Biology subjects

Shilts, M. H.

Publications and source records attributed to Shilts, M. H..

3 recordsLinked to original sources

bioRxiv2026

Fast and reliable association discovery in large-scale microbiome studies and meta-analyses using PALM

Identifying microbial features associated with various covariates is a long-standing goal in microbiome research. Modern association studies incorporate an ever-increasing number of microbial features, covariates, and datasets from diverse cohorts. However, the complexity of microbiome data challenges analysis, often leading to poor replication of findings. We introduce PALM, a quasi-Poisson regression framework that enables fast and reliable association discovery in large-scale studies and meta-analyses. Extensive, realistic simulations demonstrate PALMs advantages in controlling false discovery rates, boosting power, improving computational efficiency, and preserving cross-study homogeneity of association effects. Three real-world applications at different scales illustrate PALMs utility, underscoring its potential to advance microbiome research.

microbiology↗

bioRxiv2025

The Gut Microbiome and Butyrate Differentiate Clostridioides difficile Colonization and Infection in Children

Background and AimsSymptomatic Clostridioides difficile infection (CDI) can cause significant morbidity and mortality. Conversely, patients can be colonized with toxigenic C. difficile in the absence of symptoms, termed asymptomatic colonization. We previously demonstrated that the presence and function of C. difficile toxins do not differentiate between asymptomatic colonization and CDI in children, suggesting the influence of other factors. This study aimed to interrogate the intestinal microbiome and butyrate in stool samples from children with CDI and asymptomatic colonization. MethodsDesign: Case-control study Setting: Tertiary care childrens hospital Participants and measures: Asymptomatic children had stool tested for C. difficile by nucleic-acid amplification-based testing (NAAT) and were considered colonized if positive (N=50). Residual stool was also obtained from symptomatic children who tested positive for C. difficile by NAAT (N=55). The microbiome was assessed via 16S rRNA sequencing and butyrate via liquid chromatography-mass spectrometry. ResultsCompared to clinical co-variates and comorbidities, C. difficile symptom status (i.e., asymptomatic colonization versus symptomatic CDI) demonstrated the strongest differential abundance association on gut microbes. Symptomatic CDI was associated with increased abundance of Escherichia/Shigella (Benjamini-Hochberg adjusted q=3.94x10-5), Haemophilus (q=0.022), and Gemella (q=0.085), and depleted abundance of gut commensals such as Faecalibacterium (q=0.041), Blautia (q=0.041), and Bifidobacterium (q=0.063). We also observed depletion in the abundance of microbial butyrate producers and fecal butyrate in participants with symptomatic CDI versus asymptomatic colonization. ConclusionThe gut microbiota and butyrate differ between participants with asymptomatic C. difficile colonization and symptomatic CDI, suggesting their potential role in symptom development.

microbiology↗

bioRxiv2022

Mucosal gene expression in response to SARS-CoV-2 is associated with early viral load.

Little is known about the relationships between symptomatic early-time SARS-CoV-2 viral load and upper airway mucosal gene expression and immune response. To examine the association of symptomatic SARS-CoV-2 early viral load with upper airway mucosal gene expression, we profiled the host mucosal transcriptome from nasopharyngeal swab samples from 68 adults with symptomatic, mild-to-moderate COVID-19. We measured SARS-CoV-2 viral load using qRT-PCR. We then examined the association of SARS-CoV-2 viral load with upper airway mucosal immune response. We detected SARS-CoV-2 in all samples and recovered >80% of the genome from 85% of the samples from symptomatic COVID-19 adults. The respiratory virome was dominated by SARS-CoV-2, with limited co-detection of common respiratory viruses i.e., only the human Rhinovirus (HRV) being identified in 6% of the samples. We observed a significant positive correlation between SARS-CoV-2 viral load and interferon signaling (OAS2, OAS3, IFIT1, UPS18, ISG15, ISG20, IFITM1, and OASL), chemokine signaling (CXCL10 and CXCL11), and adaptive immune system (IFITM1, CD300E, and SIGLEC1) genes in symptomatic, mild-to-moderate COVID-19 adults, when adjusted for age, sex and race. Interestingly, the expression levels of most of these genes plateaued at a CT value of ~25. Overall, our data shows that early nasal mucosal immune response to SARS-CoV-2 infection is viral load dependent, which potentially could modify COVID-19 outcomes. AUTHOR SUMMARYSeveral prior studies have shown that SARS-CoV-2 viral load can predict the likelihood of disease spread and severity. A higher detectable SARS-CoV-2 plasma viral load was associated with worse respiratory disease severity. However, the relationship between SARS-CoV-2 viral load and airway mucosal gene expression and immune response remains elusive. We profiled the nasal mucosal transcriptome from nasal samples collected from adults infected with SARS-CoV-2 during Spring 2020 with mild-to-moderate symptoms using a comprehensive metatranscriptomics method. We observed a positive correlation between SARS-CoV-2 viral load with interferon signaling, chemokine signaling, and adaptive immune system in adults with COVID-19. Our data suggest that early nasal mucosal immune response to SARS-CoV-2 infection was viral load-dependent and may modify COVID-19 outcomes.

genomics↗