Search bioRxiv⌕ Search

Biology subjects

Grier, A.

Publications and source records attributed to Grier, A..

10 recordsLinked to original sources

Metagenomic and transcriptomic signatures of periodontitis in companion dogs

BackgroundPeriodontitis (Perio) is a progressive oral disease characterized by inflammation and degradation of the periodontal apparatus and is associated with local and systemic morbidity including loss of teeth, cardiovascular disease, and diabetes mellitus, among others. Perio is highly prevalent in domestic canines and exhibits certain parallels in pathogenesis and pathophysiology to Perio in humans, although standard treatments are less effective. In both species, a complex interplay between oral microbiota and host immune response is implicated in the etiology of Perio but is not fully understood. ResultsUsing shotgun metagenomics and RNA-seq on oral samples from companion dogs, we identify features of the oral microbiome and host transcriptional profile that are associated with Perio and its progression. We observe differences in microbiota composition between Perio and non-Perio animals that are largely consistent with what has been described in humans but also identify several species that are distinctly associated with canine Perio. We observe an abrupt shift in host gene expression related to immune response and tissue structure that is associated with disease severity, specifically the progression from mild periodontal disease (PD) to more severe Perio and the initiation of clinical attachment loss. The gingival plaque microbiota exhibits a parallel dynamic, with distinct compositional profiles in mild, moderate, and severe PD. We then examine several of the known mechanistic components of the keystone pathogen hypothesis of PD, identifying specific commonalities between canine and human pathologies, including the involvement of Porphyromonas species and related virulence factors. Additionally, we show infiltration of gingival tissue by Porphyromonas and Tannerella spp. via fluorescence microscopy. Finally, we assess correlations between host gene expression and microbial metabolic pathways which suggest additional potential virulence factors. ConclusionsThis work elucidates the metagenomic and transcriptomic signatures of Perio in companion dogs with the goals of informing veterinary medicine, evaluating the potential of canines as a model organism for the study of Perio, and clarifying the relationship between Perio development and progression, the oral microbiota, and the localized host response. Our findings provide insight into the etiopathogenesis of canine Perio and its relationship to human Perio and suggest novel targets of potential translational interest.

microbiology↗

Integrative Multi-Omics Analysis Identifies Nuclear Factor I as a Key Driver of Dysregulated Purine Metabolism in DIPG

Diffuse intrinsic pontine glioma (DIPG) is a devastating brainstem cancer in children, with a median survival of under one year and limited treatment options. Over 80% of DIPGs possess a H3K27M mutation. To identify metabolic vulnerabilities linked to this mutation, we utilized a multi-omics approach in H3K27M-expressing cells, patient-derived cell lines, and mouse models. We show that by reprogramming chromatin landscape the mutation aberrantly induces NFI transcriptional activity, leading to misregulated purine metabolism. The mutation amplifies purine biosynthesis and degradation via the enzymes ATIC and PNP, respectively. Unregulated purine degradation relieves the negative feedback of purines on their own synthesis allowing continuous synthesis, use and degradation making DIPGs reliant on purine biosynthesis. Targeting ATIC reduced tumor progression and improved survival in mice. We propose ATIC as a potential novel target in DIPG.

cancer biology↗

Activated Interferon Signaling Suppresses Age-Dependent Liver Cancer

Age is a major risk factor for liver cancer, as is the case for most adult human cancers. However, the underlying mechanisms are not well defined. A better understanding of the role of aging in liver and other cancers can facilitate approaches for risk assessment, early detection and prevention. We hypothesize that age-driven changes render aged liver more sensitive to oncogenic stress and hence tumorigenesis. To investigate how the liver changes with age, we documented the immune profile, transcriptome and epigenome of healthy livers from both young and aged mice, revealing pronounced alterations with aging. Notably, in aged hepatocytes, we identified heightened interferon (IFN) signaling, as well as simultaneous tumor suppressor and oncogene signaling at both bulk and single cell level, suggestive of an aged liver that is poised for neoplasia. To challenge this seemingly poised state, we employed adeno-associated virus (AAV)-mediated expression of a c-Myc oncogene in young and aged mouse liver hepatocytes in vivo. Analysis of aged hepatocytes expressing c-Myc revealed further elevated expression of IFN Stimulated Genes (ISGs). This ISG upregulation was evident in multiple models of oncogenic stress and transformation in older mice and also observed in aged humans with Metabolic dysfunction-Associated Steatohepatitis (MASH). We determined that Stat1 is both necessary and sufficient for the age specific elevated ISG expression in old wild type mice. Remarkably, inhibiting Jak/Stat signaling alongside ectopic c-Myc expression led to high-grade hepatocyte dysplasia and tumor formation, selectively in aged mice. Together, these results suggest that an aged liver is in a state of "precarious balance", due to concurrent activation of oncogenic and tumor suppressor pathways, but protected against neoplastic progression by IFN-signaling. Age-dependent activation of IFN signaling has been observed in many tissues and recent studies have demonstrated its detrimental consequences on aging, raising the question as to why IFN-signaling is activated during aging. We propose that aged tissues are intrinsically at higher risk of cancer and age-dependent activation of IFN-signaling is an adaptive process to protect from tumorigenesis, but one that also has maladaptive consequences.

