Shigellosis in Bay of Bengal Islands, India: clinical and seasonal patterns, surveillance of antibiotic susceptibility patterns, and molecular characterization of multidrug-resistant Shigella strains isolated during a 6-year period from 2006 to 2011

Abstract

This study aims to determine the clinical features and seasonal patterns associated with shigellosis, the antimicrobial resistance frequencies of the isolates obtained during the period 2006-2012 for 22 antibiotics, and the molecular characterization of multidrug-resistant strains isolated from endemic cases of shigellosis in the remote islands of India, with special reference to fluoroquinolone and third-generation cephalosporins resistance. During the period from January 2006 to December 2011, stool samples were obtained and processed to isolate Shigella spp. The isolates were evaluated with respect to their antibiotic resistance pattern and various multidrug resistance determinants, including resistance genes, quinolone resistance determinants, and extended-spectrum β-lactamase (ESBL) production. Morbidity for shigellosis was found to be 9.3 % among children in these islands. Cases of shigellosis occurred mainly during the rainy seasons and were found to be higher in the age group 2-5 years. A wide spectrum of resistance was observed among the Shigella strains, and more than 50 % of the isolates were multidrug-resistant. The development of multidrug-resistant strains was found to be associated with various drug-resistant genes, multiple mutations in the quinolone resistance-determining region (QRDR), and the presence of plasmid-mediated quinolone-resistant determinants and efflux pump mediators. This report represents the first presentation of the results of long-term surveillance and molecular characterization concerning antimicrobial resistances in clinical Shigella strains in these islands. Information gathered as part of the investigations will be instrumental in identifying emerging antimicrobial resistance, for developing treatment guidelines appropriate for that community, and to provide baseline data with which to compare outbreak strains in the future.