Investigation and drug resistance analysis of Vibrio parahaemolyticus contamination in nearshore seawater in Dapeng New district,Shenzhen
Objective To understand the contamination status,serotype,virulence gene distribution and drug resistance of Vibrio parahaemolyticus in nearshore seawater in Dapeng New district,Shenzhen so as to provide reference for the prevention and control of environmental contamination and foodborne diseases caused by Vibrio parahaemolyticus.Methods From November 2019 to October 2021,nearshore seawater samples in Da Peng New district,Shenzhen was collected for culture,isolation and identification of Vibrio parahaemolyticus.Slide agglutination was used for serotyping;real-time fluorescence PCR was used to analyze virulence genes,and drug resistance test was conducted using Meriere drug-sensitive bacteria identification card.Results A total of 82 strains of Vibrio parahaemolyticus were isolated from 314 samples collected from nearshore seawater,and the detection rate was 26.11％.From August to October,Vibrio parahaemolyticus contaminated the water body at its peak.Group O was divided into 9 serogroups with a composition ratio of 65.85％.No common K6 and K8 types were found.Virulence genotypes tlh+tdh+trh-,tlh+tdh-trh+and tlh+tdh-trh-were toxigenic strains,accounting for 10.98％,and tlh+tdh-trh-were non-toxigenic strains,accounting for 89.02％.The resistance rate to penicillins was high,among which the resistance rate to ampicillin was 98.78％,and the resistance rate to ceftriaxone was 4.88％,the lowest among cephalosporins.The resistance rates to aminoglycosides,quinolones and nitrofurans were 0.00％.Conclusions Vibrio parahaemolyticus contamination was found in nearshore seawater in Dapeng New district,Shenzhen,and the detection rate of Vibrio parahaemolyticus is high in autumn.Some of the isolates carried virulence genes,suggesting a risk of infection in seafood and humans.It is recommended to carry out routine monitoring of Vibrio parahaemolyticus in seawater,strengthen food safety risk monitoring,and provide early warning for foodborne disease outbreaks.
NETL
NSTL
万方数据
