Dataset Information

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.

SUBMITTER: Amin B

PROVIDER: S-EPMC7138690 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:Normal epithelium exists within a dynamic extracellular matrix (ECM) that is tuned to regulate tissue specific epithelial cell function. As such, ECM contributes to tissue homeostasis, differentiation, and disease, including cancer. Though it is now recognized that the functional unit of normal and transformed epithelium is the epithelial cell and its adjacent ECM, we lack a basic understanding of tissue-specific ECM composition and abundance, as well as how physiologic changes in ECM impact cancer risk and outcomes. While traditional proteomic techniques have advanced to robustly identify ECM proteins within tissues, methods to determine absolute abundance have lagged. Here, with a focus on tissues relevant to breast cancer, we utilize mass spectrometry methods optimized for absolute quantitative ECM analysis. Employing an extensive protein extraction and digestion method, combined with stable isotope labeled Quantitative conCATamer (QconCAT) peptides that serve as internal standards for absolute quantification of protein, we quantify 98 ECM, ECM-associated, and cellular proteins in a single analytical run. In rodent models, we applied this approach to the primary site of breast cancer, the normal mammary gland, as well as a common and particularly deadly site of breast cancer metastasis, the liver. We find that mammary gland and liver have distinct ECM abundance and relative composition. Further, we show mammary gland ECM abundance and relative compositions differ across the reproductive cycle, with the most dramatic changes occurring during the pro-tumorigenic window of weaning-induced involution. Combined, this work suggests ECM candidates for investigation of breast cancer progression and metastasis, particularly in postpartum breast cancers that are characterized by high metastatic rates. Finally, we suggest that with use of absolute quantitative ECM proteomics to characterize tissues of interest, it will be possible to reconstruct more relevant in vitro models to investigate tumor-ECM dynamics at higher resolution.

Dataset Information

Quantitative proteomics to study aging in rabbit liver.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets