Dataset Information

Multi-Omic blood analysis reveals differences in innate inflammatory sensitivity between species.

ABSTRACT: Vertebrates differ greatly in responses to pro-inflammatory agonists such as bacterial lipopolysaccharide (LPS), complicating use of animal models to study human sepsis or inflammatory disorders. We compared transcriptomes of resting and LPS-exposed blood from six LPS-sensitive species (rabbit, pig, sheep, cow, chimpanzee, human) and four LPS-resilient species (mice, rats, baboon, rhesus), as well as plasma proteomes and lipidomes. Unexpectedly, at baseline, sensitive species already had enhanced expression of LPS-responsive genes relative to resilient species. After LPS stimulation, maximally different genes in resilient species included genes that detoxify LPS, diminish bacterial growth, discriminate sepsis from SIRS, and play roles in autophagy and apoptosis. The findings reveal the molecular landscape of species differences in inflammation, and may inform better selection of species for pre-clinical models.

SUBMITTER: Gregory DJ

PROVIDER: S-EPMC10705660 | biostudies-literature | 2023 Nov

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Multi-Omic blood analysis reveals differences in innate inflammatory sensitivity between species.

Gregory David J DJ Han Feifei F Li Peng P Gritsenko Marina M Kyle Jennifer J Riley Frank E FE Chavez Deborah D Yotova Vania V Sindeaux Renata H M RHM Hawash Mohamed B F MBF Xu Fengyun F Hung Li-Yuan LY Hayden Douglas L DL Tompkins Ron G RG Lanford Robert E RE Kobzik Lester L Hellman Judith J Jacobs Jonathan M JM Barreiro Luis B LB Xiao Wenzhong W Warren H Shaw HS

medRxiv : the preprint server for health sciences 20231130

Vertebrates differ greatly in responses to pro-inflammatory agonists such as bacterial lipopolysaccharide (LPS), complicating use of animal models to study human sepsis or inflammatory disorders. We compared transcriptomes of resting and LPS-exposed blood from six LPS-sensitive species (rabbit, pig, sheep, cow, chimpanzee, human) and four LPS-resilient species (mice, rats, baboon, rhesus), as well as plasma proteomes and lipidomes. Unexpectedly, at baseline, sensitive species already had enhance ...[more]

PMID: 38076828

Similar Datasets

Project description:BackgroundInflammation is a core element of many different, systemic and chronic diseases that usually involve an important autoimmune component. The clinical phase of inflammatory diseases is often the culmination of a long series of pathologic events that started years before. The systemic characteristics and related mechanisms could be investigated through the multi-omic comparative analysis of many inflammatory diseases. Therefore, it is important to use molecular data to study the genesis of the diseases. Here we propose a new methodology to study the relationships between inflammatory diseases and signalling molecules whose dysregulation at molecular levels could lead to systemic pathological events observed in inflammatory diseases.ResultsWe first perform an exploratory analysis of gene expression data of a number of diseases that involve a strong inflammatory component. The comparison of gene expression between disease and healthy samples reveals the importance of members of gene families coding for signalling factors. Next, we focus on interested signalling gene families and a subset of inflammation related diseases with multi-omic features including both gene expression and DNA methylation. We introduce a phylogenetic-based multi-omic method to study the relationships between multi-omic features of inflammation related diseases by integrating gene expression, DNA methylation through sequence based phylogeny of the signalling gene families. The models of adaptations between gene expression and DNA methylation can be inferred from pre-estimated evolutionary relationship of a gene family. Members of the gene family whose expression or methylation levels significantly deviate from the model are considered as the potential disease associated genes.ConclusionsApplying the methodology to four gene families (the chemokine receptor family, the TNF receptor family, the TGF- β gene family, the IL-17 gene family) in nine inflammation related diseases, we identify disease associated genes which exhibit significant dysregulation in gene expression or DNA methylation in the inflammation related diseases, which provides clues for functional associations between the diseases.

Project description:Clinical outcomes of COVID-19 patients are worsened by the presence of co-morbidities, especially cancer leading to elevated mortality rates. SARS-CoV-2 infection is known to alter immune system homeostasis. Whether cancer patients developing COVID-19 present alterations of immune functions which might contribute to worse outcomes have so far been poorly investigated. We conducted a multi-omic analysis of immunological parameters in peripheral blood mononuclear cells (PBMCs) of COVID-19 patients with and without cancer. Healthy donors and SARS-CoV-2-negative cancer patients were also included as controls. At the infection peak, cytokine multiplex analysis of blood samples, cytometry by time of flight (CyTOF) cell population analyses, and Nanostring gene expression using Pancancer array on PBMCs were performed. We found that eight pro-inflammatory factors (IL-6, IL-8, IL-13, IL-1ra, MIP-1a, IP-10) out of 27 analyzed serum cytokines were modulated in COVID-19 patients irrespective of cancer status. Diverse subpopulations of T lymphocytes such as CD8+T, CD4+T central memory, Mucosal-associated invariant T (MAIT), natural killer (NK), and γδ T cells were reduced, while B plasmablasts were expanded in COVID-19 cancer patients. Our findings illustrate a repertoire of aberrant alterations of gene expression in circulating immune cells of COVID-19 cancer patients. A 19-gene expression signature of PBMCs is able to discriminate COVID-19 patients with and without solid cancers. Gene set enrichment analysis highlights an increased gene expression linked to Interferon α, γ, α/β response and signaling which paired with aberrant cell cycle regulation in cancer patients. Ten out of the 19 genes, validated in a real-world consecutive cohort, were specific of COVID-19 cancer patients independently from different cancer types and stages of the diseases, and useful to stratify patients in a COVID-19 disease severity-manner. We also unveil a transcriptional network involving gene regulators of both inflammation response and proliferation in PBMCs of COVID-19 cancer patients.

Dataset Information

Multi-Omic blood analysis reveals differences in innate inflammatory sensitivity between species.

Publications

Multi-Omic blood analysis reveals differences in innate inflammatory sensitivity between species.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets