Biology subjects

Caserta, M. T.

Publications and source records attributed to Caserta, M. T..

5 recordsLinked to original sources

bioRxiv2020

Temporal Dysbiosis of Infant Nasal Microbiota Relative to Respiratory Syncytial Virus Infection

RationaleRespiratory Syncytial Virus (RSV) infection is a leading cause of infant respiratory disease and hospitalization. Infant airway microbiota occupying the nasopharynx have been associated with respiratory disease risk and severity. The extent to which interactions between RSV and microbiota occur in the airway, and their impact on respiratory disease severity and infection susceptibility, are not well understood. ObjectivesTo characterize associations between the nasal microbiota and RSV infection before, during, and after infants first respiratory illness. MethodsNasal 16S rRNA microbial community profiling of two cohorts of infants in the first year of life: 1) a cross-sectional cohort of 89 RSV infected infants sampled during illness and 102 population matched healthy controls, and 2) an individually matched longitudinal cohort of 12 infants who developed RSV infection and 12 who did not, sampled at time points before, during, and after infection. Measurements and Main ResultsWe identified 12 taxa significantly associated with RSV infection. All 12 were differentially abundant during infection, with seven differentially abundant prior to infection, and eight differentially abundant after infection. Eight of these taxa were associated with disease severity. Nasal microbiota composition was more discriminative of healthy vs. infected than of disease severity. ConclusionsOur findings elucidate the chronology of nasal microbiota dysbiosis and suggest an altered developmental trajectory associated with first-time RSV infection. Microbial temporal dynamics reveal indicators of disease risk, correlates of illness and severity, and the impact of RSV infection on microbiota composition. Identified taxa represent appealing targets for additional translationally-oriented research.

microbiology↗

bioRxiv2019

Coordinated Postnatal Trajectories of T Cells and Microbiota in Preterm and Full- term Newborns

Neonatal immune-microbiota co-development is poorly understood, yet appropriate recognition of - and response to - pathogens and commensal microbiota is critical to health. In this longitudinal study of 148 pre- and 119 full-term infants from birth through one year of age we found that postmenstrual age, or weeks from conception, not post-natal age, is the dominant factor influencing T cell and mucosal microbiota development. Numerous features of the T cell and microbiota functional development remain unexplained, however, by either age metric and are instead shaped by discrete peri- and post-natal events. Most strikingly, we establish that prenatal antibiotics or infection disrupt the normal T cell population developmental trajectory, influencing subsequent respiratory microbial colonization and predicting respiratory morbidity. In this way, early exposures imprint the postnatal immune-microbiota axis and place an infant at significant risk for respiratory morbidity in early childhood. One Sentence SummaryT cells and microbiota follow predictable, coordinated trajectories in newborns, and their coordination is an important determinant of illness in the first year. Graphical AbstractNasal and rectal microbiome was assessed weekly in the NICU, monthly post-discharge, and when respiratory illness symptoms occurred. T cells were characterized at birth (cord blood), 36-42 weeks postmenstrual age, and at 12 months. Quarterly respiratory morbidity surveys determined the 12-month outcome of persistent respiratory disease. More frequent illnesses and chronic disease outcomes occurred by one year of age if development of these systems was discordant or disrupted. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=142 SRC="FIGDIR/small/736090v3_ufig1.gif" ALT="Figure 1"> View larger version (28K): org.highwire.dtl.DTLVardef@1f08adeorg.highwire.dtl.DTLVardef@12d3671org.highwire.dtl.DTLVardef@151396borg.highwire.dtl.DTLVardef@190dcff_HPS_FORMAT_FIGEXP M_FIG C_FIG

immunology↗

bioRxiv2019

Insufficiency in airway interferon activation defines clinical severity to infant RSV infection

