.1. Enrichment Index-based Proteomics Data Analysis Method Secretion Proteome - The Dynamic Process Of Change Of Murine Dendritic Sarcoma Cells Secrete The Protein Group. Normal Urinary Proteome Stable Expression Of The Protein Group As A Potential Biomar

Secretory proteins are important for organisms to maintain the normal biological processes. They are important sources for discovering the candidate tumour biomarkers with clinical significance. However, secretory protein samples are usually polluted by cytosolic proteins from dead cells or other proteins from the environment.We propose that a good secretory protein sample should be enriched with known secretory proteins, and a secretory protein should be enriched in the secretory protein sample compare to soluble cell lysate. A method based on enrichment index for both quality control of the sample and identification of secretory proteins was developed. Positive identifications of the proteins were subjected to quantification by spectral count. Enrichment index of the sample (EIS) and the enrichment index for protein (EIP) were set up by comparing proteins identified from secretory protein sample and soluble cell lysate sample. The quality of secretory protein sample can be evaluated with EIS. EIP was used to identify the secretory proteins.This method can identify novel secretory proteins from unconventional pathways. It can also exclude the contaminating proteins with signal peptide from dead cells. The method is simple to perform. No complicated procedures were used other than common LC-MS/MS. There was no isotopes pollution in whole operation.We analyzed the secretory proteins of mouse dendritic cell sarcoma (DCS) cell line cultured in protein-free media with insulin. The sample's EISs were 75.4 and 84.65. 141 proteins were detected, of which 73 proteins were significantly enriched and identified as secretory proteins in this study. In these 73 proteins, 33 proteins were both swiss-prot annotated and signal peptide predicted as secretory proteins. 10 proteins were identified by either signal peptide prediction or swiss-prot annotation, 30 proteins were previously unidentified as secretory proteins.The 30 novel potential secretory proteins were analyzed by SecretomeP server and ProP server which can predict the mammalian secretory protein targeted to the non-classical secretory pathway. 11 (36.7%) and 15 (50%) were predicted as secretory proteins by SecretomeP and ProP, respectively. 5 proteins were positive by both methods. Compared with the protein component of exosome in other studies, 11 proteins were in exosome in other studies. Six proteins were found in exosome from mice dendritic cells line DC1. These references provided supporting evidences for these 30 proteins as secretory proteins. Human urinary proteome analysis was a convenient approach to clarify the disease processes affecting the kidney and the urogenital tract. Many potential biomarkers have been identified by differential urinary proteome analyses. However, the urinary proteome variation has not been very well studied; it is hard to conclude whether those potential biomarkers come from differences of biological states studied or just from normal proteome variation.In this paper 1DLC/MS and spectral count as the semi-quantitative analysis were used to study human urinary proteome variation by pooled and individual urine samples. Five types of pooled urinary samples (first morning void, second morning void, excessive water drinking void, random void and 24 hour void) collected in one day from six volunteers (three males and three females) were used to analyze the urinary proteome overall intra-day variations. Six pair first morning urine collected on day 0 and day 7 from above six volunteers were utilized to study inter-day, inter-individual and inter-gender variations. We also discussed the advantages and disadvantages of pooling the samples.The intra-day, inter-day, inter-individual, inter-gender variation results showed 50% of proteins were found in various samples and more than 40% of these proteins whose spectral count variation was less than two times. Based on the proteomics data of urine from six volunteers, the intra-day variation is less than the inter-individual variation. Inter-gender stability is the worst. Some of them have been reported as potential disease biomarkers. The data presented herein should provide a pool of stable urinary proteins at different conditions. Any significant qualitative and quantitative changes of those stable proteins may have greater chances to serve as potential urinary biomarkers.