Label-free mass spectrometry-driven methods for elucidating adaptive responses of the hepatic mitochondrial proteome in an alcoholic fatty liver disease model Public Deposited


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  • Alcoholic liver disease (ALD) continues to be one of the major public health problems in the United States and worldwide. Complicated by factors including gender, polymorphisms of alcohol-metabolizing enzymes, immunologic factors, exposures to other substances/drugs, hepatic viral infections, nutritional deficiencies, and obesity, ALD is a complex disease that requires a systematic approach to dissect the mechanisms associated with organ dysfunction. Mechanistic knowledge is necessary to shed light on routes that potentially may lead to effective treatments. Proteomics as a discovery tool that may reveal new targets and pathways that can potentially be exploited for developing new preventive strategies and treatments. The mitochondrion is the pivotal organelle linked to disease progression and to the development of ALD. Studies have shown links between mitochondrial dysfunction and ethanol-induced liver injury, but the underlying mechanisms at the molecular level still remain largely unknown. In the present study we evaluated the capability of two label-free mass-spectrometry-driven approaches (i) the intensity-based MS[superscript E] method, and (ii) a spectral counting-based method that uses data-dependent acquisition (DDA). Initially a single- and a three-protein model system were utilized to evaluate differences in the performance characteristics of the two methods. To examine the performance difference of the two methods for proteome characterization, we measured changes in protein levels as a consequence of chronic alcohol consumption in rat liver mitochondria. Our results revealed that the MS[superscript E] approach had better performance in terms of precision, and dynamic range and resulted in superior accuracy for fold change determinations. The MS[superscript E] approach proved to identify more mitochondrial proteins than the two DDA methods. However, the run-to-run reproducibility of the MS[superscript E] method was lower than was observed for the DDA methods. Despite poor linear correlation between approaches, the outcomes of the proteome characterizations were rather consistent as more than half of the significantly altered proteins detected by the MS[superscript E] method were also revealed by at least one of the DDA methods. Collectively, we concluded that both MSE and DDA approaches provide satisfactory performance with the MS[superscript E] approach outperforming the DDA-based methods with respect to accuracy, linearity and dynamic range. Further, we integrated the label-free LC-MS[superscript E] quantification with bioinformatics and knowledge base to profile alteration of the mitochondrial proteome for unraveling the protective effect of MitoQ, a mitochondrial targeted ubiquinone, on ALD. With carefully maintained stability of the LC-MS system, robust proteome datasets with high technical precision were obtained. By taking advantage of the information-rich quantitative proteomic data, we quantitatively categorized the identified proteins and performed pathway analysis for each category independently. Metabolic pathways and associated proteins were highlighted with the guidance of the systems biology approach. In summary, our results indicated that the pathways enriched in response to MitoQ included acyl-CoA synthases and the carnitine shuttle, ketogenesis, the TCA cycle and oxidative phosphorylation. The MitoQ-responsive metabolic network suggested that MitoQ up-regulates fatty acid transportation to counteract accumulation of lipids in the fatty liver. For dissecting the mitochondrial proteome, we develop a "targeted" quantitative approach involving label-free mass spectrometry-based quantification, chemoselective labeling, avidin- biotin based affinity enrichment at both protein and peptide level. The approach was applied to mitochondria exposed to 4-hydroxy-2-nonenal (HNE) for depicting a subset of the mitochondrial proteome susceptible to HNE insult. The utilization of the carbonyl-selective probe, ARP, facilitated labeling of HNE-adducted proteins and enabled avidin affinity enrichment with the biotin moiety. A list of potential protein targets with concentration-dependent response and known HNE modification sites was obtained when combining results from the protein- and peptide-level enrichment workflows. The core list of putative protein targets of HNE adduction may serve as lead for further validation studies towards unraveling the pathogenesis of ALD and emerging treatment modalities using Western blotting or targeted LC-MS methods.
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Last modified: 10/27/2017

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