Evidence map›Paper›PMID 34061833›Full record

ArticlePLoS genetics2021

Towards the characterization of the hidden world of small proteins in Staphylococcus aureus, a proteogenomics approach.

Stephan Fuchs, Martin Kucklick, Erik Lehmann, Alexander Beckmann, Maya Wilkens, Baban Kolte, Ayten Mustafayeva, Tobias Ludwig, Maurice Diwo, Josef Wissing and 4 more

Open access · goldAbstract read
In one paragraph

Article in PLoS genetics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers.

0numbers the graph read from it
0cells of the map it votes in
26citing papers in PubMed
2.4field-weighted citation impact, top 10% 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

26 citing papers in PubMed, 42 citations in OpenAlex.

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  18. StORF-Reporter: finding genes between genes.Nucleic acids research · 2023
    Article
  19. Small proteins in Gram-positive bacteria.FEMS microbiology reviews · 2023
    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

14 authors at 4 institutions in 2 countries.

Stephan FuchsRobert Koch Institute, Methodenentwicklung und Forschungsinfrastruktur (MF), Berlin, Germany.
Martin KucklickUniversity of Technical Sciences Braunschweig, Institute for Microbiology, Braunschweig, Germany.ORCID 0000-0002-7289-3915
Erik LehmannUniversity of Technical Sciences Braunschweig, Institute for Microbiology, Braunschweig, Germany.ORCID 0000-0001-9266-4944
Alexander BeckmannUniversity of Technical Sciences Braunschweig, Institute for Microbiology, Braunschweig, Germany.ORCID 0000-0002-6110-2751
Maya WilkensRobert Koch Institute, Methodenentwicklung und Forschungsinfrastruktur (MF), Berlin, Germany.ORCID 0000-0003-4631-6177
Baban KolteUniversity of Hamburg, Institute of Biochemistry and Molecular Biology, Hamburg, Germany.
Ayten MustafayevaUniversity of Technical Sciences Braunschweig, Institute for Microbiology, Braunschweig, Germany.
Tobias LudwigUniversity of Technical Sciences Braunschweig, Institute for Microbiology, Braunschweig, Germany.
Maurice DiwoUniversity of Technical Sciences Braunschweig, Institute for Microbiology, Braunschweig, Germany.ORCID 0000-0001-6107-0801
Josef WissingHelmholtz Center for Infection Research GmbH, Cellular Proteomics, Braunschweig, Germany.
Lothar JänschHelmholtz Center for Infection Research GmbH, Cellular Proteomics, Braunschweig, Germany.
Christian H AhrensAgroscope, Research Group Molecular Diagnostics, Genomics and Bioinformatics & SIB Swiss Institute of Bioinformatics, Basel, Switzerland.ORCID 0000-0002-8148-7257
Zoya IgnatovaUniversity of Hamburg, Institute of Biochemistry and Molecular Biology, Hamburg, Germany.ORCID 0000-0002-9478-8825
Susanne EngelmannUniversity of Technical Sciences Braunschweig, Institute for Microbiology, Braunschweig, Germany.ORCID 0000-0002-1201-3488
Helmholtz Centre for Infection Research · DERobert Koch Institute · DEUniversität Hamburg · DESIB Swiss Institute of Bioinformatics · CH

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Small proteins play essential roles in bacterial physiology and virulence, however, automated algorithms for genome annotation are often not yet able to accurately predict the corresponding genes. The accuracy and reliability of genome annotations, particularly for small open reading frames (sORFs), can be significantly improved by integrating protein evidence from experimental approaches. Here we present a highly optimized and flexible bioinformatics workflow for bacterial proteogenomics covering all steps from (i) generation of protein databases, (ii) database searches and (iii) peptide-to-genome mapping to (iv) visualization of results. We used the workflow to identify high quality peptide spectrum matches (PSMs) for small proteins (≤ 100 aa, SP100) in Staphylococcus aureus Newman. Protein extracts from S. aureus were subjected to different experimental workflows for protein digestion and prefractionation and measured with highly sensitive mass spectrometers. In total, 175 proteins with up to 100 aa (SP100) were identified. Out of these 24 (ranging from 9 to 99 aa) were novel and not contained in the used genome annotation.144 SP100 are highly conserved and were found in at least 50% of the publicly available S. aureus genomes, while 127 are additionally conserved in other staphylococci. Almost half of the identified SP100 were basic, suggesting a role in binding to more acidic molecules such as nucleic acids or phospholipids.

Indexed as

Bacterial ProteinsComputer SimulationDatabases, ProteinMass SpectrometryMolecular Sequence AnnotationOpen Reading FramesPeptide HydrolasesPhylogenyProteogenomicsStaphylococcus aureusBacterial ProteinsPeptide Hydrolases

Identifiers

PMID34061833
PMCPMC8195425
OpenAlexW3165523943

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.