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Comparative Analysis of Quantitative Mass Spectrometric Methods for Subcellular Proteomics.

ABSTRACT: Knowledge of intracellular location can provide important insights into the function of proteins and their respective organelles, and there is interest in combining classical subcellular fractionation with quantitative mass spectrometry to create global cellular maps. To evaluate mass spectrometric approaches specifically for this application, we analyzed rat liver differential centrifugation and Nycodenz density gradient subcellular fractions by tandem mass tag (TMT) isobaric labeling with reporter ion measurement at the MS2 and MS3 level and with two different label-free peak integration approaches, MS1 and data independent acquisition (DIA). TMT-MS2 provided the greatest proteome coverage, but ratio compression from contaminating background ions resulted in a narrower accurate dynamic range compared to TMT-MS3, MS1, and DIA, which were similar. Using a protein clustering approach to evaluate data quality by assignment of reference proteins to their correct compartments, all methods performed well, with isobaric labeling approaches providing the highest quality localization. Finally, TMT-MS2 gave the lowest percentage of missing quantifiable data when analyzing orthogonal fractionation methods containing overlapping proteomes. In summary, despite inaccuracies resulting from ratio compression, data obtained by TMT-MS2 assigned protein localization as well as other methods but achieved the highest proteome coverage with the lowest proportion of missing values.

SUBMITTER: Tannous A

PROVIDER: S-EPMC8063867 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Skeletal muscle is a key tissue site of insulin resistance in type 2 diabetes. Human myotubes are primary skeletal muscle cells displaying both morphological and biochemical characteristics of mature skeletal muscle and the diabetic phenotype is conserved in myotubes derived from subjects with type 2 diabetes. Several abnormalities have been identified in skeletal muscle from type 2 diabetic subjects, however, the exact molecular mechanisms leading to the diabetic phenotype has still not been found. Here we present a large-scale study in which we combine a quantitative proteomic discovery strategy using isobaric peptide tags for relative and absolute quantification (iTRAQ) and a label-free study with a targeted quantitative proteomic approach using selected reaction monitoring to identify, quantify, and validate changes in protein abundance among human myotubes obtained from nondiabetic lean, nondiabetic obese, and type 2 diabetic subjects, respectively. Using an optimized protein precipitation protocol, a total of 2832 unique proteins were identified and quantified using the iTRAQ strategy. Despite a clear diabetic phenotype in diabetic myotubes, the majority of the proteins identified in this study did not exhibit significant abundance changes across the patient groups. Proteins from all major pathways known to be important in type 2 diabetic subjects were well-characterized in this study. This included pathways like the trichloroacetic acid (TCA) cycle, lipid oxidation, oxidative phosphorylation, the glycolytic pathway, and glycogen metabolism from which all but two enzymes were found in the present study. None of these enzymes were found to be regulated at the level of protein expression or degradation supporting the hypothesis that these pathways are regulated at the level of post-translational modification. Twelve proteins were, however, differentially expressed among the three different groups. Thirty-six proteins were chosen for further analysis and validation using selected reaction monitoring based on the regulation identified in the iTRAQ discovery study. The abundance of adenosine deaminase was considerably down-regulated in diabetic myotubes and as the protein binds propyl dipeptidase (DPP-IV), we speculate whether the reduced binding of adenosine deaminase to DPP-IV may contribute to the diabetic phenotype in vivo by leading to a higher level of free DPP-IV to bind and inactivate the anti-diabetic hormones, glucagon-like peptide-1 and glucose-dependent insulintropic polypeptide.

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Comparative Analysis of Quantitative Mass Spectrometric Methods for Subcellular Proteomics.

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