Evidence map›Paper›PMID 29069469›Full record

ArticleNucleic acids research2018

Polysome-profiling in small tissue samples.

Shuo Liang, Hermano Martins Bellato, Julie Lorent, Fernanda C S Lupinacci, Christian Oertlin, Vincent van Hoef, Victor P Andrade, Martín Roffé, Laia Masvidal, Glaucia N M Hajj and 1 more

Open access · goldAbstract read
In one paragraph

Article in Nucleic acids research, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 48 papers.

0numbers the graph read from it
0cells of the map it votes in
48citing papers in PubMed
2.8field-weighted citation impact, top 9% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

48 citing papers in PubMed, 77 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Review
  11. Article
  12. Multi Omics Applications in Biological Systems.Current issues in molecular biology · 2024
    Review
  13. Article
  14. Article
  15. Article
  16. Review
  17. Review
  18. Review
  19. Article
  20. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors at 3 institutions in 2 countries.

Shuo LiangDepartment of Oncology-Pathology, Science for Life Laboratory, Karolinska Institutet, Stockholm, Sweden.
Hermano Martins BellatoInternational Research Center, A.C.Camargo Cancer Center, São Paulo, Brazil.
Julie LorentDepartment of Oncology-Pathology, Science for Life Laboratory, Karolinska Institutet, Stockholm, Sweden.
Fernanda C S LupinacciInternational Research Center, A.C.Camargo Cancer Center, São Paulo, Brazil.
Christian OertlinDepartment of Oncology-Pathology, Science for Life Laboratory, Karolinska Institutet, Stockholm, Sweden.
Vincent van HoefDepartment of Oncology-Pathology, Science for Life Laboratory, Karolinska Institutet, Stockholm, Sweden.
Victor P AndradeDepartment of Pathology, A.C.Camargo Cancer Center, São Paulo, Brazil.
Martín RofféInternational Research Center, A.C.Camargo Cancer Center, São Paulo, Brazil.
Laia MasvidalDepartment of Oncology-Pathology, Science for Life Laboratory, Karolinska Institutet, Stockholm, Sweden.
Glaucia N M HajjInternational Research Center, A.C.Camargo Cancer Center, São Paulo, Brazil.
Ola LarssonDepartment of Oncology-Pathology, Science for Life Laboratory, Karolinska Institutet, Stockholm, Sweden.
AC Camargo Hospital · BRScience for Life Laboratory · SEKarolinska Institutet · SE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

Protein BiosynthesisBreast NeoplasmsFemaleHCT116 CellsHumansMCF-7 CellsMutationPolyribosomesRibosomesRNA, MessengerSequence Analysis, RNATumor Suppressor Protein p53RNA, MessengerTumor Suppressor Protein p53

Identifiers

PMID29069469
PMCPMC5758873
OpenAlexW2950337279

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.