cancer biology↗

Genetic Variation and Disease Severity of Respiratory Syncytial Viruses

Respiratory Syncytial Virus (RSV) disease in newborns ranges from mild symptoms to severe disease requiring hospitalization. RSV is classified into two subtypes (RSVA and RSVB) based on antigenic and genetic differences. The role these genomic variations play in disease severity remains unknown. Genome sequences were obtained using next-generation RNA sequencing on archived frozen nasal swabs of young children (< 8 months-old) infected with RSV in Rochester, NY between 1977-1998. Samples were chosen from both children hospitalized with severe RSV disease (inpatient) and those presenting with mild symptoms (outpatient) during their first cold-season. Both A and B subtypes demonstrated significant differences in the phylogeny and primary-protein structure during this time period. We found a significant association between RSV phylogeny over this time period and disease severity. For both subtypes, the G-protein demonstrated the greatest amino acid substitutions, although the number of amino acid substitutions was higher in the RSVA subtype. We found a significant association between G-protein variation and disease severity for RSVA, but not RSVB. For both subtypes, variation in the M2-2 protein was significantly associated with disease severity. These results suggest that the genetic variability of RSV proteins may contribute to disease severity in humans. ImportanceEach cold-season Respiratory Syncytial Virus (RSV) infects thousands of children in the US. Some will display mild cold symptoms while others develop severe disease, sometimes resulting in lifelong lung problems or fatality. RSV initiates infection and replicates in the nasopharynx. Substitutions in the RSV genome can be found in clinically isolated nasal-swab samples of RSV infected children. Whether these genome variations contribute to severe disease is unknown. Here we found a statistically significant association between RSV phylogeny and disease severity. Furthermore, we found specific RSV proteins (G and M2-2) whose amino acid variation was statistically associated with severe disease, although which protein was associated depended on subtype. Taken together, our results suggest that RSV genotype contributed to disease severity over this time period.

microbiology↗

Transkingdom Analysis of the Female Reproductive Tract Reveals Bacteriophages Form Communities

The female reproductive tract (FRT) microbiome plays an important role in maintaining vaginal health. Viruses play a key role in regulating other microbial ecosystems, but little is known about how the FRT viruses (virome), particularly bacteriophages, impacts FRT health and dysbiosis. We hypothesize that bacterial vaginosis is associated with alterations in the FRT virome, and these changes correlate with bacteriome shifts. We conducted a retrospective, longitudinal analysis of vaginal swabs collected from 54 bacterial vaginosis (BV)-positive and 46 BV-negative South African women. Bacteriome analysis revealed samples clustered into five distinct bacterial community groups (CG). Bacterial alpha diversity was significantly associated with BV. Virome analysis on a subset of baseline samples showed FRT bacteriophages clustering into novel viral state types (VSTs), a viral community clustering system based on virome composition and abundance. Distinct BV bacteriophage signatures included increased alpha diversity along with Bacillus, Burkholderia and Escherichia bacteriophages. Discriminate bacteriophage-bacteria transkingdom associations were also identified between Bacillus and Burkholderia viruses and BV-associated bacteria, providing key insight for future studies elucidating transkingdom interactions driving BV-associated microbiome perturbations. In this cohort, bacteriophage-bacterial associations suggest complex interactions which may play a role in the establishment and maintenance of BV.

microbiology↗

A systems genomics approach uncovers molecular associates of RSV severity

Globally, RSV infection results in millions of hospitalizations and thousands of deaths each year. Specific factors that contribute to disease severity, such as premature birth and certain comorbidities, are well established. Additionally, genetic variants resulting in alterations in the adaptive and innate immune response appear to be associated with RSV severity. While previous studies focused on a single aspect of the disease, we jointly modeled the association of disparate data modalities with RSV severity. To investigate the host response to respiratory syncytial virus (RSV) infection in infants, we performed a systems-level study of RSV pathophysiology, incorporating high-throughput measurements of the peripheral innate and adaptive immune systems and the airway epithelium and microbiota. Specifically, we developed and employed a novel multi-omic data integration method based on multilayered principal component analysis, penalized regression, and feature weight back-propagation. Our novel approach enabled us to identify cell type specific and shared cellular pathways associated with RSV severity. Of particular interest was the association between RSV severity, activation of pathways controlling Th17 and acute phase response signaling, and inhibition of B cell receptor signaling, which were present in both airway and immune cells. These data identify specific aspects of dysregulation between the humoral and mucosal response to RSV that may play a critical role in determining illness severity.

genomics↗

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↗

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↗

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↗

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↗