Biology subjects

Methe, B.

Publications and source records attributed to Methe, B..

4 recordsLinked to original sources

bioRxiv2022

Antibodies targeting conserved non-canonical antigens and endemic coronaviruses associate with favorable outcomes in severe COVID-19

While there have been extensive analyses characterizing cellular and humoral responses across the severity spectrum in COVID-19, predictors of outcomes within severe COVID-19 remain to be comprehensively elucidated. Recently, we identified divergent monocyte states as predictors of outcomes within severe COVID-19, but corresponding humoral profiles of risk have not been delineated. Furthermore, the nature of antibodies (Abs) directed against viral antigens beyond the spike protein or endemic coronavirus antigens and their associations with disease severity and outcomes remain poorly defined. We performed deep molecular profiling of Abs directed against a wide range of antigenic specificities in severe COVID-19 patients admitted to the ICU. The profiles consisted of canonical (S, RBD, N) and non-canonical (orf3a, orf8, nsp3, nps13 and M) antigenic specificities. Notably, multivariate machine learning (ML) models, generated using profiles of Abs directed against canonical or non-canonical antigens, were equally discriminative of recovery and mortality COVID-19 outcomes. In both ML models, survivors were associated with increased virus-specific IgA and IgG3 antibodies and with higher antigen-specific antibody galactosylation. Intriguingly, pre-pandemic healthy controls had cross-reactive Abs directed against nsp13 which is a conserved protein in other alpha and beta coronaviruses. Notably, higher levels of nsp13-specific IgA antibodies were associated with recovery in severe COVID-19. In keeping with these findings, a model built on Ab profiles for endemic coronavirus antigens was also predictive of COVID-19 outcome bifurcation, with higher levels of IgA and IgG3 antibodies against OC43 S and NL63 S being associated with survival. Our results suggest the importance of Abs targeting non-canonical SARS-CoV-2 antigens as well as those directed against endemic coronaviruses in favorable outcomes of severe COVID-19.

immunology↗

bioRxiv2021

Bifurcated monocyte states are predictive of mortality in severe COVID-19

Coronavirus disease 2019 (COVID-19) caused by SARS-CoV-2 infection presents with varied clinical manifestations1, ranging from mild symptoms to acute respiratory distress syndrome (ARDS) with high mortality2,3. Despite extensive analyses, there remains an urgent need to delineate immune cell states that contribute to mortality in severe COVID-19. We performed high-dimensional cellular and molecular profiling of blood and respiratory samples from critically ill COVID-19 patients to define immune cell genomic states that are predictive of outcome in severe COVID-19 disease. Critically ill patients admitted to the intensive care unit (ICU) manifested increased frequencies of inflammatory monocytes and plasmablasts that were also associated with ARDS not due to COVID-19. Single-cell RNAseq (scRNAseq)-based deconvolution of genomic states of peripheral immune cells revealed distinct gene modules that were associated with COVID-19 outcome. Notably, monocytes exhibited bifurcated genomic states, with expression of a cytokine gene module exemplified by CCL4 (MIP-1{beta}) associated with survival and an interferon signaling module associated with death. These gene modules were correlated with higher levels of MIP-1{beta} and CXCL10 levels in plasma, respectively. Monocytes expressing genes reflective of these divergent modules were also detectable in endotracheal aspirates. Machine learning algorithms identified the distinctive monocyte modules as part of a multivariate peripheral immune system state that was predictive of COVID-19 mortality. Follow-up analysis of the monocyte modules on ICU day 5 was consistent with bifurcated states that correlated with distinct inflammatory cytokines. Our data suggests a pivotal role for monocytes and their specific inflammatory genomic states in contributing to mortality in life-threatening COVID-19 disease and may facilitate discovery of new diagnostics and therapeutics.

immunology↗

bioRxiv2020

Evolution and adaptation of Pseudomonas aeruginosa in the paranasal sinuses of people with cystic fibrosis

People with the genetic disorder cystic fibrosis (CF) harbor lifelong respiratory infections, with morbidity and mortality frequently linked to chronic lung infections dominated by the opportunistically pathogenic bacterium Pseudomonas aeruginosa. During chronic CF lung infections, a single clone of P. aeruginosa can persist for decades and dominate end-stage CF lung disease due to its propensity to adaptively evolve to the respiratory environment, a process termed "pathoadaptation". Chronic rhinosinusitis (CRS), chronic inflammation and infection of the sinonasal space, is highly prevalent in CF and the sinuses may serve as the first site in the respiratory tract to become colonized by bacteria that then proceed to seed lung infections. We identified three evolutionary genetic routes by which P. aeruginosa evolves in the sinuses of people with CF, including through the evolution of mutator lineages and proliferative insertion sequences and culminating in early genomic signatures of host-restriction. Our findings raise the question of whether a significant portion of the pathoadaptive phenotypes previously thought to have evolved in response to selective pressures in the CF lungs may have first arisen in the sinuses and underscore the link between sinonasal and lung disease in CF. Graphical abstract and highlightsO_LIPseudomonas aeruginosa undergoes adaptive evolution in the sinuses of people with CF C_LIO_LIOver time, pathoadapted strains display early signatures of genome degradation consistent with recent host restriction C_LIO_LIMutations previously thought to occur in CF lungs may have first evolved in sinuses C_LI O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=200 SRC="FIGDIR/small/359844v1_ufig1.gif" ALT="Figure 1"> View larger version (50K): org.highwire.dtl.DTLVardef@13b36aborg.highwire.dtl.DTLVardef@8230e1org.highwire.dtl.DTLVardef@1570c3eorg.highwire.dtl.DTLVardef@1e4e530_HPS_FORMAT_FIGEXP M_FIG C_FIG

microbiology↗

bioRxiv2018

Microbiome disturbance and resilience dynamics of the upper respiratory tract in response to influenza A virus infection in analog hosts

Infection with influenza can be aggravated by bacterial co-infections, which often results in disease exacerbation because of host responses and cellular damage. The native upper respiratory tract (URT) microbiome likely plays a role, yet the effects of influenza infection on the URT microbiome are largely unknown. We performed a longitudinal study to assess the temporal dynamics of the URT microbiomes of uninfected and influenza virus-infected humans and ferrets. Uninfected human patients and ferret URT microbiomes had stable \"heathy ecostate\" communities both within and between individuals. In contrast, infected patients and ferrets exhibited large changes in bacterial community composition over time and between individuals. The \"unhealthy\" ecostates of infected individuals progressed towards the \"healthy ecostate\" over time, coinciding with viral clearance and recovery. Blooms of Pseudomonas were a statistically associated constant in the disturbed microbiomes of infected individuals. The dynamic and resilient nature of the microbiome during influenza virus infection in multiple hosts provides a compelling rationale for the maintenance of the microbiome homeostasis as a potential therapeutic target to prevent IAV associated bacterial co-infections.\n\nOne Sentence SummaryDynamics of the upper respiratory tract microbiome during influenza A virus infection

microbiology↗