Proteomic Analysis Of Differential Expression Research Articles

Proteomic analysis of differential expression of lung proteins in response to highly pathogenic avian influenza virus infection in chickens

Elucidation of the molecular pathogenesis underlying virus-host interactions is important for the development of new diagnostic and therapeutic strategies against highly pathogenic avian influenza (HPAI) virus infection in chickens. However, the pathogenesis of HPAI virus in chickens is not completely understood. To identify the intracellular signaling pathways and critical host proteins associated with influenza pathogenesis, we analyzed the lung proteome of a chicken infected with HPAI H5N1 virus (A/duck/India/02CA10/2011/Agartala). Mass spectrometry data sets were searched against the chicken UniProt reference database. At the local false discovery rate level of 5%, a total of 3313 proteins with the presence of at least one unique peptide were identified in the chicken lung proteome datasets. Differential expression analysis of these proteins showed that 247 and 1754 proteins were downregulated at 12 h and 48 h postinfection, respectively. We observed expression of proteins of the predominant signaling pathways, including Toll-like receptors (TLRs), retinoic acid-inducible gene I-like receptors (RLRs), NOD-like receptors (NLRs), and JAK-STAT signaling. Activation of these pathways is associated with the cytokine storm effect and thus may be the cause of the severity of HPAI H5N1 infection in chickens. We also observed the expression of myeloid differentiation primary response protein (MyD88), inhibitor of nuclear factor kappa B kinase subunit beta (IKBKB), interleukin 1 receptor associated kinase 4 (IRAK4), RELA proto-oncogene NF-κB subunit (RELA), and mitochondrial antiviral signaling protein (MAVS), which are involved in critical signaling pathways, as well as other, less-commonly identified proteins such as hepatocyte nuclear factor 4 alpha (HNF4A), ELAV-like RNA binding protein 1 (ELAVL1), fibronectin 1 (FN1), COP9 signalosome subunit 5 (COPS5), cullin 1 (CUL1), breast cancer type 1 susceptibility protein (BRCA1), and the FYN proto-oncogene Src family tyrosine kinase (FYN) as main hub proteins that might play important roles in influenza pathogenesis in chickens. In summary, we identified the signaling pathways and the proteomic determinants associated with disease pathogenesis in chickens infected with HPAI H5N1 virus.

Proteomic Analysis of Differential Expression of Cellular Proteins in Response to Avian H9N2 Virus Infection of A549 Cells.

In this study, differentially expressed proteins in A549 cells (human lung adenocarcinoma epithelial cell line) infected with H9N2 avian influenza virus (AIV) were investigated by two-dimensional electrophoresis (2-DE). Sixteen different spots between the groups (ratio > 2, p < 0.05) were identified with mass spectrometry identification. Proteins located in the downstream of the NF-κB and IFN transcription factor pathways were identified, e.g., ISG15. Actin and keratin were also identified, suggesting that the cytoskeleton may plays an important role in the AIV infection of mammalian cells. These findings could provide insights into the interaction between host and influenza viruses and might provide valuable information for clarifying the pathogenesis of viral infections as well.

Statistical Analysis of the Experimental Variation in the Proteomic Characterization of Human Plasma by Two-Dimensional Difference Gel Electrophoresis

The complexity of human plasma presents a number of challenges to the efficient and reproducible proteomic analysis of differential expression in response to disease. Before individual variation and disease-specific protein biomarkers can be identified from human plasma, the experimental variability inherent in the protein separation and detection techniques must be quantified. We report on the variation found in two-dimensional difference gel electrophoresis (2-D DIGE) analysis of human plasma. Eight aliquots of a human plasma sample were subjected to top-6 highest abundant protein depletion and were subsequently analyzed in triplicate for a total of 24 DIGE samples on 12 gels. Spot-wise standard deviation estimates indicated that fold changes greater than 2 can be detected with a manageable number of replicates in simple ANOVA experiments with human plasma. Mixed-effects statistical modeling quantified the effect of the dyes, and segregated the spot-wise variance into components of sample preparation, gel-to-gel differences, and random error. The gel-to-gel component was found to be the largest source of variation, followed by the sample preparation step. An improved protocol for the depletion of the top-6 high-abundance proteins is suggested, which, along with the use of statistical modeling and future improvements in gel quality and image processing, can further reduce the variation and increase the efficiency of 2-D DIGE proteomic analysis of human plasma.