Advanced DNA fingerprint genotyping based on a model developed from real chip electrophoresis data

Rapid high-resolution melting genotyping scheme for Escherichia coli based on MLST derived single nucleotide polymorphisms

Routinely used typing methods including MLST, rep-PCR and whole genome sequencing (WGS) are time-consuming, costly, and often low throughput. Here, we describe a novel mini-MLST scheme for Eschericha coli as an alternative method for rapid genotyping. Using the proposed mini-MLST scheme, 10,946 existing STs were converted into 1,038 Melting Types (MelTs). To validate the new mini-MLST scheme, in silico analysis was performed on 73,704 strains retrieved from EnteroBase resulting in discriminatory power D = 0.9465 (CI 95% 0.9726-0.9736) for mini-MLST and D = 0.9731 (CI 95% 0.9726-0.9736) for MLST. Moreover, validation on clinical isolates was conducted with a significant concordance between MLST, rep-PCR and WGS. To conclude, the great portability, efficient processing, cost-effectiveness, and high throughput of mini-MLST represents immense benefits, even when accompanied with a slightly lower discriminatory power than other typing methods. This study proved mini-MLST is an ideal method to screen and subgroup large sets of isolates and/or quick strain typing during outbreaks. In addition, our results clearly showed its suitability for prospective surveillance monitoring of emergent and high-risk E. coli clones'.

Word Entropy-Based Approach to Detect Highly Variable Genetic Markers for Bacterial Genotyping

Genotyping methods are used to distinguish bacterial strains from one species. Thus, distinguishing bacterial strains on a global scale, between countries or local districts in one country is possible. However, the highly selected bacterial populations (e.g., local populations in hospital) are typically closely related and low diversified. Therefore, currently used typing methods are not able to distinguish individual strains from each other. Here, we present a novel pipeline to detect highly variable genetic segments for genotyping a closely related bacterial population. The method is based on a degree of disorder in analyzed sequences that can be represented by sequence entropy. With the identified variable sequences, it is possible to find out transmission routes and sources of highly virulent and multiresistant strains. The proposed method can be used for any bacterial population, and due to its whole genome range, also non-coding regions are examined.