Prediction and Analysis in silico of Genomic Islands in Aeromonas hydrophila

Antonio Camilo da Silva Filho; Jeroniza Nunes Marchaukoski; Roberto Tadeu Raittz; Camilla Reginatto De Pierri; Diogo de Jesus Soares Machado; Cyntia Maria Telles Fadel-Picheth; Geraldo Picheth

doi:10.3389/fmicb.2021.769380

Prediction and Analysis in silico of Genomic Islands in Aeromonas hydrophila

Front Microbiol. 2021 Nov 29:12:769380. doi: 10.3389/fmicb.2021.769380. eCollection 2021.

Authors

Antonio Camilo da Silva Filho¹, Jeroniza Nunes Marchaukoski², Roberto Tadeu Raittz², Camilla Reginatto De Pierri³, Diogo de Jesus Soares Machado², Cyntia Maria Telles Fadel-Picheth¹, Geraldo Picheth¹

Affiliations

¹ Department of Clinical Analysis, Federal University of Parana, Curitiba, Brazil.
² Department of Bioinformatics, Professional and Technical Education Sector, Federal University of Parana, Curitiba, Brazil.
³ Department of Biochemistry and Molecular Biology, Federal University of Parana, Curitiba, Brazil.

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.

Keywords: Aeromonas hydrophila; antibiotic resistance; genomic island; metabolism; virulence.