Hepatic proteome analysis reveals altered mitochondrial metabolism and suppressed acyl-CoA synthetase-1 in colon-26 tumor-induced cachexia

Cachexia is a life-threatening complication of cancer traditionally characterized by weight loss and muscle dysfunction. Cachexia, however, is a systemic disease that also involves remodeling of nonmuscle organs. The liver exerts major control over systemic metabolism, yet its role in cancer cachexia is not well understood. To advance the understanding of how the liver contributes to cancer cachexia, we used quantitative proteomics and bioinformatics to identify hepatic pathways and cellular processes dysregulated in mice with moderate and severe colon-26 tumor-induced cachexia; ~300 differentially expressed proteins identified during the induction of moderate cachexia were also differentially regulated in the transition to severe cachexia. KEGG pathway enrichment revealed representation by oxidative phosphorylation, indicating altered hepatic mitochondrial function as a common feature across cachexia severity. Glycogen catabolism was also observed in cachexic livers along with decreased pyruvate dehydrogenase protein X component (Pdhx), increased lactate dehydrogenase A chain (Ldha), and increased lactate transporter Mct1. Together this suggests altered lactate metabolism and transport in cachexic livers, which may contribute to energetically inefficient interorgan lactate cycling. Acyl-CoA synthetase-1 (ACSL1), known for activating long-chain fatty acids, was decreased in moderate and severe cachexia based on LC-MS/MS analysis and immunoblotting. ACSL1 showed strong linear relationships with percent body weight change and muscle fiber size (R2 = 0.73–0.76, P < 0.01). Mitochondrial coupling efficiency, which is compromised in cachexic livers to potentially increase energy expenditure and weight loss, also showed a linear relationship with ACSL1. Findings suggest altered mitochondrial and substrate metabolism of the liver in cancer cachexia, and possible hepatic targets for intervention

A General Method for Targeted Quantitative Cross-Linking Mass Spectrometry

Chemical cross-linking mass spectrometry (XL-MS) provides protein structural information by identifying covalently linked proximal amino acid residues on protein surfaces. The information gained by this technique is complementary to other structural biology methods such as x-ray crystallography, NMR and cryo-electron microscopy[1]. The extension of traditional quantitative proteomics methods with chemical cross-linking can provide information on the structural dynamics of protein structures and protein complexes. The identification and quantitation of cross-linked peptides remains challenging for the general community, requiring specialized expertise ultimately limiting more widespread adoption of the technique. We describe a general method for targeted quantitative mass spectrometric analysis of cross-linked peptide pairs. We report the adaptation of the widely used, open source software package Skyline, for the analysis of quantitative XL-MS data as a means for data analysis and sharing of methods. We demonstrate the utility and robustness of the method with a cross-laboratory study and present data that is supported by and validates previously published data on quantified cross-linked peptide pairs. This advance provides an easy to use resource so that any lab with access to a LC-MS system capable of performing targeted quantitative analysis can quickly and accurately measure dynamic changes in protein structure and protein interactions

Quantification of BSA cross-linked peptide pairs with Skyline.

<p><b>A.</b> MS2 spectrum for the cross-linked peptide pair linking residues K235-K28 (ALK²³⁵AWSVAR_DTHK²⁸SEIAHR), obtained from a 500 ng injection of cross-linked BSA digest. <b>B.</b> Extracted ion chromatograms for the PRM transitions observed for the cross-linked peptide pair in A. <b>C.</b> Skyline generated bar plot illustrating the normalized peak areas for the cross-linked peptide pair linking K28-K235. Peak areas are shown for triplicate analyses of varying injection amounts (100, 200, 500, and 1000 ng cross-linked BSA digest). Bars are color coded to indicate the contribution of each individual transition to the total peak area and match the color scheme in panel B. </p

Cross-laboratory quantification of BSA-BDP cross-linked peptide pairs.

<p><b>A.</b> Average cross-linked peptide response curve comparing data collected in the Bruce Lab and CSHL for 30 cross-linked peptide pairs. <b>B.</b> Scatter plot illustrating the R² values for linear regression analysis of the data shown in A and B.</p

Experimental outline.

<p><b>A.</b> Biological samples are prepared for qXL-MS comparing two or more conditions. The samples are treated with chemical cross-linker either as (1) a mixed sample if SILAC labeling was used or (2) as separate samples if carrying out a label free experiment or using isotopically labeled cross-linkers. Following the cross-linking reaction proteins are extracted, enzymatically digested, and subjected to various strategies (i.e. strong cation exchange and affinity chromatography) for enrichment cross-linked peptide pairs. <b>B.</b> LC-MS analysis of samples enriched for cross-linked peptide pairs is carried out. This consists of reversed phase chromatographic separation by LC followed by analysis by MS. The mass spectrometer is operated in PRM mode where an inclusion list of <i>m/z</i> values for the precursor ions of interest is used to target specific cross-linked peptides. The PRM mass spectrometric analysis used here consists of three steps including isolation of precursor ions, fragmentation by collision with neutral gasses, and detection of mass to charge ratios of the resulting fragment ions. <b>C)</b> Resulting MS2 data are converted into transition lists and imported into Skyline for analysis.</p