Dataset Information

Evaluation of Two Simultaneous Metabolomic and Proteomic Extraction Protocols Assessed by Ultra-High-Performance Liquid Chromatography Tandem Mass Spectrometry.

ABSTRACT: Untargeted multi-omics analysis of plasma is an emerging tool for the identification of novel biomarkers for evaluating disease prognosis, and for developing a better understanding of molecular mechanisms underlying human disease. The successful application of metabolomic and proteomic approaches relies on reproducibly quantifying a wide range of metabolites and proteins. Herein, we report the results of untargeted metabolomic and proteomic analyses from blood plasma samples following analyte extraction by two frequently-used solvent systems: chloroform/methanol and methanol-only. Whole blood samples were collected from participants (n = 6) at University Hospital Sharjah (UHS) hospital, then plasma was separated and extracted by two methods: (i) methanol precipitation and (ii) 4:3 methanol:chloroform extraction. The coverage and reproducibility of the two methods were assessed by ultra-high-performance liquid chromatography-electrospray ionization quadrupole time-of-flight mass spectrometry (UHPLC-ESI-QTOF-MS). The study revealed that metabolite extraction by methanol-only showed greater reproducibility for both metabolomic and proteomic quantifications than did methanol/chloroform, while yielding similar peptide coverage. However, coverage of extracted metabolites was higher with the methanol/chloroform precipitation.

SUBMITTER: Zenati RA

PROVIDER: S-EPMC9865896 | biostudies-literature | 2023 Jan

REPOSITORIES: biostudies-literature

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Evaluation of Two Simultaneous Metabolomic and Proteomic Extraction Protocols Assessed by Ultra-High-Performance Liquid Chromatography Tandem Mass Spectrometry.

Zenati Ruba A RA Giddey Alexander D AD Al-Hroub Hamza M HM Hagyousif Yousra A YA El-Huneidi Waseem W Bustanji Yasser Y Abu-Gharbieh Eman E Alqudah Mohammad A Y MAY Shara Mohd M Abuhelwa Ahmad Y AY Soares Nelson C NC Semreen Mohammad H MH

International journal of molecular sciences 20230110 2

Untargeted multi-omics analysis of plasma is an emerging tool for the identification of novel biomarkers for evaluating disease prognosis, and for developing a better understanding of molecular mechanisms underlying human disease. The successful application of metabolomic and proteomic approaches relies on reproducibly quantifying a wide range of metabolites and proteins. Herein, we report the results of untargeted metabolomic and proteomic analyses from blood plasma samples following analyte ex ...[more]

PMID: 36674867

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Project description:BACKGROUND:Breast cancer is the fifth most prevalent cause of death among women worldwide. It is also one of the most common types of cancer among Malaysian women. This study aimed to characterize and differentiate the proteomics profiles of different stages of breast cancer and its matched adjacent normal tissues in Malaysian breast cancer patients. Also, this study aimed to construct a pertinent protein pathway involved in each stage of cancer. METHODS:In total, 80 samples of tumor and matched adjacent normal tissues were collected from breast cancer patients at Seberang Jaya Hospital (SJH) and Kepala Batas Hospital (KBH), both in Penang, Malaysia. The protein expression profiles of breast cancer and normal tissues were mapped by sodium dodecyl sulfate polyacrylamide gel electrophoresis (SDS-PAGE). The Gel-Eluted Liquid Fractionation Entrapment Electrophoresis (GELFREE) Technology System was used for the separation and fractionation of extracted proteins, which also were analyzed to maximize protein detection. The protein fractions were then analyzed by tandem mass spectrometry (LC-MS/MS) analysis using LC/MS LTQ-Orbitrap Fusion and Elite. This study identified the proteins contained within the tissue samples using de novo sequencing and database matching via PEAKS software. We performed two different pathway analyses, DAVID and STRING, in the sets of proteins from stage 2 and stage 3 breast cancer samples. The lists of molecules were generated by the REACTOME-FI plugin, part of the CYTOSCAPE tool, and linker nodes were added in order to generate a connected network. Then, pathway enrichment was obtained, and a graphical model was created to depict the participation of the input proteins as well as the linker nodes. RESULTS:This study identified 12 proteins that were detected in stage 2 tumor tissues, and 17 proteins that were detected in stage 3 tumor tissues, related to their normal counterparts. It also identified some proteins that were present in stage 2 but not stage 3 and vice versa. Based on these results, this study clarified unique proteins pathways involved in carcinogenesis within stage 2 and stage 3 breast cancers. CONCLUSIONS:This study provided some useful insights about the proteins associated with breast cancer carcinogenesis and could establish an important foundation for future cancer-related discoveries using differential proteomics profiling. Beyond protein identification, this study considered the interaction, function, network, signaling pathway, and protein pathway involved in each profile. These results suggest that knowledge of protein expression, especially in stage 2 and stage 3 breast cancer, can provide important clues that may enable the discovery of novel biomarkers in carcinogenesis.

Dataset Information

Evaluation of Two Simultaneous Metabolomic and Proteomic Extraction Protocols Assessed by Ultra-High-Performance Liquid Chromatography Tandem Mass Spectrometry.

Publications

Evaluation of Two Simultaneous Metabolomic and Proteomic Extraction Protocols Assessed by Ultra-High-Performance Liquid Chromatography Tandem Mass Spectrometry.

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