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Finding Potential Therapeutic Targets against Shigella flexneri through Proteome Exploration.

ABSTRACT: Background:Shigella flexneri is a gram negative bacteria that causes the infectious disease "shigellosis." S. flexneri is responsible for developing diarrhea, fever, and stomach cramps in human. Antibiotics are mostly given to patients infected with shigella. Resistance to antibiotics can hinder its treatment significantly. Upon identification of essential therapeutic targets, vaccine and drug could be effective therapy for the treatment of shigellosis. Methods: The study was designed for the identification and qualitative characterization for potential drug targets from S. flexneri by using the subtractive proteome analysis. A set of computational tools were used to identify essential proteins those are required for the survival of S. flexneri. Total proteome (13,503 proteins) of S. flexneri was retrieved from NCBI and further analyzed by subtractive channel analysis. After identification of the metabolic proteins we have also performed its qualitative characterization to pave the way for the identification of promising drug targets. Results: Subtractive analysis revealed that a list of 53 targets of S. flexneri were human non-homologous essential metabolic proteins that might be used for potential drug targets. We have also found that 11 drug targets are involved in unique pathway. Most of these proteins are cytoplasmic, can be used as broad spectrum drug targets, can interact with other proteins and show the druggable properties. The functionality and drug binding site analysis suggest a promising effective way to design the new drugs against S. flexneri. Conclusion: Among the 53 therapeutic targets identified through this study, 13 were found highly potential as drug targets based on their physicochemical properties whilst only one was found as vaccine target against S. flexneri. The outcome might also be used as module as well as circuit design in systems biology.

SUBMITTER: Hossain MU

PROVIDER: S-EPMC5118456 | biostudies-literature | 2016

REPOSITORIES: biostudies-literature

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Finding Potential Therapeutic Targets against Shigella flexneri through Proteome Exploration.

Hossain Mohammad Uzzal MU Khan Md Arif MA Hashem Abu A Islam Md Monirul MM Morshed Mohammad Neaz MN Keya Chaman Ara CA Salimullah Md M

Frontiers in microbiology 20161122

Background:Shigella flexneri is a gram negative bacteria that causes the infectious disease "shigellosis." S. flexneri is responsible for developing diarrhea, fever, and stomach cramps in human. Antibiotics are mostly given to patients infected with shigella. Resistance to antibiotics can hinder its treatment significantly. Upon identification of essential therapeutic targets, vaccine and drug could be effective therapy for the treatment of shigellosis. Methods: The s ...[more]

PMID: 27920755

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Project description: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.

Project description:BackgroundThis study aimed to analyze non-coding RNA sequencing results, screen differentially expressed long non-coding RNAs (lncRNAs), and predict lncRNA target genes. It further clarifies the potential functions of lncRNAs, thus exploring potential biomarkers and therapeutic targets for stroke.MethodsLncRNA sequencing data of blood samples from stroke patients and healthy subjects (GSE102541 and GSE140275) were downloaded from the Gene Expression Omnibus (GEO) database. This study used R software and related R packages to conduct a batch correction and differential analysis of sequencing results. It also screened differentially expressed lncRNAs and visualized the correlations between significantly different lncRNAs. Target genes of differential lncRNAs were predicted by the StarBase database. Gene ontology (GO) functional enrichment analysis of related target genes was performed using the DAVID database. Principal component analysis was performed based on the expression levels of lncRNAs with the most significant differences in stroke blood samples.ResultsA total of 239 differentially expressed lncRNAs were screened out in this study, of which 146 were upregulated and 93 were downregulated. According to |log2FC| values from highest to lowest, the top 10 lncRNAs with the most significant differences were selected. The upregulated lncRNAs were LINC02334, TARID, MRGPRF-AS1, CAI2, LINC00189, TUG1, and RNF5P1. The downregulated lncRNAs included AC005180.2, ADAMTS9-AS1, and AC036108.3. TARID was strongly correlated with MRGPRF-AS1. Meanwhile, LINC02334 was strongly correlated with TUG1. CAI2, LINC00189, and RNF5P1 were at the core of the correlation network and may therefore be the critical lncRNAs in stroke pathogenesis. GO functional enrichment results indicated that genes were significantly enriched in muscle contraction, RNA polymerase II promoter transcription regulation, muscle structure composition, focal adhesion, endothelial cell chemotaxis, actin, actin cytoskeleton, actin filament binding, blood lipid regulation, smooth muscle contraction regulation, skeletal muscle cell differentiation, and other functions. Principal component analysis showed that the 10 lncRNAs with significant differences could significantly distinguish stroke blood samples from healthy control blood samples, and could characterize the essential characteristics of stroke.ConclusionsLINC02334, TARID, MRGPRF-AS1, CAI2, LINC00189, TUG1, RNF5P1, AC005180.2, ADAMTS9-AS1, and AC036108.3 play an essential role in the pathogenesis of stroke, and may be potential therapeutic targets.

Project description:Shigella flexneri is an intracellular human pathogen that invades colonic cells and causes bloody diarrhea. S. flexneri evolved from commensal Escherichia coli, and genome comparisons reveal that S. flexneri has lost approximately 20% of its genes through the process of pathoadaptation, including a disproportionate number of genes associated with the turnover of the nucleotide-based second messenger cyclic di-GMP (c-di-GMP); however, the remaining c-di-GMP turnover enzymes are highly conserved. c-di-GMP regulates many behavioral changes in other bacteria in response to changing environmental conditions, including biofilm formation, but this signaling system has not been examined in S. flexneri. In this study, we expressed VCA0956, a constitutively active c-di-GMP synthesizing diguanylate cyclase (DGC) from Vibrio cholerae, in S. flexneri to determine if virulence phenotypes were regulated by c-di-GMP. We found that expressing VCA0956 in S. flexneri increased c-di-GMP levels, and this corresponds with increased biofilm formation and reduced acid resistance, host cell invasion, and plaque size. We examined the impact of VCA0956 expression on the S. flexneri transcriptome and found that genes related to acid resistance were repressed, and this corresponded with decreased survival to acid shock. We also found that individual S. flexneri DGC mutants exhibit reduced biofilm formation and reduced host cell invasion and plaque size, as well as increased resistance to acid shock. This study highlights the importance of c-di-GMP signaling in regulating S. flexneri virulence phenotypes. IMPORTANCE The intracellular human pathogen Shigella causes dysentery, resulting in as many as one million deaths per year. Currently, there is no approved vaccine for the prevention of shigellosis, and the incidence of antimicrobial resistance among Shigella species is on the rise. Here, we explored how the widely conserved c-di-GMP bacterial signaling system alters Shigella behaviors associated with pathogenesis. We found that expressing or removing enzymes associated with c-di-GMP synthesis results in changes in Shigella's ability to form biofilms, invade host cells, form lesions in host cell monolayers, and resist acid stress.

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Finding Potential Therapeutic Targets against Shigella flexneri through Proteome Exploration.

Publications

Finding Potential Therapeutic Targets against <i>Shigella flexneri</i> through Proteome Exploration.

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