Dataset Information

PINE: An Automation Tool to Extract & Visualize Functionally Enriched Networks from Mass Spectrometry-Based Proteomics Datasets

ABSTRACT: Recent surges in mass spectrometry-based proteomics studies demands a concurrent rise in speedy and optimized data processing tools and pipelines. While several stand-alone databases exist that store gene interaction and annotation information, we developed Protein Interaction Network Extractor (PINE) as a fully-automated, user-friendly, graphical interface-based bioinformatics tool that has an easily adoptable framework suitable for study of all proteins and post-translational modifications (PTMs) sites enabling simple, quick and robust visualization of differentially expressed proteins or PTMs and their interaction or functionally enriched networks. PINE tool can be applied not only to better understand protein functional interaction networks but also to analyze PTMs involved and their effect. To illustrate the relevance of the tool, we explore the total proteome and its PTM -associated relationships in two different nonalcoholic steatohepatitis (NASH) mouse models to show different context-specific use cases. The strength of this tool relies in its ability to (1) perform accurate protein identifier mapping to resolve any ambiguity, (2) retrieve interaction data from multiple publicly available protein-protein interaction databases, (3) assimilate these complex networks into meaningful functionally enriched pathways. Ultimately this tool can be used as an extremely powerful approach for novel hypothesis generation towards understanding disease mechanisms and potential therapeutics.

ORGANISM(S): Mus Musculus

SUBMITTER: Vidya Venkatraman

PROVIDER: PXD017324 | panorama | Tue Feb 23 00:00:00 GMT 2021

REPOSITORIES: PanoramaPublic

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Publications

PINE: An Automation Tool to Extract and Visualize Protein-Centric Functional Networks.

Sundararaman Niveda N Go James J Robinson Aaron E AE Mato José M JM Lu Shelly C SC Van Eyk Jennifer E JE Venkatraman Vidya V

Journal of the American Society for Mass Spectrometry 20200611 7

Recent surges in mass spectrometry-based proteomics studies demand a concurrent rise in speedy and optimized data processing tools and pipelines. Although several stand-alone bioinformatics tools exist that provide protein-protein interaction (PPI) data, we developed Protein Interaction Network Extractor (PINE) as a fully automated, user-friendly, graphical user interface application for visualization and exploration of global proteome and post-translational modification (PTM) based networks. PI ...[more]

PMID: 32463229

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Project description:Background: Tuberculosis (TB), caused by Mycobacterium TB (MTB), remains a significant global health issue, particularly in developing nations. MicroRNAs (miRNAs) are non-coding RNAs (ncRNAs) that modulate immune responses and play a pivotal role in the pathogenesis of MTB by altering host immune defenses. Insights into the regulatory functions of these miRNAs have revealed mechanisms through which MTB evades immune surveillance and establishes persistent infections, highlighting the critical role of miRNA networks in TB pathogenesis. Objective: The purpose of this study was to analyze miRNA expression in plasma from TB patients, to predict target genes, and to construct regulatory networks to elucidate the roles of miRNAs in TB pathogenesis. Methods: This study recruited six participants, comprising three patients with active TB and three healthy controls (HCs). High-throughput sequencing was employed to profile miRNAs. Differentially expressed miRNAs (DEMs) were identified, and their target genes were predicted using the TargetScan and miRWalk databases. The Gene Ontology (GO) and KEGG databases facilitated the construction of regulatory pathway networks. Additionally, the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) analyzed protein-protein interaction (PPI) networks for genes enriched in immune-related pathways, highlighting key genes. Results: The study identified 23 DEMs, with 17 upregulated and 6 downregulated. PRKCB was recognized as a potential diagnostic target. Analyses using GO and KEGG identified pivotal pathways implicated in TB pathogenesis, particularly involving miRNAs hsa-let-7a-5p and NovelmiRNA-41 in the PRKCB-related regulatory network. Conclusion: We identified 23 DEMs and a key gene, PRKCB, associated with TB pathogenesis. The MAPK and chemokine pathways were identified as central to the regulatory mechanisms of MTB infection, presenting new possibilities for the development of early diagnostic and therapeutic strategies.

Dataset Information

PINE: An Automation Tool to Extract & Visualize Functionally Enriched Networks from Mass Spectrometry-Based Proteomics Datasets

Publications

PINE: An Automation Tool to Extract and Visualize Protein-Centric Functional Networks.

Similar Datasets

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