Cited by 78RNA and protein synthesis mechanismsRNA Research and SplicingSingle-cell and spatial transcriptomics

Polysome-profiling in small tissue samples

Open access
Liang, Shuo, Bellato, Hermano Martins, Lorent, Julie, Lupinacci, Fernanda C S, Oertlin, Christian, van Hoef, Vincent, Andrade, Victor P, Roffé, Martín +3 more·2018·Nucleic Acids Research

Published version of a preprint

Abstract

Polysome-profiling is commonly used to study translatomes and applies laborious extraction of efficiently translated mRNA (associated with >3 ribosomes) from a large volume across many fractions. This property makes polysome-profiling inconvenient for larger experimental designs or samples with low RNA amounts. To address this, we optimized a non-linear sucrose gradient which reproducibly enriches for efficiently translated mRNA in only one or two fractions, thereby reducing sample handling 5-10-fold. The technique generates polysome-associated RNA with a quality reflecting the starting material and, when coupled with smart-seq2 single-cell RNA sequencing, translatomes in small tissues from biobanks can be obtained. Translatomes acquired using optimized non-linear gradients resemble those obtained with the standard approach employing linear gradients. Polysome-profiling using optimized non-linear gradients in serum starved HCT-116 cells with or without p53 showed that p53 status associates with changes in mRNA abundance and translational efficiency leading to changes in protein levels. Moreover, p53 status also induced translational buffering whereby changes in mRNA levels are buffered at the level of mRNA translation. Thus, here we present a polysome-profiling technique applicable to large study designs, primary cells and frozen tissue samples such as those collected in biobanks.

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Authors
Liang, S., Bellato, H. M., Lorent, J., Lupinacci, F. C. S., Oertlin, C., van Hoef, V., Andrade, V. P., Roffé, M., Masvidal, L., Hajj, G. N. M., & Larsson, O.
Affiliations
  • Science for Life Laboratory (SE)
  • AC Camargo Hospital (BR)
Corresponding author
  • Hajj, Glaucia N M
  • Larsson, Ola
Venue
Nucleic Acids Research
Published
2017-10-23
Volume
46
Issue
1
Pages
e3-e3
ISSN
  • 0305-1048 (ISSN-L)
  • 1362-4962
OpenAlex
W2950337279
Cited by
78
References
5
Citations by year
2026: 8 · 2025: 11 · 2024: 6 · 2023: 14 · 2022: 8 · 2021: 5 · 2020: 17 · 2019: 5 · 2018: 4
FWCI
2.91
Type
journal article
Language
en
Open access
Locations
  • Nucleic Acids Research (publishedVersion, cc-by-nc)
  • bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion)
  • PubMed Central (publishedVersion, cc-by-nc)
  • PubMed (publishedVersion)
Funders
  • Swedish Foundation for International Cooperation in Research and Higher Education
  • Fundação de Amparo à Pesquisa do Estado de São Paulo (15/15451-3, 2014/, 14/15550-9, 2015/)
  • Cancerfonden
  • Knut och Alice Wallenbergs Stiftelse
  • Vetenskapsrådet
  • Barncancerfonden
  • Cancerföreningen i Stockholm
  • Science for Life Laboratory
  • Uppsala Multidisciplinary Center for Advanced Computational Science
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › RNA and protein synthesis mechanisms
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › RNA Research and Splicing
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Single-cell and spatial transcriptomics
Keywords
polysome profiling, translatome, ribosome-associated mRNA, small tissue samples, biobank samples, single-cell RNA sequencing, SmartSeq2, p53, translation efficiency, HCT116 cells, primary cells
MeSH terms
Breast Neoplasms, Female, Humans, Mutation, Polyribosomes, Ribosomes, RNA, Messenger, Protein Biosynthesis, Tumor Suppressor Protein p53, Sequence Analysis, RNA, HCT116 Cells, MCF-7 Cells

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