative factor; however, not all heavy smokers develop COPD. Microbial colonization and infections are contributing factors to disease progression in advanced stages. Objectives: We investigated whether lower airway dysbiosis occurs in mild-to-moderate COPD and analyzed possible mechanistic contributions to COPD pathogenesis. Methods: We recruited 57 patients with a >10 pack-year smoking history: 26 had physiological evidence of COPD, and 31 had normal lung function (smoker control subjects). Bronchoscopy sampled the upper airways, lower airways, and environmental background. Samples were analyzed by 16S rRNA gene sequencing, whole genome, RNA metatranscriptome, and host RNA transcriptome. A preclinical mouse model was used to evaluate the contributions of cigarette smoke and dysbiosis on lower airway inflammatory injury. Measurements and Main Results: Compared with smoker control subjects, microbiome analyses showed that the lower airways of subjects with COPD were enriched with common oral commensals. The lower airway host transcriptomics demonstrated differences in markers of inflammation and tumorigenesis, such as upregulation of IL-17, IL-6, ERK/MAPK, PI3K, MUC1, and MUC4 in mild-to-moderate COPD. Finally, in a preclinical murine model exposed to cigarette smoke, lower airway dysbiosis with common oral commensals augments the inflammatory injury, revealing transcriptomic signatures similar to those observed in human subjects with COPD. Conclusions: Lower airway dysbiosis in the setting of smoke exposure contributes to inflammatory injury early in COPD. Targeting the lower airway microbiome in combination with smoking cessation may be of potential therapeutic relevance.

Miniature spatial transcriptomics for studying parasite-endosymbiont relationships at the micro scale

Several important human infectious diseases are caused by microscale-sized parasitic nematodes like filarial worms. Filarial worms have their own spatial tissue organization; to uncover this tissue structure, we need methods that can spatially resolve these miniature specimens. Most filarial worms evolved a mutualistic association with endosymbiotic bacteria Wolbachia. However, the mechanisms underlying the dependency of filarial worms on the fitness of these bacteria remain unknown. As Wolbachia is essential for the development, reproduction, and survival of filarial worms, we spatially explored how Wolbachia interacts with the worm's reproductive system by performing a spatial characterization using Spatial Transcriptomics (ST) across a posterior region containing reproductive tissue and developing embryos of adult female Brugia malayi worms. We provide a proof-of-concept for miniature-ST to explore spatial gene expression patterns in small sample types, demonstrating the method's ability to uncover nuanced tissue region expression patterns, observe the spatial localization of key B. malayi - Wolbachia pathway genes, and co-localize the B. malayi spatial transcriptome in Wolbachia tissue regions, also under antibiotic treatment. We envision our approach will open up new avenues for the study of infectious diseases caused by micro-scale parasitic worms.

Optimized quantification of intra-host viral diversity in SARS-CoV-2 and influenza virus sequence data

High error rates of viral RNA-dependent RNA polymerases lead to diverse intra-host viral populations during infection. Errors made during replication that are not strongly deleterious to the virus can lead to the generation of minority variants. However, accurate detection of minority variants in viral sequence data is complicated by errors introduced during sample preparation and data analysis. We used synthetic RNA controls and simulated data to test seven variant-calling tools across a range of allele frequencies and simulated coverages. We show that choice of variant caller and use of replicate sequencing have the most significant impact on single-nucleotide variant (SNV) discovery and demonstrate how both allele frequency and coverage thresholds impact both false discovery and false-negative rates. When replicates are not available, using a combination of multiple callers with more stringent cutoffs is recommended. We use these parameters to find minority variants in sequencing data from SARS-CoV-2 clinical specimens and provide guidance for studies of intra-host viral diversity using either single replicate data or data from technical replicates. Our study provides a framework for rigorous assessment of technical factors that impact SNV identification in viral samples and establishes heuristics that will inform and improve future studies of intra-host variation, viral diversity, and viral evolution. IMPORTANCE When viruses replicate inside a host cell, the virus replication machinery makes mistakes. Over time, these mistakes create mutations that result in a diverse population of viruses inside the host. Mutations that are neither lethal to the virus nor strongly beneficial can lead to minority variants that are minor members of the virus population. However, preparing samples for sequencing can also introduce errors that resemble minority variants, resulting in the inclusion of false-positive data if not filtered correctly. In this study, we aimed to determine the best methods for identification and quantification of these minority variants by testing the performance of seven commonly used variant-calling tools. We used simulated and synthetic data to test their performance against a true set of variants and then used these studies to inform variant identification in data from SARS-CoV-2 clinical specimens. Together, analyses of our data provide extensive guidance for future studies of viral diversity and evolution.

Host obesity impacts genetic variation in influenza A viral populations

Obesity is a chronic health condition characterized by excess adiposity leading to a systemic increase in inflammation and dysregulation of metabolic hormones and immune cell populations. Obesity is well established as a risk factor for many noncommunicable diseases; however, its consequences for infectious disease are poorly understood. Influenza A virus (IAV) is a highly infectious pathogen responsible for seasonal and pandemic influenza. Host risk factors, including compromised immunity and pre-existing health conditions, can contribute to increased infection susceptibility and disease severity. During viral replication in a host, the negative sense single stranded RNA genome of IAV accumulates genetic diversity that may have important consequences for viral evolution and transmission. Here, we investigated the impact of host obesity on IAV genetic variation using a diet induced obesity ferret model. We infected obese and lean male ferrets with the A/Hong Kong/1073/1999 (H9N2) IAV strain. Using a co-caging study design, we investigated the maintenance, generation, and transmission of intrahost IAV genetic variation by sequencing viral genomic RNA obtained from nasal wash samples over multiple days of infection. We found evidence for an enhanced role of positive selection acting on de novo mutations in obese hosts that led to nonsynonymous changes that rose to high frequency. In addition, we identified numerous cases of recurrent low-frequency mutations throughout the genome that were specific to obese hosts. Despite these obese-specific variants, overall viral genetic diversity did not differ significantly between obese and lean hosts. This is likely due to the high supply rate of de novo variation and common evolutionary adaptations to the ferret host regardless of obesity status, which we show are mediated by variation in the hemagglutinin (HA) and polymerase genes (PB2 and PB1). As with single nucleotide variants, we identified a class of defective viral genomes (DVGs) that were found uniquely in either obese or lean hosts, but overall DVG diversity and dynamics did not differ between the two groups. Our study provides the first insight into the consequences of host obesity on viral genetic diversity and adaptation, suggesting that host factors associated with obesity alter the selective environment experienced by a viral population, thereby impacting the spectrum of genetic variation.

