Evidence map›Paper›PMID 31555062›Full record

ArticleCurrent genomics2019

Domain-based Comparative Analysis of Bacterial Proteomes: Uniqueness, Interactions, and the Dark Matter.

Liang Wang, Jianye Yang, Yaping Xu, Xue Piao, Jichang Lv

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PubMed Full text at PMC Publisher
In one paragraph

Article in Current genomics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

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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

3 citing papers in PubMed.

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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

5 authors.

Liang Wang1Department of Bioinformatics, School of Medical Informatics, Xuzhou Medical University, Xuzhou, Jiangsu, 221000, P.R. China; 2Key Laboratory of New Drug Research and Clinical Pharmacy of Jiangsu Province, Xuzhou Medical University, Xuzhou, Jiangsu, 221000, P.R. China; 3School of Information and Control Engineering, China University of Mining and Technology, Xuzhou, Jiangsu, 221116, P.R. China.
Jianye Yang1Department of Bioinformatics, School of Medical Informatics, Xuzhou Medical University, Xuzhou, Jiangsu, 221000, P.R. China; 2Key Laboratory of New Drug Research and Clinical Pharmacy of Jiangsu Province, Xuzhou Medical University, Xuzhou, Jiangsu, 221000, P.R. China; 3School of Information and Control Engineering, China University of Mining and Technology, Xuzhou, Jiangsu, 221116, P.R. China.
Yaping Xu1Department of Bioinformatics, School of Medical Informatics, Xuzhou Medical University, Xuzhou, Jiangsu, 221000, P.R. China; 2Key Laboratory of New Drug Research and Clinical Pharmacy of Jiangsu Province, Xuzhou Medical University, Xuzhou, Jiangsu, 221000, P.R. China; 3School of Information and Control Engineering, China University of Mining and Technology, Xuzhou, Jiangsu, 221116, P.R. China.
Xue Piao1Department of Bioinformatics, School of Medical Informatics, Xuzhou Medical University, Xuzhou, Jiangsu, 221000, P.R. China; 2Key Laboratory of New Drug Research and Clinical Pharmacy of Jiangsu Province, Xuzhou Medical University, Xuzhou, Jiangsu, 221000, P.R. China; 3School of Information and Control Engineering, China University of Mining and Technology, Xuzhou, Jiangsu, 221116, P.R. China.
Jichang Lv1Department of Bioinformatics, School of Medical Informatics, Xuzhou Medical University, Xuzhou, Jiangsu, 221000, P.R. China; 2Key Laboratory of New Drug Research and Clinical Pharmacy of Jiangsu Province, Xuzhou Medical University, Xuzhou, Jiangsu, 221000, P.R. China; 3School of Information and Control Engineering, China University of Mining and Technology, Xuzhou, Jiangsu, 221116, P.R. China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundProteins may have none, single, double, or multiple domains, while a single domain may appear in multiple proteins. Their distribution patterns may have impacts on bacterial physi-ology and lifestyle.Objective: This study aims to understand how domains are distributed and duplicated in bacterial prote-omes, in order to better understand bacterial physiology and lifestyles.

methodsIn this study, we used 16712 Hidden Markov Models to screen 944 bacterial reference prote-omes versus a threshold E-value<0.001. The number of non-redundant domains and duplication rates of redundant domains for each species were calculated. The unique domains, if any, were also identified for each species. In addition, the properties of no-domain proteins were investigated in terms of physico-chemical properties.

resultsThe increasing number of non-redundant domains for a bacterial proteome follows the trend of an asymptotic function. The domain duplication rate is positively correlated with proteome size and in-creases more rapidly. The high percentage of single-domain proteins is more associated with small pro-teome size. For each proteome, unique domains were also obtained. Moreover, no-domain proteins show differences with the other three groups for several physicochemical properties analysed in this study.

conclusionThe study confirmed that a low domain duplication rate and a high percentage of single-domain proteins are more likely to be associated with bacterial host-dependent or restricted niche-adapted lifestyle. In addition, the unique lifestyle and physiology were revealed based on the analysis of species-specific domains and core domain interactions or co-occurrences.

Indexed as

Bacterial lifestyleBacterial proteomeDomain interactionDomain redundancyHidden markov modelPfam

Identifiers

PMID31555062
PMCPMC6728903

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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.