Open Access

Complete genome sequence of new bacteriophage phiE142, which causes simultaneously lysis of multidrug-resistant Escherichia coli O157:H7 and Salmonella enterica

  • Luis Amarillas1, 2,
  • Cristobal Chaidez3,
  • Arturo González-Robles4 and
  • Josefina León-Félix1Email author
Standards in Genomic Sciences201611:89

https://doi.org/10.1186/s40793-016-0211-5

Received: 2 June 2016

Accepted: 26 November 2016

Published: 13 December 2016

Abstract

The emergence of antibiotic-resistant foodborne bacteria is a global health problem that requires immediate attention. Bacteriophages are a promising biotechnological alternative approach against bacterial pathogens. However, a detailed analysis of phage genomes is essential to assess the safety of the phages prior to their use as biocontrol agents. Therefore, here we report the complete genome sequence of bacteriophage phiE142, which is able to lyse Salmonella and multidrug-resistant Escherichia coli O157:H7 strains. Bacteriophage phiE142 belongs to the Myoviridae family due to the presence of long non-flexible tail and icosahedral head. The genome is composed of 121,442 bp and contains 194 ORFs, and 2 tRNAs. Furthermore, the phiE142 genome does not contain any genes coding for food-borne allergens, antibiotics resistance, virulence factors, or associated with lysogenic conversion. The bacteriophage phiE142 is characterized by broad host range and compelling genetic attributes making them potential candidates as a biocontrol agent.

Keywords

Short genome report phiE142 Enterobacteriaceae bacteriophage Genome sequence Potential biocontrol agent

Introduction

Foodborne diseases are an important cause of morbidity and mortality worldwide, therefore are a serious public health problem [1]. Bacteria cause the majorities of foodborne illnesses; Escherichia coli and Salmonella are among the most common foodborne pathogens that affect millions of people annually [2]. Furthermore, the emergence of antimicrobial resistance E. coli and Salmonella strains makes more difficult its control [3]. Hence, novel control methods for reducing the risk of bacterial food contamination, which are both environmental friendly, are urgently needed.

In this context, bacteriophages have several potential applications in the food industry; these killing-bacteria viruses are alternatives to conventional antimicrobials method for the control of pathogenic bacteria and have great potential in the improvement of food safety [46]. Bacteriophages suitable for biocontrol purposes must be genetically sequenced to ensure that are strictly lytic (always lyse infected cells host), does not encode any bacterial virulence factors or proteins with a potential to cause allergenicity [7, 8].

The primary aim of our research group is increase knowledge of phage biodiversity and contribute to the understanding of different types of phages in several regions of Sinaloa, an important agricultural region in Northwestern Mexico. Recently, a new bacteriophage, designated as phiE142, one of phages isolated, exhibits a high potential as a biocontrol agent [9]. However, information about genome of phage phiE142 is still limited; therefore, to further understand the phage biology, the genome was sequenced.

Organism information

Classification and features

The bacteriophage phiE142 was previously isolated in Food and Environmental Microbiology Laboratory at the Research Center for Food and Development from animal feces samples collected on a farm in Northwestern Mexico. An E. coli strain EC-48 (bacterial used for bacteriophage propagation and titration), was also isolated from the same geographical region two years before the isolation of the phage [10]. Phage phiE142 produced clear plaques of 2 to 3 mm in diameter on the E. coli EC-48 lawn; the plaques were already visible after four to six hours of incubation time at 37 °C.

We analyzed the lytic host range of phage using spot tests assays of different bacterial, including 48 Salmonella strains and 33 E. coli strains (Additional file 1: Table S1). Based upon spot testing results, the phage phiE142 had lytic activity against 76% of the E. coli strains and 29% of Salmonella strains tested. These results indicate that bacteriophage phiE142 has the potential to be evaluated as an alternative strategy to biocontrol of E. coli and Salmonella .

