W120 Classification Essay

1. Introduction

Bacterial viruses (bacteriophages) are considered to be the most prevalent entities in the biosphere [1]. Both lytic and temperate phages act as architects of bacterial evolution and diversification through predation and the facilitation of horizontal gene transfer [2]. The genomic diversity of the bacteriophages appears to be immense and has been proposed to represent the largest source of gene diversity in the natural world, a feature emphasised by the large number of novel genes of unknown function revealed by genome sequencing and meta-genomic studies [3]. The comparative analysis of bacteriophage genome sequences has greatly enhanced our understanding of their diversity, revealing relationships between phage genomes often infecting distantly related host bacteria. Detailed comparative analyses have been applied to phages infecting hosts including Bacillus, Lactococcus, Mycobacterium, Pseudomonas, Salmonella and Vibrio species, marine cyanobacteria, as well as for 337 phages infecting the family Enterobacteriaceae [4,5,6,7,8,9,10,11,12,13,14]. Comparative genomics has revealed the genomes of the dsDNA tailed bacteriophages to be modular. The isolation of phages, closely related at both the nucleotide and protein level, across disparate geographic locations, environments and time indicates that many phage clades are widely distributed and that horizontal gene transfer does not completely mask phage evolution [15,16,17]. Additional selective pressures influencing phage evolution include bacterial immunity systems such as CRISPR (clustered regularly interspaced short palindromic repeats), restriction-modification and abortive infection systems [18,19].

Members of the genus Acinetobacter are strict aerobes, non-motile, non-fermentative, catalase-positive and oxidase-negative Gram-negative rods [20]. The genus has undergone extensive taxonomic changes with members historically classified as Bacterium anitratum (B5W group), Herella vaginicola, Moraxella glucidolytica, Moraxella lwoffii, Micrococcus calcoaceticus, Mima plomorpha and Achromobacter sp [21]. Today, the genus is a complex and heterogeneous group comprised of 55 species with valid names [22]. A variety of molecular methods are employed for species identification including DNA-DNA hybridisation [23], amplified ribosomal DNA restriction analysis [24], multi-locus sequence typing [25,26] and genome sequence data [27]. The first electron micrographs of Acinetobacter phages were published in 1966 and over 100 isolates have since been documented worldwide [28,29,30]. Interest in bacteriophages infecting species of Acinetobacter has increased in recent years, primarily due to the emergence of multi-drug resistant A. baumannii as a prominent opportunistic pathogen associated with nosocomial and community-acquired infections [31]. The significance of multiple-drug resistance in A. baumannii is reflected by the recent classification of this species as a “Priority 1: Critical” pathogen in the World Health Organisation list of pathogens for the research and development of new antibiotics [32]. Infections associated with A. baumannii include ventilator-associated pneumonia, soft tissue infections associated with wounds and burns, bacteraemia, urinary tract infections and secondary meningitis [33]. Notably, other Acinetobacter species are being associated with nosocomial infections with increasing frequency and have been suggested to represent emerging pathogens [34].

This work presents a review of the Acinetobacter phages sequenced to date, expanding upon previous classifications to encompass new phage isolates using available genomic and morphological data [29]. To investigate their genetic diversity, 37 sequenced Acinetobacter phage genomes were re-annotated and examined using a comparative bioinformatics approach based upon whole genome alignments, protein clustering and phylogenetic analysis.

2. Materials and Methods

Whole genome sequences were downloaded from GenBank (Table 1). Five Acinetobacter prophages isolated and sequenced following induction from their bacterial host were deliberately excluded from this study. Searches were performed using BLASTn (megablast and dc-megablast) and tBLASTx with an E-value cut-off of 0.1 for each phage to identify similar phage genomes deposited in the international sequence databases [35]. Nucleotide dot-plots were prepared using Gepard [36] and average nucleotide identity (ANI) was calculated using the BLASTn algorithm in JSpecies 1.2.1 [37].

Phage genomes were re-annotated using a combination of GeneMark, Glimmer and Prodigal to identify open reading frames (ORFs) [38,39,40]. Where the ORF predictions did not agree, start sites were chosen after manual inspection of upstream sequences for putative ribosome binding sites and evidence obtained from searches using BLASTp. Functional inferences for ORFs encoded by all phages were obtained from searches of the non-redundant database using BLASTp with an e-value cut-off of 0.1 as well as conserved domains and motifs identified using pfam_scan.pl against the Pfam31 database and InterProScan 5.25-64 [41,42]. Translated ORF sequences were also searched against hidden Markov model profiles downloaded from the prokaryotic Virus Orthologous Groups database [43] using hmmscan [44] with an e-value cut-off of 1 × 10−3. Matches to pVOG profiles were considered significant at an e-value of ≤ 1 × 10−15 and ≥35% coverage of the profile HMM. Putative rho-independent terminators were predicted using ARNold and TransTermHP v2.0.9, respectively [45,46]. tRNAScan-SE and ARAGORN were used to predict tRNAs [47,48].

For the identification of orthologous groups of proteins, translated ORF sequences were clustered into groups using OrthoMCL with an e-value of 1e−5 and an inflation value of 1.15 [49]. The OrthoMCL matrix was converted to a binary matrix such that the presence and absence of a gene was denoted as 1 and 0, respectively, for each phage isolate. This matrix was used to calculate Jaccard distances between each phage and was subsequently converted to Nexus format using the phylogeny.fr format converter [50,51] and loaded into SplitsTree [52]. Proteins grouped by OrthoMCL were aligned using Clustal Omega [53] and these alignments were then used to search the uniprot20_2015_06 database using HHblits with one iteration and an e-value threshold of 0.001 [54]. Hidden Markov models were constructed from the expanded HHblits alignments produced using HHmake and then queried against the pdb70_from_mmcif_05July17 database using HHsearch. Remote homologies identified using HHsearch were used to further refine the phage genome annotations. Comparisons of conserved gene product content between the Acinetobacter phages and the wider sequenced phage pool were performed using CoreGenes3.5 [55]. Genome maps were prepared in Scalable Vector Graphics format using the CGView Comparison Tool [56] or EasyFig [57] and edited using Adobe Illustrator.

