Prediction and Analysis in silico of Genomic Islands in Aeromonas hydrophila

Abstract

Aeromonas are Gram-negative rods widely distributed in the environment. They can cause severe infections in fish related to financial losses in the fish industry, and are considered opportunistic pathogens of humans causing infections ranging from diarrhea to septicemia. The objective of this study was to determine in silico the contribution of genomic islands to A. hydrophila. The complete genomes of 17 A. hydrophila isolates, which were separated into two phylogenetic groups, were analyzed using a genomic island (GI) predictor. The number of predicted GIs and their characteristics varied among strains. Strains from group 1, which contains mainly fish pathogens, generally have a higher number of predicted GIs, and with larger size, than strains from group 2 constituted by strains recovered from distinct sources. Only a few predicted GIs were shared among them and contained mostly genes from the core genome. Features related to virulence, metabolism, and resistance were found in the predicted GIs, but strains varied in relation to their gene content. In strains from group 1, O Ag biosynthesis clusters OX1 and OX6 were identified, while strains from group 2 each had unique clusters. Metabolic pathways for myo-inositol, L-fucose, sialic acid, and a cluster encoding QueDEC, tgtA5, and proteins related to DNA metabolism were identified in strains of group 1, which share a high number of predicted GIs. No distinctive features of group 2 strains were identified in their predicted GIs, which are more diverse and possibly better represent GIs in this species. However, some strains have several resistance attributes encoded by their predicted GIs. Several predicted GIs encode hypothetical proteins and phage proteins whose functions have not been identified but may contribute to Aeromonas fitness. In summary, features with functions identified on predicted GIs may confer advantages to host colonization and competitiveness in the environment.

Aeromonas hydrophila ST251 and Aeromonas dhakensis are major emerging pathogens of striped catfish in Vietnam

“…The restricted singleton presentation of vAh ST251 is unusual given the high strain diversity typically encountered in A. hydrophila. Further, the global dissemination of the vAh ST251 epidemic strain is limited to fish hosts thus far, and the pan-genomic analysis presented herein supports the existence of vAh-specific regions within core and accessory genomes that could explain the hypervirulence and host specificity phenotype (Pang et al, 2015;Rasmussen-Ivey et al, 2016;da Silva Filho et al, 2021). Indeed, gene clusters unique to the vAh ST251 lineage have been described previously in relation to prophages, O-antigen biosynthesis and fucose and myo-inositol metabolism (Hossain et al, 2013;Rasmussen-Ivey et al, 2016;Ngo et al, 2022).…”

“…The detection and clonal nature of A. dhakensis was unexpected because A. hydrophila is often cited to be the most important pathogen responsible for MAS in striped catfish in Vietnam (Ngo et al, 2022 ). However, given that A. dhakensis (Aravena-Román et al, 2011 ) and A. hydrophila (Beaz-Hidalgo et al, 2013 ) are frequently misidentified due to overlapping phenotypic traits, shifting classification schemes and a lack of reliable discriminatory tools (Awan et al, 2018 ; da Silva Filho et al, 2021 ), it is highly likely that A. dhakensis is an under-reported cause of mortality in aquatic animals, with disease outbreaks attributed instead to A. hydrophila (Aravena-Román et al, 2011 ). Previously, A. dhakensis (formerly Aeromonas aquariorum ) has been reported in disease events of ornamental fish in Portugal (Martinez-Murcia et al, 2008 ) and Sri Lanka (Jagoda et al, 2014 ), and in eels in Spain (Esteve et al, 2012 ) and China (Guo et al, 2016 ).…”

Whole spectrum of Aeromonas hydrophila virulence determinants and the identification of novel SNPs using comparative pathogenomics

“…Strain misidentification may have a significant impact on the results of diagnostic investigations concerned with microbial pathogens. In a previous study carried out by da Silva Filho et al 41 four misidentified A. hydrophila strains were eliminated from their analysis. Continuous updating of the NCBI database would reflect these rearrangements to avoid any ambiguity during routine BLAST searches, as well as primer or probe design for diagnostics or epidemiological applications.…”