[Characterization by pulsed-field gel electrophoresis of Salmonella typhimurium isolates recovered in the acute diarrheal disease surveillance program in Colombia, 1997-2004].

INTRODUCTION

In Colombia Salmonella Typhimurium is the second most frequently isolated Salmonella serotype (after S. Enteritidis) from human clinical samples. This serotype represents 28.2% (n=468) of the 1659 Salmonella isolates recovered by the Instituto Nacional de Salud (INS) Acute Diarrheal Diseases Surveillance Program from 1997 to 2004. Previously, little was known about the molecular attributes of these strains and commonality of genetic subtypes among S. Typhimurium isolated from humans in Colombia.

OBJECTIVE

The purpose of this study was to characterize S. Typhimurium isolates circulating in Colombia using pulsed-field gel electrophoresis in order to establish genetic profiles and determine their potential relatedness.

MATERIALS AND METHODS

468 S. Typhimurium isolates were submitted to INS by 14 Public Health Laboratories from January 1997 to December 2004. The pulsed-field gel electrophoresis was performed using restriction enzyme Xbal according to the PulseNet standard protocol (CDC, Atlanta). Restriction pattern analysis and cluster definition were performed using Molecular Analyst Fingerprinting II software.

RESULTS

180 distinct electrophoretic patterns were obtained. Pattern COINJPX.X01.0062 was the most common (21.3% of the 473 isolates, n=101), followed by COINJPX.X01.0001 (8.4%, n=40), COINJPX.X01.0058 (3%, n=13), COINJPX.X01.0003 (2.5%, n=12), COINJPX.X01.0066 (2.3%, n=11), and COINJPX.X01.0108 (1.4%, n=6). COINJPX.X01.0001, was the most prevalent pattern among S. Typhimurium isolated in Bogotá from 1997-2002, but appeared to be replaced both in Bogotá and nationally by COINJPX.X01.0062 in 2003-2004. Cluster analysis demonstrated three distinct groups with 53% and 82% similarity indicating heterogeneity within the serotype.

CONCLUSIONS

The study provides important electrophoretic pattern baseline data, which will be useful for prospective real-time comparison of profiles of future isolates. Cluster detection using this method will facilitate outbreak detection and will enhance our ability to find common sources for seemingly unrelated infections.