Phage transmission electron micrographs were provided courtesy of members of the phage research community (c.f. Acknowledgements) or are reproduced with the permission of the respective publishers. The micrograph of phage 133 was reproduced from Archives of Virology, A catalogue of T4-type bacteriophages, volume 142, 1997, page 2337, Ackermann, H.-W. & Krisch, H.M. (© Springer-Verlag 1997) with permission of Springer. The micrograph of phiAB2 was reproduced from Lin et al. Isolation and characterization of ϕAB2: a novel bacteriophage of Acinetobacter baumannii. Research in Microbiology 2010; 161(4):308–314. Copyright © 2010 Elsevier Masson SAS. All rights reserved. The micrograph of R3177 was reproduced from Archives of Virology, Complete genome sequence of the siphoviral bacteriophage Βϕ-R3177, which lyses an OXA-66-producing carbapenem-resistant Acinetobacter baumannii isolate, volume 160, 2015, page 3158, Jeon et al. (© Springer-Verlag Wien 2015) with permission of Springer. Micrographs of IME-AB2 and Acibel007 were reproduced from [58,59], respectively, under the terms of the Creative Commons Attribution license.

3. Results

3.1. Acinetobacter Phages with Whole Genome Sequences

Bacteriophages are classified by the International Committee on Taxonomy of Viruses (ICTV) according to phenotypic and genotypic parameters that encompass virion morphology, nucleic acid type, genome organisation, nucleotide sequence identity, number of shared proteins and phylogenetic analysis of encoded proteins [60]. With the exception of the ssRNA Levivirus AP205, the sequenced phages infecting Acinetobacter spp. thus far belong exclusively to clades within the three families of the Order Caudovirales; the Myoviridae, Podoviridae and Siphoviridae (Table 1).

3.2. Whole Genome and Proteome Comparisons of the Acinetobacter Phages

To visualize relationships between the sequenced Acinetobacter phages, the phage genomes were analysed using whole genome dot plots, pairwise sequence identity and shared proteins. Dot plots and nucleotide sequence alignments after genome co-linearization indicate that while there is substantial diversity among the sequenced Acinetobacter phages, there is also sufficient similarity to allow these phages to be placed in six discrete clusters designated A–G (Figure 1 and Figure S1). Since several phages exhibited a significant proportion of shared gene content without having substantial nucleotide identity, clusters were defined on the basis of at least 40% of shared gene content.

With the exception of clusters A and C, each cluster possesses a minimum of 40% ANI and greater than 50% conservation at the protein level (Figure S2). This division is further supported by morphological similarity (Figure 2) and by low standard deviation in genome size, G + C content and the number of genes encoded between members of each group (Table 1). Three of the proposed clusters correspond to ICTV taxonomic assignments: Cluster A comprises phages related to members of the Tevenvirinae subfamily while two clusters, B and E, correspond to the formally established genera Fri1virus and Ap22virus. Two phages, ME3 and Presley did not reveal a clear relationship to the other phages and are designated as genomic singletons. Several phages exhibited low ANI to the defined clusters. Specifically, phiAC-1 exhibits ANI ranging from 16.2% to 21.4% with phages of the Ap22virus (Cluster B) while phages F1245/05, Acibel007 and Petty possess between 9.3% and 25.6% ANI with phages assigned to the Fri1virus (Cluster D).

The comparison of gene content provides a secondary assessment of genomic diversity. During a manual pairwise comparison, it was observed that some candidate ORFs had not been identified and others had optimal ribosome binding sequences that differ from the published annotations. For these reasons, each phage was re-annotated prior to protein clustering (File S1). Initially, proteins from the five clusters were assembled separately into groups using OrthoMCL. From these results, sets of proteins were identified for each cluster of phages that (i) were present in all genomes within that cluster, (ii) were encoded on two or more but not all, of the genomes in a cluster and (iii) proteins that were unique to a single phage genome (Figure 3).

To estimate the gene content relationship between all 37 phages, OrthoMCL was used to cluster all 4065 proteins, which assembled into 737 groups of two or more proteins and 975 orphans (File S2). This approach allowed the inter- and intra-cluster relationship in gene content amongst the Acinetobacter phages to be represented as a network phylogeny, the results of which show agreement with the clusters designated from nucleotide sequence comparisons (Figure 4). Highlighting their status as singletons, 260 and 80 of the proteins encoded by ME3 and Presley, respectively, were unique orphans. The relationship between the more distantly related phages is more apparent from the gene content analysis where Petty, F1245/05 and Acibel007 each encode 22 proteins (41.5% to 48.9% of ORFs) that represent core protein groups of the Fri1virus. Similarly, 29 proteins (35.4% of ORFs) encoded by phiAC-1 fall within the core Ap22virus protein groups. These more distant relationships are represented by common branches in the network phylogeny (Figure 4).

Functional inferences for the grouped and unique protein sequences were obtained using a combination of BLASTP, InterProScan and the HHsuite tools, HHblits and HHsearch. Of the 4067 proteins, a putative function based on bioinformatics analysis could be ascribed to 1762 (322 protein groups and 172 orphans) while 2305 (56.6%) were annotated as hypothetical proteins of unknown function. The majority of proteins formed mutually exclusive groups common to two or more members of a single cluster (File S2).

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