Unknown,Transcriptomics,Genomics,Proteomics

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Transcription profiling of human breast cancer-derived OCUB-M cells transfected with expression vector encoding IGF1R

ABSTRACT: To identify genes that influence resistance to mastitis, we scanned; a whole genome of 181 susceptible and 297 resistant cows and revealed; significant linkage to Bos taurus autosomal chromosome (BTA) 21 with a; likelihood of odds (LOD) score of 28. Because FEZL is a transcription factor that influences resistance to mastitis, we compared LOD scores of BTA21 among cows carrying 12G/12G, 12G/13G, and 12G/13GFEZL to evaluate whether FEZL affects linkage in this chromosome. Cows carrying 13G/13GFEZL had the most significant linkage with a LOD score of 35, despite a decrease in the number of samples from 478 to 224. This finding suggested that the gene influencing resistance to mastitis on BTA21 might be controlled by FEZL. To investigate genes that might influence resistance to mastitis through FEZL, we screened human breast cancer-derived OCUB-M cells transfected with expression vector encoding 12GFEZL using microarray analysis. Experiment Overall Design: OCUBM cells were transfected with/without 12G FEZL for RNA extraction and hybridization on Affymetrix microarrays.

ORGANISM(S): Homo sapiens

SUBMITTER: Mayumi Sugimoto

PROVIDER: E-GEOD-5224 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Project description:Bovine mastitis, the infection of the mammary gland which leads to great health and economic challenges for dairy farmers is accompanied by dramatic changes in the milk proteome. In this study of naturally occurring mastitis not only have the changes in the milk proteome been quantified in subclinical and clinical mastitis but simultaneous changes in the serum proteome have also been characterised and quantified. Milk and serum samples from healthy dairy cows (n=12) were compared to those of cows with subclinical (n=10) and clinical mastitis (n=112) using TMT label-based proteomic approach. The study included the milk and serum samples taken from thirty-two dairy cows ( kept on private farms located in Croatia. All cows were checked by physical examination. Somatic cells count (SCC) and mastitis test in milk samples were performed. According to the results, cows were assigned into three groups: Group I (control, n=10) consisted of healthy cows with SCC below 400,000 cells/ml on the monthly check-up and a negative mastitis test and without any clinical sign of mastitis. Group II (subclinical mastitis, n=12) comprised cows without clinical signs of mastitis but with SCC above 400,000 cells/ml on the monthly basis and a positive mastitis test at the time of sampling. Group III (clinical mastitis, n=10) consisted of cows with clinical signs of mastitis which include changes in milk appearance (flakes and clots in milk), different stages of udder inflammation (hyperemia, edema, pain, udder enlargement and elevated udder temperature) and disturbance of general health (depression, relaxed cold ears, dehydration, elevated body temperature, increased heart and respiratory rate, decreased ruminal contraction and decreased appetite). Blood samples were taken from v. coccygea and centrifuged at 3000 g for 15 min after clotting for two hours at room temperature. Serum samples were stored at -80°C until analysis. Milk samples were taken aseptically before the morning milking. First few streams were discarded. Teat ends were disinfected with cotton swabs soaked with 70% ethanol. Samples were taken into sterile tubes and transported to laboratory on ice within a few hours.

Project description:Mastitis is a very costly and common disease in the dairy industry. The study of the transcriptome from healthy and mastitic milk somatic cell samples using RNA-Sequencing technology (RNA-Seq) can provide measurements of transcript levels associated with the immune response to the infection. The objective of this study was to characterize the Holstein milk somatic cells transcriptome from 6 cows to determine host response to intramammary infections. RNA-Sequencing was performed on two samples from each cow from two separate quarters, one classified as healthy (n = 6) and one as mastitic (n = 6). In total, 449 genes were differentially expressed between the healthy and mastitic quarters (P-value < 0.01, FDR < 0.05, FC > ±2). Among the differentially expressed genes, the most expressed genes based on Reads Per Kilo base per Million mapped reads (RPKM) in the healthy group were associated with milk components (CSN2 and CSN3), and in the mastitic group they were associated with immunity (B2M and CD74). In-silico functional analysis was performed using the list of 449 differentially expressed genes, which identified 36 significantly enriched metabolic pathways (FDR < 0.01), some of which were associated with the immune system, such as cytokine-cytokine interaction and cell adhesion molecules. Seven functional candidate genes were selected, based on the criteria of being highly expressed and present in significant pathways that are relevant to the inflammatory process (GLYCAM1, B2M, CD74, BoLA DR-Alpha, FCER1G, SDS and NFKBIA). Lastly, we identified the differentially expressed genes that are located in QTL regions previously known to be associated with mastitis, specifically clinical mastitis, somatic cell count and somatic cell score. It was concluded that there are multiple genes within QTL regions that could potentially impact host response to mastitis causing agents, making some cows more susceptible to intramammary infections. The identification of key genes with functional, statistical, biological and positional relevance associated with host defense to infection, will contribute to a better understanding of the underlying genetic architecture associated with mastitis. This in turn will improve the sustainability of agricultural practices, by facilitating the selection of cows with improved host defense leading to increased resistance to mastitis.

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Transcription profiling of human breast cancer-derived OCUB-M cells transfected with expression vector encoding IGF1R

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