Invariable stoichiometry of ribosomal proteins in mouse brain tissues with aging

Abstract

Across phyla, the ribosomes—the central molecular machines for translation of genetic information—exhibit an overall preserved architecture and a conserved functional core. The natural heterogeneity of the ribosome periodically phases a debate on their functional specialization and the tissue-specific variations of the ribosomal protein (RP) pool. Using sensitive differential proteomics, we performed a thorough quantitative inventory of the protein composition of ribosomes from 3 different mouse brain tissues, i.e., hippocampus, cortex, and cerebellum, across various ages, i.e., juvenile, adult, and middle-aged mouse groups. In all 3 brain tissues, in both monosomal and polysomal ribosome fractions, we detected an invariant set of 72 of 79 core RPs, RACK1 and 2 of the 8 RP paralogs, the stoichiometry of which remained constant across different ages. The amount of a few RPs punctually varied in either one tissue or one age group, but these fluctuations were within the tight bounds of the measurement noise. Further comparison with the ribosomes from a high-metabolic-rate organ, e.g., the liver, revealed protein composition identical to that of the ribosomes from the 3 brain tissues. Together, our data show an invariant protein composition of ribosomes from 4 tissues across different ages of mice and support the idea that functional heterogeneity may arise from factors other than simply ribosomal protein stoichiometry.

Loss of coordinated expression between ribosomal and mitochondrial genes revealed by comprehensive characterization of a large family with a rare mendelian disorder

“…As previously implicated and shown in this study, feedback loops connect the expression of functionally related genes such as ribosomal proteins [24,25] (Figure-6A). As a control, we conducted the same analysis with CDK11, a gene we found to be differentially increased in carriers (Figure-3A).…”

“…Expression of ribosomal components is stochiometric [24,25]. Loss of expression coordination leads to unproductive energy consumption, proteotoxic stress [26], impaired cell proliferation, tumorigenesis and metastasis [examples: RPS3A [27], RPL5 [28], RPL15 [29][30][31][32].…”

Sequence variation, common tissue expression patterns and learning models: a genome-wide survey of vertebrate ribosomal proteins

“…The discovery of dynamic RP stoichiometry, by which sub-cellular populations of ribosomes are subjected to regulation by external stimuli ( 95 ) and determine the translation of selected mRNAs ( 95 , 96 ), strengthen this hypothesis. Nonetheless, several independent studies have not been able to identify different RP stoichiometry in proteomic analysis of isolated ribosomes ( 89 , 97–99 ), as well as in murine brain (hippocampus, cortex and cerebellum), liver and age groups (juvenile, adult, and middle-aged) ( 99 ). Differences may arise from paralog gene expression or limited cases in ribosomal function, as in the example of RPL3L (see Results ) or RPLP1/P1 ( Supplementary Figure S11 ), respectively.…”

Analyzing Ribosome Remodeling in Health and Disease

“…For example, the degree of ribosome remodeling (if any at all) is very small during the aging of mouse brains. [68] As observed RP changes can be small, they may be comparable to or smaller than the measurement noise.…”

“…[18,66,67] In some studies, the measurement noise is comparable to the variability of RPs across conditions. [68] In such cases, we may conclude that ribosomes do not remodel across the examined conditions or the degree of remodeling it too small to be detected by the methodology used. The smaller the measurement errors, the more confident we may be that ribosomes do not remodel across the set of studied conditions.…”