The phiE142 phage was stained with 2% uranyl acetate and examined by transmission electron microscopy (TEM) and classified into its appropriate viral morphotype according to Ackermann’s classification [11]. The analysis suggests that phage phiE142 belongs to the order Caudovirales and family Myoviridae based on the presence of almost isometric head with an average diameter of  58 nm, long non-flexible contractile tail about 120 nm in length (Fig. 1) [12]. Phage phiE142 has a genome of 121,442 bp, with a coding region of 94.4%, GC content of 37.4%, and the gene density is 1.60. It contains 194 coding sequences ranging from 102 bp to 3,300 bp, with 53 genes on the positive strand and 141 genes on the negative strand. Phylogenetic characteristics of this phage are indicated in Table 1.
Fig. 1

Transmission electron microscopy (TEM) of bacteriophage phiE142, which exhibits an icosahedral head, long and non-flexible tail. This morphology corresponds to the Myoviridae family

Table 1

Classification and general features of Enterobacteria phage phiE142 according to the MIGS recommendation [29]

MIGS ID

Property

Term

Evidence codea

 

Classification

Domain: viruses, dsDNA viruses, no RNA stage

TAS [11]

  

Phylum: unassigned

 
  

Class: unassigned

 
  

Order: Caudovirales

TAS [11]

  

Family: Myoviridae

TAS [11]

  

Genus: unassigned

 
  

Species: unassigned

 
  

Strain: phiE142

 
 

Gram stain

Not-applicate

 
 

Particle shape

Icosahedral head with long contractile tail

IDA

 

Motility

Not-applicate

IDA

 

Sporulation

Not-applicate

IDA

 

Temperature range

Not-reported

 
 

Optimum temperature

Not-reported

 
 

pH range; Optimum

Not-reported

 
 

Carbon source

Not-applicate

 

MIGS-6

Habitat

Equine gut

IDA

MIGS-6.3

Salinity

Not-reported

 

MIGS-22

Oxygen requirement

Not-applicate

 

MIGS-15

Biotic relationship

Intracellular parasite of E. coli strain EC-48

IDA

MIGS-14

Pathogenicity

Lytic phage of E. coli strain EC-48

IDA

MIGS-4

Geographic location

Elota, Sinaloa, México

IDA

MIGS-5

Sample collection

March 04, 2014

IDA

MIGS-4.1

Latitude

23°54′35.8″N

IDA

MIGS-4.2

Longitude

106°54′28.2″W

IDA

MIGS-4.3

Depth

0 m

IDA

MIGS-4.4

Altitude

20 m

IDA

a Evidence codes - IDA Inferred from Direct Assay, TAS Traceable Author Statement. These evidence codes are from the Gene Ontology project [30]

The sequence of DNA polymerase has become a commonly-used marker for constructing phylogenetic analysis, therefore the phylogenetic tree was performed based of DNA polymerase deduced amino acid sequences. According to the phylogenetic tree, the phage phiE142 and others eight phages that infect the bacterial family Enterobacteriaceae were clustered in the same group (Figs. 2 and 3). All of these phages are members of the Tevenvirinae subfamily and are strictly lytic (Based on PHACTS program server). Considering the close relationship among these phages, it is likely that phiE142 also belongs to this genus. This result confirms the findings obtained by electron microscopy.
Fig. 2

Phylogenetic tree based on the predicted amino acid sequences of the DNA polymerase of 17 bacteriophages. Phylogenetic tree was performed in MEGA 6.0 version by the neighbor joining method with the Jukes Cantor model. The percentages of bootstrap samples (of 1,000) are indicated for each internal branch. The scale bar indicates the proportion of substitutions per site

Fig. 3

Diagram of bacteriophage genome. The arrows indicated open reading frame (ORF), the orientation of which shows the direction of transcription. Putative genes are colored according to the predicted functions of their products: Phage structural proteins (blue arrows), DNA regulation module (green arrows), packaging module (pink arrows), host lysis proteins (red arrows), and hypothetical proteins (gray arrows)