Influenza Defective Interfering Virus Promotes Multiciliated Cell Differentiation and Reduces the Inflammatory Response in Mice

Influenza defective interfering (DI) viruses have long been considered promising antiviral candidates because of their ability to interfere with replication-competent viruses and induce antiviral immunity. However, the mechanisms underlying DI-mediated antiviral immunity have not been extensively explored. Here, we demonstrated the interferon (IFN)-independent protection conferred by the influenza DI virus against homologous virus infection in mice deficient in type I and III IFN signaling. We identified unique host signatures responding to DI coinfection by integrating transcriptional and posttranscriptional regulatory data. DI-treated mice exhibited reduced viral transcription, less intense inflammatory and innate immune responses, and primed multiciliated cell differentiation in their lungs at an early stage of infection, even in the absence of type I or III IFNs. This increased multiciliogenesis could also be detected at the protein level via the immunofluorescence staining of lung tissue from DI-treated mice. Overall, our study provides mechanistic insight into the protection mediated by DIs, implying a unifying theme involving inflammation and multiciliogenesis in maintaining respiratory homeostasis and revealing their IFN-independent antiviral activity. IMPORTANCE During replication, the influenza virus generates genetically defective viruses. These are found in natural infections as part of the virus population within the infected host. Some versions of these defective viruses are thought to have protective effects through their interference with replication-competent viruses and induction of antiviral immunity. To better determine the mechanisms underlying the protective effects of these defective interfering (DI) viruses, we tested a DI that we previously identified in vitro with mice. Mice that were infected with a mix of wild-type influenza and DI viruses had less intense inflammatory and innate immune responses than did mice that were infected with the wild-type virus only, even when type I or III interferons, which are cytokines that play a prominent role in defending the respiratory epithelial barrier, were absent. More interestingly, the DI-infected mice had primed multiciliated cell differentiation in their lungs, indicating the potential promotion of epithelial repair by DIs.

CRISPR arrays as high-resolution markers to track microbial transmission during influenza infection

BACKGROUND

Disruption of the microbial community in the respiratory tract due to infections, like influenza, could impact transmission of bacterial pathogens. Using samples from a household study, we determined whether metagenomic-type analyses of the microbiome provide the resolution necessary to track transmission of airway bacteria. Microbiome studies have shown that the microbial community across various body sites tends to be more similar between individuals who cohabit in the same household than between individuals from different households. We tested whether there was increased sharing of bacteria from the airways within households with influenza infections as compared to control households with no influenza.

RESULTS

We obtained 221 respiratory samples that were collected from 54 individuals at 4 to 5 time points across 10 households, with and without influenza infection, in Managua, Nicaragua. From these samples, we generated metagenomic (whole genome shotgun sequencing) datasets to profile microbial taxonomy. Overall, specific bacteria and phages were differentially abundant between influenza positive households and control (no influenza infection) households, with bacteria like Rothia, and phages like Staphylococcus P68virus that were significantly enriched in the influenza-positive households. We identified CRISPR spacers detected in the metagenomic sequence reads and used these to track bacteria transmission within and across households. We observed a clear sharing of bacterial commensals and pathobionts, such as Rothia, Neisseria, and Prevotella, within and between households. However, due to the relatively small number of households in our study, we could not determine if there was a correlation between increased bacterial transmission and influenza infection.

CONCLUSION

We observed that airway microbial composition differences across households were associated with what appeared to be different susceptibility to influenza infection. We also demonstrate that CRISPR spacers from the whole microbial community can be used as markers to study bacterial transmission between individuals. Although additional evidence is needed to study transmission of specific bacterial strains, we observed sharing of respiratory commensals and pathobionts within and across households. Video Abstract.

US National Institutes of Health Prioritization of SARS-CoV-2 Variants

Since late 2020, SARS-CoV-2 variants have regularly emerged with competitive and phenotypic differences from previously circulating strains, sometimes with the potential to escape from immunity produced by prior exposure and infection. The Early Detection group is one of the constituent groups of the US National Institutes of Health National Institute of Allergy and Infectious Diseases SARS-CoV-2 Assessment of Viral Evolution program. The group uses bioinformatic methods to monitor the emergence, spread, and potential phenotypic properties of emerging and circulating strains to identify the most relevant variants for experimental groups within the program to phenotypically characterize. Since April 2021, the group has prioritized variants monthly. Prioritization successes include rapidly identifying most major variants of SARS-CoV-2 and providing experimental groups within the National Institutes of Health program easy access to regularly updated information on the recent evolution and epidemiology of SARS-CoV-2 that can be used to guide phenotypic investigations.

Tracking the emergence of antigenic variants in influenza A virus epidemics in Brazil

Influenza A virus (IAV) circulation patterns differ in North America and South America, with influenza seasons often characterized by different subtypes and strains. However, South America is relatively undersampled considering the size of its population. To address this gap, we sequenced the complete genomes of 220 IAVs collected between 2009 and 2016 from hospitalized patients in southern Brazil. New genetic drift variants were introduced into southern Brazil each season from a global gene pool, including four H3N2 clades (3c, 3c2, 3c3, and 3c2a) and five H1N1pdm clades (clades 6, 7, 6b, 6c, and 6b1). In 2016, H1N1pdm viruses belonging to a new 6b1 clade caused a severe influenza epidemic in southern Brazil that arrived early and spread rapidly, peaking mid-autumn. Inhibition assays showed that the A/California/07/2009(H1N1) vaccine strain did not protect well against 6b1 viruses. Phylogenetically, most 6b1 sequences that circulated in southern Brazil belong to a single transmission cluster that rapidly diffused across susceptible populations, leading to the highest levels of influenza hospitalization and mortality seen since the 2009 pandemic. Continuous genomic surveillance is needed to monitor rapidly evolving IAVs for vaccine strain selection and understand their epidemiological impact in understudied regions.

Influenza A virus reassortment is strain dependent

RNA viruses can exchange genetic material during coinfection, an interaction that creates novel strains with implications for viral evolution and public health. Influenza A viral genetic exchange can occur when genome segments from distinct strains reassort in coinfected cells. Predicting potential genomic reassortment between influenza strains has been a long-standing goal. Experimental coinfection studies have shed light on factors that limit or promote reassortment. However, determining the reassortment potential between diverse Influenza A strains has remained elusive. To address this challenge, we developed a high throughput genotyping approach to quantify reassortment among a diverse panel of human influenza virus strains encompassing two pandemics (swine and avian origin), three specific epidemics, and both circulating human subtypes A/H1N1 and A/H3N2. We found that reassortment frequency (the proportion of reassortants generated) is an emergent property of specific pairs of strains where strain identity is a predictor of reassortment frequency. We detect little evidence that antigenic subtype drives reassortment as intersubtype (H1N1xH3N2) and intrasubtype reassortment frequencies were, on average, similar. Instead, our data suggest that certain strains bias the reassortment frequency up or down, independently of the coinfecting partner. We observe that viral productivity is also an emergent property of coinfections, but uncorrelated to reassortment frequency; thus viral productivity is a separate factor affecting the total number of reassortants produced. Assortment of individual segments among progeny and pairwise segment combinations within progeny generally favored homologous combinations. These outcomes were not related to strain similarity or shared subtype but reassortment frequency was closely correlated to the proportion of both unique genotypes and of progeny with heterologous pairwise segment combinations. We provide experimental evidence that viral genetic exchange is potentially an individual social trait subject to natural selection, which implies the propensity for reassortment is not evenly shared among strains. This study highlights the need for research incorporating diverse strains to discover the traits that shift the reassortment potential to realize the goal of predicting influenza virus evolution resulting from segment exchange.

Clinical, Virologic, and Immunologic Evaluation of Symptomatic Coronavirus Disease 2019 Rebound Following Nirmatrelvir/Ritonavir Treatment

BACKGROUND

Nirmatrelvir/ritonavir, the first severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) protease inhibitor, reduces the risk of hospitalization and death by coronavirus disease 2019 (COVID-19) but has been associated with symptomatic rebound after therapy completion.

