An Excel Macro for Determining Allelic and Sequence Types of Bacterial Clones in Multilocus Sequence Typing

© The Korean Society for Laboratory Medicine..

BACKGROUND: Multilocus sequence typing (MLST) was designed to overcome the low discriminatory power and poor reproducibility of previous molecular typing schemes, and it is useful for inter-laboratory, inter-regional, and inter-national comparison of pathogenic clones. MLST includes labor-intensive sequencing processes and meticulous allelic/sequence type (ST) determination processes, often prone to error. We developed a free automated MLST determination program (MLST typer) based on the Visual Basic for Applications macro, which runs on Microsoft Excel.

METHODS: MLST typer imports sequence data in the FASTA format, converts reverse complement counterparts of the reverse sequences, assembles forward and reverse-complement converted sequences, and returns allelic numbers for each gene and ST of each isolate. To evaluate the performance of MLST typer, we tested the sequence data from 200 clinical isolates, each consisting of seven housekeeping gene sequences, with a total of 1,400 allelic number determinations. The results were compared with manual assessment.

RESULTS: MLST typer comprises three worksheets: the Main page, Result page, and Summary page. The Main page console operates the process according to user-specified parameters. The Result and Summary pages provide the allelic type and ST determinations. It took approximately 12 minutes to analyze the sequence data from 200 clinical isolates. Compared with manual assessment, the rate of correct identification was 97.2% (1,361/1,400).

CONCLUSIONS: MLST typer can be widely used for epidemiological studies owing to its thoroughness in repetitive functions, good compatibility with FASTA type data files, and easy-to-understand outputs for allelic and ST determinations.

Medienart:

E-Artikel

Erscheinungsjahr:

2019

Erschienen:

2019

Enthalten in:

Zur Gesamtaufnahme - volume:39

Enthalten in:

Annals of laboratory medicine - 39(2019), 2 vom: 01. März, Seite 183-189

Sprache:

Englisch

Beteiligte Personen:

Park, Yu Jin [VerfasserIn]
Choi, Min Hyuk [VerfasserIn]
Kim, Dokyun [VerfasserIn]
Lee, Kwangjun [VerfasserIn]
Kim, Hyun Ok [VerfasserIn]
Jeong, Seok Hoon [VerfasserIn]

Links:

Volltext

Themen:

Automatic data processing
Journal Article
Macro
Microsoft Excel
Molecular epidemiology
Multilocus sequence typing
Software

Anmerkungen:

Date Completed 20.02.2019

Date Revised 20.03.2019

published: Print

Citation Status MEDLINE

doi:

10.3343/alm.2019.39.2.183

funding:

Förderinstitution / Projekttitel:

PPN (Katalog-ID):

NLM290629977