Genome sequencing information

Genome project history

The bacteriophage phiE142 is one of the first genome to be completely sequenced publicly available for a phage infecting E. coli and Salmonella strains isolated from environmental sources in Northwest Mexico. The analysis of more genomes of bacteriophages is necessary to increase our understanding of the genetic diversity of bacteriophages, phage biology, basic molecular mechanisms, and provide a deeper insight into the relationship of phages with their hosts. Furthermore, analysis of phage genomes may reveal novel antimicrobial peptides and enzymes with bactericidal activity. In addition, the genome well understood is an essential requisite to ensure the safety of the phages prior to their use as biocontrol agents. Therefore, the genome project was deposited in the Genomes On Line Database (GOLD). The genome sequence of bacteriophage phiE142 was deposited in GenBank under accession number KU255730. The summary of genome project is available in the Table 2.
Table 2

Project information

MIGS ID

Property

Term

MIGS 31

Finishing quality

Finishing

MIGS-28

Libraries used

Standard Illumina paired-end

MIGS 29

Sequencing platforms

Illumina HiSeq

MIGS 31.2

Fold coverage

~10,000×

MIGS 30

Assemblers

Velvet-Geneious R8

MIGS 32

Gene calling method

Geneious R8

 

Locus Tag

phiE142_

 

Genbank ID

KU255730.1

 

GenBank Date of Release

January 19, 2016

 

GOLD ID

Gp0128385

 

BIOPROJECT

NAa

MIGS 13

Source Material Identifier

NAa

 

Project relevance

Bacteriophage candidate as a biological control agent

Growth conditions and genomic DNA preparation

Standard double-layer agar plate method was used to obtain high-titer stocks of the phage phiE142 [13], with some modifications. Briefly, 100 μl of phage stock and 1 ml of overnight culture of E. coli strain EC-48 were mixed with 3 ml TSB with 0.4% agarose, spread on TSA plates, and incubated overnight at 37 °C. After, phage was subsequently collected by adding 6 ml of SM buffer (50 mM Tris-HCl, pH 7.5, 0.1 M NaCl, 8 mM MgSO4, 0.01% gelatin) to the surface of each plate and the soft agar was scraped off the surface of the agar plates. Cell debris was removed by subsequent centrifugation at 5,500 × g for 10 min, the supernatant was filtered with 0.22 μm syringe filters, and phage particles were precipitated by centrifugation at 40,000 × g at 4 ° C for 2 h. The phage pellet was suspended in SM buffer and stored at 4°C. Bacteriophage DNA was isolated by the method of proteinase K and phenol–chloroform as previously described [14], with minor modifications. One milliliter of purified phage suspension was treated with 1 μg/ml of DNaseI and RNaseA (Sigma-Aldrich) at 37 °C for 1 h. Subsequently, sodium dodecyl sulfate (final concentration, 0.5%), EDTA (20 mM, pH 8.0), and proteinase K (final concentration, 25 μg/ml) were added, and the suspension was incubated at 56 °C for 1 h. After proteins were removed by an equal volume of phenol-chloroform (1:1), and DNA was precipitated from the aqueous phase by cold ethanol. Following centrifugation at 15, 000 × g for 15 min at 4 °C, the pellet was washed twice with 70% ethanol, centrifuged at the same conditions. Finally, the dried DNA pellet was suspended in nuclease-free water. Concentration of phage DNA was estimated with a NanoDrop spectrophotometer (Thermo Fisher Scientific, Wilmington, DE) and also the quality of extracted DNA was also tested visually with electrophoresis on a 1% agarose.

