Dataset Information

Sus scrofa (pig) small intestinal mucosa LC-MS/MS

ABSTRACT: In this study, we applied the isobaric tags for relative and absolute quantitation (iTRAQ) technique to detect alterations in the proteomic profile of the jejunal mucosa using a porcine model in which piglets were offered the protein-limited (PL) diet. Protein identification and quantification for iTRAQ experiments were performed using ProteinPilot (v4.0.8085) software. The LC-MS/MS data were searched against the UniProtKB (sus scrofa). To minimize the false discovery rate (FDR), a threshold for protein identification was applied, with the confident value > 95% (amount to the confident value “unused ProtScore” > 1.3 in ProteinPilot software), and at least one unique peptide was considered for protein identification. Proteins that were quantified with fold change > 2.0 were considered to be differentially expressed proteins. We identified 5275 proteins, 202 of which were differentially expressed. Furthermore, we adopted function annotation analysis of all identified proteins and function enrichment analysis of all differentially expressed proteins to explore more meaningful proteins and pathways.

INSTRUMENT(S): TripleTOF 5600

ORGANISM(S): Sus Scrofa Domesticus (domestic Pig)

TISSUE(S): Jejunal Mucosa

SUBMITTER: Jingdong Yin

LAB HEAD: Jingdong Yin, State Key Lab of Animal Nutrition, College of Animal Science and Technology, China Agricultural University

PROVIDER: PXD004069 | Pride | 2016-12-22

REPOSITORIES: Pride

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Publications

A proteomic adaptation of small intestinal mucosa in response to dietary protein limitation.

Qin Chunfu C Qiu Kai K Sun Wenjuan W Jiao Ning N Zhang Xin X Che Lianqiang L Zhao Haiyi H Shen Hexiao H Yin Jingdong J

Scientific reports 20161114

Dietary protein limitation (PL) is not only beneficial to human health but also applied to minimize nitrogen excretion in livestock production. However, the impact of PL on intestinal physiology is largely unknown. In this study, we identified 5275 quantitative proteins using a porcine model in which pigs suffered PL. A total of 202 proteins |log<sub>2</sub> fold-change| > 1 were taken as differentially expressed proteins and subjected to functional and pathway enrichment analysis to reveal prot ...[more]

PMID: 27841298

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Project description:Background: Results obtained from our previous study using a label-free quantitation (LF) proteomic approach in which dynamic range compression was used to profile lower abundance proteins, demonstrated few proteins that were differentially abundant within the synovial fluid (SF) when comparing Autologous Chondrocyte Implantation (ACI) responders and non-responders at baseline (1). This study builds upon our previous findings by assessing higher abundance proteins within these SFs; providing a more global proteome analysis from which we can understand more fully the biology underlying ACI success or failure. Methods: Isobaric tagging for relative and absolute quantitation (iTRAQ) proteomics was used to assess SFs from ACI responders (mean Lysholm improvement of 33; n=14) and non-responders (mean Lysholm decrease of 14; n=13) at the two stages of surgery (cartilage harvest and chondrocyte implantation). Differentially abundant proteins were investigated using pathway analyses and the iTRAQ proteomic dataset was combined with our published proteomic dataset of dynamically compressed SFs, from which an interactome network model of systemic protein interactions was generated. Results: iTRAQ proteomics has confirmed our previous finding that there is a marked proteome shift in response to cartilage harvest (70 and 54 proteins demonstrating ≥2.0 fold change between Stages I and II in responders and non-responders, respectively) and has highlighted 28 proteins that were differentially abundant between responders and non-responders to ACI, that were not found in the LF study; 16 of which were altered at baseline. Two protein abundance changes (Complement C1S subcomponent and Matrix metalloproteinase 3 (MMP3), have been biochemically validated. Combination of the iTRAQ and LF proteomic datasets has generated in-depth SF proteome information that has been used to generate interactome networks representing ACI success or failure, from which functional pathways that are dysregulated in ACI non-responders have been identified. Conclusions: Several candidate biomarkers for baseline prediction of ACI outcome have been identified. A holistic overview of the SF proteome in responders and non-responders to ACI has been profiled providing a better understanding of the biological pathways underlying clinical outcome, particularly the differential response to cartilage harvest in non-responders.

Project description:The recent development within high-throughput technologies for expression profiling has allowed for parallel analysis of transcriptomes and proteomes in biological systems such as comparative analysis of transcript and protein levels of tissue regulated genes. Until now, such studies of have only included microarray or short length sequence tags for transcript profiling. Furthermore, most comparisons of transcript and protein levels have been based on absolute expression values from within the same tissue and not relative expression values based on tissue ratios. Presented here is a novel study of two porcine tissues based on integrative analysis of data from expression profiling of identical samples using cDNA microarray, 454-sequencing and iTRAQ-based proteomics. Sequence homology identified 2.541 unique transcripts that are detectable by both microarray hybridizations and 454-sequencing of 1.2 million cDNA tags. Both transcript-based technologies showed high reproducibility between sample replicates of the same tissue, but the correlation across these two technologies was modest. Thousands of genes being differentially expressed were identified with microarray. Out of the 306 differentially expressed genes, identified by 454-sequencing, 198 (65 %) were also found by microarray. The relationship between the regulation of transcript and protein levels was analyzed by integrating iTRAQ-based proteomics data. Protein expression ratios were determined for 354 genes, of which 148 could be mapped to both microarray and 454-sequencing data. A comparison of the expression ratios from the three technologies revealed that differences in transcript and protein levels across heart and muscle tissues are positively correlated. We show that the reproducibility within cDNA microarray and 454-sequencing is high, but that the agreement across these two technologies is modest. We demonstrate that the regulation of transcript and protein levels across identical tissue samples is positively correlated when the tissue expression ratios are used for comparison. The results presented are of interest in systems biology research in terms of integration and analysis of high-throughput expression data from mammalian tissues. Keywords: tissue comparison, platform comparison Tissue samples of heart (HEA) and Longissimus dorsi (LDO) were prepared by pooling from five healthy Hampshire gilts at age four to six months and division into six sub-samples, three for each tissue named HEA1, HEA2, HEA3, LDO1, LDO2 and LDO3. The exact same six tissue samples were used for subsequent expression profiling with cDNA microarray, 454-sequencing and iTRAQ-based proteomics. A reference sample for the cDNA microarray experiment and iTRAQ-based proteomics was constructed by combining the six samples. In the microarray experiment, three cDNA microarray slides were used per sample.

Dataset Information

Sus scrofa (pig) small intestinal mucosa LC-MS/MS

Publications

A proteomic adaptation of small intestinal mucosa in response to dietary protein limitation.

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