Dataset Information

Quantitative proteomics by SWATH-MS reveals altered expression of nucleic acid binding and regulatory proteins in HIV-1-infected macrophages.

ABSTRACT: Human immunodeficiency virus type 1 (HIV-1) infection remains a worldwide epidemic, and innovative therapies to combat the virus are needed. Developing a host-oriented antiviral strategy capable of targeting the biomolecules that are directly or indirectly required for viral replication may provide advantages over traditional virus-centric approaches. We used quantitative proteomics by SWATH-MS in conjunction with bioinformatic analyses to identify host proteins, with an emphasis on nucleic acid binding and regulatory proteins, which could serve as candidates in the development of host-oriented antiretroviral strategies. Using SWATH-MS, we identified and quantified the expression of 3608 proteins in uninfected and HIV-1-infected monocyte-derived macrophages. Of these 3608 proteins, 420 were significantly altered upon HIV-1 infection. Bioinformatic analyses revealed functional enrichment for RNA binding and processing as well as transcription regulation. Our findings highlight a novel subset of proteins and processes that are involved in the host response to HIV-1 infection. In addition, we provide an original and transparent methodology for the analysis of label-free quantitative proteomics data generated by SWATH-MS that can be readily adapted to other biological systems.

SUBMITTER: Haverland NA

PROVIDER: S-EPMC3993959 | biostudies-literature | 2014 Apr

REPOSITORIES: biostudies-literature

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Quantitative proteomics by SWATH-MS reveals altered expression of nucleic acid binding and regulatory proteins in HIV-1-infected macrophages.

Haverland Nicole A NA Fox Howard S HS Ciborowski Pawel P

Journal of proteome research 20140310 4

Human immunodeficiency virus type 1 (HIV-1) infection remains a worldwide epidemic, and innovative therapies to combat the virus are needed. Developing a host-oriented antiviral strategy capable of targeting the biomolecules that are directly or indirectly required for viral replication may provide advantages over traditional virus-centric approaches. We used quantitative proteomics by SWATH-MS in conjunction with bioinformatic analyses to identify host proteins, with an emphasis on nucleic acid ...[more]

PMID: 24564501

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Project description:BACKGROUND:SWATH-MS has emerged as the strategy of choice for biomarker discovery due to the proteome coverage achieved in acquisition and provision to re-interrogate the data. However, in quantitative analysis using SWATH, each sample from the comparison group is run individually in mass spectrometer and the resulting inter-run variation may influence relative quantification and identification of biomarkers. Normalization of data to diminish this variation thereby becomes an essential step in SWATH data processing. In most reported studies, data normalization methods used are those provided in instrument-based data analysis software or those used for microarray data. This study, for the first time provides an experimental evidence for selection of normalization method optimal for biomarker identification. METHODS:The efficiency of 12 normalization methods to normalize SWATH-MS data was evaluated based on statistical criteria in 'Normalyzer'-a tool which provides comparative evaluation of normalization by different methods. Further, the suitability of normalized data for biomarker discovery was assessed by evaluating the clustering efficiency of differentiators, identified from the normalized data based on p-value, fold change and both, by hierarchical clustering in Genesis software v.1.8.1. RESULTS:Conventional statistical criteria identified VSN-G as the optimal method for normalization of SWATH data. However, differentiators identified from VSN-G normalized data failed to segregate test and control groups. We thus assessed data normalized by eleven other methods for their ability to yield differentiators which segregate the study groups. Datasets in our study demonstrated that differentiators identified based on p-value from data normalized with Loess-R stratified the study groups optimally. CONCLUSION:This is the first report of experimentally tested strategy for SWATH-MS data processing with an emphasis on identification of clinically relevant biomarkers. Normalization of SWATH-MS data by Loess-R method and identification of differentiators based on p-value were found to be optimal for biomarker discovery in this study. The study also demonstrates the need to base the choice of normalization method on the application of the data.

Dataset Information

Quantitative proteomics by SWATH-MS reveals altered expression of nucleic acid binding and regulatory proteins in HIV-1-infected macrophages.

Publications

Quantitative proteomics by SWATH-MS reveals altered expression of nucleic acid binding and regulatory proteins in HIV-1-infected macrophages.

Similar Datasets

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