Dataset Information

HyperQuant-A Computational Pipeline for Higher Order Multiplexed Quantitative Proteomics.

ABSTRACT: Quantitative proteomics has evolved considerably over the last decade with the advent of higher order multiplexing (HOM) techniques. With the development of methods such as-multitagging, cPILOT, hyperplexing, BONPlex, and MITNCAT, the HOM technique is rapidly taking the center stage in multiplexed quantitative proteomics. These studies combined MS1 and MS2 labels in a single experiment enabling higher sample throughput. While HOM is highly promising, the computational analysis is still a big challenge, as the available tools cannot harness its power completely. We have developed a new quantitative pipeline, HyperQuant to aid in accurately quantitating complex HOM data. The pipeline uses identification results from either MaxQuant or any other search engine and quantitation results from QuantWizIQ. The Mapper and Combiner modules of HyperQuant allow facile integration of the labeled data, along with peptide spectrum match (PSM) intensity/ratio integration for proteins, respectively, for each PSM label combination. This also includes appropriate combination of replicates/fractions before summarizing the protein intensity/ratio, leading to robust quantitation. To the best of our knowledge, this is the first tool for the quantitation of HOM data with flexibility for any combination of MS1 and MS2 labels. We demonstrate its utility in analyzing two 18-plex data sets from the hyperplexing and the BONplex studies. The tool is open source and freely available for noncommercial use. HyperQuant is a highly valuable tool that will help in advancing the field of multiplexed quantitative proteomics.

SUBMITTER: Aggarwal S

PROVIDER: S-EPMC7240821 | biostudies-literature | 2020 May

REPOSITORIES: biostudies-literature

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HyperQuant-A Computational Pipeline for Higher Order Multiplexed Quantitative Proteomics.

Aggarwal Suruchi S Kumar Ajay A Jamwal Shilpa S Midha Mukul Kumar MK Talukdar Narayan Chandra NC Yadav Amit Kumar AK

ACS omega 20200507 19

Quantitative proteomics has evolved considerably over the last decade with the advent of higher order multiplexing (HOM) techniques. With the development of methods such as-multitagging, cPILOT, hyperplexing, BONPlex, and MITNCAT, the HOM technique is rapidly taking the center stage in multiplexed quantitative proteomics. These studies combined MS<sup>1</sup> and MS<sup>2</sup> labels in a single experiment enabling higher sample throughput. While HOM is highly promising, the computational analy ...[more]

PMID: 32455206

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Project description:Protein localization is paramount to protein function, and the intracellular movement of proteins underlies the regulation of numerous cellular processes. Given advances in spatial proteomics, the investigation of protein localization at a global scale has become attainable. Also becoming apparent is the need for dedicated analytical frameworks that allow the discovery of global intracellular protein movement events. Here, we describe TRANSPIRE, a computational pipeline that facilitates TRanslocation ANalysis of SPatIal pRotEomics data sets. TRANSPIRE leverages synthetic translocation profiles generated from organelle marker proteins to train a probabilistic Gaussian process classifier that predicts changes in protein distribution. This output is then integrated with information regarding co-translocating proteins and complexes and enriched gene ontology associations to discern the putative regulation and function of movement. We validate TRANSPIRE performance for predicting nuclear-cytoplasmic shuttling events. Analyzing an existing data set of nuclear and cytoplasmic proteomes during Kaposi Sarcoma-associated herpesvirus (KSHV)-induced cellular mRNA decay, we confirm that TRANSPIRE readily discerns expected translocations of RNA binding proteins. We next investigate protein translocations during infection with human cytomegalovirus (HCMV), a ?-herpesvirus known to induce global organelle remodeling. We find that HCMV infection induces broad changes in protein localization, with over 800 proteins predicted to translocate during virus replication. Evident are protein movements related to HCMV modulation of host defense, metabolism, cellular trafficking, and Wnt signaling. For example, the low-density lipoprotein receptor (LDLR) translocates to the lysosome early in infection in conjunction with its degradation, which we validate by targeted mass spectrometry. Using microscopy, we also validate the translocation of the multifunctional kinase DAPK3, a movement that may contribute to HCMV activation of Wnt signaling.

Dataset Information

HyperQuant-A Computational Pipeline for Higher Order Multiplexed Quantitative Proteomics.

Publications

HyperQuant-A Computational Pipeline for Higher Order Multiplexed Quantitative Proteomics.

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