Gene network analysis of efflux pump proteins in Shigella spp.

Puzari, Minakshi; Baishya, Somorita; Choudhury, Manabendra Dutta; Chetia, Pankaj

doi:10.1016/j.genrep.2020.100839

Cited by 4 publications

(5 citation statements)

References 33 publications

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“…The resulting gene network revealed several key regulatory hubs, including the transcription factors AlgU and RhlR, and the stress response pathway mediated by the sigma factor RpoS [18]. Similarly in another study by Puzari M et al [12] showed that AcrB and TolC as promising drug targets for combating antibiotic resistance in bacteria, with AcrD, mdtA, and mdtC also showing potential in Shigella spp [12,19].…”

Section: Discussionmentioning

confidence: 99%

“…"The network analyzer plug-in Cytoscape was used to compute topological parameters. Those were average shortest path length(ASPL)-which indicates shortest distance between two nodes, betweenness centrality which indicates the extent of influence a node has on the network" [12].…”

Section: Analysis Of Parametersmentioning

confidence: 99%

“…The green, red and dark blue lines indicate predicted interactions from gene neighbourhood, gene fusions and gene cooccurrence respectively. The yellow, black and pale blue lines denote other sources like text mining, co-expression and protein homology respectively" [12].…”

Section: Functional Annotation Of Genesmentioning

confidence: 99%

“…"Based on the combined scores from all sources of evidence, assigned to each functional partner of every input, the average local clustering coefficient was calculated for each network as shown in Table 1 with average node degree" [12].…”

Section: Gene Network Constructionmentioning

confidence: 99%

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Gene Network Analysis of Efflux Pump Proteins in Escherichia coli

Sarmah

Mech

2023

UPJOZ

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Multidrug-resistant bacteria are now becoming a great global concern and Escherichia coli is also one of them that has developed multidrug resistance. Although most of the strains do not cause disease some strains cause disease i.e they are pathogenic to humans and other animals also. One of the main reasons for the development of drug resistance in bacteria is their efflux pumps. So it is necessary to formulate new drugs with the help of which we can manage these antibiotic-resistant strains. In my study, a network of directly interacting proteins with the components of the MdtABC-TolC efflux system of Escherichia coli was generated. Functional enrichment analysis was performed for the concerned genes. The proteins interaction network was grouped in clustered. Topological parameters were also analysed and found that TolC seems to be the most well connected and more networking and relationship exist between MdtA-MdtB and MdtC-TolC. Among all the proteins in the merged network, MdtC has the maximum value for betweenness centrality and a high number of node degrees. So it can be concluded that MdtC from cluster2 is the most promising drug target.

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Section: Discussionmentioning

confidence: 99%

Section: Analysis Of Parametersmentioning

confidence: 99%

Section: Functional Annotation Of Genesmentioning

confidence: 99%

Section: Gene Network Constructionmentioning

confidence: 99%

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Gene Network Analysis of Efflux Pump Proteins in Escherichia coli

Sarmah

Mech

2023

UPJOZ

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“…Understanding the PPI networks among Shigella genomes and the strength of association between two or more proteins makes it easier to select drug targets. The high clustering coefficient indicates highly connected networks, while node degree denotes the number of interactions the network proteins have on average [ 54 ]. The merged network, subjected to cluster analysis, showed that the proteins fall into three clusters with significant variations.…”

Section: Discussionmentioning

confidence: 99%

Genome-Wide Investigation Reveals Potential Therapeutic Targets in Shigella spp.

Hossain,

Al Amin,

Khan

et al. 2024

BioMed Research International

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Shigella stands as a major contributor to bacterial dysentery worldwide scale, particularly in developing countries with inadequate sanitation and hygiene. The emergence of multidrug-resistant strains exacerbates the challenge of treating Shigella infections, particularly in regions where access to healthcare and alternative antibiotics is limited. Therefore, investigations on how bacteria evade antibiotics and eventually develop resistance could open new avenues for research to develop novel therapeutics. The aim of this study was to analyze whole genome sequence (WGS) of human pathogenic Shigella spp. to elucidate the antibiotic resistance genes (ARGs) and their mechanism of resistance, gene-drug interactions, protein-protein interactions, and functional pathways to screen potential therapeutic candidate(s). We comprehensively analyzed 45 WGS of Shigella, including S. flexneri (n=17), S. dysenteriae (n=14), S. boydii (n=11), and S. sonnei (n=13), through different bioinformatics tools. Evolutionary phylogenetic analysis showed three distinct clades among the circulating strains of Shigella worldwide, with less genomic diversity. In this study, 2,146 ARGs were predicted in 45 genomes (average 47.69 ARGs/genome), of which only 91 ARGs were found to be shared across the genomes. Majority of these ARGs conferred their resistance through antibiotic efflux pump (51.0%) followed by antibiotic target alteration (23%) and antibiotic target replacement (18%). We identified 13 hub proteins, of which four proteins (e.g., tolC, acrR, mdtA, and gyrA) were detected as potential hub proteins to be associated with antibiotic efflux pump and target alteration mechanisms. These hub proteins were significantly (p<0.05) enriched in biological process, molecular function, and cellular components. Therefore, the finding of this study suggests that human pathogenic Shigella strains harbored a wide range of ARGs that confer resistance through antibiotic efflux pumps and antibiotic target modification mechanisms, which must be taken into account to devise and formulate treatment strategy against this pathogen. Moreover, the identified hub proteins could be exploited to design and develop novel therapeutics against MDR pathogens like Shigella.

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