Back

PulseNet international: the missing link between PFGE and WGS

Adam, I. E.-k. M.

2021-03-09 bioinformatics
10.1101/2021.03.08.434411 bioRxiv
Show abstract

IntroductionDNA-based surveillance of bacterial diseases has been using pulsed field gel electrophoresis (PFGE) since 1996. Currently, the international surveillance network (PulseNet international) is turning toward whole genome sequencing (WGS). ATCGs of WGS are compared using several sequence alignment methods. While patterns of horizontal lines of PFGE profiles are being compared using relative positioning of bands within a range of tolerance. A recently suggested image analysis algorithm and a deployed database (geltowgs.uofk.edu) collectively invented a promising method for comparing PFGE to in-silico obtained digestion models (DMs) derived from WGS. The database requires a parameter that determines PFGE resolution. Here, the author suggests a new method for calculating this factor. Epidemiological and molecular conclusions returned by the database are evaluated. Methodologytwo PFGE profiles representing XbaI digests of E. coli and Salmonella enterica analyzed by the suggested image analysis algorithm were submitted to the database after calculating resolution of PFGE using Dice percentage of difference between the closest PFGE bands in length. E. coli and Salmonella enterica test subjects were compared to 489 and 401 DMs respectively. The three data sets returned were analyzed. Results and conclusionsaccording to modified PFGE evaluation criteria; a single DM is possibly related to E. coli test subject. It belonged to the same serovar. No epidemiologically related DM was shown for S. enterica test subject. Conclusions mentioned earlier could never be made ignoring co-migration. Standardization of both; suggested image analysis and database algorithms will deepen our understanding of bacterial epidemiology by means of possible qualitative approach built upon identification of fragment sequences and their locations within chromosomes.

Matching journals

The top 5 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.