Genome sequencing and assembly

High-throughput DNA Sequencing of phage genomic DNA was performed using HiSeq 2000 technology (Illumina) to produce 100 bp paired-end reads, library construction and sequencing were performed according to the manufacturer’s instructions. In total, about 18 million pair reads of 100 bases in length were obtained with a quality filter threshold of Q30. The reads were analyzed and quality checked using FastQC and Geneious software package R8 (Biomatters Ltd., New Zealand) was used to trim raw reads with a low quality score. The de novo assembly was conducted with Velvet (implemented in Geneious, running VelvetOptimiser for selection of k-mer), resulting in one final contig with coverage from approximately 10,000-fold. Additional manual functional annotation and genome map was performed using Geneious software.

Genome annotation

Open reading frames (ORFs) were identified using Glimmer 3.02 [15], GeneMark.hmm [16], and ORF Finder [17]. The putative functions of the ORFs were analyzed by protein BLASTp searches, with a cut off E value of 10−4. Predicted protein sequences were analyzed against InterProScan [18], Pfam [19] and TMHMM Server version 2.0 [20] for conservative domain identification. Signal peptides were predicted using SignalP 4.1. The search of putative tRNA encoding genes was done using ARAGORN [21] and tRNAscan-SE [22]. The origin of replication was predicted using a GC-skew plot generated by GenSkew [23]. Moreover, all identified ORFs were compared against the virulence factor database [24] and the ResFinder database [25]. Additionally, the predicted phage protein sequences were searched to identify proteins potentially allergenic using tools from the Food Allergy Research and Resource Programme [26]. The lifestyle of the phages was predicted using the PHACTS program [27]. Whole genome comparisons were carried out using Mauve [28].

Genome properties

The detailed annotation information for phage genome was summarized in Table 3. The phage has a DNA genome consisting of 121,442 bp with a GC content of 37.4%, which is significantly lower than that of the host E. coli (about 50% GC). Genome analysis of the phage revealed 194 putative open reading frames (94.4% of the genome consists of a coding region), with 26 oriented in a forward orientation and 168 in a reverse orientation, and two tRNA genes were identified. Based on BLAST results, functions were assigned to 95 of the genes; most of the annotated genes (98 genes) were hypothetical proteins, probably due to the enormous diversity of bacteriophages and the insufficient database information about the functional genes of phage. Only one gene product is hypothetical novel proteins (Additional file 2: Table S2). The distribution of the ORFs into COG functional categories is provided in Table 4.
Table 3

Genome statistics

Attribute

Value

% of Totala

Genome size (bp)

121,442

100.00

DNA coding (bp)

114,642

94.40

DNA G + C (bp)

