Project description:High-temperature stress is a critical environmental parameter for all organisms and induces a cellular heat shock response, characterized by an upregulation of heat shock proteins. For Crenarchaeota, it is unknown how this response is regulated, given the lack of conservation of known prokaryotic or eukaryotic heat shock-regulating transcription factors and how cellular processes are affected. To this end, we studied the heat shock response of the thermoacidophilic Sulfolobus acidocaldarius, thriving in volcanic hot springs at 75°C, upon shift to 86°C, at the transcriptome and proteome level. By pulse-labeling of neosynthesized RNA and proteins upon heat shock, we show a drastic reduction of the cell’s major transcriptional activity immediately after shift and neosynthesis of certain abundant (heat shock) proteins, including the thermosome. By combining RNA-sequencing and mass spectrometry, we show that RNA levels of half of the genes are affected immediately after temperature shift and that reprogramming of the protein landscape takes at least one hour and changes are more subtle. Correlation analysis provides evidence that considerable post-transcriptional and post-translational regulation is occurring upon heat shock. Functional enrichment analysis indicates that nearly all biological processes are affected by heat shock. An overall downregulation is observed for transcription, translation, DNA replication and cell division. However, quality control of translation and of the protein landscape is increased. Many DNA repair pathways are differentially expressed, accompanied with an increase in a DNA import system. Furthermore, expression of DNA topoisomerases is investigated, coinciding with a significant differential expression of nucleoid-associated proteins. Based on these findings and considering the absence of a conserved DNA-binding motif, we propose that regulation of the heat shock response in Sulfolobales is most likely not established by a classical transcription factor, but is rather caused by changes in chromosome organization or established at the post-transcriptional level.

Project description:The presence of variability in the response of pigs to Porcine Reproductive and Respiratory Syndrome virus (PRRSv) infection, and recent demonstration of significant genetic control of such responses, leads us to believe that selection towards more disease resistant pigs could be a valid strategy to reduce its economic impact on the swine industry. To find underlying molecular differences in PRRS susceptible versus more resistant pigs, 100 animals with extremely different growth rates and viremia levels after PRRSv infection were selected from a total of 600 infected pigs. A microarray experiment was conducted on whole blood RNA samples taken at 0, 4 and 7 days post infection (dpi) from these pigs. From these data, we examined associations of gene expression with weight gain and viral load phenotypes. The single nucleotide polymorphism (SNP) marker WUR10000125 (WUR) on the porcine 60K SNP chip was shown to be associated with viral load and weight gain after PRRSv infection, and so, additionally, the effect of the WUR10000125 (WUR) genotype was examined. Limited information was obtained through linear modeling of blood gene differential expression (DE) that contrasted pigs with extreme phenotypes, for growth or viral load or between animals with different WUR genotype. However, using network-based approaches, molecular pathway differences between extreme phenotypic classes could be identified. Several gene clusters of interest were found when Weighted Gene Co-expression Network Analysis (WGCNA) was applied to 4dpi contrasted with 0dpi data. The expression pattern of one such cluster of genes correlated with weight gain and WUR genotype, contained numerous immune response genes such as cytokines, chemokines, interferon type I stimulated genes, apoptotic genes and genes regulating complement activation. In addition, Partial Correlation and Information Theory (PCIT) identified differentially hubbed (DH) genes between the phenotypically divergent groups. GO enrichment revealed that the target genes of these DH genes are enriched in adaptive immune pathways. There are molecular differences in blood RNA patterns between pigs with extreme phenotypes or with a different WUR genotype in early responses to PRRSv infection, though they can be quite subtle and more difficult to discover with conventional DE expression analyses. Co-expression analyses such as WGCNA and PCIT can be used to reveal network differences between such extreme response groups. three timepoints from 100 animals are hibridized following a blocked reference design; Blood gene expression of pigs 4 days post infection

Project description:The presence of variability in the response of pigs to Porcine Reproductive and Respiratory Syndrome virus (PRRSv) infection, and recent demonstration of significant genetic control of such responses, leads us to believe that selection towards more disease resistant pigs could be a valid strategy to reduce its economic impact on the swine industry. To find underlying molecular differences in PRRS susceptible versus more resistant pigs, 100 animals with extremely different growth rates and viremia levels after PRRSv infection were selected from a total of 600 infected pigs. A microarray experiment was conducted on whole blood RNA samples taken at 0, 4 and 7 days post infection (dpi) from these pigs. From these data, we examined associations of gene expression with weight gain and viral load phenotypes. The single nucleotide polymorphism (SNP) marker WUR10000125 (WUR) on the porcine 60K SNP chip was shown to be associated with viral load and weight gain after PRRSv infection, and so, additionally, the effect of the WUR10000125 (WUR) genotype was examined. Limited information was obtained through linear modeling of blood gene differential expression (DE) that contrasted pigs with extreme phenotypes, for growth or viral load or between animals with different WUR genotype. However, using network-based approaches, molecular pathway differences between extreme phenotypic classes could be identified. Several gene clusters of interest were found when Weighted Gene Co-expression Network Analysis (WGCNA) was applied to 4dpi contrasted with 0dpi data. The expression pattern of one such cluster of genes correlated with weight gain and WUR genotype, contained numerous immune response genes such as cytokines, chemokines, interferon type I stimulated genes, apoptotic genes and genes regulating complement activation. In addition, Partial Correlation and Information Theory (PCIT) identified differentially hubbed (DH) genes between the phenotypically divergent groups. GO enrichment revealed that the target genes of these DH genes are enriched in adaptive immune pathways. There are molecular differences in blood RNA patterns between pigs with extreme phenotypes or with a different WUR genotype in early responses to PRRSv infection, though they can be quite subtle and more difficult to discover with conventional DE expression analyses. Co-expression analyses such as WGCNA and PCIT can be used to reveal network differences between such extreme response groups. three timepoints from 100 animals are hibridized following a blocked reference design; Blood gene expression of pigs 7 days post infection

			Action	DRS
	MP02T1_1.raw	Raw
	MP02T1_2.raw	Raw
	MP02T2_1.raw	Raw
	MP02T2_2.raw	Raw
	MP02T3_1.raw	Raw

Dataset Information

Peptidomic Analysis of Hemorrhagic Shock Pig Plasma

Dataset's files

Publications

High-Resolution Mass Spectrometry-Based Approaches for the Detection and Quantification of Peptidase Activity in Plasma.

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