scholarly journals KOMBAT: Knowledgebase of Microbes’ Battling Agents for Therapeutics

2021 ◽  
Author(s):  
Anasuya Bhargav ◽  
Srijanee Gupta ◽  
Surabhi Seth ◽  
Sweety James ◽  
Firdaus Fatima ◽  
...  
Keyword(s):  
Antibiotic Resistance ◽  
Small Molecules ◽  
Safety Information ◽  
Antibiotic Resistance Genes ◽  
Therapeutic Strategies ◽  
Microbial Pathogens ◽  
Effective Prevention ◽  
Natural Tendency ◽  
Incomplete Treatment ◽  
New Strategies

Antimicrobial resistance (AMR) is one of the top 10 threats affecting global health. AMR defeats the effective prevention and treatment of infections caused by microbial pathogens including bacteria, parasites, viruses and fungi (WHO). Microbial pathogens have natural tendency to evolve and mutate over time resulting in AMR strains. The set of genes involved in antibiotic resistance also termed as “antibiotic resistance genes” (ARGs) spread through species by lateral gene transfer thereby causing global dissemination. While this biological mechanism is prevalent in the spread of AMR, human methods also augment through various mechanisms such as over prescription, incomplete treatment, environmental waste etc. A considerable portion of scientific community is engrossed in AMR related work trying to discover novel therapeutic solutions for tackling resistant pathogens. Comprehensive inspection of the literature shows that diverse therapeutic strategies have evolved over recent years. Collectively, these therapeutic strategies include novel small molecules, newly identified antimicrobial peptides, bacteriophages, phytochemicals, nanocomposites, novel phototherapy against bacteria, fungi and virus. In this work we have developed a comprehensive knowledgebase by collecting alternative antimicrobial therapeutic strategies from literature data. We have used subjective approach for datamining new strategies resulting in broad coverage of entities and subsequently add objective data like entity name, potency, safety information etc. The extracted data was organized KOMBAT (Knowledgebase Of Microbes’ Battling Agents for Therapeutics). A lot of these data are tested against AMR pathogens. We envision that this database will be noteworthy for developing future therapeutics against resistant pathogens. The database can be accessed through http://kombat.igib.res.in/.

scholarly journals Screening Currency Notes for Microbial Pathogens and Antibiotic Resistance Genes Using a Shotgun Metagenomic Approach

PLoS ONE ◽  
2015 ◽  
Vol 10 (6) ◽  
pp. e0128711 ◽  
Author(s):  
Saakshi Jalali ◽  
Samantha Kohli ◽  
Chitra Latka ◽  
Sugandha Bhatia ◽  
Shamsudheen Karuthedath Vellarikal ◽  
...  
Keyword(s):  
Antibiotic Resistance ◽  
Resistance Genes ◽  
Antibiotic Resistance Genes ◽  
Microbial Pathogens ◽  
Metagenomic Approach

scholarly journals Analysis of the Distribution Characteristics of Antibiotic Resistance Gene Pollution and Related Moving Factors in the Main Facility Agricultural Soils in Liaoning Province

2021 ◽  
Author(s):  
Yi Wu ◽  
Xun Zhang ◽  
Baiyu Wang ◽  
Ying Wang ◽  
Yuzhu Gao ◽  
...  
Keyword(s):  
Antibiotic Resistance ◽  
Resistance Genes ◽  
Detection Rate ◽  
Antibiotic Resistance Gene ◽  
Antibiotic Resistance Genes ◽  
Transmission Risk ◽  
Liaoning Province ◽  
Distribution Characteristics ◽  
Effective Prevention ◽  
Vegetable Soil

Abstract To understand the distribution characteristics of antibiotic resistance genes (ARGs) and mobile genetic elements (MGEs) in vegetable soil in the main facility agriculture distribution centres of Liaoning Province, 13 soil samples from seven sites including Chaoyang Yandu Xincheng, Zhuanghe, and Fushun were collected to detect the species and abundance of ARGs and MGEs, and analyse their correlation. The results showed that the ARGs were mainly tetracycline and macrolide antibiotic resistance genes, the transportable elements were transposases, and the cell protection and cell discharge pump was the main resistance mechanism. The detection rate of tetm-02, oprj, sul2, blaTEM, fox5, ermX, ermB, and ermF was 100%. The detection rate of integron IntΙ-1 and transposable enzyme tnpA-01 was 100%. The highest content of antibiotic resistance genes was found in Qiandangpu Village, Daying Town, and Zhuanghe City, followed by Wutun Village, Miaojia Village, Daying Town, and Dalian. Correlation analysis showed a correlation between the abundance of ARGs and the abundance of MGEs in agricultural soil. There was a significant positive correlation between the abundance of ARGs and integron (P < 0.05). The results of this study provide data support for the assessment of soil ARG pollution levels and the effective prevention and control of ARG transmission risk in the main protected vegetable fields in Liaoning Province.

Quintuplex PCR to Detect Antibiotic Resistance Genes in Streptococcus pneumoniae

2016 ◽  
Vol 1 (2) ◽  
pp. 22 ◽  
Author(s):  
Navindra Kumari Palanisamy ◽  
Parasakthi Navaratnam ◽  
Shamala Devi Sekaran
Keyword(s):  
Antibiotic Resistance ◽  
Streptococcus Pneumoniae ◽  
Resistance Genes ◽  
Bacterial Pathogen ◽  
Antibiotic Resistance Genes ◽  
Pcr Amplification ◽  
Penicillin Resistance ◽  
Penicillin Binding Proteins ◽  
Efflux Mechanism ◽  
Mic Value

Introduction: Streptococcus pneumoniae is an important bacterial pathogen, causing respiratory infection. Penicillin resistance in S. pneumoniae is associated with alterations in the penicillin binding proteins, while resistance to macrolides is conferred either by the modification of the ribosomal target site or efflux mechanism. This study aimed to characterize S. pneumoniae and its antibiotic resistance genes using 2 sets of multiplex PCRs. Methods: A quintuplex and triplex PCR was used to characterize the pbp1A, ermB, gyrA, ply, and the mefE genes. Fifty-eight penicillin sensitive strains (PSSP), 36 penicillin intermediate strains (PISP) and 26 penicillin resistance strains (PRSP) were used. Results: Alteration in pbp1A was only observed in PISP and PRSP strains, while PCR amplification of the ermB or mefE was observed only in strains with reduced susceptibility to erythromycin. The assay was found to be sensitive as simulated blood cultures showed the lowest level of detection to be 10cfu. Conclusions: As predicted, the assay was able to differentiate penicillin susceptible from the non-susceptible strains based on the detection of the pbp1A gene, which correlated with the MIC value of the strains.

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