Quantitative proteomics to study aging in rabbit liver

Abstract

Aging globally effects cellular and organismal metabolism across a range of mammalian species, including humans and rabbits. Rabbits (Oryctolagus cuniculus are an attractive model system of aging due to their genetic similarity with humans and their short lifespans. This model can be used to understand metabolic changes in aging especially in major organs such as liver where we detected pronounced variations in fat metabolism, mitochondrial dysfunction, and protein degradation. Such changes in the liver are consistent across several mammalian species however in rabbits the downstream effects of these changes have not yet been explored. We have applied proteomics to study changes in the liver proteins from young, middle, and old age rabbits using a multiplexing cPILOT strategy. This resulted in the identification of 2,586 liver proteins, among which 45 proteins had significant p < 0.05) changes with aging. Seven proteins were differentially-expressed at all ages and include fatty acid binding protein, aldehyde dehydrogenase, enoyl-CoA hydratase, 3-hydroxyacyl CoA dehydrogenase, apolipoprotein C3, peroxisomal sarcosine oxidase, adhesion G-protein coupled receptor, and glutamate ionotropic receptor kinate. Insights to how alterations in metabolism affect protein expression in liver have been gained and demonstrate the utility of rabbit as a model of aging.

Keywords: Aging; Enhanced multiplexing; Liver; Metabolism; Oryctolagus cuniculus; Proteomics; Rabbit; cPILOT.

Figure 1.. Experimental workflow:

Male, New Zealand white rabbits (Oryctolagus cuniculus) of mean age 251 days (N=4), 682 days (N=4), and 1349 days (N=4) were categorized as young, middle, and old age groups, respectively. Proteins were extracted from liver tissues and pooled samples were generated by mixing equimolar amounts of protein from all rabbits prior to trypsin/Lys-C digestion. Peptides were labeled using the cPILOT strategy, pooled, and separated by offline high-pH fractionation. Each of the 12 fractions was analyzed on an Orbitrap Fusion Lumos MS. Light and heavy dimethylated peptide peak pairs were fragmented with CID-MS/MS, and the 10 most intense MS/MS fragments were subjected to HCD fragmentation for the detection of reporter ions at the MS³ level.

Figure 2.. Distribution of proteins across age groups (A-C).

Volcano plots of A) middle/young, B) old/young, and C) old/middle protein comparisons. Proteins with p < 0.05 are present above the horizontal lines (grey). Proteins with significant fold-change are outside the grey vertical lines. The total number of proteins that are higher in expression (red circle) and lower in expression (yellow circle) for each comparison are noted.

Figure 3.. Distribution of protein intensities as a function of age.

To highlight the increasing and decreasing trend of protein intensities, we have generated a heat map of protein intensities for all 45 proteins which change significantly across all ages.

Figure 4.. Molecular pathways of differentially-expressed proteins involved in aging.

STRING analyses of differentially-expressed proteins revealed several metabolic pathways (noted by legend) where dynamic levels of proteins are associated with aging processes in rabbits. Abbreviations for the proteins are: PPAR, peroxisome proliferator activated receptor; V, valine; L, leucine; I, isoleucine; K, lysine; EHHADH, enoyl-CoA hydratase and 3-hydroxyacyl CoA dehydrogenase; FABP1, fatty acid binding protein; ALDH2, aldehyde dehydrogenase; APOC3, apolipoprotein C3; PIPOX, peroxisomal sarcosine oxidase; DDO, D-aspartate oxidase; HSD17B13, hydroxylsteroid-17-beta dehydrogenase 13; CYP1A2, cytochrome P450 family 1A member 2; SLCO1B3, solute carrier organic anion transporter family; HMGCS2, 3-hydroxy-3-methylglutaryl coenzyme A synthase; FAU, 40S ribosomal protein S30; and ABCD3, ATP binding cassette subfamily D member; RPS25, 40S ribosomal protein S25; ACSS2, Acyl-CoA synthetase short chain family member 2; SFXN2, sideroflexin; CYP4B1, cytochrome P450 family 4B member 1; COL14A1, collagen alpha-1.

Figure 5.. Molecular functions and biological processes of differentially-expressed proteins.

Bar charts showing the number of differentially-expressed proteins in a given A) biological processes or B) molecular functions when searched against GO Terms and KEGG pathways. Abbreviations for the proteins are: ACSS2, Acyl-CoA synthetase short chain family member 2; ADGRF3, adhesion G-protein receptor; and GRIK2, glutamate ionotropic receptor kinate.