ArticleScientific reports2016
Comparative genomic analysis of novel Acinetobacter symbionts: A combined systems biology and genomics approach.
Article in Scientific reports, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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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.
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Who cites it
8 citing papers in PubMed, 26 citations in OpenAlex.
- The whole-cell proteome shows the characteristics of macrolides-resistant Bordetella pertussis in China linked to the biofilm formation.Archives of microbiology · 2023Article
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- Extensive microbial diversity within the chicken gut microbiome revealed by metagenomics and culture.PeerJ · 2021Article
- Prediction of Transcription Factors and Their Involvement in Regulating Rifamycin Production inIndian journal of microbiology · 2020Article
- Taxonomically Characterized and Validated Bacterial Species Based on 16S rRNA Gene Sequences from India During the Last Decade.Indian journal of microbiology · 2020Review
- Internal and External Microbial Community of theMicroorganisms · 2019Article
- Comparative Genomic Analyses Reveal Core-Genome-Wide Genes Under Positive Selection and Major Regulatory Hubs in Outlier Strains ofFrontiers in microbiology · 2019Article
- Community-led comparative genomic and phenotypic analysis of the aquaculture pathogen Pseudomonas baetica a390T sequenced by Ion semiconductor and Nanopore technologies.FEMS microbiology letters · 2018Article
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Authors and funding
9 authors at 3 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The increasing trend of antibiotic resistance in Acinetobacter drastically limits the range of therapeutic agents required to treat multidrug resistant (MDR) infections. This study focused on analysis of novel Acinetobacter strains using a genomics and systems biology approach. Here we used a network theory method for pathogenic and non-pathogenic Acinetobacter spp. to identify the key regulatory proteins (hubs) in each strain. We identified nine key regulatory proteins, guaA, guaB, rpsB, rpsI, rpsL, rpsE, rpsC, rplM and trmD, which have functional roles as hubs in a hierarchical scale-free fractal protein-protein interaction network. Two key hubs (guaA and guaB) were important for insect-associated strains, and comparative analysis identified guaA as more important than guaB due to its role in effective module regulation. rpsI played a significant role in all the novel strains, while rplM was unique to sheep-associated strains. rpsM, rpsB and rpsI were involved in the regulation of overall network topology across all Acinetobacter strains analyzed in this study. Future analysis will investigate whether these hubs are useful as drug targets for treating Acinetobacter infections.
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