Dataset Information

NAguideR: performing and prioritizing missing value imputations for consistent bottom-up proteomic analyses.

ABSTRACT: Mass spectrometry (MS)-based quantitative proteomics experiments frequently generate data with missing values, which may profoundly affect downstream analyses. A wide variety of imputation methods have been established to deal with the missing-value issue. To date, however, there is a scarcity of efficient, systematic, and easy-to-handle tools that are tailored for proteomics community. Herein, we developed a user-friendly and powerful stand-alone software, NAguideR, to enable implementation and evaluation of different missing value methods offered by 23 widely used missing-value imputation algorithms. NAguideR further evaluates data imputation results through classic computational criteria and, unprecedentedly, proteomic empirical criteria, such as quantitative consistency between different charge-states of the same peptide, different peptides belonging to the same proteins, and individual proteins participating protein complexes and functional interactions. We applied NAguideR into three label-free proteomic datasets featuring peptide-level, protein-level, and phosphoproteomic variables respectively, all generated by data independent acquisition mass spectrometry (DIA-MS) with substantial biological replicates. The results indicate that NAguideR is able to discriminate the optimal imputation methods that are facilitating DIA-MS experiments over those sub-optimal and low-performance algorithms. NAguideR further provides downloadable tables and figures supporting flexible data analysis and interpretation. NAguideR is freely available at http://www.omicsolution.org/wukong/NAguideR/ and the source code: https://github.com/wangshisheng/NAguideR/.

SUBMITTER: Wang S

PROVIDER: S-EPMC7641313 | biostudies-literature | 2020 Aug

REPOSITORIES: biostudies-literature

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NAguideR: performing and prioritizing missing value imputations for consistent bottom-up proteomic analyses.

Wang Shisheng S Li Wenxue W Hu Liqiang L Cheng Jingqiu J Yang Hao H Liu Yansheng Y

Nucleic acids research 20200801 14

Mass spectrometry (MS)-based quantitative proteomics experiments frequently generate data with missing values, which may profoundly affect downstream analyses. A wide variety of imputation methods have been established to deal with the missing-value issue. To date, however, there is a scarcity of efficient, systematic, and easy-to-handle tools that are tailored for proteomics community. Herein, we developed a user-friendly and powerful stand-alone software, NAguideR, to enable implementation and ...[more]

PMID: 32526036

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Project description:Ant species have specialized venom systems developed to sting and inoculate a biological cocktail of organic compounds, including peptide and polypeptide toxins, for the purpose of predation and defense. The genus Dinoponera comprises predatory giant ants that inoculate venom capable of causing long-lasting local pain, involuntary shaking, lymphadenopathy, and cardiac arrhythmias, among other symptoms. To deepen our knowledge about venom composition with regard to protein toxins and their roles in the chemical-ecological relationship and human health, we performed a bottom-up proteomics analysis of the crude venom of the giant ant D. quadriceps, popularly known as the "false" tocandiras. For this purpose, we used two different analytical approaches: (i) gel-based proteomics approach, wherein the crude venom was resolved by denaturing sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE) and all protein bands were excised for analysis; (ii) solution-based proteomics approach, wherein the crude venom protein components were directly fragmented into tryptic peptides in solution for analysis. The proteomic data that resulted from these two methodologies were compared against a previously annotated transcriptomic database of D. quadriceps, and subsequently, a homology search was performed for all identified transcript products. The gel-based proteomics approach unequivocally identified nine toxins of high molecular mass in the venom, as for example, enzymes [hyaluronidase, phospholipase A1, dipeptidyl peptidase and glucose dehydrogenase/flavin adenine dinucleotide (FAD) quinone] and diverse venom allergens (homologous of the red fire ant Selenopsis invicta) and venom-related proteins (major royal jelly-like). Moreover, the solution-based proteomics revealed and confirmed the presence of several hydrolases, oxidoreductases, proteases, Kunitz-like polypeptides, and the less abundant inhibitor cysteine knot (ICK)-like (knottin) neurotoxins and insect defensin. Our results showed that the major components of the D. quadriceps venom are toxins that are highly likely to damage cell membranes and tissue, to cause neurotoxicity, and to induce allergic reactions, thus, expanding the knowledge about D. quadriceps venom composition and its potential biological effects on prey and victims.

Dataset Information

NAguideR: performing and prioritizing missing value imputations for consistent bottom-up proteomic analyses.

Publications

NAguideR: performing and prioritizing missing value imputations for consistent bottom-up proteomic analyses.

Similar Datasets

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