Molecular epidemiology of beta-lactamase producing nosocomial Gram-negative pathogens from North and South Indian hospitals

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Resistant Gram-negative bacterial (GNB) infections, apart from tremendously escalating the cost of treatment, are a cause for substantial morbidity and mortality among hospitalized patients. Such bacteria are rapidly acquiring resistance to many antimicrobial agents, especially the beta-lactams which are the most frequently prescribed antimicrobials in hospital and community patient care settings, and now also to colistin; a last-line drug to treat infections with such bacteria. The greatest threat to antimicrobial treatment is the production of metallo beta-lactamases, and plasmid-mediated serine carbapenemases.


We conducted a two-year study to observe the pattern of beta-lactamase enzyme production (extended spectrum beta-lactamases (ESBLs), AmpC and carbapenemases) among the nosocomial GNB isolated from intensive care units (ICUs) of North and South Indian hospitals. A total of 761 non-duplicate GNB were included in the study from North (554; 73%) and South India (207; 27%). All strains were subjected to Clinical and Laboratory Standards Institute (CLSI) recommended screening tests for detection of beta-lactamase production, followed by polymerase chain reaction (PCR)-based detection of clinically important beta-lactamase genes mediating resistant phenotypes among these isolates.


Out of the 761 GNB, Acinetobacter spp., Klebsiella spp., Pseudomonas spp., Enterobacter spp. and others were 27, 23, 21, 17, 5 and 7% respectively. A high prevalence of ESBL was found across all genera in these strains. The carbapenem resistance was higher in North than in South Indian GNB. The level of AmpC production was comparatively lower in both North and South Indian strains.


Beta-lactamases showed tremendous variation in geographic distribution. Thus, their detection and characterization is important from a clinical-epidemiological, laboratory and infection control point of view. Knowledge of this epidemiology can predict the empiric antimicrobial treatment.

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