45,419

37.40

DNA scaffolds

1

100.00

Total genes

196

100.00

Protein coding genes

194

98.98

RNA genes

2

1.02

Pseudo genes

0

0.00

Genes in internal clusters

0

0.00

Genes with function prediction

95

48.47

Genes assigned to COGs

148

75.51

Genes with Pfam domains

62

31.96

Genes with signal peptides

5

2.57

Genes with transmembrane helices

15

7.73

CRISPR repeats

0

0.00

aThe total is based on the total number of protein coding genes in the genome

Table 4

Number of genes associated with general COG functional categories

Code

Value

% of Totala

Description

J

5

2.55

Translation, ribosomal structure and biogenesis

A

1

0.51

RNA processing and modification

K

3

1.53

Transcription

L

17

8.67

Replication, recombination and repair

B

0

0.00

Chromatin structure and dynamics

D

2

1.02

Cell cycle control, Cell division, chromosome partitioning

V

0

0.00

Defense mechanisms

T

6

3.06

Signal transduction mechanisms

M

0

0.00

Cell wall/membrane biogenesis

N

0

0.00

Cell motility

U

0

0.00

Intracellular trafficking and secretion

O

6

3.06

Posttranslational modification, protein turnover, chaperones

C

0

0.00

Energy production and conversion

G

0

0.00

Carbohydrate transport and metabolism

E

12

6.12

Amino acid transport and metabolism

F

11

5.61

Nucleotide transport and metabolism

H

5

2.55

Coenzyme transport and metabolism

I

0

0.00

Lipid transport and metabolism

P

0

0.00

Inorganic ion transport and metabolism

Q

0

0.00

Secondary metabolites biosynthesis, transport and catabolism

R

20

10.20

General function prediction only

S

60

30.61

Function unknown

-

48

24.48

Not in COGs

aThe total is based on the total number of protein coding genes in the genome

Insights from the genome sequence

The results of BLAST revealed that the genome of phage phiE142 has a high similarity (query coverage, 94%; identity, 97%) with coliphage vB_EcoM_PhAPEC2, which belong to the Tevenvirinae subfamily of the genus T4-like viruses, an observation that is consistent with the analysis of the DNA polymerase. We therefore concluded that phiE142, based on sequence similarity, belong to the Tevenvirinae subfamily. However, some differences in genome organization were observed, because progressive Mauve genome alignment revealed one colinear block that is in the different order in both bacteriophages (Additional file 3: Figure S3). The principle region of genomic dissimilarity was located between 110,000 pb and 121,000 pb, this region includes a set of ORFs found to be associated with phage-host recognition, suggesting specific features of phage evolution.

The phiE142 genome is functionally organized into four modules containing gene clusters for virion morphogenesis, DNA replication/regulation, DNA packaging, and host cell lysis. This modular organization of the genome is typical of bacteriophages.

Thirty-one ORFs were found to encode proteins involved in the morphogenesis of virions. These include the ORFs 1–3, 170, 172, 175–185, and 187–194, which are proposed to be genes encoding the components of the tail fiber and baseplate. Databases homology searches suggested that ORFs encoding capsid protein are 46, 139, 142, and 174. Additionally, the proteins encoded by ORFs 185 and 186 are most similar in its amino acid sequence to neck protein.

Overall, a total of 46 ORFs are associated with processing of the viral DNA. Our analysis of the phage genomes reveals several genes potentially involved in nucleotide metabolism, including ORFs 14–15, 38–39, 47, 64, 70, 96, 100–101, 125, and 171. In addition, genes that encode proteins involved in replication and transcription of its own DNA were identified in ORFs 5, 7, 12–13, 18, 20–21, 24–25, 28–29, 32, 34–35, 37, 49, 56, 59, 61, 66, 71, 73–76, 78, 81, 86, 102, 106, 130, 132, 141, 144, and 173.

Two ORFs exhibit similarity to a gene involved in the host cell lysis, including endolysin and holin. The protein encoded by ORF 143 displays a high degree of identity with the endolysin. This ORF contained one glycohydrolase domain (hydrolyse the beta-1,4-glycosidic bond between N-acetylmuramic acid and N-acetylglucosamine), which indicates that this protein is probably an enzyme that degrades peptidoglycan. While the putative protein of ORF 4 was identified as a holin protein. Unusually, this ORF is not located adjacent to the endolysin ORF, in most genomes bacteriophages, the holin ORF is adjacent or overlaps a ORF encoding an endolysin. The deduced holin encoded by phiE142 phage has one putative transmembrane domain, and thus resembles class III holins.

The phage lifestyle prediction result of PHACTS indicated that the phiE142 is a virulent phage, consistent with the results of genomic analysis, which revealed the absence of genes associated with the establishment and maintenance of lysogenic cycle.

The DNA packaging module includes ORF 60, which encode the putative portal protein. However, it was not possible to identify the terminase subunits.

Conclusions

Our data suggest that phiE142 is a member of T4-like virus genus of the Myoviridae family and the Tevenvirinae subfamily. Interestingly, in silico analyses of phiE142 genome did not exhibit homology to known virulence-associated genes, genes involved in lysogeny nor to antibiotic resistance genes or potential immunoreactive allergens. These results indicate that phage phiE142 exhibits genetics properties suitable for evaluation as a biocontrol agent.