METHODS

Six individuals with relapse of COVID-19 symptoms after treatment with nirmatrelvir/ritonavir, 2 individuals with rebound symptoms without prior antiviral therapy and 7 patients with acute Omicron infection (controls) were studied. Soluble biomarkers and serum SARS-CoV-2 nucleocapsid protein were measured. Nasal swabs positive for SARS-CoV-2 underwent viral isolation and targeted viral sequencing. SARS-CoV-2 anti-spike, anti-receptor-binding domain, and anti-nucleocapsid antibodies were measured. Surrogate viral neutralization tests against wild-type and Omicron spike protein, as well as T-cell stimulation assays, were performed.

RESULTS

High levels of SARS-CoV-2 anti-spike immunoglobulin G (IgG) antibodies were found in all participants. Anti-nucleocapsid IgG and Omicron-specific neutralizing antibodies increased in patients with rebound. Robust SARS-CoV-2-specific T-cell responses were observed, higher in rebound compared with early acute COVID-19 patients. Inflammatory markers mostly decreased during rebound. Two patients sampled longitudinally demonstrated an increase in activated cytokine-producing CD4+ T cells against viral proteins. No characteristic resistance mutations were identified. SARS-CoV-2 was isolated by culture from 1 of 8 rebound patients; Polybrene addition increased this to 5 of 8.

CONCLUSIONS

Nirmatrelvir/ritonavir treatment does not impede adaptive immune responses to SARS-CoV-2. Clinical rebound corresponds to development of a robust antibody and T-cell immune response, arguing against a high risk of disease progression. The presence of infectious virus supports the need for isolation and assessment of longer treatment courses.

CLINICAL TRIALS REGISTRATION

NCT04401436.

Bordetella bronchiseptica-Mediated Interference Prevents Influenza A Virus Replication in the Murine Nasal Cavity

Colonization resistance, also known as pathogen interference, describes the ability of a colonizing microbe to interfere with the ability of an incoming microbe to establish infection, and in the case of pathogenic organisms, cause disease in a susceptible host. Furthermore, colonization-associated dysbiosis of the commensal microbiota can alter host immunocompetence and infection outcomes. Here, we investigated the role of Bordetella bronchiseptica nasal colonization and associated disruption of the nasal microbiota on the ability of influenza A virus to establish infection in the murine upper respiratory tract. Targeted sequencing of the microbial 16S rRNA gene revealed that B. bronchiseptica colonization of the nasal cavity efficiently displaced the resident commensal microbiota-the peak of this effect occurring 7 days postcolonization-and was associated with reduced influenza associated-morbidity and enhanced recovery from influenza-associated clinical disease. Anti-influenza A virus hemagglutinin-specific humoral immune responses were not affected by B. bronchiseptica colonization, although the cellular influenza PA-specific CD8+ immune responses were dampened. Notably, influenza A virus replication in the nasal cavity was negated in B. bronchiseptica-colonized mice. Collectively, this work demonstrates that B. bronchiseptica-mediated pathogen interference prevents influenza A virus replication in the murine nasal cavity. This may have direct implications for controlling influenza A virus replication in, and transmission events originating from, the upper respiratory tract. IMPORTANCE The interplay of microbial species in the upper respiratory tract is important for the ability of an incoming pathogen to establish and, in the case of pathogenic organisms, cause disease in a host. Here, we demonstrate that B. bronchiseptica efficiently colonizes and concurrently displaces the commensal nasal cavity microbiota, negating the ability of influenza A virus to establish infection. Furthermore, B. bronchiseptica colonization also reduced influenza-associated morbidity and enhanced recovery from influenza-associated disease. Collectively, this study indicates that B. bronchiseptica-mediated interference prevents influenza A virus replication in the upper respiratory tract. This result demonstrates the potential for respiratory pathogen-mediated interference to control replication and transmission dynamics of a clinically important respiratory pathogen like influenza A virus.

Successful lung transplantation using an allograft from a COVID-19-recovered donor: a potential role for subgenomic RNA to guide organ utilization

Although the risk of SARS-CoV-2 transmission through lung transplantation from acutely infected donors is high, the risks of virus transmission and long-term lung allograft outcomes are not as well described when using pulmonary organs from COVID-19-recovered donors. We describe successful lung transplantation for a COVID-19-related lung injury using lungs from a COVID-19-recovered donor who was retrospectively found to have detectable genomic SARS-CoV-2 RNA in the lung tissue by multiple highly sensitive assays. However, SARS-CoV-2 subgenomic RNA (sgRNA), a marker of viral replication, was not detectable in the donor respiratory tissues. One year after lung transplantation, the recipient has a good functional status, walking 1 mile several times per week without the need for supplemental oxygen and without any evidence of donor-derived SARS-CoV-2 transmission. Our findings highlight the limitations of current clinical laboratory diagnostic assays in detecting the persistence of SARS-CoV-2 RNA in the lung tissue. The persistence of SARS-CoV-2 RNA in the donor tissue did not appear to represent active viral replication via sgRNA testing and, most importantly, did not negatively impact the allograft outcome in the first year after lung transplantation. sgRNA is easily performed and may be a useful assay for assessing viral infectivity in organs from donors with a recent infection.

Metagenomic sequencing of the bronchoalveolar lavage extracellular virome and cellular transcriptome of sarcoidosis patients does not detect rubella virus

BACKGROUND

  Sarcoidosis is a multisystem granulomatous inflammatory disease of unclear etiology that involves the lung, skin and other organs, with an unknown antigenic trigger. Recently, evidence has been found in both immune deficient and immune competent patients for rubella virus in cutaneous granulomas. These granulomatous lesions share overlapping features with cutaneous sarcoidosis, raising the question of rubella virus in sarcoidosis.

OBJECTIVE

To investigate the presence of rubella virus in sarcoidosis lung samples.

METHODS

We employed metagenomic sequencing to interrogate extracellular virome preparations and cellular transcriptomes from bronchoalveolar lavage (BAL) of 209 sarcoidosis patients for rubella virus sequences.

RESULTS

We found no evidence for rubella virus genomes in acellular fluid or rubella virus gene expression in BAL cells of sarcoidosis patients.

CONCLUSIONS

These findings argue against rubella virus infection or persistence within the lung at time of sampling as a sarcoidosis trigger.

Vaccination History, Body Mass Index, Age, and Baseline Gene Expression Predict Influenza Vaccination Outcomes

Seasonal influenza is a primary public health burden in the USA and globally. Annual vaccination programs are designed on the basis of circulating influenza viral strains. However, the effectiveness of the seasonal influenza vaccine is highly variable between seasons and among individuals. A number of factors are known to influence vaccination effectiveness including age, sex, and comorbidities. Here, we sought to determine whether whole blood gene expression profiling prior to vaccination is informative about pre-existing immunological status and the immunological response to vaccine. We performed whole transcriptome analysis using RNA sequencing (RNAseq) of whole blood samples obtained prior to vaccination from 275 participants enrolled in an annual influenza vaccine trial. Serological status prior to vaccination and 28 days following vaccination was assessed using the hemagglutination inhibition assay (HAI) to define baseline immune status and the response to vaccination. We find evidence that genes with immunological functions are increased in expression in individuals with higher pre-existing immunity and in those individuals who mount a greater response to vaccination. Using a random forest model, we find that this set of genes can be used to predict vaccine response with a performance similar to a model that incorporates physiological and prior vaccination status alone. A model using both gene expression and physiological factors has the greatest predictive power demonstrating the potential utility of molecular profiling for enhancing prediction of vaccine response. Moreover, expression of genes that are associated with enhanced vaccination response may point to additional biological pathways that contribute to mounting a robust immunological response to the seasonal influenza vaccine.

