P-MartCancer–Interactive Online Software to Enable Analysis of Shotgun Cancer Proteomic Datasets

Webb-Robertson, Bobbie-Jo M.; Bramer, Lisa; Jensen, Jeffrey L.; Kobold, Markus A.; Stratton, Kelly G.; White, A. M.; Rodland, Karin D.

doi:10.1158/0008-5472.can-17-0335

Cited by 6 publications

(7 citation statements)

References 12 publications

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“…Protein quantification was performed with standard reference-based median averages ( Polpitiya et al, 2008 ; Matzke et al, 2013 ). Statistics included standard methods ( Webb-Robertson et al, 2017 ). For this specific dataset, we utilized an analysis of variance (ANOVA) with Tukey’s adjustment to compare all strains to on another within each time point.…”

Section: Methodsmentioning

confidence: 99%

Integration of Proteomics and Metabolomics Into the Design, Build, Test, Learn Cycle to Improve 3-Hydroxypropionic Acid Production in Aspergillus pseudoterreus

Pomraning

Dai

Munoz

et al. 2021

Front. Bioeng. Biotechnol.

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Biological engineering of microorganisms to produce value-added chemicals is a promising route to sustainable manufacturing. However, overproduction of metabolic intermediates at high titer, rate, and yield from inexpensive substrates is challenging in non-model systems where limited information is available regarding metabolic flux and its control in production conditions. Integrated multi-omic analyses of engineered strains offers an in-depth look at metabolites and proteins directly involved in growth and production of target and non-target bioproducts. Here we applied multi-omic analyses to overproduction of the polymer precursor 3-hydroxypropionic acid (3HP) in the filamentous fungus Aspergillus pseudoterreus. A synthetic pathway consisting of aspartate decarboxylase, beta-alanine pyruvate transaminase, and 3HP dehydrogenase was designed and built for A. pseudoterreus. Strains with single- and multi-copy integration events were isolated and multi-omics analysis consisting of intracellular and extracellular metabolomics and targeted and global proteomics was used to interrogate the strains in shake-flask and bioreactor conditions. Production of a variety of co-products (organic acids and glycerol) and oxidative degradation of 3HP were identified as metabolic pathways competing with 3HP production. Intracellular accumulation of nitrogen as 2,4-diaminobutanoate was identified as an off-target nitrogen sink that may also limit flux through the engineered 3HP pathway. Elimination of the high-expression oxidative 3HP degradation pathway by deletion of a putative malonate semialdehyde dehydrogenase improved the yield of 3HP by 3.4 × after 10 days in shake-flask culture. This is the first report of 3HP production in a filamentous fungus amenable to industrial scale biomanufacturing of organic acids at high titer and low pH.

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Section: Methodsmentioning

confidence: 99%

Integration of Proteomics and Metabolomics Into the Design, Build, Test, Learn Cycle to Improve 3-Hydroxypropionic Acid Production in Aspergillus pseudoterreus

Pomraning

Dai

Munoz

et al. 2021

Front. Bioeng. Biotechnol.

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“…The statistics and protein quantification capabilities will be described briefly, but additional detail can be found in the P-MartCancer description. 18 A concise and simple format for user uploads has been developed that can be generated from most peptide or protein abundance files. This format is easily generated from common formats output by MaxQuant and mzMine.…”

Section: Resultsmentioning

confidence: 99%

“…The web service is wrapped up as a Docker Container, so it can be used in various computing environments (). The web service offers the same files as those in the pmartRdata package in the format needed for upload into the web application as well as access to multiple cancer proteomics data sets and their clinical data generated through the CPTAC preloaded for exploration. , …”

Section: Software Methodsmentioning

confidence: 99%

“…P-Mart's overarching capabilities in the context of analyzing existing Clinical Proteomics Tumor Analysis Consortium (CPTAC) data 17 has been previously described. 18 Herein we describe P-Mart as a capability for use with user-uploaded data to allow the discovery and exploration of potential biomarker candidates for many user-defined global peak-intensity proteomics data sets.…”

Section: Introductionmentioning

confidence: 99%

“…The web-development process for P-Mart integrates R functions in a straightforward manner, which will allow developers to easily add new capabilities to P-Mart beyond the current set included in the initial release. P-Mart’s overarching capabilities in the context of analyzing existing Clinical Proteomics Tumor Analysis Consortium (CPTAC) data has been previously described . Herein we describe P-Mart as a capability for use with user-uploaded data to allow the discovery and exploration of potential biomarker candidates for many user-defined global peak-intensity proteomics data sets.…”

Section: Introductionmentioning

confidence: 99%

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P-Mart: Interactive Analysis of Ion Abundance Global Proteomics Data

et al. 2019

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The use of mass-spectrometry-based techniques for global protein profiling of biomedical or environmental experiments has become a major focus in research centered on biomarker discovery; however, one of the most important issues recently highlighted in the new era of omics data generation is the ability to perform analyses in a robust and reproducible manner. This has been hypothesized to be one of the issues hindering the ability of clinical proteomics to successfully identify clinical diagnostic and prognostic biomarkers of disease. P-Mart (https:// pmart.labworks.org) is a new interactive web-based software environment that enables domain scientists to perform quality-control processing, statistics, and exploration of large-complex proteomics data sets without requiring statistical programming. P-Mart is developed in a manner that allows researchers to perform analyses via a series of modules, explore the results using interactive visualization, and finalize the analyses with a collection of output files documenting all stages of the analysis and a report to allow reproduction of the analysis. Graphical Abstract *Corresponding Author: bj@pnnl.gov. Keywordssoftware; proteomics; web service; reproducibility; statistics; exploratory data analysis; visualization 16 which offers many downstream processing options and is a great solution for many proteomics data-processing tasks. The gaps that P-Mart fills with respect to the existing suite Bramer et al.

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