Abbreviations

GOLD: 

Genomes On Line Database

ORFs: 

Open reading frames

PHACTS: 

Phage Classification Tool Set

TEM: 

Transmission electron microscopy

TSA: 

Tryptic soy agar

TSB: 

Tryptic soy broth

Declarations

Acknowledgements

The support from the Fundación Produce Sinaloa is gratefully acknowledged. The authors thank the National Food Safety Research Laboratory (LANIIA) at the Research Center for Food and Development (CIAD, Mexico) for providing laboratory facilities during the research. We thank Dr. Mitzi Estrada Acosta for her assistance with data presentation. The authors would like to acknowledge the technical assistance of QFB Lucía Margarita Rubí Rangel and QFB Jesús Héctor Carrillo Yáñez.

Authors’ contributions

LA analyzed the genome sequence and participated in the sequence alignment and drafted the manuscript. JLF conceived of the study, and participated in its design and coordination and helped to draft the manuscript. CC participated in the design of the study and helped to revise the manuscript. Transmission electron microscopy examinations were done by AGR. All authors read and approved the final manuscript.

Competing interests

The authors declare that they have no competing interests.

Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

Authors’ Affiliations

(1)
Laboratorio de Biología Molecular y Genómica Funcional, Centro de Investigación en Alimentación y Desarrollo, A.C
(2)
Laboratorio de Genética, Instituto de Investigación Lightbourn. A. C
(3)
Laboratorio Nacional para la Investigación en Inocuidad Alimentaria, Centro de Investigación en Alimentación y Desarrollo
(4)
Departamento de Infectómica y Patogénesis Molecular, Centro de Investigación y de Estudios Avanzados, Instituto Politécnico Nacional