Respiratory syncytial virus (RSV) is the leading cause of severe respiratory disease in infants. Other than age at the time of infection, the causes and correlates of severe illness in infants lacking known risk factors are poorly defined. We recruited a cohort of confirmed RSV-infected infants and simultaneously assayed the presence of resident airway microbiota and the molecular status of their airways using a novel method. Rigorous statistical analyses identified a molecular airway gene expression signature of severe illness dominated by excessive chemokine expression. Global 16S rRNA sequencing confirmed an association between H. influenzae and clinical severity. Interestingly, adjusting for H. influenzae in our gene expression analysis revealed an association between severity and airway lymphocyte accumulation. Exploring the relationship between airway gene expression and the time of onset of clinical symptoms revealed a robust, acute activation of interferon (IFN) signaling, which was absent in subjects with severe illness. Finally, we explored the relationship between IFN activity, airway gene expression and productive RSV infection using a novel in vitro model of bona fide pediatric human airway epithelial cells. Interestingly, blocking IFN signaling, but not IFN ligand production, in these cells leads to increased viral infection. Our data reveal that acute airway interferon responses are physiologically relevant in the context of infant RSV infection and may be a target for therapeutic intervention. Additionally, the airway gene expression signature we define may be useful as a biomarker for efficacy of intervention responses.

genomics↗

bioRxiv2019

Airway Gene-Expression Classifiers for Respiratory Syncytial Virus (RSV) Disease Severity in Infants

BackgroundA substantial number of infants infected with RSV develop severe symptoms requiring hospitalization. We currently lack accurate biomarkers that are associated with severe illness. MethodWe defined airway gene expression profiles based on RNA sequencing from nasal brush samples from 106 full-tem previously healthy RSV infected subjects during acute infection (day 1-10 of illness) and convalescence stage (day 28 of illness). All subjects were assigned a clinical illness severity score (GRSS). Using AIC-based model selection, we built a sparse linear correlate of GRSS based on 41 genes (NGSS1). We also built an alternate model based upon 13 genes associated with severe infection acutely but displaying stable expression over time (NGSS2). ResultsNGSS1 is strongly correlated with the disease severity, demonstrating a naive correlation ({rho}) of {rho}=0.935 and cross-validated correlation of 0.813. As a binary classifier (mild versus severe), NGSS1 correctly classifies disease severity in 89.6% of the subjects following cross-validation. NGSS2 has slightly less, but comparable, accuracy with a cross-validated correlation of 0.741 and classification accuracy of 84.0%. ConclusionAirway gene expression patterns, obtained following a minimally-invasive procedure, have potential utility for development of clinically useful biomarkers that correlate with disease severity in primary RSV infection.

immunology↗

bioRxiv2018

Neonate gut and respiratory microbiota: coordinated development through time and space

Background: Postnatal development of the microbiota in early life influences immunity, metabolism, neurodevelopment and long-term infant health. Microbiome development occurs at multiple body sites, each with distinct community compositions and functions. Associations between microbiota at multiple sites represent an unexplored influence on the infant microbiome. Here, we examined co-occurrence patterns of gut and respiratory microbiota in pre- and full-term infants over the first year of life, a period critical to neonatal development and risk of respiratory diseases.\n\nResults: Gut and respiratory microbiota collected as longitudinal rectal, throat and nasal samples from 38 pre-term and 44 full-term infants were first clustered into community state types (CSTs) on the basis of their composition. Multiple methods were used to relate the occurrence of CSTs to several measures of infant maturity, including gestational age (GA) at birth, week of life (WOL), and post menstrual age (PMA: equal to GA plus WOL). Manifestation of CSTs followed one of three patterns with respect to infant maturity. First, chronological: independent of infant maturity (GA) at birth, and strongly associated with post-natal age (WOL). Second, idiosyncratic: primarily dependent on maturity (GA) at birth, with persistent differences in CST occurrence between pre- and full-term infants through the first year of life. Third, convergent: CSTs appear earlier in infants with greater maturity (GA) at birth, but after a sufficient post-natal interval their occurrence in pre-term infants reaches parity with full-term infants. The composition of CSTs was highly dissimilar between different body sites, but the CST of any one body site was highly predictive of the CSTs at other body sites. There were significant associations between the abundance of individual taxa at each body site and the CSTs of the other body sites, which persisted after stringent control for the non-linear effects of infant maturity. Significant canonical correlations exist between the microbiota composition at each pair of body sites, with the strongest correlations between more proximal locations.\n\nConclusion: Cross-body site associations of developing infant microbiota suggest the importance of research and clinical practices that focus on dynamic interactions between multiple microbial communities to elucidate and promote systemic microbiota development.

developmental biology↗