2020
DOI: 10.1093/nar/gkaa1103
|View full text |Cite
|
Sign up to set email alerts
|

Translation elongation rate varies among organs and decreases with age

Abstract: There has been a surge of interest towards targeting protein synthesis to treat diseases and extend lifespan. Despite the progress, few options are available to assess translation in live animals, as their complexity limits the repertoire of experimental tools to monitor and manipulate processes within organs and individual cells. It this study, we developed a labeling-free method for measuring organ- and cell-type-specific translation elongation rates in vivo. It is based on time-resolved delivery of translat… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
1
1

Citation Types

1
34
0
1

Year Published

2021
2021
2024
2024

Publication Types

Select...
6
2
1

Relationship

0
9

Authors

Journals

citations
Cited by 54 publications
(41 citation statements)
references
References 40 publications
1
34
0
1
Order By: Relevance
“…Rapidly accumulating ribosome profiling works begin to bring new insights into the translational control of aged cells [ 60–62 ]. Universal characteristics of translation-level responses from these works have emerged across aged (replicatively) yeast [ 63 ], mouse [ 64 , 65 ] and human cells [ 46 , 66 ], where reduced translational engagement and elongation rates were observed. Ribosome profiling studies in mouse liver, kidney [ 65 ] and skeletal muscle [ 64 ], and human skeletal muscle [ 66 ], revealed reduced translation of mitochondrial, ribosomal and translation factor transcripts in the aged tissues ( Table 3 ).…”
Section: Introductionmentioning
confidence: 99%
See 1 more Smart Citation
“…Rapidly accumulating ribosome profiling works begin to bring new insights into the translational control of aged cells [ 60–62 ]. Universal characteristics of translation-level responses from these works have emerged across aged (replicatively) yeast [ 63 ], mouse [ 64 , 65 ] and human cells [ 46 , 66 ], where reduced translational engagement and elongation rates were observed. Ribosome profiling studies in mouse liver, kidney [ 65 ] and skeletal muscle [ 64 ], and human skeletal muscle [ 66 ], revealed reduced translation of mitochondrial, ribosomal and translation factor transcripts in the aged tissues ( Table 3 ).…”
Section: Introductionmentioning
confidence: 99%
“…Universal characteristics of translation-level responses from these works have emerged across aged (replicatively) yeast [ 63 ], mouse [ 64 , 65 ] and human cells [ 46 , 66 ], where reduced translational engagement and elongation rates were observed. Ribosome profiling studies in mouse liver, kidney [ 65 ] and skeletal muscle [ 64 ], and human skeletal muscle [ 66 ], revealed reduced translation of mitochondrial, ribosomal and translation factor transcripts in the aged tissues ( Table 3 ). Human heart tissue also exhibited reduced translation of nuclear-encoded mitochondrial proteins, whilst translation of cytosolic ribosome components, including 14 Ribosomal Protein Small subunit ( RPS ) and 18 Ribosomal Protein Large subunit ( RPL ) transcripts, increased [ 46 ].…”
Section: Introductionmentioning
confidence: 99%
“…2F). HHT inhibits translation initiation rapidly (13). Therefore, after its addition, puromycin labeling specifically measures the elongation phase of protein synthesis.…”
Section: Resultsmentioning
confidence: 99%
“…A custom proteogenomic search database was constructed combining the known Mus musculus UniProt reference proteome (downloaded at 8/10/2020) and an alternative proteome based on the sORFs.org method (Olexiouk et al, 2016(Olexiouk et al, , 2018 and the OpenProt repository (Brunet et al, 2021). First, seven publicly available ribosome profiling datasets from mouse brain tissues were downloaded from NCBI Gene Expression Omnibus (GEO) [GSE140565, GSE143330, and GSE143331 (Shah et al, 2020), GSE94982, GSE112223 (Gerashchenko et al, 2021), GSE119681 (Zhao et al, 2019), GSE51424 (Gonzalez et al, 2014), and GSE74683 (Laguesse et al, 2015)]. These datasets were subjected to the previously published sORF prediction pipeline (Olexiouk et al, 2018) with minor code modifications (available upon request).…”
Section: Peptide Identification: Database Construction and Searchingmentioning
confidence: 99%