References

  1. Torgerson PR, de Silva NR, Fèvre EM, Kasuga F, Rokni MB, Zhou X-N, et al. The global burden of foodborne parasitic diseases: An update. Trends Parasitol. 2014;30:20–6. Available at: http://www.ncbi.nlm.nih.gov/pubmed/24314578.View ArticlePubMedGoogle Scholar
  2. Ahmed A, Shimamoto T. Isolation and molecular characterization of Salmonella enterica, Escherichia coli O157:H7 and Shigella spp. from meat and dairy products in Egypt. Int J Food Microbiol. 2013;168:57–62. Available at: http://www.ncbi.nlm.nih.gov/pubmed/24239976.PubMedGoogle Scholar
  3. Johannessen GS, Eckner KF, Heiberg N, Monshaugen M, Begum M, Økland M, et al. Occurrence of Escherichia coli, Campylobacter, Salmonella and Shiga-Toxin producing E. coli in Norwegian primary strawberry production. Int J Environ Res Public Health. 2015;12:6919–32.View ArticlePubMedPubMed CentralGoogle Scholar
  4. Ghasemi SM, Bouzari M, Emtiazi G. Preliminary characterization of Lactococcus garvieae bacteriophage isolated from wastewater as a potential agent for biological control of lactococcosis in aquaculture. Aquacult Int. 2014;22:1469–80. Available at: http://www.mdpi.com/1660-4601/12/6/6919.View ArticleGoogle Scholar
  5. Carlton R, Noordman W, Biswas B, de Meester ED, Loessner M. Bacteriophage P100 for control of Listeria monocytogenes in foods: Genome sequence, bioinformatic analyses, oral toxicity study, and application. Regul Toxicol Pharmacol. 2005;43:301–12. Available at: http://www.ncbi.nlm.nih.gov/pubmed/16188359.View ArticlePubMedGoogle Scholar
  6. Hudson J, Billington C, Wilson T, On S. Effect of phage and host concentration on the inactivation of Escherichia coli O157: H7 on cooked and raw beef. Food Sci Technol Int. 2013;21:104–9. Available at: http://www.ncbi.nlm.nih.gov/pubmed/24285831.View ArticlePubMedGoogle Scholar
  7. Hagens S, Loessner MJ. Application of bacteriophages for detection and control of foodborne pathogens. Appl Microbiol Biotechnol. 2007;76:513–9. Available at: http://www.ncbi.nlm.nih.gov/pubmed/17554535.View ArticlePubMedGoogle Scholar
  8. Hungaro HM, Mendonça RCS, Gouvêa DM, Vanetti MCD, de Oliveira PCL. Use of bacteriophages to reduce in chicken skin in comparison with chemical agents. Food Res Int. 2013;52:75–81. Available at: http://www.sciencedirect.com/science/article/pii/S0963996913001373.View ArticleGoogle Scholar
  9. CastrodelCampo N, Amarillas Bueno LA, García Camarena MG, Chaidez Quiroz C, León Félix J, Martínez Rodríguez CI. Presencia de Salmonella y Escherichia coli O157:H7 en la zona centro del estado de Sinaloa y su control biológico mediante el uso de bacteriófagos [abstract no. C39], XIII Congreso Internacional de Inocuidad de Alimentos. 2011. p. 165–8. Available at: http://sistemanodalsinaloa.gob.mx/archivoscomprobatorios/_14_resumeneventoscientificos/1034.pdf.Google Scholar
  10. Amézquita-López B, Quiñones B, Cooley M, León-Félix J, Campo C, Mandrell R, et al. Genotypic analyses of Shiga toxin-producing Escherichia coli O157 and non-O157 recovered from feces of domestic animals on rural farms in Mexico. PLoS One. 2012;7:e51565. Available at: http://www.ncbi.nlm.nih.gov/pubmed/23251577.View ArticlePubMedPubMed CentralGoogle Scholar
  11. Ackermann H-W. Phage classification and characterization. In: Clokie MRJ, Kropinski A, editors. Methods in Molecular Biology. ᅟ: Springer Science + Business Media; 2009. p. 127–40. Available at: http://www.springer.com/us/book/9781588296825.Google Scholar
  12. King AMQ, Adams MJ, Carstens EB, Lefkowitz EJ. Virus taxonomy: classification and nomenclature of viruses: ninth report of the international committee on taxonomy of viruses. San Diego: Elsevier Academic Press; 2012. p. 855–80.Google Scholar
  13. Carey-Smith G, Billington C, Cornelius A, Hudson J, Heinemann J. Isolation and characterization of bacteriophages infecting Salmonella spp. FEMS Microbiol Lett. 2006;258:182–6. Available at: http://www.ncbi.nlm.nih.gov/pubmed/16640570.View ArticlePubMedGoogle Scholar
  14. Sambrook J, Russell DW. Molecular Cloning: A laboratory manual. 3rd ed. New York: Cold Spring Harbor Laboratory Press; 2001.Google Scholar