Common and species-specific molecular signatures, networks, and regulators of influenza virus infection in mice, ferrets, and humans

Molecular responses to influenza A virus (IAV) infections vary between mammalian species. To identify conserved and species-specific molecular responses, we perform a comparative study of transcriptomic data derived from blood cells, primary epithelial cells, and lung tissues collected from IAV-infected humans, ferrets, and mice. The molecular responses in the human host have unique functions such as antigen processing that are not observed in mice or ferrets. Highly conserved gene coexpression modules across the three species are enriched for IAV infection-induced pathways including cell cycle and interferon (IFN) signaling. TDRD7 is predicted as an IFN-inducible host factor that is up-regulated upon IAV infection in the three species. TDRD7 is required for antiviral IFN response, potentially modulating IFN signaling via the JAK/STAT/IRF9 pathway. Identification of the common and species-specific molecular signatures, networks, and regulators of IAV infection provides insights into host-defense mechanisms and will facilitate the development of novel therapeutic interventions against IAV infection.

Within-host genetic diversity of SARS-CoV-2 in the context of large-scale hospital-associated genomic surveillance

The COVID-19 pandemic has resulted in extensive surveillance of the genomic diversity of SARS-CoV-2. Sequencing data generated as part of these efforts can also capture the diversity of the SARS-CoV-2 virus populations replicating within infected individuals. To assess this within-host diversity of SARS-CoV-2 we quantified low frequency (minor) variants from deep sequence data of thousands of clinical samples collected by a large urban hospital system over the course of a year. Using a robust analytical pipeline to control for technical artefacts, we observe that at comparable viral loads, specimens from patients hospitalized due to COVID-19 had a greater number of minor variants than samples from outpatients. Since individuals with highly diverse viral populations could be disproportionate drivers of new viral lineages in the patient population, these results suggest that transmission control should pay special attention to patients with severe or protracted disease to prevent the spread of novel variants.

Optimized Quantification of Intrahost Viral Diversity in SARS-CoV-2 and Influenza Virus Sequence Data

High error rates of viral RNA-dependent RNA polymerases lead to diverse intra-host viral populations during infection. Errors made during replication that are not strongly deleterious to the virus can lead to the generation of minority variants. However, accurate detection of minority variants in viral sequence data is complicated by errors introduced during sample preparation and data analysis. We used synthetic RNA controls and simulated data to test seven variant calling tools across a range of allele frequencies and simulated coverages. We show that choice of variant caller, and use of replicate sequencing have the most significant impact on single nucleotide variant (SNV) discovery and demonstrate how both allele frequency and coverage thresholds impact both false discovery and false negative rates. We use these parameters to find minority variants in sequencing data from SARS-CoV-2 clinical specimens and provide guidance for studies of intrahost viral diversity using either single replicate data or data from technical replicates. Our study provides a framework for rigorous assessment of technical factors that impact SNV identification in viral samples and establishes heuristics that will inform and improve future studies of intrahost variation, viral diversity, and viral evolution.

IMPORTANCE

When viruses replicate inside a host, the virus replication machinery makes mistakes. Over time, these mistakes create mutations that result in a diverse population of viruses inside the host. Mutations that are neither lethal to the virus, nor strongly beneficial, can lead to minority variants that are minor members of the virus population. However, preparing samples for sequencing can also introduce errors that resemble minority variants, resulting in inclusion of false positive data if not filtered correctly. In this study, we aimed to determine the best methods for identification and quantification of these minority variants by testing the performance of seven commonly used variant calling tools. We used simulated and synthetic data to test their performance against a true set of variants, and then used these studies to inform variant identification in data from clinical SARS-CoV-2 clinical specimens. Together, analyses of our data provide extensive guidance for future studies of viral diversity and evolution.

COVID-19 redux: clinical, virologic, and immunologic evaluation of clinical rebound after nirmatrelvir/ritonavir

Clinical rebound of COVID-19 after nirmatrelvir/ritonavir treatment has been reported. We performed clinical, virologic, and immune measurements in seven patients with symptomatic rebound, six after nirmatrelvir/ritonavir treatment and one without previous treatment. There was no evidence of severe disease or impaired antibody and T-cell responses in people with rebound symptoms.

Defining the risk of SARS-CoV-2 variants on immune protection

The global emergence of many severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants jeopardizes the protective antiviral immunity induced after infection or vaccination. To address the public health threat caused by the increasing SARS-CoV-2 genomic diversity, the National Institute of Allergy and Infectious Diseases within the National Institutes of Health established the SARS-CoV-2 Assessment of Viral Evolution (SAVE) programme. This effort was designed to provide a real-time risk assessment of SARS-CoV-2 variants that could potentially affect the transmission, virulence, and resistance to infection- and vaccine-induced immunity. The SAVE programme is a critical data-generating component of the US Government SARS-CoV-2 Interagency Group to assess implications of SARS-CoV-2 variants on diagnostics, vaccines and therapeutics, and for communicating public health risk. Here we describe the coordinated approach used to identify and curate data about emerging variants, their impact on immunity and effects on vaccine protection using animal models. We report the development of reagents, methodologies, models and notable findings facilitated by this collaborative approach and identify future challenges. This programme is a template for the response to rapidly evolving pathogens with pandemic potential by monitoring viral evolution in the human population to identify variants that could reduce the effectiveness of countermeasures.

Evaluation of determinants of the serological response to the quadrivalent split-inactivated influenza vaccine

The seasonal influenza vaccine is only effective in half of the vaccinated population. To identify determinants of vaccine efficacy, we used data from > 1,300 vaccination events to predict the response to vaccination measured as seroconversion as well as hemagglutination inhibition (HAI) titer levels one year after. We evaluated the predictive capabilities of age, body mass index (BMI), sex, race, comorbidities, vaccination history, and baseline HAI titers, as well as vaccination month and vaccine dose in multiple linear regression models. The models predicted the categorical response for > 75% of the cases in all subsets with one exception. Prior vaccination, baseline titer level, and age were the major determinants of seroconversion, all of which had negative effects. Further, we identified a gender effect in older participants and an effect of vaccination month. BMI had a surprisingly small effect, likely due to its correlation with age. Comorbidities, vaccine dose, and race had negligible effects. Our models can generate a new seroconversion score that is corrected for the impact of these factors which can facilitate future biomarker identification.

