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Comparative genomic analysis of bacteriophages specific to the channel catfish pathogen Edwardsiella ictaluri.

ABSTRACT: BACKGROUND: The bacterial pathogen Edwardsiella ictaluri is a primary cause of mortality in channel catfish raised commercially in aquaculture farms. Additional treatment and diagnostic regimes are needed for this enteric pathogen, motivating the discovery and characterization of bacteriophages specific to E. ictaluri. RESULTS: The genomes of three Edwardsiella ictaluri-specific bacteriophages isolated from geographically distant aquaculture ponds, at different times, were sequenced and analyzed. The genomes for phages eiAU, eiDWF, and eiMSLS are 42.80 kbp, 42.12 kbp, and 42.69 kbp, respectively, and are greater than 95% identical to each other at the nucleotide level. Nucleotide differences were mostly observed in non-coding regions and in structural proteins, with significant variability in the sequences of putative tail fiber proteins. The genome organization of these phages exhibit a pattern shared by other Siphoviridae. CONCLUSIONS: These E. ictaluri-specific phage genomes reveal considerable conservation of genomic architecture and sequence identity, even with considerable temporal and spatial divergence in their isolation. Their genomic homogeneity is similarly observed among E. ictaluri bacterial isolates. The genomic analysis of these phages supports the conclusion that these are virulent phages, lacking the capacity for lysogeny or expression of virulence genes. This study contributes to our knowledge of phage genomic diversity and facilitates studies on the diagnostic and therapeutic applications of these phages.

SUBMITTER: Carrias A

PROVIDER: S-EPMC3025963 | biostudies-literature | 2011

REPOSITORIES: biostudies-literature

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Comparative genomic analysis of bacteriophages specific to the channel catfish pathogen Edwardsiella ictaluri.

Carrias Abel A Welch Timothy J TJ Waldbieser Geoffrey C GC Mead David A DA Terhune Jeffery S JS Liles Mark R MR

Virology journal 20110107

<h4>Background</h4>The bacterial pathogen Edwardsiella ictaluri is a primary cause of mortality in channel catfish raised commercially in aquaculture farms. Additional treatment and diagnostic regimes are needed for this enteric pathogen, motivating the discovery and characterization of bacteriophages specific to E. ictaluri.<h4>Results</h4>The genomes of three Edwardsiella ictaluri-specific bacteriophages isolated from geographically distant aquaculture ponds, at different times, were sequenced ...[more]

PMID: 21214923

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Project description:Assessments of genomic prediction accuracies using artificial intelligent (AI) algorithms (i.e., machine and deep learning methods) are currently not available or very limited in aquaculture species. The principal aim of this study was to examine the predictive performance of these new methods for disease resistance to Edwardsiella ictaluri in a population of striped catfish Pangasianodon hypophthalmus and to make comparisons with four common methods, i.e., pedigree-based best linear unbiased prediction (PBLUP), genomic-based best linear unbiased prediction (GBLUP), single-step GBLUP (ssGBLUP) and a nonlinear Bayesian approach (notably BayesR). Our analyses using machine learning (i.e., ML-KAML) and deep learning (i.e., DL-MLP and DL-CNN) together with the four common methods (PBLUP, GBLUP, ssGBLUP, and BayesR) were conducted for two main disease resistance traits (i.e., survival status coded as 0 and 1 and survival time, i.e., days that the animals were still alive after the challenge test) in a pedigree consisting of 560 individual animals (490 offspring and 70 parents) genotyped for 14,154 single nucleotide polymorphism (SNPs). The results using 6,470 SNPs after quality control showed that machine learning methods outperformed PBLUP, GBLUP, and ssGBLUP, with the increases in the prediction accuracies for both traits by 9.1-15.4%. However, the prediction accuracies obtained from machine learning methods were comparable to those estimated using BayesR. Imputation of missing genotypes using AlphaFamImpute increased the prediction accuracies by 5.3-19.2% in all the methods and data used. On the other hand, there were insignificant decreases (0.3-5.6%) in the prediction accuracies for both survival status and survival time when multivariate models were used in comparison to univariate analyses. Interestingly, the genomic prediction accuracies based on only highly significant SNPs (P < 0.00001, 318-400 SNPs for survival status and 1,362-1,589 SNPs for survival time) were somewhat lower (0.3-15.6%) than those obtained from the whole set of 6,470 SNPs. In most of our analyses, the accuracies of genomic prediction were somewhat higher for survival time than survival status (0/1 data). It is concluded that although there are prospects for the application of genomic selection to increase disease resistance to E. ictaluri in striped catfish breeding programs, further evaluation of these methods should be made in independent families/populations when more data are accumulated in future generations to avoid possible biases in the genetic parameters estimates and prediction accuracies for the disease-resistant traits studied in this population of striped catfish P. hypophthalmus.

Project description:Edwardsiella ictaluri and Edwardsiella piscicida are important fish pathogens affecting cultured and wild fish worldwide. To investigate the genome-level differences and similarities between catfish-adapted strains in these two species, the complete E. ictaluri 93-146 and E. piscicida C07-087 genomes were evaluated by applying comparative genomics analysis. All available complete (10) and non-complete (19) genomes from five Edwardsiella species were also included in a systematic analysis. Average nucleotide identity and core-genome phylogenetic tree analyses indicated that the five Edwardsiella species were separated from each other. Pan-/core-genome analyses for the 29 strains from the five species showed that genus Edwardsiella members have 9474 genes in their pan genome, while the core genome consists of 1421 genes. Orthology cluster analysis showed that E. ictaluri and E. piscicida genomes have the greatest number of shared clusters. However, E. ictaluri and E. piscicida also have unique features; for example, the E. ictaluri genome encodes urease enzymes and cytochrome o ubiquinol oxidase subunits, whereas E. piscicida genomes encode tetrathionate reductase operons, capsular polysaccharide synthesis enzymes and vibrioferrin-related genes. Additionally, we report for what is believed to be the first time that E. ictaluri 93-146 and three other E. ictaluri genomes encode a type IV secretion system (T4SS), whereas none of the E. piscicida genomes encode this system. Additionally, the E. piscicida C07-087 genome encodes two different type VI secretion systems. E. ictaluri genomes tend to encode more insertion elements, phage regions and genomic islands than E. piscicida. We speculate that the T4SS could contribute to the increased number of mobilome elements in E. ictaluri compared to E. piscicida. Two of the E. piscicida genomes encode full CRISPR-Cas regions, whereas none of the E. ictaluri genomes encode Cas proteins. Overall, comparison of the E. ictaluri and E. piscicida genomes reveals unique features and provides new insights on pathogenicity that may reflect the host adaptation of the two species.

Dataset Information

Comparative genomic analysis of bacteriophages specific to the channel catfish pathogen Edwardsiella ictaluri.

Publications

Comparative genomic analysis of bacteriophages specific to the channel catfish pathogen Edwardsiella ictaluri.

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