Whole genome analysis unveils genetic diversity and potential virulence determinants in Vibrio parahaemolyticus associated with disease outbreak among cultured Litopenaeus vannamei (Pacific white shrimp) in India.
Kattapuni Suresh PrithvisagarBallamoole Krishna KumarToshio KodamaPraveen RaiTetsuya IidaIddya KarunasagarIndrani KarunasagarPublished in: Virulence (2022)
Vibrio parahaemolyticus has caused widespread mortality in Indian shrimp aquaculture in recent years. However, there are insufficient genome data for the isolates from Indian shrimp vibriosis to analyze genetic diversity and track the acquisition of genetic features that could be involved in virulence and fitness. In this study, we have performed genome analysis of V. parahaemolyticus isolated from moribund shrimps collected from shrimp farms along coastal Karnataka, India, for better understanding of their diversity and virulence. Five newly sequenced genomes of V. parahaemolyticus along with 40 genomes retrieved from NCBI were subjected to comparative genome analysis. The sequenced genomes had an overall genome size of 5.2 Mb. MLST analysis and core genome phylogenomic analysis revealed considerable genetic diversity among the isolates obtained from the moribund shrimps. Interestingly, none of the V. parahaemolyticus isolates possessed the classical features (PirAB) of the strains associated with Acute Hepatopancreatic Necrosis Disease (AHPND). This study also revealed the presence of multiple virulence attributes, including ZOT, ACE and RTX toxins, secretion systems, and mobile genetic elements. The findings of this study provide insights into the possible transition of an environmental V. parahaemolyticus to emerge as pathogens of aquaculture species by increasing its virulence and host adaptation. Future studies focusing on continuous genomic surveillance of V. parahaemolyticus are required to study the evolution and transmission of new variants in shrimp aquaculture, as well as to design and implement biosecurity programs to prevent disease outbreaks.
Keyphrases
- genetic diversity
- escherichia coli
- pseudomonas aeruginosa
- biofilm formation
- staphylococcus aureus
- antimicrobial resistance
- genome wide
- public health
- type diabetes
- cardiovascular disease
- machine learning
- intensive care unit
- single cell
- coronary artery disease
- risk assessment
- deep learning
- liver failure
- multidrug resistant
- drug induced
- respiratory failure