Sex disparities in influenza: A multiscale network analysis

Sex differences in the pathogenesis of infectious diseases because of differential immune responses between females and males have been well-documented for multiple pathogens. However, the molecular mechanism underlying the observed sex differences in influenza virus infection remains poorly understood. In this study, we used a network-based approach to characterize the blood transcriptome collected over the course of infection with influenza A virus from female and male ferrets to dissect sex-biased gene expression. We identified significant differences in the temporal dynamics and regulation of immune responses between females and males. Our results elucidate sex-differentiated pathways involved in the unfolded protein response (UPR), lipid metabolism, and inflammatory responses, including a female-biased IRE1/XBP1 activation and male-biased crosstalk between metabolic reprogramming and IL-1 and AP-1 pathways. Overall, our study provides molecular insights into sex differences in transcriptional regulation of immune responses and contributes to a better understanding of sex biases in influenza pathogenesis.

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Regulation of immune responses between females and males is significantly different

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Rapid activation of UPR in females triggers potent immune and inflammatory responses

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Male-specific regulatory pattern in the AP1 pathway indicate a bias in immune response

Year-long COVID-19 infection reveals within-host evolution of SARS-CoV-2 in a patient with B cell depletion

B-cell depleting therapies may lead to prolonged disease and viral shedding in individuals infected with SARS-CoV-2 and this viral persistence raises concern for viral evolution. We report on the sequencing of early and late samples from a 335-day infection in an immunocompromised patient. The virus accumulated a unique deletion in the amino-terminal domain of the spike protein, and complete deletion of ORF7b and ORF8, the first report of its kind in an immunocompromised patient. Overall, the unique viral mutations found in this study highlight the importance of analyzing viral evolution in protracted SARS-CoV-2 infection, especially in immunosuppressed hosts.

Year-long COVID-19 infection reveals within-host evolution of SARS-CoV-2 in a patient with B cell depletion

Background

B-cell depleting therapies may lead to protracted disease and prolonged viral shedding in individuals infected with SARS-CoV-2. Viral persistence in the setting of immunosuppression raises concern for viral evolution.

Methods

Amplification of sub-genomic transcripts for the E gene (sgE) was done on nasopharyngeal samples over the course of 355 days in a patient infected with SARS-CoV-2 who had previously undergone CAR T cell therapy and had persistently positive SARS-CoV-2 nasopharyngeal swabs. Whole genome sequencing was performed on samples from the patient's original presentation and 10 months later.

Results

Over the course of almost a year, the virus accumulated a unique in-frame deletion in the amino-terminal domain of the spike protein, and complete deletion of ORF7b and ORF8, the first report of its kind in an immunocompromised patient. Also, minority variants that were identified in the early samples-reflecting the heterogeneity of the initial infection-were found to be fixed late in the infection. Remdesivir and high-titer convalescent plasma treatment were given, and the infection was eventually cleared after 335 days of infection.

Conclusions

The unique viral mutations found in this study highlight the importance of analyzing viral evolution in protracted SARS-CoV-2 infection, especially in immunosuppressed hosts, and the implication of these mutations in the emergence of viral variants.

Summary

We report an immunocompromised patient with persistent symptomatic SARS-CoV-2 infection for 335 days. During this time, the virus accumulated a unique in-frame deletion in the spike, and a complete deletion of ORF7b and ORF8 which is the first report of its kind in an immunocompromised patient.

Microbial signatures in the lower airways of mechanically ventilated COVID-19 patients associated with poor clinical outcome

Respiratory failure is associated with increased mortality in COVID-19 patients. There are no validated lower airway biomarkers to predict clinical outcome. We investigated whether bacterial respiratory infections were associated with poor clinical outcome of COVID-19 in a prospective, observational cohort of 589 critically ill adults, all of whom required mechanical ventilation. For a subset of 142 patients who underwent bronchoscopy, we quantified SARS-CoV-2 viral load, analysed the lower respiratory tract microbiome using metagenomics and metatranscriptomics and profiled the host immune response. Acquisition of a hospital-acquired respiratory pathogen was not associated with fatal outcome. Poor clinical outcome was associated with lower airway enrichment with an oral commensal (Mycoplasma salivarium). Increased SARS-CoV-2 abundance, low anti-SARS-CoV-2 antibody response and a distinct host transcriptome profile of the lower airways were most predictive of mortality. Our data provide evidence that secondary respiratory infections do not drive mortality in COVID-19 and clinical management strategies should prioritize reducing viral replication and maximizing host responses to SARS-CoV-2.

Functional lower airways genomic profiling of the microbiome to capture active microbial metabolism

BACKGROUND

Microbiome studies of the lower airways based on bacterial 16S rRNA gene sequencing assess microbial community structure but can only infer functional characteristics. Microbial products, such as short-chain fatty acids (SCFAs), in the lower airways have significant impact on the host's immune tone. Thus, functional approaches to the analyses of the microbiome are necessary.

METHODS

Here we used upper and lower airway samples from a research bronchoscopy smoker cohort. In addition, we validated our results in an experimental mouse model. We extended our microbiota characterisation beyond 16S rRNA gene sequencing with the use of whole-genome shotgun (WGS) and RNA metatranscriptome sequencing. SCFAs were also measured in lower airway samples and correlated with each of the sequencing datasets. In the mouse model, 16S rRNA gene and RNA metatranscriptome sequencing were performed.

RESULTS

Functional evaluations of the lower airway microbiota using inferred metagenome, WGS and metatranscriptome data were dissimilar. Comparison with measured levels of SCFAs shows that the inferred metagenome from the 16S rRNA gene sequencing data was poorly correlated, while better correlations were noted when SCFA levels were compared with WGS and metatranscriptome data. Modelling lower airway aspiration with oral commensals in a mouse model showed that the metatranscriptome most efficiently captures transient active microbial metabolism, which was overestimated by 16S rRNA gene sequencing.

CONCLUSIONS

Functional characterisation of the lower airway microbiota through metatranscriptome data identifies metabolically active organisms capable of producing metabolites with immunomodulatory capacity, such as SCFAs.

Microbial signatures in the lower airways of mechanically ventilated COVID19 patients associated with poor clinical outcome.. [PMID: 33791687 PMCID: PMC8010736 DOI: 10.21203/rs.3.rs-266050/v1]

Mortality among patients with COVID-19 and respiratory failure is high and there are no known lower airway biomarkers that predict clinical outcome. We investigated whether bacterial respiratory infections and viral load were associated with poor clinical outcome and host immune tone. We obtained bacterial and fungal culture data from 589 critically ill subjects with COVID-19 requiring mechanical ventilation. On a subset of the subjects that underwent bronchoscopy, we also quantified SARS-CoV-2 viral load, analyzed the microbiome of the lower airways by metagenome and metatranscriptome analyses and profiled the host immune response. We found that isolation of a hospital-acquired respiratory pathogen was not associated with fatal outcome. However, poor clinical outcome was associated with enrichment of the lower airway microbiota with an oral commensal (Mycoplasma salivarium), while high SARS-CoV-2 viral burden, poor anti-SARS-CoV-2 antibody response, together with a unique host transcriptome profile of the lower airways were most predictive of mortality. Collectively, these data support the hypothesis that 1) the extent of viral infectivity drives mortality in severe COVID-19, and therefore 2) clinical management strategies targeting viral replication and host responses to SARS-CoV-2 should be prioritized.

