DMITRIY BABENKO1, ANAR TURMUHAMBETOVA1, TIM SANDLE2, SORINA ANAMARIA PESTREA3, DAN MORARU4, ANTONELLA CHEŞCĂ4,5
1Karaganda State Medical University, Kazakhstan - 2University of Manchester, United Kingdom - 3Clinical Hospital of Psychiatry and Neurology Braşov - 4Clinical Hospital of Pneumophtysiology Braşov - 5Transilvania University Braşov, Romania
Introduction: Pseudomonas aeruginosa is an important pathogen in nosocomial infections and developed typing techniques are essential allowing researchers to understanding hospital epidemiology. Monitoring the emergence and transmission of Pseudomonas aeruginosa strains permits the elucidation of the source of infection and routes of bacterial transmission. The aim of the present study was an in silico comparison of Pulsed-field gel electrophoresis with different schemes of Multiple Locus Variable- number Tandem Repeat Analysis in terms of discriminatory power and concordance.
Materials and methods: 58 P.aeruginosa whole genomes have been analyzed in silico to determine SpeIdigested PFGE type and subspecies types using different MLVA methods. Resolution power, strength and direction of the concordance between typing methods have been estimated by calculation of the Simpson’s index, the adjusted Rand and the adjusted Wallace coefficients.
Results: The Simpson’s indices of diversity were 1.0 for PFGE and from 0.995 to 0.999 for MLVA schemes with 6-19 markers. The congruence between PFGE and different MLVA methods measured by the adjusted Rand index were from 0.306 to 0.665 on cluster level for PFGE and type level for MLVA. The congruence was slightly higher at the clonal cluster level - from 0.46 to 0.694.
Conclusion: Our in silico study for comparing different MLVA schemes with PFGE, based on Pseudomonas aeruginosa genomes showed, on the one hand, the same high level of discriminatory power of PFGE and MLVA even with 6 tandems markers; nonetheless, on the other hand, there was moderate/poor congruence (no more 70%) between PFGE and MLVA schemes on cluster level.
MLVA, PFGE, Pseudomonas aeruginosa, In Silico, Simpson index, Adjusted Rand index, Adjusted Wallace coefficient