  15. Delcher AL, Bratke KA, Powers EC, Salzberg SL. Identifying bacterial genes and endosymbiont DNA with glimmer. Bioinformatics. 2007;23:673–9. Available at: http://www.ncbi.nlm.nih.gov/pubmed/17237039.View ArticlePubMedPubMed CentralGoogle Scholar
  16. Besemer J, Lomsadze A, Borodovsky M. GeneMarkS: A self-training method for prediction of gene starts in microbial genomes. Implications for finding sequence motifs in regulatory regions. Nucleic Acids Res. 2001;29:2607–18. Available at: http://www.ncbi.nlm.nih.gov/pubmed/11410670.View ArticlePubMedPubMed CentralGoogle Scholar
  17. Rombel IT, Sykes KF, Rayner S, Johnston SA. ORF-FINDER: A vector for high-throughput gene identification. Gene. 2002;282:33–41. Available at: http://www.ncbi.nlm.nih.gov/pubmed/11814675.View ArticlePubMedGoogle Scholar
  18. Quevillon E, Silventoinen V, Pillai S, Harte N, Mulder N, Apweiler R, Lopez R. InterProScan: Protein domains identifier. Nucleic Acids Res. 2005;33:116–20. Available at: http://nar.oxfordjournals.org/content/33/suppl_2/W116.full.View ArticleGoogle Scholar
  19. Finn RD, Bateman A, Clements J, Coggill P, Eberhardt RY, Eddy SR, Heger A, Hetherington K, Holm L, Mistry J, Sonnhammer ELL, Tate J, Punta M. The Pfam protein families database. Nucleic Acids Res. 2014;42:D222–30. Available at: http://nar.oxfordjournals.org/content/42/D1/D222.long.View ArticlePubMedGoogle Scholar
  20. Krogh A, Larsson B, von Heijne G, Sonnhammer EL. Predicting transmembrane protein topology with a hidden markov model: Application to complete genomes. J Mol Biol. 2001;305:567–80. Available at: http://www.ncbi.nlm.nih.gov/pubmed/11152613.View ArticlePubMedGoogle Scholar
  21. Laslett D, Canback B. ARAGORN, a program to detect tRNA genes and tmRNA genes in nucleotide sequences. Nucleic Acids Res. 2004;32:11–6. Available at: http://www.ncbi.nlm.nih.gov/pubmed/14704338.View ArticlePubMedPubMed CentralGoogle Scholar
  22. Lowe TM, Eddy SR. TRNAscan-sE: A program for improved detection of transfer RNA genes in Genomic sequence. Nucleic Acids Res. 1997;25:955–64. Available at: http://nar.oxfordjournals.org/content/25/5/0955.full.View ArticlePubMedPubMed CentralGoogle Scholar
  23. GenSkew – visualization of nucleotide skew in genome sequences. http://mips.gsf.de/services/analysis/genskew.
  24. Chen L, Xiong Z, Sun L, Yang J, Jin Q. VFDB 2012 update: Toward the genetic diversity and molecular evolution of bacterial virulence factors. Nucleic Acids Res. 2011;40:D641-5. Available at: http://www.ncbi.nlm.nih.gov/pubmed/22067448.PubMedGoogle Scholar
  25. Kleinheinz KA, Joensen KG, Larsen MV. Applying the ResFinder and VirulenceFinder web-services for easy identification of acquired antibiotic resistance and E. coli virulence genes in bacteriophage and prophage nucleotide sequences. Bacteriophage. 2014;4:e27943. Available at: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3926868/.View ArticlePubMedPubMed CentralGoogle Scholar
  26. Food Allergy Research and Resource Programme (FARRP). http://www.allergenonline.com.
  27. McNair K, Bailey BA, Edwards RA. PHACTS, a computational approach to classifying the lifestyle of phages. Bioinformatics. 2012;28:614–8. Available at: http://www.ncbi.nlm.nih.gov/pubmed/22238260.View ArticlePubMedPubMed CentralGoogle Scholar
  28. Darling AE, Mau B, Perna NT. Progressive Mauve: Multiple genome alignment with gene gain, loss and rearrangement. PLoS One. 2010;5:e11147. Available at: http://journals.plos.org/plosone/article?id=10.1371%2Fjournal.pone.0011147.View ArticlePubMedPubMed CentralGoogle Scholar
  29. Field D, Garrity G, Gray T, Morrison N, Selengut J, Sterk P, et al. The minimum information about a genome sequence (MIGS) specification. Nat Biotechnol. 2008;26:541–7. Available at: http://www.ncbi.nlm.nih.gov/pubmed/18464787.View ArticlePubMedPubMed CentralGoogle Scholar
  30. Ashburner M, Ball CA, Blake JA, Botstein D, Butler H, Cherry JM, et al. Gene ontology: Tool for the unification of biology. Nat Genet. 2000;25:25–9. Available at: http://www.ncbi.nlm.nih.gov/pubmed/10802651.View ArticlePubMedPubMed CentralGoogle Scholar

Copyright

© The Author(s). 2016