Project description:Staphylococci are major pathogens in humans and animals and emerging antibiotic-resistant strains have further increased the importance of this health issue. The existence of a genetic basis of host response to bacterial infections has been widely documented but the underlying mechanisms and genes are still largely unknown. Previously, two divergent lines of sheep selected on their milk somatic cell count called high and low SCS lines, have been showed to be respectively more and less susceptible to intra mammary infections (IMI). Transcriptional profiling of milk somatic cells (MSC) of high and low SCS sheep infected successively by S. epidermidis and S. aureus was performed to provide enhanced knowledge about the genetic basis of differential host response to IMI with Staphylococci. Gene expression in MSC of high and low SCS sheep collected 12h post-challenge was performed on a 15K gene ovine oligoarray (Agilent). MSC were mainly neutrophils. The high number of differentially expressed genes between the two bacterial strains indicated, among others, increased number of T-cells in MSC after S. aureus, compared to S. epidermidis challenge. Differential regulation of 366 genes between resistant and susceptible animals was largely associated with immune and inflammatory response (including pathogen recognition TLR2 pathway and cell migration), signal transduction, cell proliferation and apoptosis. Close biological connection between most of differentially expressed genes into Ingenuity Pathway Analysis networks further indicated consistency between the genes that were differentially-expressed between resistant and susceptible animals. Gene profiling in high and low SCS sheep provided strong candidates for biological pathway and gene underlying genetically determined resistance and susceptibility towards Staphylococci infections opening new fields for further investigation. Keywords: Staphylococcus epidermidis, Staphylococcus aureus, milk somatic cells, mammalian, transcriptome, immunity, mastitis 22 samples in a two-colour dye-swap experimental design

Project description:Staphylococci are major pathogens in humans and animals and emerging antibiotic-resistant strains have further increased the importance of this health issue. The existence of a genetic basis of host response to bacterial infections has been widely documented but the underlying mechanisms and genes are still largely unknown. Previously, two divergent lines of sheep selected on their milk somatic cell count called high and low SCS lines, have been showed to be respectively more and less susceptible to intra mammary infections (IMI). Transcriptional profiling of milk somatic cells (MSC) of high and low SCS sheep infected successively by S. epidermidis and S. aureus was performed to provide enhanced knowledge about the genetic basis of differential host response to IMI with Staphylococci. Gene expression in MSC of high and low SCS sheep collected 12h post-challenge was performed on a 15K gene ovine oligoarray (Agilent). MSC were mainly neutrophils. The high number of differentially expressed genes between the two bacterial strains indicated, among others, increased number of T-cells in MSC after S. aureus, compared to S. epidermidis challenge. Differential regulation of 366 genes between resistant and susceptible animals was largely associated with immune and inflammatory response (including pathogen recognition TLR2 pathway and cell migration), signal transduction, cell proliferation and apoptosis. Close biological connection between most of differentially expressed genes into Ingenuity Pathway Analysis networks further indicated consistency between the genes that were differentially-expressed between resistant and susceptible animals. Gene profiling in high and low SCS sheep provided strong candidates for biological pathway and gene underlying genetically determined resistance and susceptibility towards Staphylococci infections opening new fields for further investigation. Keywords: Staphylococcus epidermidis, Staphylococcus aureus, milk somatic cells, mammalian, transcriptome, immunity, mastitis

Project description:The counts of total white blood cells (WBCs) and WBC subsets are well-established diagnostic factors for various diseases. It has been shown that variations in WBC counts are significantly controlled by individuals’ genetics in swine. However, despite detection of quantitative trait loci (QTLs) for these phenotypes, little is known on the molecular basis underlying their variations. Our aim was to study gene profiling variations according to variations in WBC counts and to connect results with available QTL mapping. Whole blood transcriptome of animals contrasted for levels of WBC counts were compared. A pig generic microarray enriched in immunity-related genes was used. 378 probes representing 334 genes were found significantly differentially expressed between high- and low-count WBC groups. 65 genes were associated with hematological system development and function. 336 probes could be mapped on all autosomes and the X chromosome, and 59 transcripts fell within 28 QTLs reported to affect the counts of WBC and WBC subsets. By combining probe mapping results and biological functions, 6 genes (CDKN2A, TCIRG1, SIPA1, RGL2, FLT1 and CFLAR) were found as putative relevant positional candidate genes for the WBC traits. Genetic linkage experiments are warranted to validate these candidate genes, and further investigating a possible pleiotropic effect of these genes could contribute to elucidate molecular mechanisms involved in WBC development. differentially expressed genes or transccripts between high- and low-count white blood cells groups The dual channel microarray experiments were carried out using a common reference hybridization design. In this study the reference RNA sample was prepared by pooling of total RNAs from different porcine tissues. The test samples were RNA samples isolated from total porcine blood. According to the total white blood cells count, 18 animals were selected from the edges of the distribution, named high-count group (HC, 9 animals) and low-count group (LC, 9 animals).

Dataset Information

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets