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Molecular characterization and evaluation of the emerging antibiotic-resistant Streptococcus pyogenes from eastern India

Overview of attention for article published in BMC Infectious Diseases, December 2016
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Title
Molecular characterization and evaluation of the emerging antibiotic-resistant Streptococcus pyogenes from eastern India
Published in
BMC Infectious Diseases, December 2016
DOI 10.1186/s12879-016-2079-9
Pubmed ID
Authors

Dipanwita Ray, Somnath Saha, Sukanta Sinha, Nishith Kumar Pal, Basudev Bhattacharya

Abstract

Group A Streptococcus strains causing wide variety of diseases, recently became noticeable in eastern India, are not amenable to standard treatment protocol thus enhancing the possibility of disease morbidity by becoming antibiotic resistance. The association of Lancefield group A Streptococcal variation with degree of vir architectural diversity was evaluated using emm typing and restriction fragment length polymorphism analyses. The antibiotic sensitivity patterns were examined by modified Kirby-Bauer method of disk diffusion. Percentage calculations, 95% confidence interval and one-way ANOVA were used to assess differences in proportions. Our observations revealed 20 different emm types and 13 different HaeIII vir typing patterns. A 1.2 kb fragment was found in all HaeIII typing pattern. Fragments of 1.2 kb and 550 bp were conserved in majority of the isolates. HinfI digestion was found proficient in differentiating the strains of same vir typing patterns. Strong predominance of speC (85%) and speF (80%) genes have been observed encoding exotoxins production. 4 isolates were found to be erythromycin resistant and were of genotype emm49. High degree of tetracycline resistance was shown by 53.57% isolates which belonged to 12 different emm genotypes. These findings suggested that in addition to emm typing, sequential application of HaeIII and HinfI restriction enzymes in vir typing analysis is an effective tool for group A streptococcal molecular characterization associated with antibiotic resistance.

Twitter Demographics

The data shown below were collected from the profile of 1 tweeter who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 30 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 30 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 6 20%
Student > Postgraduate 3 10%
Student > Doctoral Student 3 10%
Student > Ph. D. Student 3 10%
Researcher 3 10%
Other 6 20%
Unknown 6 20%
Readers by discipline Count As %
Medicine and Dentistry 7 23%
Immunology and Microbiology 5 17%
Biochemistry, Genetics and Molecular Biology 3 10%
Pharmacology, Toxicology and Pharmaceutical Science 2 7%
Environmental Science 2 7%
Other 3 10%
Unknown 8 27%

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 18 December 2016.
All research outputs
#7,621,872
of 8,787,207 outputs
Outputs from BMC Infectious Diseases
#3,475
of 3,878 outputs
Outputs of similar age
#244,204
of 299,663 outputs
Outputs of similar age from BMC Infectious Diseases
#139
of 188 outputs
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