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Optimization of computer software settings improves accuracy of pulsed-field gel electrophoresis macrorestriction
William M Duck1, Christine D Steward, Shailen N Banerjee
1Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, Georgia 30322 and Division of Healthcare Quality Promotion, Centers for Disease Control and Prevention, Atlanta, Georgia 30333, USA.
Abstract:
Computer-assisted analysis of pulsed-field gel electrophoresis (PFGE) libraries can facilitate comparisons of fragment patterns present on multiple gels. We evaluated the ability of the Advanced Analysis (version 4.01) and Database (version 1.12) modules of the Phoretix gel analysis software package (Nonlinear USA, Inc., Durham, N.C.) to accurately match DNA fragment patterns. Two gels containing 38 lanes of SmaI-digested Enterococcus faecalis OG1RF DNA were analyzed to assess the impact of (i) varying the lane position of the standards, (ii) using gel plugs made at different times, and (iii) normalizing the fragment patterns by using molecular weight (MW) algorithms versus retardation factor (R(f)) algorithms. Two sets of PFGE libraries (one containing SmaI restriction patterns from 62 Enterococcus faecium isolates and the other containing SmaI restriction patterns of 89 Staphylococcus aureus isolates) were analyzed to assess the impact of varying the matching tolerance algorithm (designated as the vector box setting [VBS]) in the Phoretix software. Varying the lane position of standards on a gel and using gel plugs made on different days resulted in different VBSs, although it was not possible to judge whether those differences were statistically significant. Normalization of E. faecalis OG1RF fragment patterns by R(f) and MW methodology yielded no statistically significant differences in variability between the same fragment on different lanes. Suboptimal VBSs decreased the specificity with which related isolates were grouped together in dendrograms. The optimal VBS for analysis of PFGE fragment patterns from E. faecalis isolates differed from that for S. aureus isolates and sometimes was not that recommended by the manufacturer. Thus, computer-assisted analysis of PFGE patterns seemed to compensate for the intra- and intergel variation evaluated in the present study, and optimizing the software for the species to be tested was a critical preliminary step before further PFGE library analysis.