Microbial signatures in the lower airways of mechanically ventilated COVID19 patients associated with poor clinical outcome

Mortality among patients with COVID-19 and respiratory failure is high and there are no known lower airway biomarkers that predict clinical outcome. We investigated whether bacterial respiratory infections and viral load were associated with poor clinical outcome and host immune tone. We obtained bacterial and fungal culture data from 589 critically ill subjects with COVID-19 requiring mechanical ventilation. On a subset of the subjects that underwent bronchoscopy, we also quantified SARS-CoV-2 viral load, analyzed the microbiome of the lower airways by metagenome and metatranscriptome analyses and profiled the host immune response. We found that isolation of a hospital-acquired respiratory pathogen was not associated with fatal outcome. However, poor clinical outcome was associated with enrichment of the lower airway microbiota with an oral commensal ( Mycoplasma salivarium ), while high SARS-CoV-2 viral burden, poor anti-SARS-CoV-2 antibody response, together with a unique host transcriptome profile of the lower airways were most predictive of mortality. Collectively, these data support the hypothesis that 1) the extent of viral infectivity drives mortality in severe COVID-19, and therefore 2) clinical management strategies targeting viral replication and host responses to SARS-CoV-2 should be prioritized.

Mapping the evolutionary landscape of Zika virus infection in immunocompromised mice

The fundamental basis of how arboviruses evolve in nature and what regulates the adaptive process remain unclear. To address this problem, we established a Zika virus (ZIKV) vector-borne transmission system in immunocompromised mice to study the evolutionary characteristics of ZIKV infection. Using this system, we defined factors that influence the evolutionary landscape of ZIKV infection and show that transmission route and specific organ microenvironments impact viral diversity and defective viral genome production. In addition, we identified in mice the emergence of ZIKV mutants previously seen in natural infections, including variants present in currently circulating Asian and American strains, as well as mutations unique to the mouse infections. With these studies, we have established an insect-to-mouse transmission model to study ZIKV evolution in vivo. We also defined how organ microenvironments and infection route impact the ZIKV evolutionary landscape, providing a deeper understanding of the factors that regulate arbovirus evolution and emergence.

iGenomics: Comprehensive DNA sequence analysis on your Smartphone

BACKGROUND

Following the miniaturization of integrated circuitry and other computer hardware over the past several decades, DNA sequencing is on a similar path. Leading this trend is the Oxford Nanopore sequencing platform, which currently offers the hand-held MinION instrument and even smaller instruments on the horizon. This technology has been used in several important applications, including the analysis of genomes of major pathogens in remote stations around the world. However, despite the simplicity of the sequencer, an equally simple and portable analysis platform is not yet available.

RESULTS

iGenomics is the first comprehensive mobile genome analysis application, with capabilities to align reads, call variants, and visualize the results entirely on an iOS device. Implemented in Objective-C using the FM-index, banded dynamic programming, and other high-performance bioinformatics techniques, iGenomics is optimized to run in a mobile environment. We benchmark iGenomics using a variety of real and simulated Nanopore sequencing datasets of viral and bacterial genomes and show that iGenomics has performance comparable to the popular BWA-MEM/SAMtools/IGV suite, without necessitating a laptop or server cluster.

CONCLUSIONS

iGenomics is available open source (https://github.com/stuckinaboot/iGenomics) and for free on Apple's App Store (https://apple.co/2HCplzr).

Age-Dependent Glycomic Response to the 2009 Pandemic H1N1 Influenza Virus and Its Association with Disease Severity

Influenza A viruses cause a spectrum of responses, from mild coldlike symptoms to severe respiratory illness and death. Intrinsic host factors, such as age, can influence disease severity. Glycosylation plays a critical role in influenza pathogenesis; however, the molecular drivers of influenza outcomes remain unknown. In this work, we characterized the host glycomic response to the H1N1 2009 pandemic influenza A virus (H1N1pdm09) as a function of age-dependent severity in a ferret model. Using our dual-color lectin microarray technology, we examined baseline glycosylation and glycomic response to infection in newly weaned and aged animals, models for young children and the elderly, respectively. Compared to adult uninfected ferrets, we observed higher levels of α-2,6-sialosides, the receptor for H1N1pdm09, in newly weaned and aged animals. We also observed age-dependent loss of O-linked α-2,3-sialosides. The loss of these highly charged groups may impact viral clearance by mucins, which corresponds to the lower clearance rates observed in aged animals. Upon infection, we observed dramatic changes in the glycomes of aged animals, a population severely impacted by the virus. In contrast, no significant alterations were observed in the newly weaned animals, which show mild to moderate responses to the H1N1pdm09. High mannose, a glycan recently identified as a marker of severity in adult animals, increased with severity in the aged population. However, the response was delayed, in line with the delayed development of pneumonia observed. Overall, our results may help explain the differential susceptibility to influenza A infection and severity observed as a function of age.

Modeling the metabolic interplay between a parasitic worm and its bacterial endosymbiont allows the identification of novel drug targets

The filarial nematode Brugia malayi represents a leading cause of disability in the developing world, causing lymphatic filariasis in nearly 40 million people. Currently available drugs are not well-suited to mass drug administration efforts, so new treatments are urgently required. One potential vulnerability is the endosymbiotic bacteria Wolbachia-present in many filariae-which is vital to the worm. Genome scale metabolic networks have been used to study prokaryotes and protists and have proven valuable in identifying therapeutic targets, but have only been applied to multicellular eukaryotic organisms more recently. Here, we present iDC625, the first compartmentalized metabolic model of a parasitic worm. We used this model to show how metabolic pathway usage allows the worm to adapt to different environments, and predict a set of 102 reactions essential to the survival of B. malayi. We validated three of those reactions with drug tests and demonstrated novel antifilarial properties for all three compounds.

Quantifying between-Host Transmission in Influenza Virus Infections

The error-prone replication and life cycle of influenza virus generate a diverse set of genetic variants. Transmission between hosts strictly limits both the number of virus particles and the genetic diversity of virus variants that reach a new host and establish an infection. This sharp reduction in the virus population at transmission--the transmission bottleneck--is significant to the evolution of influenza virus and to its epidemic and pandemic potential. This review describes transmission bottlenecks and their effect on the diversity and evolution of influenza virus. It also reviews the methods for calculating and predicting bottleneck sizes and highlights the host and viral determinants of influenza transmissibility.

Prediction pipeline for discovery of regulatory motifs associated with Brugia malayi molting

Filarial nematodes can cause debilitating diseases in humans. They have complicated life cycles involving an insect vector and mammalian hosts, and they go through a number of developmental molts. While whole genome sequences of parasitic worms are now available, very little is known about transcription factor (TF) binding sites and their cognate transcription factors that play a role in regulating development. To address this gap, we developed a novel motif prediction pipeline, Emotif Alpha, that integrates ten different motif discovery algorithms, multiple statistical tests, and a comparative analysis of conserved elements between the filarial worms Brugia malayi and Onchocerca volvulus, and the free-living nematode Caenorhabditis elegans. We identified stage-specific TF binding motifs in B. malayi, with a particular focus on those potentially involved in the L3-L4 molt, a stage important for the establishment of infection in the mammalian host. Using an in vitro molting system, we tested and validated three of these motifs demonstrating the accuracy of the motif prediction pipeline.

