Multicolor Melting Curve Analysis-Based Multilocus Melt Typing of Vibrio parahaemolyticus

Abstract

Vibrio parahaemolyticus is the leading cause of seafood-borne gastroenteritis outbreaks. To track the source of these diseases in a timely manner, a high throughput typing method is critical. We hereby describe a novel genotyping method for V. parahaemolyticus, termed multilocus melt typing (MLMT), based on multilocus sequence typing (MLST). MLMT utilizes melting curve analysis to interrogate the allelic types of a set of informative single nucleotide polymorphisms (SNPs) derived from the housekeeping genes used in MLST. For each SNP, one allelic type generates distinct Tm values, which are converted into a binary code. Multiple SNPs thus generate a series of binary codes, forming a melt type (MT) corresponding with a sequence type (ST) of MLST. Using a set of 12 SNPs, the MLMT scheme could resolve 218 V.parahaemolyticus isolates into 50 MTs corresponding with 56 STs. The discriminatory power of MLMT and MLST was similar with Simpson's index of diversity of 0.638 and 0.646, respectively. The global (adjusted Rand index = 0.982) and directional congruence (adjusted Wallace coefficient, MT→ST = 0.965; ST→MT = 1.000) between the two typing approaches was high. The entire procedure of MLMT could be finished within 3 h with negligible hands on time in a real-time PCR machine. We conclude that MLMT provides a reliable and efficient approach for V. parahaemolyticus genotyping and might also find use in other pathogens.

Fig 1. Flowchart of MLMT analysis of V. parahaemolyticus.

The flowchart illustrates the typing procedure from SNP detecting to data handling. Isolated genomic DNA is first aliquoted into four PCR reactions (R1-R4). Each reaction detects three SNP sites using three differently fluorophore-labeled probes (FAM, HEX, and ROX). The produced twelve T_m values by four PCR reactions are then converted into a 12-digit binary code, which forms a melt type (MT). Isolate A (MT-3) and isolate B (MT-68) are shown as examples. The rule of converting T_ms into binary codes is illustrated in the insert.

Fig 2. MLMT analysis results of 218 V. parahaemolyticus isolates.

The frequency of each MT is given together with the number of the corresponding ST. Also given are the type and number of STs of all the MTs obtained from the 218 isolates. The size of the pies illustrates the relative number of MTs but not in a true scale.

Fig 3. Melting curves obtained from the 218 isolates.

Melting curves from those isolates displaying unique T_m values are shown in color. The non-template controls are shown in grey.

Fig 4. A goeBURST snapshot for population structures of 56 STs derived from 218 V. parahaemolyticus isolates superimposed by the corresponding MTs.

Colored circles represent clinical isolates from Shenzhen (red), clinical isolates from Xiamen (blue), and environmental isolates from Xiamen (green). The size of the circle represents the relative abundance of the ST. The orange dots linked by grey lines represent those STs differed by a single locus variation from the ancestral ST within one CC. The boxes with dotted lines represent one MT. The numbers shown in grey color are from the MLST database but absent in this study. Panels from A to E represent five levels of relatedness between MT and ST.