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Spurbeck, R. R.

Publications and source records attributed to Spurbeck, R. R..

3 recordsLinked to original sources

Human Immune Cell Epigenomic Signatures in Response to Infectious Diseases and Chemical Exposures

The epigenomic landscape of human immune cells is dynamically shaped by both genetic factors and environmental exposures. However, the relative contributions of these elements are still not fully understood. In this study, we employed single-nucleus methylation sequencing and ATAC-seq to systematically explore how pathogen and chemical exposures, along with genetic variation, influence the immune cell epigenome. We identified distinct exposure-associated differentially methylated regions (eDMRs) corresponding to each exposure, revealing how environmental factors remodel the methylome, alter immune cell states, and affect transcription factor binding. Furthermore, we observed a significant correlation between changes in DNA methylation and chromatin accessibility, underscoring the coordinated response of the epigenome. We also uncovered genotype-associated DMRs (gDMRs), demonstrating that while eDMRs are enriched in regulatory regions, gDMRs are preferentially located in gene body marks, suggesting that exposures and genetic factors exert differential regulatory control. Notably, disease-associated SNPs were frequently colocalized with meQTLs, providing new cell-type-specific insights into the genetic basis of disease. Our findings underscore the intricate interplay between genetic and environmental factors in sculpting the immune cell epigenome, offering a deeper understanding of how immune cell function is regulated in health and disease.

genomics↗

UltraSEQ: a universal bioinformatic platform for information-based clinical metagenomics and beyond

Applied metagenomics is a powerful emerging capability enabling untargeted detection of pathogens, and its application in clinical diagnostics promises to alleviate the limitations of current targeted assays. While metagenomics offers a hypothesis-free approach to identify any pathogen, including unculturable and potentially novel pathogens, its application in clinical diagnostics has so far been limited by workflow-specific requirements, computational constraints, and lengthy expert review requirements. To address these challenges, we developed UltraSEQ, a first-of its kind metagenomics-based clinical diagnostics and biosurveillance tool that is accurate and scalable. Here we present results for evaluation of our novel UltraSEQ pipeline using an in silico synthesized metagenome, mock microbial community datasets, and publicly available clinical datasets from samples of different infection types, and both short-read and long-read sequencing data. Our results show that UltraSEQ successfully detected all expected species across the tree of life in the in silico sample and detected all 10 bacterial and fungal species in the mock microbial community dataset. For clinical datasets, even without requiring dataset-specific configuration settings changes, background sample subtraction, or prior sample information, UltraSEQ achieved an overall accuracy of 91%. Further, we demonstrated UltraSEQs ability to provide accurate antibiotic resistance and virulence factor genotypes that are consistent with phenotypic results. Taken together, the above results demonstrates that the UltraSEQ platform offers a transformative approach to microbial and metagenomic sample characterization, employing a biologically informed detection logic, deep metadata, and a flexible system architecture for classification and characterization of taxonomic origin, gene function, and user-defined functions, including disease-causing infection.

bioinformatics↗

Whole genome 6-methyladenosine sequencing (6-mA-Seq) enables bacterial epigenomics studies.

Methylation sequencing using bisulfite treatment has revolutionized the field of molecular biology for eukaryotic systems, unveiling levels of intricacy in regulation of gene expression in response to different environmental conditions. While bacteria also utilize methylation to regulate gene expression, bisulfite sequencing does not work as well in bacteria as in eukaryotes, because bacteria methylate adenosine instead of cytosine. Therefore, global bacterial methylation patterns cannot be studied using common Illumina sequencers. In this work, we demonstrate 6mA-seq, a method that can be used to identify patterns in bacteria that methylate adenosines at GATC sites. Furthermore, this method was used on Escherichia coli cultured on four different carbon sources to demonstrate different methylation patterns due to carbon utilization. 6mA-seq can increase the speed in which epigenetic research is conducted in bacteria.

genomics↗