A new class of protein biomarkers based on subcellular distribution: application to a mouse liver cancer model

To-date, most proteomic studies aimed at discovering tissue-based cancer biomarkers have compared the quantity of selected proteins between case and control groups. However, proteins generally function in association with other proteins to form modules localized in particular subcellular compartments in specialized cell types and tissues. Sub-cellular mislocalization of proteins has in fact been detected as a key feature in a variety of cancer cells. Here, we describe a strategy for tissue-biomarker detection based on a mitochondria! fold enrichment (mtFE) score, which is sensitive to protein abundance changes as well as changes in subcellular distribution between mitochondria and cytosol. The mtFE score integrates protein abundance data from total cellular lysates and mitochondria-enriched fractions, and provides novel information for the classification of cancer samples that is not necessarily apparent from conventional abundance measurements alone. We apply this new strategy to a panel of wild-type and mutant mice with a liver-specific gene deletion of Liver receptor homolog 1 (Lrh-1(hep-/-)), with both lines containing control individuals as well as individuals with liver cancer induced by diethylnitrosamine (DEN). Lrh-1 gene deletion attenuates cancer cell metabolism in hepatocytes through mitochondria! glutamine processing. We show that proteome changes based on mtFE scores outperform protein abundance measurements in discriminating DEN-induced liver cancer from healthy liver tissue, and are uniquely robust against genetic perturbation. We validate the capacity of selected proteins with informative mtFE scores to indicate hepatic malignant changes in two independent mouse models of hepatocellular carcinoma (HCC), thus demonstrating the robustness of this new approach to biomarker research. Overall, the method provides a novel, sensitive approach to cancer biomarker discovery that considers contextual information of tested proteins.

Systems proteomics of liver mitochondria function

Ruedi Aebersold, Tiffany Amariuta, Johan Auwerx, Sébastien Dubuis, Pooja Jha, Evan Graehl Williams

Recent improvements in quantitative proteomics approaches, including Sequential Window Acquisition of all Theoretical Mass Spectra (SWATH-MS), permit reproducible large-scale protein measurements across diverse cohorts. Together with genomics, transcriptomics, and other technologies, transomic data sets can be generated that permit detailed analyses across broad molecular interaction networks. Here, we examine mitochondrial links to liver metabolism through the genome, transcriptome, proteome, and metabolome of 386 individuals in the BXD mouse reference population. Several links were validated between genetic variants toward transcripts, proteins, metabolites, and phenotypes. Among these, sequence variants in Cox7a2l alter its protein's activity, which in turn leads to downstream differences in mitochondrial supercomplex formation. This data set demonstrates that the proteome can now be quantified comprehensively, serving as a key complement to transcriptomics, genomics, and metabolomics--a combination moving us forward in complex trait analysis.

American Association for the Advancement of Science2016

The NAD(+)-dependent deacetylase SIRT2 attenuates oxidative stress and mitochondrial dysfunction and improves insulin sensitivity in hepatocytes

Vera Monica Lemos Da Silva

Insulin resistance is a major predictor of the development of metabolic disorders. Sirtuins (SIRTs) have emerged as potential targets that can be manipulated to counteract age-related diseases, including type 2 diabetes. SIRT2 has been recently shown to exert important metabolic effects, but whether SIRT2 regulates insulin sensitivity in hepatocytes is currently unknown. The aim of this study is to investigate this possibility and to elucidate underlying molecular mechanisms. Here, we show that SIRT2 is downregulated in insulin-resistant hepatocytes and livers, and this was accompanied by increased generation of reactive oxygen species, activation of stress-sensitive ERK1/2 kinase, and mitochondrial dysfunction. Conversely, SIRT2 overexpression in insulin-resistant hepatocytes improved insulin sensitivity, mitigated reactive oxygen species production and ameliorated mitochondrial dysfunction. Further analysis revealed a reestablishment of mitochondrial morphology, with a higher number of elongated mitochondria rather than fragmented mitochondria instigated by insulin resistance. Mechanistically, SIRT2 was able to increase fusion-related protein Mfn2 and decrease mitochondrial-associated Drp1. SIRT2 also attenuated the downregulation of TFAM, a key mtDNA-associated protein, contributing to the increase in mitochondrial mass. Importantly, we found that SIRT2 expression in PBMCs of human subjects was negatively correlated with obesity and insulin resistance. These results suggest a novel function for hepatic SIRT2 in the regulation of insulin sensitivity and raise the possibility that SIRT2 activators may offer novel opportunities for preventing or treating insulin resistance and type 2 diabetes.

Oxford Univ Press2017

Quantifying and Localizing the Mitochondrial Proteome Across Five Tissues in A Mouse Population

Ruedi Aebersold, Johan Auwerx, Moaraj Hasan, Pooja Jha, Jun Yong Kim, Jiayi Lan, Dongryeol Ryu, Evan Graehl Williams

We have used SWATH mass spectrometry to quantify 3648 proteins across 76 proteomes collected from genetically diverse BXD mouse strains in two fractions (mitochondria and total cell) from five tissues: liver, quadriceps, heart, brain, and brown adipose (BAT). Across tissues, expression covariation between genes' proteins and transcripts-measured in the same individuals-broadly aligned. Covariation was however far stronger in certain subsets than others: only 8% of transcripts in the lowest expression and variance quintile covaried with their protein, in contrast to 65% of transcripts in the highest quintiles. Key functional differences among the 3648 genes were also observed across tissues, with electron transport chain (ETC) genes particularly investigated. ETC complex proteins covary and form strong gene networks according to tissue, but their equivalent transcripts do not. Certain physiological consequences, such as the depletion of ATP synthase in BAT, are thus obscured in transcript data. Lastly, we compared the quantitative proteomic measurements between the total cell and mitochondrial fractions for the five tissues. The resulting enrichment score highlighted several hundred proteins which were strongly enriched in mitochondria, which included several dozen proteins were not reported in literature to be mitochondrially localized. Four of these candidates were selected for biochemical validation, where we found MTAP, SOAT2, and IMPDH2 to be localized inside the mitochondria, whereas ABCC6 was in the mitochondria-associated membrane. These findings demonstrate the synergies of a multi-omics approach to study complex metabolic processes, and this provides a resource for further discovery and analysis of proteoforms, modified proteins, and protein localization.

AMER SOC BIOCHEMISTRY MOLECULAR BIOLOGY INC2018

Quantifying and Localizing the Mitochondrial Proteome Across Five Tissues in A Mouse Population

Ruedi Aebersold, Johan Auwerx, Moaraj Hasan, Pooja Jha, Jun Yong Kim, Jiayi Lan, Dongryeol Ryu, Evan Graehl Williams

AMER SOC BIOCHEMISTRY MOLECULAR BIOLOGY INC2018