Evidence map›Paper›PMID 20959013›Full record

ArticleBMC genomics2010

An inventory of the Aspergillus niger secretome by combining in silico predictions with shotgun proteomics data.

Machtelt Braaksma, Elena S Martens-Uzunova, Peter J Punt, Peter J Schaap

Open access · goldAbstract read
In one paragraph

Article in BMC genomics, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers.

0numbers the graph read from it
0cells of the map it votes in
25citing papers in PubMed
4.1field-weighted citation impact, top 5% 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

25 citing papers in PubMed, 83 citations in OpenAlex.

  1. FungiProteomeDB: a database for the molecular weight and isoelectric points of the fungal proteomes.Database : the journal of biological databases and curation · 2023
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  8. A community-driven reconstruction of theFungal biology and biotechnology · 2018
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  9. PApplied and environmental microbiology · 2017
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  10. Expression ofBiotechnology for biofuels · 2017
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  13. Review
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  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. How many signal peptides are there in bacteria?Environmental microbiology · 2013
    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

4 authors at 2 institutions in 1 country.

Machtelt BraaksmaTNO Quality of Life, Zeist, the Netherlands.
Elena S Martens-Uzunova
Peter J Punt
Peter J Schaap
Cancer Genomics Centre · NLPension Fund for Care and Well-Being · NL

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe ecological niche occupied by a fungal species, its pathogenicity and its usefulness as a microbial cell factory to a large degree depends on its secretome. Protein secretion usually requires the presence of a N-terminal signal peptide (SP) and by scanning for this feature using available highly accurate SP-prediction tools, the fraction of potentially secreted proteins can be directly predicted. However, prediction of a SP does not guarantee that the protein is actually secreted and current in silico prediction methods suffer from gene-model errors introduced during genome annotation.

resultsA majority rule based classifier that also evaluates signal peptide predictions from the best homologs of three neighbouring Aspergillus species was developed to create an improved list of potential signal peptide containing proteins encoded by the Aspergillus niger genome. As a complement to these in silico predictions, the secretome associated with growth and upon carbon source depletion was determined using a shotgun proteomics approach. Overall, some 200 proteins with a predicted signal peptide were identified to be secreted proteins. Concordant changes in the secretome state were observed as a response to changes in growth/culture conditions. Additionally, two proteins secreted via a non-classical route operating in A. niger were identified.

conclusionsWe were able to improve the in silico inventory of A. niger secretory proteins by combining different gene-model predictions from neighbouring Aspergilli and thereby avoiding prediction conflicts associated with inaccurate gene-models. The expected accuracy of signal peptide prediction for proteins that lack homologous sequences in the proteomes of related species is 85%. An experimental validation of the predicted proteome confirmed in silico predictions.

Indexed as

Aspergillus nigerCarbohydrate MetabolismFungal ProteinsGenome, FungalMass SpectrometryModels, GeneticMolecular Sequence AnnotationPectinsPeptide HydrolasesPeptidesProteomeProteomicsReproducibility of ResultsSpecies SpecificitySubcellular FractionsFungal ProteinsPectinsPeptide HydrolasesPeptidesProteome

Identifiers

PMID20959013
PMCPMC3091731
OpenAlexW2115318565

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.