Diseases caused by parasitic worms such as the filariae are among the leading causes of morbidity in the developing world. Very little is known about how development is regulated in these vector-transmitted parasites. We have developed a computational method to identify motifs that correspond to transcription factor binding sites in the genome of the parasitic worm, Brugia malayi, one of the causative agents of lymphatic filariasis. Using this approach, we were able to predict stage-specific transcription factor binding sites involved in a stage of the molting process important for the establishment of the infection. We validated the role of these motifs using an in vitro molting system.

Sex chromosome evolution in parasitic nematodes of humans

Sex determination mechanisms often differ even between related species yet the evolution of sex chromosomes remains poorly understood in all but a few model organisms. Some nematodes such as Caenorhabditis elegans have an XO sex determination system while others, such as the filarial parasite Brugia malayi, have an XY mechanism. We present a complete B. malayi genome assembly and define Nigon elements shared with C. elegans, which we then map to the genomes of other filarial species and more distantly related nematodes. We find a remarkable plasticity in sex chromosome evolution with several distinct cases of neo-X and neo-Y formation, X-added regions, and conversion of autosomes to sex chromosomes from which we propose a model of chromosome evolution across different nematode clades. The phylum Nematoda offers a new and innovative system for gaining a deeper understanding of sex chromosome evolution.

Characterization of antibiotic resistance and host-microbiome interactions in the human upper respiratory tract during influenza infection

BACKGROUND

The abundance and diversity of antibiotic resistance genes (ARGs) in the human respiratory microbiome remain poorly characterized. In the context of influenza virus infection, interactions between the virus, the host, and resident bacteria with pathogenic potential are known to complicate and worsen disease, resulting in coinfection and increased morbidity and mortality of infected individuals. When pathogenic bacteria acquire antibiotic resistance, they are more difficult to treat and of global health concern. Characterization of ARG expression in the upper respiratory tract could help better understand the role antibiotic resistance plays in the pathogenesis of influenza-associated bacterial secondary infection.

RESULTS

Thirty-seven individuals participating in the Household Influenza Transmission Study (HITS) in Managua, Nicaragua, were selected for this study. We performed metatranscriptomics and 16S rRNA gene sequencing analyses on nasal and throat swab samples, and host transcriptome profiling on blood samples. Individuals clustered into two groups based on their microbial gene expression profiles, with several microbial pathways enriched with genes differentially expressed between groups. We also analyzed antibiotic resistance gene expression and determined that approximately 25% of the sequence reads that corresponded to antibiotic resistance genes mapped to Streptococcus pneumoniae and Staphylococcus aureus. Following construction of an integrated network of ARG expression with host gene co-expression, we identified several host key regulators involved in the host response to influenza virus and bacterial infections, and host gene pathways associated with specific antibiotic resistance genes.

CONCLUSIONS

This study indicates the host response to influenza infection could indirectly affect antibiotic resistance gene expression in the respiratory tract by impacting the microbial community structure and overall microbial gene expression. Interactions between the host systemic responses to influenza infection and antibiotic resistance gene expression highlight the importance of viral-bacterial co-infection in acute respiratory infections like influenza. Video abstract.

Global phylogeography and ancient evolution of the widespread human gut virus crAssphage

Microbiomes are vast communities of microorganisms and viruses that populate all natural ecosystems. Viruses have been considered to be the most variable component of microbiomes, as supported by virome surveys and examples of high genomic mosaicism. However, recent evidence suggests that the human gut virome is remarkably stable compared with that of other environments. Here, we investigate the origin, evolution and epidemiology of crAssphage, a widespread human gut virus. Through a global collaboration, we obtained DNA sequences of crAssphage from more than one-third of the world's countries and showed that the phylogeography of crAssphage is locally clustered within countries, cities and individuals. We also found fully colinear crAssphage-like genomes in both Old-World and New-World primates, suggesting that the association of crAssphage with primates may be millions of years old. Finally, by exploiting a large cohort of more than 1,000 individuals, we tested whether crAssphage is associated with bacterial taxonomic groups of the gut microbiome, diverse human health parameters and a wide range of dietary factors. We identified strong correlations with different clades of bacteria that are related to Bacteroidetes and weak associations with several diet categories, but no significant association with health or disease. We conclude that crAssphage is a benign cosmopolitan virus that may have coevolved with the human lineage and is an integral part of the normal human gut virome.

Global phylogeography and ancient evolution of the widespread human gut virus crAssphage

Microbiomes are vast communities of microorganisms and viruses that populate all natural ecosystems. Viruses have been considered to be the most variable component of microbiomes, as supported by virome surveys and examples of high genomic mosaicism. However, recent evidence suggests that the human gut virome is remarkably stable compared with that of other environments. Here, we investigate the origin, evolution and epidemiology of crAssphage, a widespread human gut virus. Through a global collaboration, we obtained DNA sequences of crAssphage from more than one-third of the world's countries and showed that the phylogeography of crAssphage is locally clustered within countries, cities and individuals. We also found fully colinear crAssphage-like genomes in both Old-World and New-World primates, suggesting that the association of crAssphage with primates may be millions of years old. Finally, by exploiting a large cohort of more than 1,000 individuals, we tested whether crAssphage is associated with bacterial taxonomic groups of the gut microbiome, diverse human health parameters and a wide range of dietary factors. We identified strong correlations with different clades of bacteria that are related to Bacteroidetes and weak associations with several diet categories, but no significant association with health or disease. We conclude that crAssphage is a benign cosmopolitan virus that may have coevolved with the human lineage and is an integral part of the normal human gut virome.

Age-Related Pathology Associated with H1N1 A/California/07/2009 Influenza Virus Infection

Influenza virus infection causes a spectrum of diseases, ranging from mild upper respiratory tract infection to severe lower respiratory tract infection, that can lead to diffuse alveolar damage, interstitial and airspace inflammation, or acute respiratory failure. Mechanisms instructing disease severity are not completely understood, but host, viral, and bacterial factors influence disease outcome. With age being one host factor associated with a higher risk of severe influenza, we investigated regional pulmonary distribution and severity of pneumonia after 2009 H1N1 influenza virus infection in newly weaned, adult, and aged ferrets to better understand age-dependent susceptibility and pathology. Aged ferrets exhibited greater weight loss and higher rates of mortality than adult ferrets, whereas most newly weaned ferrets did not lose weight but had a lack of weight gain. Newly weaned ferrets exhibited minimal pneumonia, whereas adult and aged ferrets had a spectrum of pneumonia severity. Influenza virus-induced pneumonia peaked earliest in adult ferrets, whereas aged ferrets had delayed presentation. Bronchial severity differed among groups, but bronchial pathology was comparable among all cohorts. Alveolar infection was strikingly different among groups. Newly weaned ferrets had little alveolar cell infection. Adult and aged ferrets had alveolar infection, but aged ferrets were unable to clear infection. These different age-related pneumonia and infection patterns suggest therapeutic strategies to treat influenza should be tailored contingent on age.

