Clinical Waste Water (CWW) possesses the risks of spreading antibiotic resistant bacteria in the environment. In Bangladesh, liquid discharge is directly released into the municipal sewage system and pollutes the surr...Clinical Waste Water (CWW) possesses the risks of spreading antibiotic resistant bacteria in the environment. In Bangladesh, liquid discharge is directly released into the municipal sewage system and pollutes the surroundings water bodies/rivers. Liquid samples were collected from the three CWW discharge sites connected to DMCH (Dhaka Medical College Hospital) and from one control group non-connected to DMCH. About 32, 30 and 26 times higher ciprofloxacin, cefixime and multi-drug resistant bacterial count were found in CWW over control samples. Among the isolates, two Escherichia spp. isolates, denoted 26N and 28N, were found to be resistant against fluoroquinolone (MBC of Ciprofloxacin > 1024 μg/ml), cephalosporin, glycopeptide, monobactam, penicillin, tetracycline, rifampicin, macrolides, sulfonamide and nitrofuran classes of drugs and were also ESBL positive through phenotypic assay. Plasmid curing experiment detected possible plasmid mediated resistance of fluoroquinolone, cephalosporin, tetracycline, lincosamide and nitrofuran classes of antibiotics. Phylogenetically, isolate 26N and 28N were characterized as Escherichia coli and Escherichia fergusonii. These MDR and ESBL positive bacteria are potent to disseminate resistant determinants in the surrounding environments.展开更多
Presumptive identifcation of different Enterobaeteriaeeae species is routinely achieved based on biochemical properties. Traditional practice includes manual comparison of each biochem- ical property of the unknown sa...Presumptive identifcation of different Enterobaeteriaeeae species is routinely achieved based on biochemical properties. Traditional practice includes manual comparison of each biochem- ical property of the unknown sample with known reference samples and inference of its identity based on the maximum similarity pattern with the known samples. This process is labor- intensive, time-consuming, error-prone, and subjective. Therefore, automation of sorting and sim- ilarity in calculation would be advantageous. Here we present a MATLAB-based graphical user interface （GUI） tool named BioCluster. This tool was designed for automated clustering and iden- tification of Enterobacteriaceae based on biochemical test results. In this tool, we used two types of algorithms, i.e., traditional hierarchical clustering （HC） and the Improved Hierarchical Clustering （IHC）, a modified algorithm that was developed specifically for the clustering and identification of within this species. IHC takes into account the variability in result of 1-47 biochemical tests family. This tool also provides different options to optimize the clus- tering in a user-friendly way. Using computer-generated synthetic data and some real data, we have demonstrated that BioCluster has high accuracy in clustering and identifying enterobacterial species based on biochemical test data. This tool can be freely downloaded at http：//microbialgen.du.ac.bd/ biocluster/.展开更多
文摘Clinical Waste Water (CWW) possesses the risks of spreading antibiotic resistant bacteria in the environment. In Bangladesh, liquid discharge is directly released into the municipal sewage system and pollutes the surroundings water bodies/rivers. Liquid samples were collected from the three CWW discharge sites connected to DMCH (Dhaka Medical College Hospital) and from one control group non-connected to DMCH. About 32, 30 and 26 times higher ciprofloxacin, cefixime and multi-drug resistant bacterial count were found in CWW over control samples. Among the isolates, two Escherichia spp. isolates, denoted 26N and 28N, were found to be resistant against fluoroquinolone (MBC of Ciprofloxacin > 1024 μg/ml), cephalosporin, glycopeptide, monobactam, penicillin, tetracycline, rifampicin, macrolides, sulfonamide and nitrofuran classes of drugs and were also ESBL positive through phenotypic assay. Plasmid curing experiment detected possible plasmid mediated resistance of fluoroquinolone, cephalosporin, tetracycline, lincosamide and nitrofuran classes of antibiotics. Phylogenetically, isolate 26N and 28N were characterized as Escherichia coli and Escherichia fergusonii. These MDR and ESBL positive bacteria are potent to disseminate resistant determinants in the surrounding environments.
基金supported by the grants from the Ministry of Science and Technology (S&T) of Bangladesh (Grant No.HEQEP CP236)the University Grants Commission (UGC).
文摘Presumptive identifcation of different Enterobaeteriaeeae species is routinely achieved based on biochemical properties. Traditional practice includes manual comparison of each biochem- ical property of the unknown sample with known reference samples and inference of its identity based on the maximum similarity pattern with the known samples. This process is labor- intensive, time-consuming, error-prone, and subjective. Therefore, automation of sorting and sim- ilarity in calculation would be advantageous. Here we present a MATLAB-based graphical user interface （GUI） tool named BioCluster. This tool was designed for automated clustering and iden- tification of Enterobacteriaceae based on biochemical test results. In this tool, we used two types of algorithms, i.e., traditional hierarchical clustering （HC） and the Improved Hierarchical Clustering （IHC）, a modified algorithm that was developed specifically for the clustering and identification of within this species. IHC takes into account the variability in result of 1-47 biochemical tests family. This tool also provides different options to optimize the clus- tering in a user-friendly way. Using computer-generated synthetic data and some real data, we have demonstrated that BioCluster has high accuracy in clustering and identifying enterobacterial species based on biochemical test data. This tool can be freely downloaded at http：//microbialgen.du.ac.bd/ biocluster/.
