Single-cell transcriptomic and chromatin accessibility analyses of dairy cattle peripheral blood mononuclear cells and their responses to lipopolysaccharide

Abstract

Background Gram-negative bacteria are important pathogens in cattle, causing severe infectious diseases, including mastitis. Lipopolysaccharides (LPS) are components of the outer membrane of Gram-negative bacteria and crucial mediators of chronic inflammation in cattle. LPS modulations of bovine immune responses have been studied before. However, the single-cell transcriptomic and chromatin accessibility analyses of bovine peripheral blood mononuclear cells (PBMCs) and their responses to LPS stimulation were never reported. Results We performed single-cell RNA sequencing (scRNA-seq) and single-cell sequencing assay for transposase-accessible chromatin (scATAC-seq) in bovine PBMCs before and after LPS treatment and demonstrated that seven major cell types, which included CD4 T cells, CD8 T cells, and B cells, monocytes, natural killer cells, innate lymphoid cells, and dendritic cells. Bioinformatic analyses indicated that LPS could increase PBMC cell cycle progression, cellular differentiation, and chromatin accessibility. Gene analyses further showed significant changes in differential expression, transcription factor binding site, gene ontology, and regulatory interactions during the PBMC responses to LPS. Consistent with the findings of previous studies, LPS induced activation of monocytes and dendritic cells, likely through their upregulated TLR4 receptor. NF-κB was observed to be activated by LPS and an increased transcription of an array of pro-inflammatory cytokines, in agreement that NF-κB is an LPS-responsive regulator of innate immune responses. In addition, by integrating LPS-induced differentially expressed genes (DEGs) with large-scale GWAS of 45 complex traits in Holstein, we detected trait-relevant cell types. We found that selected DEGs were significantly associated with immune-relevant health, milk production, and body conformation traits. Conclusion This study provided the first scRNAseq and scATAC-seq data for cattle PBMCs and their responses to the LPS stimulation to the best of our knowledge. These results should also serve as valuable resources for the future study of the bovine immune system and open the door for discoveries about immune cell roles in complex traits like mastitis at single-cell resolution.

Gut microbiome is linked to functions of peripheral immune cells in transition cows during excessive lipolysis

“…The batch correction was performed using Harmony [52] (v 0.1.0) and "FindAllMarkers" function was used to identify the marker genes (| 'avg_logFC'|> 0.25 and 'P_val_adj' < 0.05) of each cluster. The annotate of each cell type was based on the published well-known marker genes that were reported in the scRNA-seq studies of peripheral immune cells [53][54][55]. Based on the gene × cells matrix, differentially expressed genes between LNF and HNF cows of each cluster were identified using a Wilcoxon rank sum test within the "Find-AllMarkers" function [50].…”

The single-cell transcriptome and chromatin accessibility datasets of peripheral blood mononuclear cells in Chinese holstein cattle

“…Large-scale single-cell PBMC profiling and their responses to LPS stimulation in cattle need to be investigated to determine cell types and functions of PBMCs and further understanding of LPS-mediated bovine PBMC responses regarding the gene transcriptional, chromatin accessibility, and gene-based changes in PBMCs at the single-cell resolution [ 11 ]. Therefore, these single-cell transcriptome and chromatin accessibility datasets will permit investigators to summarize the cell types and functions of PBMCs to interrogate complex cellular differentiation, regulations, and interactions when responding to LPS stimulation in vitro.…”

Single-Cell Sequencing Technology in Ruminant Livestock: Challenges and Opportunities

“…Furthermore, the application of single-cell genomics in livestock research has the potential to accelerate the pace of genetic improvement by facilitating the identification of cell-type-specific gene expression, along with gene regulatory elements and networks associated with various traits important to livestock production . Adipose Nuclei RNA GEO GSE211707 [7] Embryo (8-and 16-cell stage) Cell RNA GEO GSE99210 [8] Embryo (peri-implantation) Cell RNA GEO GSE234335 [9] Embryo (SCNT) Cell RNA SRA PRJNA727165 [10] Embryo (trophectoderm) Cell RNA GEO GSE200216 [11] Fetal Gonads Cell RNA GEO GSE162952 [12] Milk Somatic Cells Cell RNA ENA PRJEB73560 [13] Muscle Cell RNA GEO GSE205347 [14] Muscle Cell RNA, ATAC GSA CRA006626 [15] PBMC * Cell RNA, ATAC GEO GSE225962 [16] PBMC * Cell RNA, ATAC GEO GSE166473 [17] Placenta (developing) Cell RNA GEO GSE234524 [18] Placenta (mature) Nuclei RNA GEO GSE214407 [19] Primary Mammary Epithelial Cells Cell RNA FAANG PRJEB41576 [20] Ruminal epithelial cells Cell RNA GEO GSE166473 [21] Satellite cells Cell RNA GEO GSE184128 [22] Satellite cells Cell RNA GEO GSE211428 [23] Despite the potential benefits, the application of sc/snRNA-seq and sc/snATAC-seq in ruminant livestock species presents challenges. Standardized computational analysis pipelines that are species-agnostic are essential, and the discovery and annotation of cell populations can be difficult in non-model organisms and for tissues such as the rumen, which are unique to these species [44][45][46].…”