Pyruvate produced by Brugia spp. via glycolysis is essential for maintaining the mutualistic association between the parasite and its endosymbiont, Wolbachia

Human parasitic nematodes are the causative agents of lymphatic filariasis (elephantiasis) and onchocerciasis (river blindness), diseases that are endemic to more than 80 countries and that consistently rank in the top ten for the highest number of years lived with disability. These filarial nematodes have evolved an obligate mutualistic association with an intracellular bacterium, Wolbachia, a symbiont that is essential for the successful development, reproduction, and survival of adult filarial worms. Elimination of the bacteria causes adult worms to die, making Wolbachia a primary target for developing new interventional tools to combat filariases. To further explore Wolbachia as a promising indirect macrofilaricidal drug target, the essential cellular processes that define the symbiotic Wolbachia-host interactions need to be identified. Genomic analyses revealed that while filarial nematodes encode all the enzymes necessary for glycolysis, Wolbachia does not encode the genes for three glycolytic enzymes: hexokinase, 6-phosphofructokinase, and pyruvate kinase. These enzymes are necessary for converting glucose into pyruvate. Wolbachia, however, has the full complement of genes required for gluconeogenesis starting with pyruvate, and for energy metabolism via the tricarboxylic acid cycle. Therefore, we hypothesized that Wolbachia might depend on host glycolysis to maintain a mutualistic association with their parasitic host. We did conditional experiments in vitro that confirmed that glycolysis and its end-product, pyruvate, sustain this symbiotic relationship. Analysis of alternative sources of pyruvate within the worm indicated that the filarial lactate dehydrogenase could also regulate the local intracellular concentration of pyruvate in proximity to Wolbachia and thus help control bacterial growth via molecular interactions with the bacteria. Lastly, we have shown that the parasite's pyruvate kinase, the enzyme that performs the last step in glycolysis, could be a potential novel anti-filarial drug target. Establishing that glycolysis is an essential component of symbiosis in filarial worms could have a broader impact on research focused on other intracellular bacteria-host interactions where the role of glycolysis in supporting intracellular survival of bacteria has been reported.

Profiling the airway in the macaque model of tuberculosis reveals variable microbial dysbiosis and alteration of community structure

BACKGROUND

The specific interactions of Mycobacterium tuberculosis (Mtb), the causative agent of tuberculosis (TB), and the lung microbiota in infection are entirely unexplored. Studies in cancer and other infectious diseases suggest that there are important exchanges occurring between host and microbiota that influence the immunological landscape. This can result in alterations in immune regulation and inflammation both locally and systemically. To assess whether Mtb infection modifies the lung microbiome, and identify changes in microbial abundance and diversity as a function of pulmonary inflammation, we compared infected and uninfected lung lobe washes collected serially from 26 macaques by bronchoalveolar lavage over the course of infection.

RESULTS

We found that Mtb induced an initial increase in lung microbial diversity at 1 month post infection that normalized by 5 months of infection across all macaques. Several core genera showed global shifts from baseline and throughout infection. Moreover, we identified several specific taxa normally associated with the oral microbiome that increased in relative abundance in the lung following Mtb infection, including SR1, Aggregatibacter, Leptotrichia, Prevotella, and Campylobacter. On an individual macaque level, we found significant heterogeneity in both the magnitude and duration of change within the lung microbial community that was unrelated to lung inflammation and lobe involvement as seen by positron emission tomography/computed tomography (PET/CT) imaging. By comparing microbial interaction networks pre- and post-infection using the predictive algorithm SPIEC-EASI, we observe that extra connections are gained by Actinomycetales, the order containing Mtb, in spite of an overall reduction in the number of interactions of the whole community post-infection, implicating Mtb-driven ecological reorganization within the lung.

CONCLUSIONS

This study is the first to probe the dynamic interplay between Mtb and host microbiota longitudinally and in the macaque lung. Our findings suggest that Mtb can alter the microbial landscape of infected lung lobes and that these interactions induce dysbiosis that can disrupt oral-airway boundaries, shift overall lung diversity, and modulate specific microbial relationships. We also provide evidence that this effect is heterogeneous across different macaques. Overall, however, the changes to the airway microbiota after Mtb infection were surprisingly modest, despite a range of Mtb-induced pulmonary inflammation in this cohort of macaques.

Tropheryma whipplei colonization in HIV-infected individuals is not associated with lung function or inflammation

Studies demonstrate that Tropheryma whipplei (T. whipplei) is present in the lungs of healthy individuals without acute respiratory symptoms or acute respiratory infection and is more common in the lungs of HIV-infected individuals and in smokers. The impact of T. whipplei colonization in the lung on local inflammation and pulmonary dysfunction in HIV-infected individuals is currently unknown. In this study, we performed specific polymerase chain reaction (PCR) and sequencing for T. whipplei in bronchoalveolar lavage (BAL) and induced sputum (IS) samples in 76 HIV-infected participants from three clinical sites. Pulmonary function and proinflammatory cytokine and chemokine levels in BAL were measured. Frequency of T. whipplei in either BAL or IS was 43.4%. The sensitivity and specificity of IS compared to BAL for detection of T. whipplei was 92.3% and 84.2%, respectively, and isolates of T. whipplei in the BAL and IS in the same subject shared genetic identity. Pulmonary function measures were not associated with T. whipplei colonization, and proinflammatory cytokine and chemokine levels in BAL and plasma as well as percentages of inflammatory cells in BAL and IS were not higher in colonized individuals. Overall, these results indicate that T. whipplei colonization in the lung is common, but may not be associated with decreased pulmonary function or inflammation in HIV-infected individuals.

Measuring associations between the microbiota and repeated measures of continuous clinical variables using a lasso-penalized generalized linear mixed model

Background

Human microbiome studies in clinical settings generally focus on distinguishing the microbiota in health from that in disease at a specific point in time. However, microbiome samples may be associated with disease severity or continuous clinical health indicators that are often assessed at multiple time points. While the temporal data from clinical and microbiome samples may be informative, analysis of this type of data can be problematic for standard statistical methods.

Results

To identify associations between microbiota and continuous clinical variables measured repeatedly in two studies of the respiratory tract, we adapted a statistical method, the lasso-penalized generalized linear mixed model (LassoGLMM). LassoGLMM can screen for associated clinical variables, incorporate repeated measures of individuals, and address the large number of species found in the microbiome. As is common in microbiome studies, when the number of variables is an order of magnitude larger than the number of samples LassoGLMM can be imperfect in its variable selection. We overcome this limitation by adding a pre-screening step to reduce the number of variables evaluated in the model. We assessed the use of this adapted two-stage LassoGLMM for its ability to determine which microbes are associated with continuous repeated clinical measures.

We found associations (retaining a non-zero coefficient in the LassoGLMM) between 10 laboratory measurements and 43 bacterial genera in the oral microbiota, and between 2 cytokines and 3 bacterial genera in the lung. We compared our associations with those identified by the Wilcoxon test after dichotomizing our outcomes and identified a non-significant trend towards differential abundance between high and low outcomes. Our two-step LassoGLMM explained more of the variance seen in the outcome of interest than other variants of the LassoGLMM method.

Conclusions

We demonstrated a method that can account for the large number of genera detected in microbiome studies and repeated measures of clinical or longitudinal studies, allowing for the detection of strong associations between microbes and clinical measures. By incorporating the design strengths of repeated measurements and a prescreening step to aid variable selection, our two-step LassoGLMM will be a useful analytic method for investigating relationships between microbes and repeatedly measured continuous outcomes.

Electronic supplementary material

The online version of this article (10.1186/s13040-018-0173-9) contains supplementary material, which is available to authorized users.