Evidence map›Paper›PMID 32456206›Full record

ArticleProteomes2020

Is It Possible to Find Needles in a Haystack? Meta-Analysis of 1000+ MS/MS Files Provided by the Russian Proteomic Consortium for Mining Missing Proteins.

Ekaterina Poverennaya, Olga Kiseleva, Ekaterina Ilgisonis, Svetlana Novikova, Arthur Kopylov, Yuri Ivanov, Alexei Kononikhin, Mikhail Gorshkov, Nikolay Kushlinskii, Alexander Archakov and 1 more

Abstract read
In one paragraph

Article in Proteomes, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

11 authors.

Ekaterina PoverennayaInstitute of Biomedical Chemistry, Moscow 119121, Russia.
Olga KiselevaInstitute of Biomedical Chemistry, Moscow 119121, Russia.
Ekaterina IlgisonisInstitute of Biomedical Chemistry, Moscow 119121, Russia.
Svetlana NovikovaInstitute of Biomedical Chemistry, Moscow 119121, Russia.ORCID 0000-0003-2777-2476
Arthur KopylovInstitute of Biomedical Chemistry, Moscow 119121, Russia.ORCID 0000-0002-7199-372X
Yuri IvanovInstitute of Biomedical Chemistry, Moscow 119121, Russia.ORCID 0000-0001-5041-1914
Alexei KononikhinSkolkovo Institute of Science and Technology, Skolkovo 143026, Russia.ORCID 0000-0002-2238-3458
Mikhail GorshkovV.L. Talrose Institute for Energy Problems of Chemical Physics, Federal Research Center of Chemical Physics, Russian Academy of Sciences, Moscow 119334, Russia.ORCID 0000-0001-9572-3452
Nikolay KushlinskiiBlokhin Russian Cancer Research Center, Moscow 115478, Russia.
Alexander ArchakovInstitute of Biomedical Chemistry, Moscow 119121, Russia.
Elena PonomarenkoInstitute of Biomedical Chemistry, Moscow 119121, Russia.

Funding

State Academies of Sciences Fundamental Scientific Research Program for 2013-2020
6 · The paper itself

Abstract

Despite direct or indirect efforts of the proteomic community, the fraction of blind spots on the protein map is still significant. Almost 11% of human genes encode missing proteins; the existence of which proteins is still in doubt. Apparently, proteomics has reached a stage when more attention and curiosity need to be exerted in the identification of every novel protein in order to expand the unusual types of biomaterials and/or conditions. It seems that we have exhausted the current conventional approaches to the discovery of missing proteins and may need to investigate alternatives. Here, we present an approach to deciphering missing proteins based on the use of non-standard methodological solutions and encompassing diverse MS/MS data, obtained for rare types of biological samples by members of the Russian Proteomic community in the last five years. These data were re-analyzed in a uniform manner by three search engines, which are part of the SearchGUI package. The study resulted in the identification of two missing and five uncertain proteins detected with two peptides. Moreover, 149 proteins were detected with a single proteotypic peptide. Finally, we analyzed the gene expression levels to suggest feasible targets for further validation of missing and uncertain protein observations, which will fully meet the requirements of the international consortium. The MS data are available on the ProteomeXchange platform (PXD014300).

Indexed as

Chromosome-Centric Human Proteome Project (C-HPP)human proteomemass spectrometrymissing proteinsneXtProtproteotypic peptideuncertain proteins

Identifiers

PMID32456206
PMCPMC7356824

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Registered trials

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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.