Biology subjects

Woelk, C. H.

Publications and source records attributed to Woelk, C. H..

5 recordsLinked to original sources

bioRxiv2022

Novel neutrophil subsets associated with sepsis, vascular dysfunction and metabolic alterations identified using systems immunology

Sepsis is a life-threatening condition caused by a dysregulated host response to infection. Despite continued efforts to understand the pathophysiology of sepsis, no effective therapies are currently available. While singular components of the aberrant immune response have been investigated, comprehensive studies linking different data layers are lacking. Using an integrated systems immunology approach, we evaluated neutrophil phenotypes and concomitant changes in cytokines and metabolites in sepsis patients. Our findings identify novel differentially expressed immature neutrophil subsets in sepsis patients. These and other subsets correlate with various proteins, metabolites, and lipids, including pentraxin-3, angiopoietin-2 and lysophosphatidylcholines, in sepsis patients. These results enabled the construction of a predictive model based on weighted multi-omics linear regression analysis for patient classification. These findings could help inform earlier patient stratification and treatment options, as well as facilitate future mechanistic studies targeting the trifecta of surface marker expression, cytokines, and metabolites.

immunology↗

bioRxiv2021

Vaccine Hyporesponse Induced By Individual Antibiotic Treatment In Mice And Non-Human Primates Is Diminished Upon Recovery Of The Gut Microbiome

Emerging evidence demonstrates a connection between microbiome composition and suboptimal response to vaccines (vaccine hyporesponse). Harnessing the interaction between microbes and the immune system could provide novel therapeutic strategies for improving vaccine response. Currently we do not fully understand the mechanisms and dynamics by which the microbiome influences vaccine response. Using both mouse and non-human primate models, we report that short-term oral treatment with a single antibiotic (vancomycin) results in disruption of the gut microbiome and this correlates with a decrease in systemic levels of antigen-specific IgG upon subsequent parenteral vaccination. We further show that recovery of microbial diversity before vaccination prevents antibiotic-induced vaccine hyporesponse, and that the antigen specific IgG response correlates with the recovery of microbiome diversity. RNA-sequencing analysis of small intestine, spleen, whole blood, and secondary lymphoid organs from antibiotic treated mice revealed a dramatic impact on the immune system, and a muted inflammatory signature is correlated with loss of bacteria from Lachnospiraceae, Ruminococcaceae, and Clostridiaceae. These results suggest that microbially modulated immune pathways may be leveraged to promote vaccine response and will inform future vaccine design and development strategies. ImportanceAntibiotic-induced gut microbiome disruption has been linked to reduced vaccine efficacy. Despite these observations, there remains a knowledge gap in the specific mechanisms by which antibiotics and the gut microbiome influence vaccine efficacy. We aim to contribute to the fields growing mechanistic understanding by presenting a detailed analysis of antibiotic treatment and recovery as it relates to vaccine response and the microbiome. Using animal models, we show that short-term antibiotic treatment prior to vaccination results in diminished vaccine-specific immune responses, and that these are correlated with specific microbiome signatures. We also demonstrate the converse, in which gut microbiome recovery can result in improved vaccine response. We further reveal that antibiotics can significantly alter multiple relevant immune pathways and this alteration in immune tone may contribute to the vaccine hyporesponse. We expect our findings will enable the continued prosecution of the role of the microbiome in modulating the host immune system.

immunology↗

bioRxiv2019

Genomic programming of antigen cross-presentation in IRF4-expressing human Langerhans cells

Langerhans cells (LCs) in the epidermis present MHC I and MHC II-restricted antigens thereby priming either CD8 or CD4 T cell immune responses. The genomic programs and transcription factors regulating antigen presentation in LCs remain to be elucidated. We show human LCs are highly efficient in MHC I-antigen cross-presentation but lack the transcription factor IRF8 that is critical in dendritic cells. LC migration from the epidermis enhances their ability to cross-present antigens and is accompanied by the induction of the transcription factor IRF4, whose expression is correlated by scRNA-seq with genes involved in ubiquitin-dependent protein degradation. Chromatin profiling reveals enrichment of EICE and AICE composite DNA binding motifs in regulatory regions of antigen-presentation genes, which can be recognized by IRF4 in conjunction with PU.1 or BATF3 expressed in LCs. Thus, the genomic programming of human LCs including inducible expression of IRF4 with enhanced cross-presentation distinguishes them from conventional dendritic cells.

immunology↗

bioRxiv2018

A Deep Learning Genome-Mining Strategy Improves Biosynthetic Gene Cluster Prediction

Natural products represent a rich reservoir of small molecule drug candidates utilized as antimicrobial drugs, anticancer therapies, and immunomodulatory agents. These molecules are microbial secondary metabolites synthesized by co-localized genes termed Biosynthetic Gene Clusters (BGCs). The increase in full microbial genomes and similar resources has led to development of BGC prediction algorithms, although their precision and ability to identify novel BGC classes could be improved. Here we present a deep learning strategy (DeepBGC) that offers more accurate BGC identification and an improved ability to extrapolate and identify novel BGC classes compared to existing tools. We supplemented this with downstream random forest classifiers that accurately predicted BGC product classes and potential chemical activity. Application of DeepBGC to bacterial genomes uncovered previously undetectable BGCs that may code for natural products with novel biologic activities. The improved accuracy and classification ability of DeepBGC represents a significant step forward for in-silico BGC identification.

bioinformatics↗

bioRxiv2017

PTSD Blood Transcriptome Mega-Analysis: Shared Inflammatory Pathways Across Genders And Modes Of Traumas

Transcriptome-wide screens of peripheral blood during the onset and development of posttraumatic stress disorder (PTSD) indicate widespread immune dysregulation. However, little is known as to whether biological sex and the type of traumatic event influence shared or distinct biological pathways in PTSD. We performed a combined analysis of five independent PTSD blood transcriptome studies covering seven types of trauma in 229 PTSD and 311 comparison individuals to synthesize the extant data. Analyses by trauma type revealed a clear pattern of PTSD gene expression signatures distinguishing interpersonal (IP)-related traumas from combat-related traumas. Co-expression network analyses integrated all data and identified distinct gene expression perturbations across sex and modes of trauma in PTSD, including one wound-healing module down-regulated in men exposed to combat traumas, one IL12-mediated signaling module up-regulated in men exposed to IP-related traumas, and two modules associated with lipid metabolism and MAPK-activity up-regulated in women exposed to IP-related traumas. Remarkably, a high degree of sharing of transcriptional dysregulation across sex and modes of trauma in PTSD was also observed converging on common signaling cascades, including cytokine, innate immune and type I interferon pathways. Collectively, these findings provide a broad view of immune dysregulation in PTSD and demonstrate inflammatory pathways of molecular convergence and specificity, which may inform mechanisms and diagnostic biomarkers for the disorder.

neuroscience↗