Evidence map›Paper›PMID 22185473›Full record

ArticleBMC genomics2011

Correlation of gene expression and protein production rate - a system wide study.

Mikko Arvas, Tiina Pakula, Bart Smit, Jari Rautio, Heini Koivistoinen, Paula Jouhten, Erno Lindfors, Marilyn Wiebe, Merja Penttilä, Markku Saloheimo

Abstract read
In one paragraph

Article in BMC genomics, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers.

0numbers the graph read from it
0cells of the map it votes in
29citing papers in PubMed
–field-weighted citation impact
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

29 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Review
  6. Article
  7. The Relationship betweenReports of biochemistry & molecular biology · 2020
    Article
  8. Review
  9. Secretome Dynamics in a Gram-Positive Bacterial Model.Molecular & cellular proteomics : MCP · 2019
    Article
  10. Regulation of plant cell wall degradation by light inFungal biology and biotechnology · 2018
    Review
  11. Biotechnology for biofuels · 2017
    Article
  12. Article
  13. Article
  14. Abundance of Secreted Proteins ofFrontiers in microbiology · 2017
    Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Whole-genome metabolic model ofBiotechnology for biofuels · 2016
    Article
  20. Review
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

10 authors.

Mikko ArvasVTT Technical Research Centre of Finland, Tietotie 2, P,O, Box FI-1000, 02044 VTT, Espoo, Finland. mikko.arvas@vtt.fi
Tiina Pakula
Bart Smit
Jari Rautio
Heini Koivistoinen
Paula Jouhten
Erno Lindfors
Marilyn Wiebe
Merja Penttilä
Markku Saloheimo

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundGrowth rate is a major determinant of intracellular function. However its effects can only be properly dissected with technically demanding chemostat cultivations in which it can be controlled. Recent work on Saccharomyces cerevisiae chemostat cultivations provided the first analysis on genome wide effects of growth rate. In this work we study the filamentous fungus Trichoderma reesei (Hypocrea jecorina) that is an industrial protein production host known for its exceptional protein secretion capability. Interestingly, it exhibits a low growth rate protein production phenotype.

resultsWe have used transcriptomics and proteomics to study the effect of growth rate and cell density on protein production in chemostat cultivations of T. reesei. Use of chemostat allowed control of growth rate and exact estimation of the extracellular specific protein production rate (SPPR). We find that major biosynthetic activities are all negatively correlated with SPPR. We also find that expression of many genes of secreted proteins and secondary metabolism, as well as various lineage specific, mostly unknown genes are positively correlated with SPPR. Finally, we enumerate possible regulators and regulatory mechanisms, arising from the data, for this response.

conclusionsBased on these results it appears that in low growth rate protein production energy is very efficiently used primarly for protein production. Also, we propose that flux through early glycolysis or the TCA cycle is a more fundamental determining factor than growth rate for low growth rate protein production and we propose a novel eukaryotic response to this i.e. the lineage specific response (LSR).

Indexed as

Gene Expression ProfilingFungal ProteinsProteomicsTranscriptomeTrichodermaFungal Proteins

Identifiers

PMID22185473
PMCPMC3266662

What OpenQuestion holds

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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.